The detailed description is described with reference to the accompanying figures. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The use of the same reference numbers in different instances in the description and the figures may indicate similar or identical items. Entities represented in the figures may be indicative of one or more entities and thus reference may be made interchangeably to single or plural forms of the entities in the discussion.
Overview
Today, mobile computing devices such as laptops and tablets may be configured to support and connect to a variety of types of accessory devices by way of universal serial bus (USB) or other communication techniques. However, traditional connectors, ports, and connector cables for accessories are designed for connection in a single orientation. Accordingly, users may often attempt to make connections in the wrong way, which is not only frustrating for the user, but may also result in wear and/or damage to the connectors, ports, and connector cords.
Reversible connector techniques for accessory devices are described. In one or more implementations, a connector cable for an accessory of a host computing device is configured such that a head of the connector cable may be plugged into a corresponding port of the host in either orientation (straight or reverse). The host computing device is configured to sample signals associated with allocated pins of the connector to detect connection of the connector to an accessory port and to ascertain an orientation of the connector. A switching mechanism of the host computing device may then be configured to automatically route signals according to the orientation. In one approach, a pair of “detection” pins of the connector is dedicated for hot plug detection. A combination of high and low logic states that is conveyed via these two detection pins upon insertion of the connector may be used by a controller of the host to distinguish between different types of devices (e.g., two wire and one wire devices) and to resolve the orientation of the connector cable. Lines associated with the two detection pins may be sampled together (e.g., in parallel or in sequence) and values for obtained for the two line may be combined together to derive a combined logic state indicative of the device type and/or connector orientation. The controller may then operate to set-up signal routing according to the type of device and orientation. In order to do so, the controller may be configured to direct positions for switches and multiplexers of the host and/or the connected accessory to effectuate straight or reverse signal paths as appropriate.
In the following discussion, an example environment and devices are first described that may employ the techniques described herein. Example details and procedures are then described which may be performed in the example environment and by the devices as well as in other environments and by other devices. Consequently, implementation of the example details and procedures is not limited to the example environment/devices and the example environment/devices are not limited to the example details and procedures.
Example Operating Environment
The host computing device 102, for instance, is illustrated as including an input/output module 108. The input/output module 108 is representative of functionality relating to processing of inputs and rendering outputs of the host computing device 102. A variety of different inputs may be processed by the input/output module 108, such as inputs relating to functions that correspond to keys of the input device, keys of a virtual keyboard displayed by the display device 110 to identify gestures and cause operations to be performed that correspond to the gestures that may be recognized through the accessory device 104 and/or touchscreen functionality of the display device 110, and so forth. Thus, the input/output module 108 may support a variety of different input techniques by recognizing and leveraging a division between types of inputs including key presses, gestures, and so on.
Various configurations for an accessory device 104 are also contemplated, such as a keyboard, game controller, configuration to mimic a musical instrument, a power adapter, a docking station, a USB hub, an external battery, combinations of these configurations, and so forth. Thus, the accessory device 104 may assume a variety of different configurations to support a variety of different functionality. Different accessory devices may be removably connected to the computing device at different times.
As previously described, the accessory device 104 is physically and communicatively coupled to the host computing device 102 in this example through an interface 106. Various types of interfaces 106 and connectors are also contemplated such as uses of a flexible hinge, magnetic coupling devices, integrated communication ports and communication contacts, mechanical coupling protrusions, slots, and/or indentions, individually or in combination to form different types of interfaces 106. In one example, the interface 106 may represent an accessory port (e.g., communication port) configured to enable connection to accessory devices via a corresponding connector and/or connector cord. In accordance with techniques discussed above and below, the accessory port and corresponding connector are designed to enable reversible connection of the connector to the port. In at least some implementations, the interface 106 is configured to enable communications for authentication and control of the accessory device 104 as described herein. For example, the computing device 102 may receive credentials (e.g., data indicative of an identity of an accessory), signals, and other data regarding capabilities of the accessory device through the interface responsive to detecting the presence/attachment of the accessory device 104. The interface may also provide a power coupling for exchange of power and communication of messages to implement and update power management and control functions as described above and below.
As further illustrated in
The power controller 112 may be implemented in hardware, software, firmware and/or combinations thereof. By way of example and not limitation, the computing device 102 may include a microcontroller or other suitable hardware logic device configured to implement various functionally that is described herein in relation to power controller 112. The power controller 112 may therefore represent firmware or logic associated with a suitable hardware logic device. In addition or alternatively, the power controller 112 may be implemented by way of a processing system of the device and one or more program modules that are executable/operable via the processing system.
The power adapter 114 may be configured to selectively operate in multiple modes and supply multiple power levels to the computing device. The level of power supplied at a particular time may be based upon input, notifications, or other suitable feedback configured and sent to the power adapter 114 by the power controller 112 to cause the power adapter 114 to supply a corresponding level of power. Depending upon a power exchange state, the power adapter 114, when connected to the computing device, may charge a battery associated with one or both of the host and accessory, supply power to support operations of one or both the host and accessory, and otherwise supply power from external power sources 116 for joint charging and operation of the host and accessory in various combinations. A power scheme implemented via the power controller 112 may be configured to control flow of power between system components (e.g., host, accessory, and adapter) in dependence upon accessory identity, power exchange conditions, power source availability, and so forth. Further details regarding operation of the power controller 112 and the power adapter 114 to implement power management contracts for accessory devices can be found in the following discussion.
The example microcontrollers (μPs) represent hardware devices/systems that are designed to perform a predefined set of designated tasks. Microcontrollers may represent respective on-chip systems/circuits having self-contained resources such as processing components, I/O devices/peripherals, various types of memory (ROM, RAM, Flash, EEPROM), programmable logic, and so forth. Different microcontrollers may be configured to implement embedded applications/functionality that are implemented at least partially in hardware and perform corresponding tasks. In particular, the example microcontrollers 202, 206 enable performance of tasks for device authentication and power management outside of operation of a general purpose processing system and other applications/components of the computing device or accessory device. Generally, power consumption of the microcontrollers is low in comparison with operating a general purpose processing system for a device.
Accordingly, components implemented via microcontrollers may operate using relatively low power, independently of operating a “primary” processing system of a host computing device, and/or without booting/executing an operating system or using other device components and applications. In other words, the microcontrollers may operate to perform some power management tasks in a low power mode without having to operate or supply power to the processing system and other device components (e.g., device memory, network interface, display device, etc.) and/or without completely starting-up or waking-up the computing device.
The host computing device 202 may be connectable to different accessory devices via an accessory port 210. The accessory port 210 is representative of functionality to achieve a physical and communicative coupling between the host computing device and various accessories. For example, a connector 211 corresponding to the accessory port 210 may be employed to connect accessories to the host computing and enable exchange of control signals, data, and power. In the depicted example, the connector 211 is illustrated as a connector cord that may be removably inserted into a corresponding port associated with the accessory interface 210, although other types of connections are also contemplated, such as the flexible hinge discussed in relation to
As represented in
Thus, power exchange may occur via the accessory port 210 in some scenarios. Power supplied to the host computing device may be used to operate the host (e.g., service the system load) and/or to maintain a charge level of the power supply 204 (e.g., internal battery). Additionally, power supplied to the host may be supplied directly or indirectly to the accessory device 104 to support operations and/or charge the power supply 208 (e.g., external battery). Moreover, power may be distributed from the host computing device 102 and/or the accessory device 104 to one or more peripherals 212 that may be connected directly to the host computing device and/or connected to the system through the accessory device 104 as represented in
It should be noted that the host computing device 102 and accessory device 104 may both be configured to employ external power sources 116, such as through the use of respective power adapters 114 connected to a wall socket or another source. Power supplied directly to the accessory device 104 via a respective power adapter 114 may be used, shared, and/or exchanged between the host and accessory in a manner comparable to power that is supplied directly to the host computing device 102.
The host computing device may be further configured to implement a power scheme 214 and a security module 216 in various ways. In the illustrated example, the power scheme 214 is depicted as being implemented via the power controller 112. In this example, the power scheme 214 is configured as firmware associated with the host computing device 102. For example, the power scheme 214 may represent firmware associated with a microcontroller 202, power controller 112, or other suitable hardware logic device. Alternatively, the power scheme 214 may be implemented as a standalone module using any suitable combination of hardware, software, firmware, and/or logic devices.
The power scheme 214 represents functionality to implement power management contract techniques described above and below as well as other power management functions. In particular, the power scheme 214 may be configured to jointly manage power flow between a power adapter 114, host computing device 102, and accessory device 104. By way of example and not limitation, this may include controlling power flow to selectively charge batteries associated with the components; exchange power between the batteries, processing systems, and components; supply power to service the system load for the host and accessory; and so forth. In order to do so, the power scheme 214 may provide functionality to establish, enforce, and update power management contracts 218 between various components of the system. This functionality may include support for sending and receiving messages regarding power management between system components that may be configured in a variety of ways. For example, the messages may be configured as pulsed signal patterns that are recognizable by respective controllers of the host and accessory. Various suitable messaging protocols and corresponding message formats are also contemplated, such as using inter-integrated circuit (I2C) protocol, serial peripheral interface (SPI), universal asynchronous receiver/transmitter (UART) messaging, packet based communications, and object based messages, to name a few examples. Further, wireless messaging protocols such as near-field communication, Bluetooth, WiFi, RF protocols used in RFID, or cellular telecommunication protocols may be used.
The power management contracts 218 are configured to define operating constraints for power management including but not limited to specifying power exchange direction and current limits for different devices and scenarios. Moreover, the settings for power management contracts 218 may be modified in real-time based on conditions observed by the host or accessory. Thus, initial or default settings for a power management contracts 218 may be associated with different accessories and appropriate contracts may be activated upon initial connection and authorization of the different accessories. The initially activated power management contracts 218 may be modified thereafter based upon conditions including but not limited to relative states of charge (RSOC) for batteries of the system components, power loads being serviced, a number of peripherals 212 connected to the host and/or accessory, power source availability for system components, power supply characteristics, processing loads, and so forth. Thus, rather than fixing operating constraints for power exchange at the time accessories and/or peripherals are connected to the system, the power management contracts discussed herein are designed to enable dynamic adjustments to such constraints in response to changing conditions at any time during connection of an accessory to a host. Such modifications of initial settings for a power management contract 218 based on “real-time” conditions may be initiated by accessory devices and/or by the host computing device.
The security module 216 represents functionality operable to identify and/or authenticate accessory devices when the devices are attached/connected to the computing devices. The security module 216 may be configured to implement a variety of different authentication techniques. Generally speaking, the security module 216 performs an authentication sequence in which credentials 220 (e.g., device ID/password, alphanumeric code, an identifying resistor value, etc.) associated with an accessory device 104 are obtained and verified. In one approach, the security module 216 is configured to provide functionality to support techniques for reversible connections of the connector 211 to the accessory port. For example, the security module 216 may represent functionality of the one or more microcontrollers 202 to detect insertion of the connector into the accessory port, sample detection pins of the connector 211 to ascertain an orientation of the connector as being straight or reversed according to values for the detection pins, and/or distinguish between different types of devices and/or communication protocols based on the sampling. Distinguishing between different types of devices may include distinguishing between two wire devices that utilize separate RX and TX lines and one wire devices for which RX/TX is combined on a single line or channel. Additionally, the security module 216 may represent functionality to set-up signal routing accordingly based on the ascertained orientation and/or the type of device.
Further, the accessory device 104 in
Having considered the preceding discussion of an example operating environment, system, and devices, consider now a discussion of example devices, procedures, and scenarios which includes further details regarding techniques to implement reversible connectors for accessory devices.
Reversible Connector Details
Here, a detection pin pair including a pin A 302 (also referred to herein as “HPD1A”) and a pin B 304 (also referred to herein as “HPD1B”) is depicted. Although one pair of detection pins is shown, generally speaking two or more detection pins may be allocated for hot plug detection of accessories and be sampled to facilitate resolution of connector orientation and device type based on the signals conveyed/read via the detection pins. In the illustrated example, pin A 302 and pin B 304 are shown as being located generally on opposite edges and/or sides of a head of the connector 211. A variety of other pins 306 to support different communication protocols, buses, and high speed signals are also incorporated in the connector 211. By way of example, in addition to providing pins for authentication/power exchange/control, the connector 211 may provide pins to support USB, audio/video signals, a display port, network communications, and so forth. Generally, the pins are arranged as high speed pairs of pins. The pins 302, 304, 306 are configured to mate with a set of complimentary pins 308 included with an accessory port 210 of the host computing device.
In the illustrated arrangement pin A 302 and pin B 304 are configured to mate respectively with RX and TX pins associated with the accessory port 210 of the host computing device 102 in the “straight” orientation. In this arrangement, RX signals may be conveyed via pin A 302 and TX signals may be conveyed via pin B 304. When the connector is flipped or reversed to assume the “reverse” orientation also depicted in
The host computing device, though, may include or otherwise make use of a switching mechanism 310 to “straighten-out” the signal routing. The switching mechanism provides functionality operable to control routing of signals such that the signals are communicated effectively between the same endpoints regardless of the connector orientation. The switching mechanism 310 is used to selectively change the signal pathways for the system to configure the accessory port and/or corresponding interface based on the connector orientation and/or for the particular type of device. Thus, for example, even when the connector is in the “reverse” orientation depicted in
Example Procedures
The following discussion describes techniques that may be implemented utilizing the previously described systems and devices. Aspects of each of the procedures may be implemented in hardware, firmware, software, or a combination thereof. The procedures are shown as a set of blocks that specify operations performed by one or more devices and are not necessarily limited to the orders shown for performing the operations by the respective blocks. In portions of the following discussion, reference may be made to the example operating environment 100 of
In particular, after attachment of the accessory device, an orientation of the connection of the connector to the accessory port is ascertained (block 504). The orientation may be resolved in various ways. Generally the orientation is determined based upon signals sampled on detection pins described herein. The particular values and/or patterns that are conveyed upon connection of a connector are indicative of the type of device as well as the connector orientation. Then, a switching mechanism of the host computing device is configured to automatically route signals according to the orientation (block 506). For example, one or more microcontrollers 202 of a host computing device may operate to configure a switching mechanism 310 in the manner previously described to set signal pathways based on an ascertained orientation of a connector 211. This may involve positioning of multiplexers 312 and switches 314 associated with the switching mechanism 310. In addition or alternatively, microcontrollers 202 may communicate with microcontrollers 206 of an accessory device 104 to notify the accessory device regarding the connector orientation and/or direct the accessory device 104 to reconfigure a switching mechanism on the accessory side accordingly to set-up appropriate signal routing. In this manner, endpoints for signal pathways may remain the same regardless of connector orientation. Thus, consumers may plug in accessories to a host device via a reversible cable in either orientation (straight or reverse) and the system automatically figures out the orientation and ensures that the signals do not get mixed up.
In one or more implementations, dedicated detection pins may be employed for hot plug detection and resolution of orientation as described herein. The detection may be based upon a voltage (e.g., 5V) that is applied to the detection lines and corresponding logic states for the pins, e.g., high=1, or low=0, that are obtained/read in response to the applied voltage. Different possible combinations of logic states for the detection lines may be associated with a set of detection cases each of which corresponds to a type of device and/or an orientation of a connector 211. Lines associated with the detection pins may be sampled together (e.g., in parallel or in sequence) and values for obtained for the different lines may be combined together to derive a combined logic state that is indicative of the device type and/or connector orientation. Accordingly, a table, file, database or other data structure may be established that reflects mapping of logic state combinations (or other credentials/accessory identifiers) with corresponding detection cases. In operation, the one or more microcontrollers 202 may monitor the detection pins and obtain values on each detection line. The microcontrollers 202 may make use of a mapping of the possible logic state combinations with corresponding detection cases to resolve the device type and connector orientation.
Regarding device type, the logic state combinations provide a mechanism to enable the host to distinguish between different types of devices. In particular, a detected logic state combination indicates whether a device is a one wire device that may communicate via a single line with RX and TX combined or a two wire device that uses two different lines for RX and TX. One wire devices may be relatively simple and low cost devices that do not use complex communication schemes, such as a basic power adapter or external battery. Two wire devices may be devices that provide functionality involving advanced interfaces, high speed communications, and/or multiple types of data/protocols, such as a docking station, multi-media accessory, and so forth.
In the case of a pair of detection pins allocated for hot plug detection, such as HPD1A and HPD1B (e.g., Pin A 302 and Pin B 304), there are four possible logic state combinations, e.g., high-high, high-low, low-high, and low-low. The logic states are indicative of the type of device (e.g., one wire or two wire) and may also be used to directly or indirectly resolve the connector orientation. In particular, both of the pins HPD1A and HPD1B are not asserted (e.g., in a low state) in the absence of a connected accessory. When an accessory device is connected to the host, the particular combination of the states for HPD1A and HPD1B determines the accessory type. For one wire devices, the line on which a high state is asserted can be determined. Accordingly, the logic state combination for a one-wire device also reflects the connector orientation and may be used directly to ascertain the orientation. For two wire devices, both lines have high states and thus the logic state combination may be insufficient to resolve the orientation. Therefore, additional processing may be performed as described below to ascertain the orientation of a two wire device.
Thus, for the detection pins HPD1A and HPD1B, the following shows an illustrative table showing an example mapping of possible logic state combinations to detection cases:
Per the above table, the values 1, 1 (high-high) indicates a two wire accessory, 1, 0 (high-low) indicates a one wire accessory in a straight orientation, 0, 1 (low-high) indicates a one wire accessory in a reverse orientation, and 0, 0 (low-low) indicates that no accessory is attached. After determining the device type using a mapping such as the example of Table 1, additional processing may occur to perform authentication/authorization of device, determine a particular identity and/or capabilities of the device (as opposed to just the one wire vs two wire determination), and set-up switching mechanisms of the host and/or accessory to route signals appropriately.
For example, for a one wire device, sampling may occur via the asserted pin (either HPD1A or HPD1B) to identify and authorize the device. This may involve various different authentication techniques as described previously. The authentication enables the host/microcontroller to recognize unsupported accessories and determine specific configuration information for supported accessories based on the particular accessory identity to configure the interface and signal routing accordingly. For instance, accessory devices may be configured to supply credentials 220 to the host in various ways as mentioned previously. In one approach, accessory devices are configured to expose a respective resistor value indicative of the identity for reading by the host computing device. Different resistor values may be associated with different accessories. Thus, when an accessory is connected, the host computing device may read a corresponding resistor value and distinguish between different accessories on this basis. Alternatively, other credentials 220 may be communicated to the host by an accessory to indicate its identity, such as sending a particular numeric code, an ID field value, a device name, and so forth.
As noted, when the attached accessory is a two wire device, the logic state combination is not sufficient to enable an orientation determination. In this case, orientation is resolved through the authentication sequence. In order to do so, supported two wire devices may be configured to supply credentials 220 to the host via either or both of the signal lines. In this case, sampling occurs for both of HPD1A or HPD1B to identify and authorize the two wire device. In one approach, the two wire device may have ID resistors associated with one or both lines and may expose the resistor value(s) indicative of the identity. Again, other credentials 220 may also be communicated to the host by an accessory to indicate its identity. Orientation may then be determined based on mapping of ID validity states for each line, e.g., valid or invalid, to possible orientation cases. Thus, for the detection pins HPD1A and HPD1B, the following shows an illustrative table showing an example mapping of ID validity states orientation cases:
An accessory port is monitored (block 602) to detect connection of an accessory via a corresponding connector cord. The monitoring may be implemented by a microcontroller 202 and/or security module 216 as described herein. The accessory port 210 and connector 211 may be configured to have a pair of pins allocated for detection, e.g., detection pins HPD1A and HPD1B. A determination is made regarding whether either of pins HPD1A and HPD1B is asserted (e.g., signal value of high=1) (block 604). If not, monitoring of the port continues per block 602. If at least one of the pins is asserted, a check is made to determine if both pins are asserted (block 606). If both pins are not asserted, procedure 600 proceeds to operations associated with one wire configuration and otherwise both pins are asserted and procedure 600 proceeds to operations associated with two wire configuration.
For one wire configuration, determination is made regarding whether HPD1A is asserted (block 608) and if so, HPD1A is sampled (block 610) to obtain credentials for identification. Based on the credentials, an ID of the connected accessory is validated (block 612) and when the ID is valid, the system is configured for one wire in straight orientation (block 614). On the other hand, if the ID is not valid the accessory is an unsupported accessory (block 616) and interaction may be restricted. If HPD1A is not asserted per block 608, the other pin HPD1B is the asserted pin and is sampled (block 618). ID validation again occurs (block 620) and either, the ID is valid and the system is configured for one wire in reverse orientation (block 622) or the ID is not valid the accessory is an unsupported accessory (block 616) and may be restricted.
For two wire configuration, both HPD1A and HPD1B are sampled (block 624). ID validation occurs for HPD1A (block 626) and then for HPD1B (block 628) if the ID sampled on HPD1A is valid. If IDs for both HPD1A and HPD1B are valid, then both straight and reverse orientations are supported and configuration occurs based on the application (block 630). Otherwise, if just the ID for HPD1A is valid, then the system is configured for two wire in straight orientation (block 632). If HPD1A is not valid per block 626, ID validation occurs for HPD1B (block 634). If HPD1B is valid per block 634, then system is configured for two wire in reverse orientation (block 636). Otherwise, IDs sampled for both HPD1A and HPD1B are invalid and the accessory is an unsupported accessory (block 638) and may be restricted. Following configuration of the system in the appropriate way based on the depicted logic, signals are the routed using the configuration that us applied (block 640).
Example procedure 600 may be implemented in software, firmware, hardware, or a combination of each or some of same. A software or firmware implementation may be advantageously flexible and reconfigured with a software or firmware update. Alternatively, example procedure 600 may be implemented using discrete logic gates and analog and mixed-signal circuits, including analog-to-digital circuits. This alternative may be advantageously faster and may also comprise programmable thresholds, for example, for determining resistor values. Because of the binary nature of the decisions, digital logic may be used extensively.
Having considered the foregoing example procedures, consider now a discussion of example systems and devices that may be employed to implement aspects of reversible connector techniques in one or more embodiments.
Example System and Device
The example computing device 702 as illustrated includes a processing system 704, one or more computer-readable media 706, and one or more I/O interface 708 that are communicatively coupled, one to another. Although not shown, the computing device 702 may further include a system bus or other data and command transfer system that couples the various components, one to another. A system bus can include any one or combination of different bus structures, such as a memory bus or memory controller, a peripheral bus, a universal serial bus, and/or a processor or local bus that utilizes any of a variety of bus architectures. A variety of other examples are also contemplated, such as control and data lines.
The processing system 704 is representative of functionality to perform one or more operations using hardware. Accordingly, the processing system 704 is illustrated as including hardware element 710 that may be configured as processors, functional blocks, and so forth. This may include implementation in hardware as an application specific integrated circuit or other logic device formed using one or more semiconductors. The hardware elements 710 are not limited by the materials from which they are formed or the processing mechanisms employed therein. For example, processors may be comprised of semiconductor(s) and/or transistors (e.g., electronic integrated circuits (ICs)). In such a context, processor-executable instructions may be electronically-executable instructions.
The computer-readable storage media 706 is illustrated as including memory/storage 712. The memory/storage 712 represents memory/storage capacity associated with one or more computer-readable media. The memory/storage component 712 may include volatile media (such as random access memory (RAM)) and/or nonvolatile media (such as read only memory (ROM), Flash memory, optical disks, magnetic disks, and so forth). The memory/storage component 712 may include fixed media (e.g., RAM, ROM, a fixed hard drive, and so on) as well as removable media (e.g., Flash memory, a removable hard drive, an optical disc, and so forth). The computer-readable media 706 may be configured in a variety of other ways as further described below.
Input/output interface(s) 708 are representative of functionality to allow a user to enter commands and information to computing device 702, and also allow information to be presented to the user and/or other components or devices using various input/output devices. Examples of input devices include a keyboard, a cursor control device (e.g., a mouse), a microphone, a scanner, touch functionality (e.g., capacitive or other sensors that are configured to detect physical touch), a camera (e.g., which may employ visible or non-visible wavelengths such as infrared frequencies to recognize movement as gestures that do not involve touch), and so forth. Examples of output devices include a display device (e.g., a monitor or projector), speakers, a printer, a network card, tactile-response device, and so forth. Thus, the computing device 702 may be configured in a variety of ways to support user interaction.
The computing device 702 is further illustrated as being communicatively and physically coupled to an accessory device 714 that is physically and communicatively removable from the computing device 702. In this way, a variety of different input devices may be coupled to the computing device 702 having a wide variety of configurations to support a wide variety of functionality. In this example, the accessory device 714 includes one or more controls 716, which may be configured as press-sensitive keys, mechanically switched keys, buttons, and so forth.
The accessory device 714 is further illustrated as include one or more modules 718 that may be configured to support a variety of functionality. The one or more modules 718, for instance, may be configured to process analog and/or digital signals received from the controls 716 to determine whether an input was intended, determine whether an input is indicative of resting pressure, support authentication of the accessory device 714 for operation with the computing device 702, and so on.
Various techniques may be described herein in the general context of software, hardware elements, or program modules. Generally, such modules include routines, programs, objects, elements, components, data structures, and so forth that perform particular tasks or implement particular abstract data types. The terms “module,” “functionality,” and “component” as used herein generally represent software, firmware, hardware, or a combination thereof. The features of the techniques described herein are platform-independent, meaning that the techniques may be implemented on a variety of commercial computing platforms having a variety of processors.
An implementation of the described modules and techniques may be stored on or transmitted across some form of computer-readable media. The computer-readable media may include a variety of media that may be accessed by the computing device 702. By way of example, and not limitation, computer-readable media may include “computer-readable storage media” and “computer-readable signal media.”
“Computer-readable storage media” refers to media and/or devices that enable storage of information in contrast to mere signal transmission, carrier waves, or signals per se. Thus, computer-readable storage media does not include signals per se or signal-bearing media. The computer-readable storage media includes hardware such as volatile and non-volatile, removable and non-removable media and/or storage devices implemented in a method or technology suitable for storage of information such as computer readable instructions, data structures, program modules, logic elements/circuits, or other data. Examples of computer-readable storage media may include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, hard disks, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or other storage device, tangible media, or article of manufacture suitable to store the desired information and which may be accessed by a computer.
“Computer-readable signal media” may refer to a signal-bearing medium that is configured to transmit instructions to the hardware of the computing device 702, such as via a network. Signal media typically may embody computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as carrier waves, data signals, or other transport mechanism. Signal media also include any information delivery media. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared, and other wireless media.
As previously described, hardware elements 710 and computer-readable media 706 are representative of modules, programmable device logic and/or fixed device logic implemented in a hardware form that may be employed in some embodiments to implement at least some aspects of the techniques described herein, such as to perform one or more instructions. Hardware may include components of an integrated circuit or on-chip system, microcontroller devices, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a complex programmable logic device (CPLD), and other implementations in silicon or other hardware. In this context, hardware may operate as a processing device that performs program tasks defined by instructions and/or logic embodied by the hardware as well as a hardware utilized to store instructions for execution, e.g., the computer-readable storage media described previously.
Combinations of the foregoing may also be employed to implement various techniques described herein. Accordingly, software, hardware, or executable modules may be implemented as one or more instructions and/or logic embodied on some form of computer-readable storage media and/or by one or more hardware elements 710. The computing device 702 may be configured to implement particular instructions and/or functions corresponding to the software and/or hardware modules. Accordingly, implementation of a module that is executable by the computing device 702 as software may be achieved at least partially in hardware, e.g., through use of computer-readable storage media and/or hardware elements 710 of the processing system 704. The instructions and/or functions may be executable/operable by one or more articles of manufacture (for example, one or more computing devices 702 and/or processing systems 704) to implement techniques, modules, and examples described herein.
Although the example implementations have been described in language specific to structural features and/or methodological acts, it is to be understood that the implementations defined in the appended claims is not necessarily limited to the specific features or acts described. Rather, the specific features and acts are disclosed as example forms of implementing the claimed features.
Number | Name | Date | Kind |
---|---|---|---|
4868653 | Golin et al. | Sep 1989 | A |
5149919 | Greanias et al. | Sep 1992 | A |
5241682 | Bryant et al. | Aug 1993 | A |
5353133 | Bernkopf | Oct 1994 | A |
5450586 | Kuzara et al. | Sep 1995 | A |
5475425 | Przyborski et al. | Dec 1995 | A |
5544258 | Levien | Aug 1996 | A |
5687011 | Mowry | Nov 1997 | A |
5778404 | Capps et al. | Jul 1998 | A |
5831594 | Tognazzini et al. | Nov 1998 | A |
5867709 | Klencke | Feb 1999 | A |
5903566 | Flammer, III | May 1999 | A |
5964879 | Dunstan | Oct 1999 | A |
6028960 | Graf et al. | Feb 2000 | A |
6151643 | Cheng et al. | Nov 2000 | A |
6167377 | Gillick et al. | Dec 2000 | A |
6232972 | Arcuri et al. | May 2001 | B1 |
6263308 | Heckerman et al. | Jul 2001 | B1 |
6283858 | Hayes et al. | Sep 2001 | B1 |
6297825 | Madden et al. | Oct 2001 | B1 |
6339437 | Nielsen | Jan 2002 | B1 |
6349406 | Levine et al. | Feb 2002 | B1 |
6389181 | Shaffer et al. | May 2002 | B2 |
6452915 | Jorgensen | Sep 2002 | B1 |
6603491 | Lemelson et al. | Aug 2003 | B2 |
6757027 | Edwards et al. | Jun 2004 | B1 |
6847386 | Paleiov | Jan 2005 | B2 |
6854073 | Bates et al. | Feb 2005 | B2 |
6934370 | Leban et al. | Aug 2005 | B1 |
6970947 | Ebling et al. | Nov 2005 | B2 |
7082211 | Simon et al. | Jul 2006 | B2 |
7171432 | Wildhahen | Jan 2007 | B2 |
7194114 | Schneiderman | Mar 2007 | B2 |
7200561 | Moriya et al. | Apr 2007 | B2 |
7251812 | Jhanwar et al. | Jul 2007 | B1 |
7337112 | Moriya et al. | Feb 2008 | B2 |
7370043 | Shelton et al. | May 2008 | B1 |
7380003 | Guo et al. | May 2008 | B1 |
7387539 | Trenne | Jun 2008 | B2 |
7400439 | Holman | Jul 2008 | B2 |
7443791 | Barrett et al. | Oct 2008 | B2 |
7443807 | Cutler | Oct 2008 | B2 |
7458825 | Atsmon et al. | Dec 2008 | B2 |
7466986 | Halcrow et al. | Dec 2008 | B2 |
7496910 | Voskuil | Feb 2009 | B2 |
7525928 | Cutler | Apr 2009 | B2 |
7551754 | Steinberg et al. | Jun 2009 | B2 |
7577295 | Constantin et al. | Aug 2009 | B2 |
7577297 | Mori et al. | Aug 2009 | B2 |
7580952 | Logan et al. | Aug 2009 | B2 |
7584285 | Hudson et al. | Sep 2009 | B2 |
7614046 | Daniels et al. | Nov 2009 | B2 |
7639877 | Shiota et al. | Dec 2009 | B2 |
7680327 | Weiss | Mar 2010 | B2 |
7690042 | Rantalahti | Mar 2010 | B2 |
7697557 | Segel | Apr 2010 | B2 |
7703036 | Satterfield | Apr 2010 | B2 |
7715598 | Li et al. | May 2010 | B2 |
7716643 | Goldin | May 2010 | B2 |
7738870 | Howard | Jun 2010 | B2 |
7756538 | Bonta et al. | Jul 2010 | B2 |
7765194 | Sharma et al. | Jul 2010 | B1 |
7766498 | Sampsell | Aug 2010 | B2 |
7779367 | Oshiro et al. | Aug 2010 | B2 |
7783629 | Li et al. | Aug 2010 | B2 |
7783777 | Pabla et al. | Aug 2010 | B1 |
7835910 | Hakkani-Tur et al. | Nov 2010 | B1 |
7864967 | Takeuchi et al. | Jan 2011 | B2 |
7865952 | Hopwood et al. | Jan 2011 | B1 |
7881479 | Asada | Feb 2011 | B2 |
7900011 | Amundsen et al. | Mar 2011 | B2 |
7959308 | Freeman et al. | Jun 2011 | B2 |
7970350 | Sheynman et al. | Jun 2011 | B2 |
7970901 | Lipscomb et al. | Jun 2011 | B2 |
7978925 | Souchard | Jul 2011 | B1 |
8015006 | Kennewick et al. | Sep 2011 | B2 |
8026830 | Womble et al. | Sep 2011 | B2 |
8074213 | Holtz | Dec 2011 | B1 |
8078623 | Chou et al. | Dec 2011 | B2 |
8091074 | Lyon-Smith | Jan 2012 | B2 |
8107243 | Guccione et al. | Jan 2012 | B2 |
8149748 | Bata et al. | Apr 2012 | B2 |
8150098 | Gallagher et al. | Apr 2012 | B2 |
8155400 | Bronstein et al. | Apr 2012 | B2 |
8165352 | Mohanty | Apr 2012 | B1 |
8170298 | Li et al. | May 2012 | B2 |
8189807 | Cutler | May 2012 | B2 |
8212894 | Nozaki et al. | Jul 2012 | B2 |
8213333 | Greel et al. | Jul 2012 | B2 |
8224036 | Maruyama et al. | Jul 2012 | B2 |
8229729 | Sarikaya et al. | Jul 2012 | B2 |
8232962 | Buck | Jul 2012 | B2 |
8239446 | Navar et al. | Aug 2012 | B2 |
8245043 | Cutler | Aug 2012 | B2 |
8275615 | Kozat | Sep 2012 | B2 |
8296107 | Turner et al. | Oct 2012 | B2 |
8296673 | Lipstein et al. | Oct 2012 | B2 |
8306280 | Nozaki et al. | Nov 2012 | B2 |
8316237 | Felsher et al. | Nov 2012 | B1 |
8321220 | Chotimongkol et al. | Nov 2012 | B1 |
8326634 | Di Cristo et al. | Dec 2012 | B2 |
8331632 | Mohanty et al. | Dec 2012 | B1 |
8345934 | Obrador et al. | Jan 2013 | B2 |
8346563 | Hjelm et al. | Jan 2013 | B1 |
8358811 | Adams et al. | Jan 2013 | B2 |
8364717 | Delling et al. | Jan 2013 | B2 |
8368540 | Perkins et al. | Feb 2013 | B2 |
8373829 | Hara et al. | Feb 2013 | B2 |
8374122 | Meier et al. | Feb 2013 | B2 |
8375456 | Li et al. | Feb 2013 | B2 |
8384694 | Powell et al. | Feb 2013 | B2 |
8384791 | Porter et al. | Feb 2013 | B2 |
8392594 | Georgis et al. | Mar 2013 | B2 |
8397163 | Sran | Mar 2013 | B1 |
8400332 | Szwabowski et al. | Mar 2013 | B2 |
8406206 | Chiang | Mar 2013 | B2 |
8407472 | Hao et al. | Mar 2013 | B2 |
8412521 | Mathias et al. | Apr 2013 | B2 |
8413198 | Connor et al. | Apr 2013 | B2 |
8448847 | Lee | May 2013 | B2 |
8468548 | Kulkarni et al. | Jun 2013 | B2 |
8484314 | Luna et al. | Jul 2013 | B2 |
8493992 | Sella et al. | Jul 2013 | B2 |
8495372 | Bailey et al. | Jul 2013 | B2 |
8504823 | Carpenter | Aug 2013 | B2 |
8516471 | Bhakta et al. | Aug 2013 | B2 |
8522209 | Wintergerst et al. | Aug 2013 | B2 |
8527602 | Rasmussen et al. | Sep 2013 | B1 |
8535075 | Golko et al. | Sep 2013 | B1 |
8539477 | Balascio et al. | Sep 2013 | B2 |
8549150 | Roseman et al. | Oct 2013 | B1 |
8555364 | Filippi et al. | Oct 2013 | B2 |
8571866 | Melamed et al. | Oct 2013 | B2 |
8611678 | Hanson et al. | Dec 2013 | B2 |
8614734 | Cutler | Dec 2013 | B2 |
8619062 | Powell et al. | Dec 2013 | B2 |
8620351 | Karaoguz | Dec 2013 | B2 |
8620649 | Gao | Dec 2013 | B2 |
8626932 | Lydon et al. | Jan 2014 | B2 |
8631350 | Lepage et al. | Jan 2014 | B2 |
8670850 | Soulodre | Mar 2014 | B2 |
8686600 | Terlizzi et al. | Apr 2014 | B2 |
8701102 | Appiah et al. | Apr 2014 | B2 |
8705806 | Nakano | Apr 2014 | B2 |
8719603 | Belesiu | May 2014 | B2 |
8756507 | Fong et al. | Jun 2014 | B2 |
8924315 | Archambeau | Dec 2014 | B2 |
9017092 | McCracken et al. | Apr 2015 | B1 |
9058311 | Bertz et al. | Jun 2015 | B1 |
9088891 | Belton et al. | Jul 2015 | B2 |
20010000356 | Woods | Apr 2001 | A1 |
20020083041 | Achlioptas et al. | Jun 2002 | A1 |
20020101918 | Rodman et al. | Aug 2002 | A1 |
20020143855 | Traversat et al. | Oct 2002 | A1 |
20030068100 | Covell et al. | Apr 2003 | A1 |
20030125948 | Lyudovyk | Jul 2003 | A1 |
20030182414 | O'Neill | Sep 2003 | A1 |
20040040021 | Bharati et al. | Feb 2004 | A1 |
20040088726 | Ma et al. | May 2004 | A1 |
20040168165 | Kokkinen | Aug 2004 | A1 |
20040240711 | Hamza et al. | Dec 2004 | A1 |
20050052427 | Wu et al. | Mar 2005 | A1 |
20050114625 | Snyder | May 2005 | A1 |
20050144616 | Hammond et al. | Jun 2005 | A1 |
20050163372 | Kida et al. | Jul 2005 | A1 |
20050165839 | Madan et al. | Jul 2005 | A1 |
20050177515 | Kalavade et al. | Aug 2005 | A1 |
20050177624 | Oswald et al. | Aug 2005 | A1 |
20050245243 | Zuniga | Nov 2005 | A1 |
20060034542 | Aoyama | Feb 2006 | A1 |
20060046709 | Krumm et al. | Mar 2006 | A1 |
20060058009 | Vogedes et al. | Mar 2006 | A1 |
20060088209 | Yu et al. | Apr 2006 | A1 |
20060156222 | Chi et al. | Jul 2006 | A1 |
20060174017 | Robertson | Aug 2006 | A1 |
20060212867 | Fields et al. | Sep 2006 | A1 |
20060244845 | Craig et al. | Nov 2006 | A1 |
20060277478 | Seraji et al. | Dec 2006 | A1 |
20060280341 | Koshizen | Dec 2006 | A1 |
20060290705 | White | Dec 2006 | A1 |
20070002478 | Mowry | Jan 2007 | A1 |
20070038436 | Cristo et al. | Feb 2007 | A1 |
20070053607 | Mitsunaga | Mar 2007 | A1 |
20070055752 | Wiegand et al. | Mar 2007 | A1 |
20070058878 | Gomilla et al. | Mar 2007 | A1 |
20070147318 | Ross et al. | Jun 2007 | A1 |
20070156392 | Balchandran et al. | Jul 2007 | A1 |
20070157313 | Denton | Jul 2007 | A1 |
20070172099 | Park | Jul 2007 | A1 |
20070188477 | Rehm | Aug 2007 | A1 |
20070198950 | Dodge et al. | Aug 2007 | A1 |
20070226649 | Agmon | Sep 2007 | A1 |
20070233879 | Woods | Oct 2007 | A1 |
20080005114 | Li | Jan 2008 | A1 |
20080014563 | Visani | Jan 2008 | A1 |
20080037438 | Twiss et al. | Feb 2008 | A1 |
20080037442 | Bill | Feb 2008 | A1 |
20080046425 | Perski | Feb 2008 | A1 |
20080055278 | Locker et al. | Mar 2008 | A1 |
20080066181 | Haveson et al. | Mar 2008 | A1 |
20080089299 | Lindsley et al. | Apr 2008 | A1 |
20080143674 | Molander et al. | Jun 2008 | A1 |
20080165701 | Ananthanarayanan et al. | Jul 2008 | A1 |
20080175190 | Lee et al. | Jul 2008 | A1 |
20080183751 | Cazier et al. | Jul 2008 | A1 |
20080192820 | Brooks et al. | Aug 2008 | A1 |
20080204598 | Maurer et al. | Aug 2008 | A1 |
20080212894 | Demirli et al. | Sep 2008 | A1 |
20080235017 | Satomura | Sep 2008 | A1 |
20080253564 | Kahn et al. | Oct 2008 | A1 |
20080263130 | Michalowitz et al. | Oct 2008 | A1 |
20080273708 | Sandgren et al. | Nov 2008 | A1 |
20080313264 | Pestoni | Dec 2008 | A1 |
20090028380 | Hillebrand et al. | Jan 2009 | A1 |
20090030697 | Cerra et al. | Jan 2009 | A1 |
20090046864 | Mahabub et al. | Feb 2009 | A1 |
20090055389 | Schilit et al. | Feb 2009 | A1 |
20090055461 | Georgis et al. | Feb 2009 | A1 |
20090083148 | Hwang et al. | Mar 2009 | A1 |
20090087099 | Nakamura | Apr 2009 | A1 |
20090089801 | Jones et al. | Apr 2009 | A1 |
20090100384 | Louch | Apr 2009 | A1 |
20090100459 | Riedl et al. | Apr 2009 | A1 |
20090100489 | Strothmann | Apr 2009 | A1 |
20090116749 | Cristinacce et al. | May 2009 | A1 |
20090180671 | Lee | Jul 2009 | A1 |
20090185723 | Kurtz | Jul 2009 | A1 |
20090187593 | Chen et al. | Jul 2009 | A1 |
20090210328 | Fomenko et al. | Aug 2009 | A1 |
20090259667 | Wang et al. | Oct 2009 | A1 |
20090271735 | Anderson et al. | Oct 2009 | A1 |
20090300596 | Tyhurst et al. | Dec 2009 | A1 |
20090313330 | Sakamoto | Dec 2009 | A1 |
20090313546 | Katpelly et al. | Dec 2009 | A1 |
20100011123 | Dantzig et al. | Jan 2010 | A1 |
20100015956 | Qu et al. | Jan 2010 | A1 |
20100027663 | Dai et al. | Feb 2010 | A1 |
20100054544 | Arguelles | Mar 2010 | A1 |
20100082478 | Van Der Veen et al. | Apr 2010 | A1 |
20100103117 | Townsend et al. | Apr 2010 | A1 |
20100111059 | Bappu et al. | May 2010 | A1 |
20100121954 | Yang et al. | May 2010 | A1 |
20100128863 | Krum et al. | May 2010 | A1 |
20100135038 | Handschy et al. | Jun 2010 | A1 |
20100189313 | Prokoski | Jul 2010 | A1 |
20100205177 | Sato | Aug 2010 | A1 |
20100211695 | Steinmetz et al. | Aug 2010 | A1 |
20100229222 | Li et al. | Sep 2010 | A1 |
20100251230 | O'Farrel et al. | Sep 2010 | A1 |
20100295774 | Hennessey | Nov 2010 | A1 |
20100312546 | Chang et al. | Dec 2010 | A1 |
20110007174 | Bacivarov et al. | Jan 2011 | A1 |
20110010171 | Talwar et al. | Jan 2011 | A1 |
20110010319 | Harada | Jan 2011 | A1 |
20110010424 | Fox et al. | Jan 2011 | A1 |
20110016333 | Scott et al. | Jan 2011 | A1 |
20110023111 | Gunadisastra et al. | Jan 2011 | A1 |
20110043490 | Powell et al. | Feb 2011 | A1 |
20110055901 | Karaoguz et al. | Mar 2011 | A1 |
20110055935 | Karaoguz et al. | Mar 2011 | A1 |
20110064331 | Andres Del Valle | Mar 2011 | A1 |
20110071841 | Fomenko et al. | Mar 2011 | A1 |
20110081023 | Raghuvanshi et al. | Apr 2011 | A1 |
20110091113 | Ito | Apr 2011 | A1 |
20110093459 | Dong et al. | Apr 2011 | A1 |
20110129159 | Cifarelli | Jun 2011 | A1 |
20110135166 | Wechsler | Jun 2011 | A1 |
20110138064 | Rieger et al. | Jun 2011 | A1 |
20110144999 | Jang et al. | Jun 2011 | A1 |
20110153324 | Ballinger et al. | Jun 2011 | A1 |
20110158536 | Nakano | Jun 2011 | A1 |
20110167181 | Minoo et al. | Jul 2011 | A1 |
20110176058 | Biswas et al. | Jul 2011 | A1 |
20110177481 | Haff et al. | Jul 2011 | A1 |
20110179182 | Vadia et al. | Jul 2011 | A1 |
20110225366 | Izadi et al. | Sep 2011 | A1 |
20110231676 | Atkins et al. | Sep 2011 | A1 |
20110283266 | Gallagher et al. | Nov 2011 | A1 |
20110289482 | Bentlye | Nov 2011 | A1 |
20110321029 | Kern et al. | Dec 2011 | A1 |
20120027311 | Cok | Feb 2012 | A1 |
20120029661 | Jones et al. | Feb 2012 | A1 |
20120030325 | Silverman et al. | Feb 2012 | A1 |
20120030682 | Shaffer et al. | Feb 2012 | A1 |
20120054624 | Owens et al. | Mar 2012 | A1 |
20120065976 | Deng | Mar 2012 | A1 |
20120066642 | Shi | Mar 2012 | A1 |
20120071174 | Bao et al. | Mar 2012 | A1 |
20120072528 | Rimac et al. | Mar 2012 | A1 |
20120076427 | Hibino et al. | Mar 2012 | A1 |
20120079372 | Kandekar et al. | Mar 2012 | A1 |
20120096121 | Hao et al. | Apr 2012 | A1 |
20120106859 | Cheatle | May 2012 | A1 |
20120144288 | Caruso et al. | Jun 2012 | A1 |
20120188382 | Morrison et al. | Jul 2012 | A1 |
20120224388 | Lin | Sep 2012 | A1 |
20120225652 | Martinez et al. | Sep 2012 | A1 |
20120232885 | Barbosa et al. | Sep 2012 | A1 |
20120235887 | Border et al. | Sep 2012 | A1 |
20120242598 | Won et al. | Sep 2012 | A1 |
20120246458 | Jain et al. | Sep 2012 | A1 |
20120253802 | Heck et al. | Oct 2012 | A1 |
20120254086 | Deng | Oct 2012 | A1 |
20120254161 | Zhang et al. | Oct 2012 | A1 |
20120254227 | Heck et al. | Oct 2012 | A1 |
20120256967 | Baldwin et al. | Oct 2012 | A1 |
20120265531 | Bennett | Oct 2012 | A1 |
20120266140 | Bates | Oct 2012 | A1 |
20120269355 | Chandak et al. | Oct 2012 | A1 |
20120271617 | Nakajima et al. | Oct 2012 | A1 |
20120278430 | Lehane et al. | Nov 2012 | A1 |
20120290293 | Hakkani-Tur et al. | Nov 2012 | A1 |
20120303565 | Deng et al. | Nov 2012 | A1 |
20120308124 | Belhumeur et al. | Dec 2012 | A1 |
20120310523 | Delling et al. | Dec 2012 | A1 |
20120313865 | Pearce | Dec 2012 | A1 |
20120317197 | De Foy et al. | Dec 2012 | A1 |
20120324069 | Nori et al. | Dec 2012 | A1 |
20120327040 | Simon et al. | Dec 2012 | A1 |
20120327042 | Harley et al. | Dec 2012 | A1 |
20120330887 | Young et al. | Dec 2012 | A1 |
20120331102 | Ertugrul | Dec 2012 | A1 |
20120331111 | Wu et al. | Dec 2012 | A1 |
20130013936 | Lin et al. | Jan 2013 | A1 |
20130014050 | Queru | Jan 2013 | A1 |
20130016055 | Chuang | Jan 2013 | A1 |
20130019175 | Kotler et al. | Jan 2013 | A1 |
20130021373 | Vaught et al. | Jan 2013 | A1 |
20130031476 | Coin et al. | Jan 2013 | A1 |
20130058274 | Scherzer et al. | Mar 2013 | A1 |
20130065576 | Basir | Mar 2013 | A1 |
20130073725 | Bordeleau et al. | Mar 2013 | A1 |
20130078869 | Golko et al. | Mar 2013 | A1 |
20130085756 | Chotimongkol et al. | Apr 2013 | A1 |
20130086461 | Ashley-Rollman et al. | Apr 2013 | A1 |
20130086507 | Poston et al. | Apr 2013 | A1 |
20130091205 | Kotler et al. | Apr 2013 | A1 |
20130091440 | Kotler et al. | Apr 2013 | A1 |
20130091453 | Kotler | Apr 2013 | A1 |
20130091465 | Kikin-Gil et al. | Apr 2013 | A1 |
20130091534 | Gilde et al. | Apr 2013 | A1 |
20130094445 | De Foy et al. | Apr 2013 | A1 |
20130097481 | Kotler et al. | Apr 2013 | A1 |
20130097490 | Kotler et al. | Apr 2013 | A1 |
20130106725 | Bakken et al. | May 2013 | A1 |
20130106740 | Yilmaz et al. | May 2013 | A1 |
20130106977 | Chu et al. | May 2013 | A1 |
20130108065 | Mullins et al. | May 2013 | A1 |
20130115821 | Golko et al. | May 2013 | A1 |
20130117470 | Terlizzi et al. | May 2013 | A1 |
20130117658 | Fidler et al. | May 2013 | A1 |
20130127982 | Zhang et al. | May 2013 | A1 |
20130128364 | Wheeler et al. | May 2013 | A1 |
20130132614 | Bajpai et al. | May 2013 | A1 |
20130138436 | Yu | May 2013 | A1 |
20130148864 | Dolson et al. | Jun 2013 | A1 |
20130151441 | Archambeau | Jun 2013 | A1 |
20130151975 | Shadi et al. | Jun 2013 | A1 |
20130152092 | Yadgar | Jun 2013 | A1 |
20130156275 | Amacker et al. | Jun 2013 | A1 |
20130159021 | Felsher | Jun 2013 | A1 |
20130166742 | Wiener et al. | Jun 2013 | A1 |
20130173604 | Li et al. | Jul 2013 | A1 |
20130174047 | Sivakumar et al. | Jul 2013 | A1 |
20130185065 | Tzirkel-Hancock et al. | Jul 2013 | A1 |
20130188032 | Vertegaal | Jul 2013 | A1 |
20130191781 | Radakovitz et al. | Jul 2013 | A1 |
20130212484 | Joshi et al. | Aug 2013 | A1 |
20130217414 | Nagaraj | Aug 2013 | A1 |
20130226587 | Cheung | Aug 2013 | A1 |
20130227398 | Bolstad | Aug 2013 | A1 |
20130227415 | Gregg et al. | Aug 2013 | A1 |
20130231862 | Delling et al. | Sep 2013 | A1 |
20130234913 | Thangadorai et al. | Sep 2013 | A1 |
20130238729 | Holzman et al. | Sep 2013 | A1 |
20130238819 | Oljaca et al. | Sep 2013 | A1 |
20130242964 | Hassan et al. | Sep 2013 | A1 |
20130243328 | Irie | Sep 2013 | A1 |
20130252636 | Chang et al. | Sep 2013 | A1 |
20130254412 | Menezes et al. | Sep 2013 | A1 |
20130266196 | Kono | Oct 2013 | A1 |
20130275779 | He | Oct 2013 | A1 |
20130293530 | Perez et al. | Nov 2013 | A1 |
20130297700 | Hayton et al. | Nov 2013 | A1 |
20130298185 | Koneru et al. | Nov 2013 | A1 |
20130321390 | Latta et al. | Dec 2013 | A1 |
20130335301 | Wong et al. | Dec 2013 | A1 |
20130346494 | Nakfour et al. | Dec 2013 | A1 |
20140004741 | Jol et al. | Jan 2014 | A1 |
20140006420 | Sparrow et al. | Jan 2014 | A1 |
20140007215 | Romano et al. | Jan 2014 | A1 |
20140019626 | Hubler et al. | Jan 2014 | A1 |
20140019896 | Satterfield | Jan 2014 | A1 |
20140025380 | Koch et al. | Jan 2014 | A1 |
20140029859 | Libin | Jan 2014 | A1 |
20140046914 | Das et al. | Feb 2014 | A1 |
20140050419 | Lerios et al. | Feb 2014 | A1 |
20140072242 | Wei et al. | Mar 2014 | A1 |
20140075523 | Tuomaala et al. | Mar 2014 | A1 |
20140107921 | Delling et al. | Apr 2014 | A1 |
20140108979 | Davidson et al. | Apr 2014 | A1 |
20140157169 | Kikin-gil | Jun 2014 | A1 |
20140173602 | Kikin-gil et al. | Jun 2014 | A1 |
20140181708 | Kikin-gil et al. | Jun 2014 | A1 |
20140210797 | Kreek et al. | Jul 2014 | A1 |
20140253522 | Cueto | Sep 2014 | A1 |
20140257803 | Yu et al. | Sep 2014 | A1 |
20140258405 | Perkin | Sep 2014 | A1 |
20140297412 | Fong et al. | Oct 2014 | A1 |
20140341443 | Cao | Nov 2014 | A1 |
20140359593 | Cohen et al. | Dec 2014 | A1 |
20140372112 | Xue et al. | Dec 2014 | A1 |
20140379326 | Sarikaya et al. | Dec 2014 | A1 |
20140379353 | Boies et al. | Dec 2014 | A1 |
20150255061 | Xue et al. | Sep 2015 | A1 |
20150255069 | Adams et al. | Sep 2015 | A1 |
20150277682 | Kaufthal | Oct 2015 | A1 |
20150277708 | Rodrig et al. | Oct 2015 | A1 |
20150278191 | Levit et al. | Oct 2015 | A1 |
20150310040 | Chan et al. | Oct 2015 | A1 |
20150310261 | Lee et al. | Oct 2015 | A1 |
20150310858 | Li et al. | Oct 2015 | A1 |
20150317147 | Nachimuthu et al. | Nov 2015 | A1 |
20150317313 | Lv et al. | Nov 2015 | A1 |
20150317510 | Lee | Nov 2015 | A1 |
20150324555 | Burba et al. | Nov 2015 | A1 |
20150324556 | Hunt et al. | Nov 2015 | A1 |
20150324601 | Burba et al. | Nov 2015 | A1 |
20150325236 | Levit | Nov 2015 | A1 |
20150327068 | Hunt et al. | Nov 2015 | A1 |
20150331240 | Poulos | Nov 2015 | A1 |
20150331463 | Obie et al. | Nov 2015 | A1 |
20150347120 | Garg et al. | Dec 2015 | A1 |
20150347274 | Taylor | Dec 2015 | A1 |
20150347734 | Beigi | Dec 2015 | A1 |
20150350333 | Cutler et al. | Dec 2015 | A1 |
20150356759 | Delling et al. | Dec 2015 | A1 |
20150363919 | Suri et al. | Dec 2015 | A1 |
20150371409 | Negrila et al. | Dec 2015 | A1 |
20150373475 | Raghuvanshi et al. | Dec 2015 | A1 |
20150373546 | Haugen et al. | Dec 2015 | A1 |
20150378515 | Powell | Dec 2015 | A1 |
Number | Date | Country |
---|---|---|
101753404 | Jun 2010 | CN |
0704655 | Apr 1996 | EP |
0553101 | Jul 1997 | EP |
0816981 | Jul 1998 | EP |
1055872 | Nov 2000 | EP |
1174787 | Jan 2002 | EP |
1331566 | Jul 2003 | EP |
1628197 | Feb 2006 | EP |
1965389 | Sep 2008 | EP |
1970803 | Sep 2008 | EP |
2096577 | Sep 2009 | EP |
2267655 | Dec 2010 | EP |
2312462 | Apr 2011 | EP |
2482572 | Aug 2012 | EP |
2575128 | Apr 2013 | EP |
2650752 | Oct 2013 | EP |
2701457 | Feb 2014 | EP |
2431001 | Apr 2007 | GB |
2002091477 | Mar 2002 | JP |
20040076079 | Aug 2004 | KR |
20130022513 | Mar 2013 | KR |
WO-9304468 | Mar 1993 | WO |
WO-0250590 | Jun 2002 | WO |
WO-2005013262 | Feb 2005 | WO |
WO-2005033934 | Apr 2005 | WO |
WO-2008124181 | Oct 2008 | WO |
WO-2009015047 | Jan 2009 | WO |
WO-2009082814 | Jul 2009 | WO |
WO-2009089308 | Jul 2009 | WO |
WO-2009128021 | Oct 2009 | WO |
WO-2010141403 | Dec 2010 | WO |
WO-2011014138 | Feb 2011 | WO |
WO-2012152817 | Nov 2012 | WO |
WO-2013008026 | Jan 2013 | WO |
WO-2013048510 | Apr 2013 | WO |
WO-2013154561 | Oct 2013 | WO |
WO-2013171481 | Nov 2013 | WO |
WO-2013184225 | Dec 2013 | WO |
Entry |
---|
Adams, “The Next Generation of USB Connector Will Plug in Either Way”, Retrieved From: <http://www.popsci.com/article/gadgets/next-generation-usb-connector-will-plug-either-way> May 16, 2014, Dec. 4, 2013, 3 Pages. |
Hughes, “Apple's Lightning Port Dynamically Assigns Pins to Allow for Reversible Use”, Retrieved From: <http://appleinsider.com/articles/12/09/25/apples—lightning—port—dynamically—assigns—pins—to—allow—for—reversible—use> May 16, 2014, Sep. 25, 2012, 9 pages. |
“Acoustics—Measurement of room acoustic parameters—Part 1: Performance spaces”, In ISO 3382-1:2009, May 6, 2014, 2 pages. |
“Centrally Managed Wireless Networks”, Retrieved From: <http://www.burconix.com/?p=services-centrally-managed-wireless> Nov. 18, 2013, Sep. 5, 2013, 2 Pages. |
“Cisco Bring Your Own Device”, Available at: http://www.cisco.com/c/en/us/td/docs/solutions/Enterprise/Borderless—Networks/Unified—Access/byodwp.html, Mar. 2014, 23 Pages. |
“Connectify pro Full+Key 7 MB”, Retrieved From: <http://zonreturn.blogspot.mx/2013/05/connectify-pro-fullkey-7-mb.html> Nov. 14, 2013, May 14, 2013, 5 Pages. |
“Connecting to Multiple 802.11 Networks from One WiFi Card Simultaneously”, Retrieved From: <http://marketplace.yet2.com/app/insight/techofweek/38576> Nov. 18, 2013, Jun. 20, 2012, 2 Pages. |
“Debug Navigator Help: Using Debug Gauges”, https://developer.apple.com/library/mac/recipes/xcode—help-debug—navigator/articles/using—debug—gauges.html#//apple—ref/doc/uid/TP40010432-CH8-SW1, May 28, 2014, 3 pages. |
“Deployment Planning Tips for Office 365”, http://technet.microsoft.com/en-us/library/hh852435.aspx, Oct. 14, 2012, 7 pages. |
“Failover Cluster Step-by-Step Guide: Validating Hardware for a Failover Cluster”, http://technet.microsoft.com/en-us/library/cc732035(v=ws.10).aspx, Mar. 20, 2011, 10 pages. |
“Get history and other info about your code”, <<http://msdn.microsoft.com/en-us/library/dn269218.aspx>>, retrieved May 23, 2014,, 10 pages. |
“How to Set Up a Wireless Hotspot—From Ethernet (Windows 7)”, Available At: <http://www.instructables.com/id/How-to-Set-Up-a-Wireless-Hotspot-Windows-7/>, Apr. 3, 2012, 8 pages. |
“Interactive 3D Audio Rendering Guidelines, Level 2.0”, In proceedings of 3D Working Group of the Interactive Audio Special Interest Group, Sep. 20, 1999, 29 pages. |
“Interest Point Detection”, Available at: http://en.wikipedia.org/wiki/Interest—point—detection, Apr. 21, 2014, 3 pages. |
“Lifecycle Services for Microsoft Dynamics User Guide (LCS) [AX 2012]”, Available at: http://technet.microsoft.com/en-us/library/dn268616.aspx, Aug. 8, 2013, 5 pages. |
“Low-Footprint Adaptation and Personalization fora Deep Neural Network”, U.S. Appl. No. 14/201,704, filed Mar. 7, 2014, 20 pages. |
“Microsoft CodeLens Code Health Indicator extension”, <<https://developer.apple.com/library/ios/documentation/ToolsLanguages/Conceptual/Xcode—Overview/DebugYourApp/DebugYourApp.html>>, Mar. 10, 2014, 13 pages. |
“New CodeLens Indicator—Incoming Changes”, <<http://msdn.microsoft.com/en-us/library/dn269218.aspx>>, retrieved May 23, 2014,, 8 pages. |
“Secure Separation in Cisco Unified Data Center Architecture”, Available at: http://www.cisco.com/en//solutions/collateral/ns340/ns414/ns742/ns743/ns1050/white—paper—c11-722425.html, Oct. 1, 2013, 8 pages. |
“Shared Hidden Layer Combination for Speech Recognition Systems”, U.S. Appl. No. 14/265,110, filed Apr. 29, 2014, 22 pages. |
“Types of vCloud Hybrid Service”, Available at: http://pubs.vmware.com/vchs/index.jsp?topic=%2FGUID-FD4D5E84-1AB8-4A1B-8C3F-769176FCD154%2FGUID-375065F3-110A-4B84-99FA-FB8467361960.html, Dec. 16, 2012, 2 pages. |
“UI Element Guidelines: Menus”, Available at: https://developer.apple.com/library/mac/documentation/userexperience/conceptual/applehiguidelines/Menus/Menus.html, Sep. 26, 2011, 22 pages. |
“Unified Communications Interoperability Forum and Open Networking Foundation Announce Collaborative Relationship Between Unified Communications and Software-Defined Networks”, Retrieved From: <http://www.businesswire.com/news/home/20131120005275/en/Unified-Communications-Interoperability-Forum-Open-Networking-Foundation> Mar. 7, 2014, Nov. 20, 2013, 2 Pages. |
“Unified Communications Managed API 3.0 Core SDK Documentation”, retrieved from: http://msdn.microsoft.com/en-us/library/gg421023.aspx on Feb. 14, 2012, Dec. 1, 2011, 2 pages. |
“Xcode OpenGL ES Tools Overview”, Retrieved on: Jun. 5, 2014 Available at: https://developer.apple.com/library/prerelease/ios/documentation/3DDrawing/Conceptual/OpenGLES—ProgrammingGuide/ToolsOverview/ToolsOverview.html, 10 pages. |
Abad, et al.,' “Context Dependent Modelling Approaches for Hybrid Speech Recognizers”, In Proceeding of Interspeech, Sep. 26, 2010, 4 pages. |
Abdel-Hamid, et al.,' “Fast Speaker Adaptation of Hybrid NN/HMM Model for Speech Recognition Based on Discriminative Learning of Speaker Code”, In IEEE International Conference on Acoustics, Speech and Signal Processing, May 26, 2013, 5 pages. |
Abid, et al.,' “A New Neural Network Pruning Method Based on the Singular Value Decomposition and the Weight Initialization”, In Proceedings of 11th European Signal Processing Conference, Sep. 3, 2002, 4 pages. |
Ajdler, et al.,' “The Plenacoustic Function and Its Sampling”, In IEEE Transactions on Signal Processing, vol. 54, Issue 10, Oct. 2006, 35 pages. |
Ajmani, et al.,' “Scheduling and Simulation: How to Upgrade Distributed Systems”, In Proceedings of the 9th conference on Hot Topics in Operating Systems, vol. 9., May 18, 2013, 6 pages. |
Al-Hazmi, et al.,' “Virtualization of 802.11 Interfaces for Wireless Mesh Networks”, In Proceeding: Eighth International Conference on Wireless On-Demand Network Systems and Services, Computer Networks and Computer Communications Lab University of Passau, 94032 Passau, Germany,Jan. 26, 2011, pp. 44-51. |
Al-Kanj, et al.,' “Optimized Energy Efficient Content Distribution over Wireless Networks with Mobile-to-Mobile Cooperation”, In Proceeding: The IEEE 17th International Conference on Telecommunications, Department of Electrical and Computer Engineering, American University of Beirut,Apr. 4, 2010, pp. 471-475. |
Alt et al.,' “Increasing the User's Attention on the Web: Using Implicit Interaction Based on Gaze Behavior to Tailor Content”, In Proceedings of the 7th Nordic Conference on Human-Computer Interaction—Making Sense through Design, Oct. 14, 2012, 10 pages. |
Ananthanarayanan, et al.,' “Collaborative Downloading for Multi-homed Wireless Devices”, In Proceedings: Eighth IEEE Workshop on Mobile Computing Systems and Applications, Mar. 8, 2007, pp. 79-84. |
Ananthanarayanan, et al.,' “Combine: Leveraging the Power of Wireless Peers through Collaborative Downloading”, In Proceedings: The 5th International Conference on Mobile Systems, Applications and Services, Jun. 11, 2007, pp. 286-298. |
Azizyan, et al.,' “SurroundSense: Mobile Phone Localization via Ambience Fingerprinting”, In Proceedings of the 15th annual international conference on Mobile computing and networking, Sep. 20, 2009, 12 pages. |
Barman, et al.,' “Nonnegative Matrix Factorization (NMF) Based Supervised Feature Selection and Adaptation”, In Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning, Nov. 2, 2008, 2 pages. |
Beymer, et al.,' “WebGazeAnalyzer: A System for Capturing and Analyzing Web Reading Behavior Using Eye Gaze”, In Proceedings of Extended Abstracts on Human Factors in Computing Systems, Apr. 2, 2005, 10 pages. |
Bonzi, et al.,' “The Use of Anaphoric Resolution for Document Description in Information Retrieval”, In Proceedings of Information Processing & Management, vol. 25, Issue 4, Jun. 1989, 14 pages. |
Bradley, et al.,' “Accuracy and Reproducibility of Auditorium Acoustics Measures”, In Proceedings of British Institute of Acoustics, vol. 10, May 6, 2014, 2 pages. |
Broder, “A Taxonomy of Web Search”, In Proceedings of ACM SIGIR Forum, vol. 36, Issue 2, Sep. 2002, 8 pages. |
Burges, “From Ranknet to Lambdarank to Lambdamart: An Overview”, In Microsoft Research Technical Report MSR-TR-2010-82, Jun. 23, 2010, 19 pages. |
Burges, “Learning to Rank with Nonsmooth Cost Functions”, In Proceedings of the Advances in Neural Information Processing Systems, Dec. 2006, 8 pages. |
Buscher, et al.,' “Generating and Using Gaze-Based Document Annotations”, In Proceedings of Extended Abstracts on Human Factors in Computing Systems, Apr. 5, 2008, 6 pages. |
Calamia, “Advances in Edge-Diffraction Modeling for Virtual-Acoustic Simulations”, In Doctoral Dissertation of Princeton University, Jun. 2009, 159 pages. |
Calian, “Passage-Level Evidence in Document Retrieval”, In Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul. 3, 1994, 9 Pages. |
Castro, et al.,' “A Probabilistic Room Location Service for Wireless Networked Environments”, In Proceedings of the 3rd international conference on Ubiquitous Computing, Sep. 30, 2001, 19 pages. |
Chandak, et al.,' “AD-Frustum: Adaptive Frustum Tracing for Interactive Sound Propagation”, In IEEE Transactions on Visualization and Computer Graphics, vol. 14, Issue 6, Nov. 2008, 8 pages. |
Chandra, et al.,' “MultiNet: Connecting to Multiple IEEE 802.11 Networks Using a Single Wireless Card”, In Proceedings: IEEE INFOCOM, The 23rd Annual Joint Conference of the IEEE Computer and Communications Societies, Mar. 7, 2004, 12 Pages. |
Chen, “Building Language Model on Continuous Space using Gaussian Mixture Models”, In Proceedings of Research in Language Modeling, Jan. 2007, 66 pages. |
Cheng, et al.,' “Entityrank: Searching Entities Directly and Holistically”, In Proceedings of the 33rd International Conference on Very Large Data Bases, Sep. 23, 2007, 12 pages. |
Cheng, et al.,' “Heritage and Early History of the Boundary Element Method”, In Proceedings of Engineering Analysis with Boundary Elements, vol. 29, Issue 3, Mar. 2005, 35 pages. |
Chi, et al.,' “Visual Foraging of Highlighted Text: An Eye-Tracking Study”, In Proceedings of the 12th International Conference on Human-Computer Interaction—Intelligent Multimodal Interaction Environments, Jul. 22, 2007, 10 pages. |
Choi, et al.,' “Face Annotation for Personal Photos Using Collaborative Face Recognition in Online Social Networks”, In 16th International Conference on Digital Signal Processing, Jul. 5, 2009, 8 pages. |
Choudhury, et al.,' “A Framework for Robust Online Video Contrast Enhancement Using Modularity Optimization”, In IEEE Transactions on Circuits and Systems for Video Technology, vol. 22 , Issue: 9, Sep. 2012, 14 pages. |
Clarke, “Exploiting Redundancy in Question Answering”, In Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Sep. 9, 2001, 8 pages. |
Cucerzan, “Large-Scale Named Entity Disambiguation Based on Wikipedia Data”, In Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Jun. 28, 2007, 9 Pages. |
Dahl, et al.,' “Context-Dependent Pre-Trained Deep Neural Networks for Large Vocabulary Speech Recognition”, In IEEE Transactions on Audio, Speech, and Language Processing, vol. 20, Issue 1, Jan. 1, 2012, 13 pages. |
Dahl, et al.,' “Large Vocabulary Continuous Speech Recognition with Context-Dependent DBN-HMMs”, In IEEE International Conference on Acoustics, Speech and Signal Processing, May 22, 2011, 4 pages. |
Davis, et al.,' “Low-Rank Approximations for Conditional Feedforward Computation in Deep Neural Networks”, In Proceedings of ArXiv preprint arXiv: 1312.4461, Dec. 2013, 10 Pages. |
Edens, et al.,' “An Investigation of Broad Coverage Automatic Pronoun Resolution for Information Retrieval”, In Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul. 28, 2003, 2 pages. |
Elrakabawy, et al.,' “Peer-to-Peer File Transfer in Wireless Mesh Networks”, In Proceeding: The Fourth Annual Conference on Wireless on Demand Network Systems and Services, University of Leipzig Department of Computer Science Augustusplatz 10-11 04109 Leipzig, Germany,Jan. 24, 2007, pp. 114-121. |
Fang, et al.,' “A Formal Study of Information Retrieval Heuristics”, In Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul. 25, 2004, 8 pages. |
Ferguson, “Five Key Criteria for adaptable SDN Wi-Fi”, Retrieved From: <http://www.extremenetworks.com/five-key-criteria-for-adaptable-sdn-wi-fi/> Mar. 7, 2014, Nov. 25, 2013, 7 Pages. |
Finkel, “Incorporating Non-Local Information into Information Extraction Systems by Gibbs Sampling”, In Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, Jun. 2005, 8 pages. |
Fiore, et al.,' “Information Density Estimation for Content Retrieval in MANETs”, In Proceedings: The IEEE Transactions on Mobile Computing, vol. 8, Issue 3, Mar. 2009, pp. 289-303. |
Florescu, et al.,' “Towards a Peer-Assisted Content Delivery Architecture”, In Proceedings: The 18th International Conference on Control Systems and Computer Science, May 2011, 8 pages. |
Funkhouser, et al.,' “A Beam Tracing Method for Interactive Architectural Acoustics”, In Journal of the Acoustical Society of America, Feb. 2004, 18 pages. |
Funkhouser, et al.,' “Realtime Acoustic Modeling for Distributed Virtual Environments”, In Proceedings of the 26th annual conference on Computer graphics and interactive techniques, Jul. 1, 1999, 10 pages. |
Gade, “Acoustics in Halls for Speech and Music”, In Springer Handbook of Acoustics, May 6, 2014, 8 pages. |
Gemello, et al.,' “Adaptation of Hybrid ANN/HMM Models Using Linear Hidden Transformations and Conservative Training”, In IEEE International Conference on Acoustics, Speech and Signal Processing, May 14, 2006, 4 pages. |
Goldstein, et al.,' “Summarizing Text Documents: Sentence Selection and Evaluation Metrics”, In Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Aug. 1, 1999, 8 pages. |
Gruenstein, et al.,' “Context-Sensitive Language Modeling for Large Sets of Proper Nouns in Multimodal Dialogue Systems”, In Proceedings of IEEE/ACL Workshop on Spoken Language Technology, Dec. 10, 2006, 4 pages. |
Gumerov, et al.,' “Fast multipole methods on graphics processors”, In Journal of Computational Physics, vol. 227, Issue 18, Sep. 10, 2008, 4 pages. |
Harper, et al.,' “A Language Modelling Approach to Relevance Profiling for Document Browsing”, In Proceedings of the 2nd ACM/IEEE-CS Joint Conference on Digital Libraries, Jul. 13, 2007, 8 pages. |
Harper, et al.,' “Within-Document Retrieval: A User-Centered Evaluation of Relevance Profiling”, In Journal of Information Retrieval, vol. 7, Issue 3-4, Sep. 2004, 26 pages. |
Harris, “On the use of windows for harmonic analysis with the discrete Fourier transform”, In Proceedings of the IEEE vol. 66, Issue 1, Jan. 1978, 33 pages. |
Hawamdeh, et al.,' “Paragraph-based nearest neighbor searching in full-text documents”, In Proceedings of Electronic Publishing, vol. 2, Dec. 1989, 14 pages. |
Hearst, “Tilebars: Visualization of Term Distribution Information in Full Text Information Access”, In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, May 7, 1995, 8 pages. |
Heck, et al.,' “Robustness to Telephone Handset Distortion in Speaker Recognition by Discriminative Feature Design”, In Journal of Speech Communication—Speaker Recognition and its Commercial and Forensic Applications, vol. 31, Issue 2-3, Jun. 2000, 12 pages. |
Hefeeda, “A Framework for Cost-Effective Peer-to-Peer Content Distribution”, In Proceedings: The Eleventh ACM International Conference on Multimedia, Department of Computer Sciences Purdue University, West Lafayette, IN 47907,Nov. 2, 2003, 2 Pages. |
Hinton, et al.,' “Deep Neural Networks for Acoustic Modeling in Speech Recognition”, In IEEE Signal Processing Magazine, vol. 29, Issue 6, Nov. 2012, 27 pages. |
Hodgson, et al.,' “Experimental evaluation of radiosity for room sound-field prediction”, In the Journal of the Acoustical Society of America, Aug. 2006, 12 pages. |
Hsu, et al.,' “HBCI: Human-Building-Computer Interaction”, In Proceedings of the 2nd ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Building, Nov. 2, 2010, 6 pages. |
Jacob, “QR Directory App—Overview”, In Blog of Josh Jacob Dev, Apr. 21, 2011, 3 pages. |
Jaiswal, et al.,' “Bulk Content Delivery Using Co-Operating End-Nodes with Upload/Download Limits”, In Proceedings: Fifth International Conference on Communication Systems and Networks, Bell Labs Research India, Bangalore, India,Sep. 10, 2012, 11 Pages. |
Jaitly, et al.,' “Application of Pretrained Deep Neural Networks to Large Vocabulary Conversational Speech Recognition”, In Proceedings of 13th Annual Conference of the International Speech Communication Association, Mar. 12, 2012, 11 pages. |
Jluedemann, “Networking & wireless forum: How to set up Dual Network Adapters”, Retrieved From: <http://forums.cnet.com/7723-7589—102-531538/how-to-set-up-dual-network-adapters%20Internet%20is%20only%20available%20via%20an%20ATT%20MiFi%20hot%20spot.> Nov. 14, 2013, Jun. 27, 2011, 3 Pages. |
Jones, “Automatic Summarising: The state of the Art”, In Journal of Information Processing and Management: an International Journal, vol. 43, Issue 6, Nov. 1, 2007, 52 pages. |
Kaszkiel, et al.,' “Effective Ranking with Arbitrary Passages”, In Journal of the American Society for Information Science and Technology, vol. 52, Issue 4, Feb. 15, 2001, 21 pages. |
Kaszkiel, et al.,' “Efficient Passage Ranking for Document Databases”, In Journal of ACM Transactions on Information Systems, Oct. 1, 1999, 26 pages. |
Keller, et al.,' “MicroCast: Cooperative Video Streaming on Smartphones”, In Proceedings: The 10th International Conference on Mobile Systems, Applications, and Services, Jun. 25, 2012, 13 pages. |
Kolarik, et al.,' “Perceiving Auditory Distance Using Level and Direct-to-Reverberant Ratio Cues”, In the Journal of the Acoustical Society of America, Oct. 2011, 4 pages. |
Konig, et al.,' “Nonlinear Discriminant Feature Extraction for Robust Text-Independent Speaker Recognition”, In Proceeding of the RLA2C, ESCA workshop on Speaker Recognition and its Commercial and Forensic Applications, Apr. 1998, 4 pages. |
Koo, et al.,' “Autonomous Construction of a WiFi Access Point Map Using Multidimensional Scaling”, In Proceedings of the 9th international conference on Pervasive computing, Jun. 12, 2011, 18 pages. |
Krokstad, “The Hundred Years Cycle in Room Acoustic Research and Design”, In Proceedings of Reflections on sound, Jun. 2008, 30 pages. |
Kumar, et al.,' “Gaze-Enhanced Scrolling Techniques”, In Proceedings of the 20th Annual ACM Symposium on User Interface Software and Technology, Oct. 2007, 4 pages. |
Kuttruff, “Room Acoustics, Fourth Edition”, Available at: http://www.crcpress.com/product/isbn/9780419245803, Aug. 3, 2000, 1 page. |
Laflen, et al.,' “Introducing New Features in the VSTS Database Edition GDR”, http://msdn.microsoft.com/en-us/magazine/dd483214.aspx, Nov. 2008, 16 pages. |
Lavrenko, et al.,' “Relevance-Based Language Models”, In Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Sep. 9, 2001, 8 pages. |
Lecouteux, et al.,' “Dynamic Combination of Automatic Speech Recognition Systems By Driven Decoding”, In Journal of IEEE Transactions on Audio, Speech and Language Processing, Jan. 2013, 10 pages. |
Li et al.,' “Roles of Pre-Training and Fine-Tuning in Context-Dependent DBN-HMMs for Real-Word Speech Recognition”, In Proceeding of NIPS Workshop on Deep Learning and Unsupervised Feature Learning, Dec. 2010, 8 pages. |
Li, et al.,' “Lattice Combination for Improved Speech Recognition”, In Proceedings of the 7th International Conference of Spoken Language Processing, Sep. 16, 2002, 4 pages. |
Li, et al.,' “Spatial Sound Rendering Using Measured Room Impulse Responses”, In IEEE International Symposium on Signal Processing and Information Technology, Aug. 27, 2006, 5 pages. |
Liao, “Speaker Adaptation of Context Dependent Deep Neural Networks”, In IEEE International Conference on Acoustics, Speech and Signal Processing, May 26, 2013, 5 pages. |
Lin, et al.,' “What Makes a Good Answer? The Role of Context in Question Answering”, In Proceedings of the Ninth IFIP TC13 International Conference on Human-Computer Interaction, Sep. 2003, 8 pages. |
Liu, et al.,' “Use of Contexts in Language Model Interpolation and Adaptation”, In Journal of Computer Speech and Language vol. 27 Issue 1, Feb. 2009, 23 pages. |
Loizides, et al.,' “The Myth of Find: User Behaviour and Attitudes Towards the Basic Search Feature”, In Proceedings of the 8th ACM/IEEE-CS Joint Conference on Digital Libraries, Jun. 16, 2008, 4 pages. |
Luo, et al.,' “UCAN: A Unified Cellular and AdHoc Network Architecture”, In Proceedings: Ninth Annual International Conference on Mobile Computing and Networking, Sep. 14, 2013, 15 pages. |
Lv, et al.,' “A Comparative Study of Methods for Estimating Query Language Models with Pseudo Feedback”, In Proceedings of the 18th ACM Conference on Information and Knowledge Management, Nov. 2, 2009, 4 pages. |
Lv, et al.,' “Positional Language Models for Information Retrieval”, In Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul. 19, 2009, 8 pages. |
Machiraju, et al.,' “Designing Multitenant Applications on Windows Azure”, Available at: http://msdn.microsoft.com/en-us/library/windowsazure/hh689716.aspx, Apr. 18, 2013, 20 pages. |
Manetti, et al.,' “Next Generation CDN services for Community Networks”, In Proceedings: The Third International Conference on Next Generation Mobile Applications, Services and Technologies, Sep. 15, 2009, pp. 89-94. |
Mavridis, et al.,' “Friends with Faces: How Social Networks Can Enhance Face Recognition and Vice Versa”, In Proceedings of Computational Social Networks Analysis: Trends, Tools and Research Advances, May 24, 2010, 30 pages. |
Mehra, et al.,' “An efficient GPU-based time domain solver for the acoustic wave equation”, In Proceedings of Applied Acoustics, vol. 73, Issue 2, Feb. 2012, 13 pages. |
Mehra, et al.,' “Wave-Based Sound Propagation in Large Open Scenes Using an Equivalent Source Formulation”, In Journal of ACM transactions on Graphics, vol. 32, Issue 2, Apr. 1, 2013, 13 pages. |
Mehrotra, et al.,' “nterpolation of Combined Head and Room Impulse Response for Audio Spatialization”, In Proceeding of IEEE 13th International Workshop on Multimedia Signal Processing, Oct. 17, 2011, 6 pages. |
Meinedo, et al.,' “Combination of Acoustic Models in Continuous Speech Recognition Hybrid Systems”, In Proceedings of Sixth International Conference on Spoken Language Processing, Oct. 2000, 4 pages. |
Menezes, et al.,' “Session-based Device Configuration”, U.S. Appl. No. 14/257,502, 67 pages. |
Mihalcea, et al.,' “Wikify!: Linking Documents to Encyclopedic Knowledge”, In Proceedings of the Sixteenth ACM Conference on Conference on Information and Knowledge Management,, Nov. 6, 2007, 9 Pages. |
Militano, et al.,' “Group Interactions in Wireless Cooperative Networks”, In Proceedings: IEEE 73rd Conference on Vehicular Technology, May 15, 2011, 5 Pages. |
Mohamed, et al.,' “Acoustic Modeling Using Deep Belief Networks”, In IEEE Transactions on Audio, Speech, and Language Processing, vol. 20, Issue 1, Jan. 2012, 10 pages. |
Motlicek, et al.,' “Feature and Score Level Combination of Subspace Gaussinasin LVCSR Task”, In IEEE International Conference on Acoustics, Speech and Signal Processing, May 26, 2013, 5 pages. |
Na, et al.,' “A 2-Poisson Model for Probabilistic Coreference of Named Entities for Improved Text Retrieval”, In Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul. 19, 2009, 8 pages. |
Neve, et al.,' “Face Recognition for Personal Photos using Online Social Network Context and Collaboration”, In Guest Lecture at KAIST, Dec. 14, 2010, 54 pages. |
Novak, et al.,' “Use of Non-Negative Matrix Factorization for Language Model Adaptation in a Lecture Transcription Task”, In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 1, May 7, 2001, 4 pages. |
Papadopoulos, et al.,' “Image Clustering Through Community Detection on Hybrid Image Similarity Graphs”, In 17th IEEE International Conference on Image Processing, Sep. 26, 2014, 4 pages. |
Perenson, “In-depth Look at Google+ Photo Update with the Team that Designed it”, Available at: http://connect.dpreview.com/post/1400574775/hands-on-with-google-plus-photo-update, May 17, 2013, 10 pages. |
Peter, et al.,' “Frequency-domain edge diffraction for finite and infinite edges”, In Proceedings of Acta acustica united with acustica, vol. 95, No. 3, May 6, 2014, 2 pages. |
Petkova, et al.,' “Proximity-Based Document Representation for Named Entity Retrieval”, In Proceedings of the Sixteenth ACM Conference on Conference on Information and Knowledge Management, Nov. 6, 2007, 10 pages. |
Pierce, “An Introduction to Its Physical Principles and Applications”, In Acoustical Society of America, Jun. 1989, 1 page. |
Ponte, et al.,' “A Language Modelling Approach to Information Retrieval”, In Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Aug. 1, 1998, 7 pages. |
Poulos, et al.,' “Assisted Viewing of Web-based Resources”, U.S. Appl. No. 14/161,693, filed Jan. 23, 2014, 48 pages. |
Raghuvanshi, “Interactive Physically-based Sound Simulation”, In UMI Dissertation, Sep. 9, 2011, 187 Pages. |
Raghuvanshi, et al.,' “Efficient and Accurate Sound Propagation Using Adaptive Rectangular Decomposition”, In IEEE Transactions on Visualization and Computer Graphics, vol. 15, Issue 99, Feb. 13, 2009, 13 pages. |
Raghuvanshi, et al.,' “Precomputed wave simulation for real-time sound propagation of dynamic sources in complex scenes”, In Journal of ACM Transactions on Graphics, vol. 29, Issue 4, Jul. 26, 2010, 11 pages. |
Rindel, et al.,' “The Use of Colors, Animations and Auralizations in Room Acoustics”, In Internoise, Sep. 15, 2013, 9 Pages. |
Roberts, et al.,' “Evaluating Passage Retrieval Approaches for Question Answering”, In Proceedings of 26th European Conference on Information Retrieval, Apr. 14, 2003, 8 pages. |
Robertson, et al.,' “Okapi at TREC-3”, In Proceedings of Text Retrieval Conference, Jan. 24, 2014, 19 pages. |
Rouillard, “Contextual QR Codes”, In Proceedings of the Third International Multi-Conference on Computing in the Global Information Technology, Jul. 27, 2008, 6 pages. |
Sabine, “Room acoustics”, In Transactions of the IRE Professional Group on Audio, vol. 1, Issue 4, Jul. 1953, 9 pages. |
Sainath, et al.,' “Auto-Encoder Bottleneck Features Using Deep Belief Networks”, In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Mar. 25, 2012, 4 pages. |
Sainath, et al.,' “Low-Rank Matrix Factorization for Deep Neural Network Training with High-Dimensional Output Targets”, In proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, May 26, 2013, 5 pages. |
Sainath, et al.,' “Making Deep Belief Networks Effective for Large Vocabulary Continuous Speech Recognition”, In Proceedings of IEEE Workshop on Automatic Speech Recognition and Understanding, Dec. 11, 2011, 6 pages. |
Sakamoto, et al.,' “Calculation of impulse responses and acoustic parameters in a hall by the finite-difference time-domain method”, In Proceedings of Acoustical Science and Technology, vol. 29, Issue 4, Feb. 2008, 10 pages. |
Saluja, et al.,' “Context-aware Language Modeling for Conversational Speech Translation”, In Proceedings of Machine Translation Summit XIII, Sep. 19, 2011, 8 pages. |
Sarukkai, et al.,' “Improved Spontaneous Dialogue Recognition Using Dialogue and Utterance Triggers by Adaptive Probability Boosting”, In Fourth International Conference on Spoken Language, vol. 1, Oct. 3, 1996, 4 pages. |
Sato, et al.,' “Incentive Mechanism Considering Variety of User Cost in P2P Content Sharing”, In Proceeding: The IEEE Global Telecommunications Conference, Communications and Computer Engineering, Graduate School of Informatics, Kyoto Yoshidahonnmachi, Sakyo-ku, Kyoto, 606-8501 Japan,Nov. 30, 2008, 5 Pages. |
Satoh, et al.,' “Poster Abstract: Ambient Sound-based Proximity Detection with Smartphones”, In Proceedings of the 11th ACM Conference on Embedded Networked.Sensor Systems, Nov. 11, 2013, 2 pages. |
Savioja, “Real-Time 3D Finite-Difference Time-Domain Simulation of Mid-Frequency Room Acoustics”, In Proceedings of the 13th International Conference on Digital Audio Effects, Sep. 6, 2010, 8 pages. |
Savioja, et al.,' “Simulation of room acoustics with a 3-D finite difference mesh”, In Proceedings of the International Computer Music Conference, Sep. 1994, 4 pages. |
Sbai, et al.,' “P2P Content Sharing in Spontaneous Multi-Hop Wireless Networks”, In Proceedings: Second International Conference of Communication Systems and Networks, Jan. 5, 2010, 10 Pages. |
Seide, et al.,' “Conversational Speech Transcription using Context-Dependent Deep Neural Networks”, In Proceeding of 12th Annual Conference of the International Speech Communication Association, Aug. 28, 2011, 4 pages. |
Shah, et al.,' “All Smiles: Automatic Photo Enhancement by Facial Expression Analysis”, In Proceedings of Conference on Visual Media Production, Dec. 5, 2012, 10 pages. |
Shanklin, “Samsung Galaxy S4 to Feature Eye-Tracking Technology”, Available at: http://www.gizmag.com/galaxy-s4-eye-tracking-technology/26503/, Mar. 4, 2013, 5 pages. |
Shieh, et al.,' “Seawall: Performance Isolation for Cloud Datacenter Networks”, In Proceedings of the 2nd UNENIX Conference on Hot Topics in Cloud Computing, Jun. 22, 2010, 7 pages. |
Singhal, et al.,' “Pivoted Document Length Normalization”, In Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Aug. 18, 1996, 12 pages. |
Singh-Miller, et al.,' “Dimensionality Reduction for Speech Recognition Using Neighborhood Components Analysis”, In Proceedings of 8th Annual Conference of the International Speech Communication Association, Antwerp, Dec. 27, 2007, 4 pages. |
Siniscalchi, et al.,' “Hermitian Based Hidden Activation Functions for Adaptation of Hybrid HMM/ANN Models”, In Proceedings of 13th Annual Conference of the International Speech Communication Association Sep. 9, 2012, 4 pages. |
So, et al.,' “Routing and Channel Assignment in Multi-Channel Multi-Hop Wireless Networks with Single-NIC Devices”, In Proceeding: The Technical Report, Department of Computer Science, Department of Electrical and Computer Engineering, Coordinated Science Laboratory, University of Illinois at Urbana-Champaign,Dec. 2004, 12 Pages. |
Song, et al.,' “Optimal Resource Utilization in Content Distribution Networks”, In Proceedings: Technical Report of Computer Science, Dept. of Computer Science, Cornell University, Ithaca, NY 14853,Nov. 14, 2005, 14 Pages. |
Starr, “Facial recognition app matches strangers to online profiles”, Available at: http://www.cnet.com.au/facial-recognition-app-matches-strangers-to-online-profiles-339346355.htm, Jan. 7, 2014, 10 pages. |
Stettner, et al.,' “Computer Graphics Visualization for Acoustic Simulation”, In Proceedings of the 16th annual conference on Computer graphics and interactive techniques, vol. 23, No. 3, Jul. 1989, 12 pages. |
Su, et al.,' “Error Back Propagation for Sequence Training of Context-Dependent Deep Networks for Conversational Speech Transcription”, In IEEE International Conference on Acoustics, Speech, and Signal Processing, May 26, 2013, 5 pages. |
Svensson, et al.,' “The use of Ambisonics in describing room impulse responses”, In Proceedings of the International Congress on Acoustics, Apr. 2004, 4 pages. |
Swietojanski, et al.,' “Revisiting Hybrid and GMM-HMM System Combination Techniques”, In Proceeding of the IEEE International Conference on Acoustics, Speech and Signal Processing, May 26, 2013, 5 pages. |
Takala, et al.,' “Sound rendering”, In Proceedings of Siggraph Computer Graphics, Jul. 1992, 11 pages. |
Taylor, et al.,' “RESound: interactive sound rendering for dynamic virtual environments”, In Proceedings of the 17th ACM international conference on Multimedia, Oct. 19, 2009, 10 pages. |
Tellex, et al.,' “Quantitative Evaluation of Passage Retrieval Algorithms for Question Answering”, In Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul. 28, 2003, 7 pages. |
Thompson, “A review of finite-element methods for time-harmonic acoustics”, In Journal of Acoustical Society of America, vol. 119, Issue 3, Mar. 2006, 16 pages. |
Thouin, et al.,' “Video-on-Demand Networks: Design Approaches and Future Challenges”, In Proceeding: The IEEE Network, vol. 21, Issue 2, Mar. 2007, pp. 42-48. |
Tombros, et al.,' “Advantages of Query Biased Summaries in Information Retrieval”, In Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Aug. 1, 1998, 9 Pages. |
Trmal, et al.,' “Adaptation of a Feedforward Artificial Neural Network Using a Linear Transform”, In Proceedings of in Text, Speech and Dialogue, Sep. 10, 2010, 8 pages. |
Tsay, et al.,' “Personal Photo Organizer based on Automated Annotation Framework”, In 5th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, Sep. 12, 2009, 4 pages. |
Tysowski, et al.,' “Peer to Peer Content Sharing on Ad Hoc Networks of Smartphones”, In Proceedings: 7th International Conference of Wireless Communications and Mobile Computing, Jul. 4, 2011, pp. 1445-1450. |
Valimaki, et al.,' “Fifty Years of Artificial Reverberation. Audio, Speech, and Language Processing”, In IEEE Transactions on Audio, Speech, and Language Processing, vol. 20, Issue 5, Jul. 2012, 28 pages. |
Van “Transform Coding of Audio Impulse Responses”, In Master's Thesis of Delft University of Technology, Aug. 2003, 109 pages. |
Van “Unified Communication and Collaboration from the User's Perspective”, retrieved from: http://www.ucstrategies.com/unified-communications-expert-views/unified-communication-and-collaboration-from-the-users-perspective.aspx on Dec. 8, 2009, 2 pages. |
Vanhoucke, et al.,' “Improving the Speed of Neural Networks on CPUs”, In Proceedings of NIPS Workshop on Deep Learning and Unsupervised Feature Learning, Dec. 16, 2011, 8 pages. |
Wu, et al.,' “Adapting Boosting for Information Retrieval Measures”, In Journal of Information Retrieval, vol. 13, Issue 3, Jun. 1, 2010, 17 pages. |
Xu, et al.,' “User-Oriented Document Summarization through Vision-Based Eye-Tracking”, In Proceedings of the 14th International Conference on Intelligent User Interfaces, Feb. 8, 2009, 10 pages. |
Xue, et al.,' “Restructuring Deep Neural Network Acoustic Models”, U.S. Appl. No. 13/920,323, filed Jun. 18, 2013, 30 pages. |
Xue, et al.,' “Restructuring of Deep Neural Network Acoustic Models with Singular Value Decomposition”, In Proceedings of 14th Annual Conference of the International Speech Communication Association,, Aug. 25, 2013, 5 pages. |
Yan, et al.,' “A Scalable Approach to Using DSS-Derived Features in GMM-HMM Based Acoustic Modeling for LVCSR”, In Proceeding of the 14th Annual Conference of the International Speech Communication Association, Aug. 25, 2013, 5 pages. |
Yang, et al.,' “Qualifier in TREC-12 QA Main Task”, In Proceedings of the Twelfth Text Retrieval Conference, Nov. 2003, 9 Pages. |
Yao, et al.,' “Adaptation of Context-Dependent Deep Neural Networks for Automatic Speech Recognition”, In IEEE Spoken Language Technology Workshop, Dec. 2, 2012, 4 pages. |
Yeh, et al.,' “Wave-ray Coupling for Interactive Sound Propagation in Large Complex Scenes”, In Journal of ACM Transactions on Graphics, vol. 32 Issue 6, Nov. 2013, 10 pages. |
Yu, et al.,' “Exploiting Sparseness in Deep Neural Networks for Large Vocabulary Speech Recognition”, In Proceeding of IEEE International Conference on Acoustics, Speech and Signal Processing, Mar. 25, 2012, 4 pages. |
Yu, et al.,' “Improved Bottleneck Features Using Pretrained Deep Neural Networks”, In Proceedings of 12th Annual Conference of the International Speech Communication Association, Aug. 28, 2011, 4 pages. |
Yu, et al.,' “KL-Divergence Regularized Deep Neural Network Adaptation for Improved Large Vocabulary Speech Recognition”, In IEEE International Conference on Acoustics, Speech and Signal Processing, May 26, 2013, 5 pages. |
Zhai, et al.,' “A Study of Smoothing Methods for Language Models Applied to Ad Hoc Information Retrieval”, In Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Sep. 9, 2009, 9 Pages. |
Zwol, et al.,' “Prediction of Favourite Photos using Social, Visual, and Textual Signals”, In Proceedings of the International Conference on Multimedia, Oct. 25, 2010, 4 pages. |
“Creating Interactive Virtual Auditory Environments”, IEEE Computer Graphics and Applications, Aug. 2002, 10 pages. |
“Final Office Action”, U.S. Appl. No. 13/920,323, Sep. 24, 2015, 24 pages. |
“Integrated Vapor Chamber for Thermal Management of Computing Devices”, U.S. Appl. No. 14/294,040, filed Jun. 2, 2014, 27 pages. |
“International Search Report and the Written Opinion”, Application No. PCT/US2015/036595, Sep. 24, 2015, 10 pages. |
“International Search Report and the Written Opinion”, Application No. PCT/US2015/017872, Jun. 25, 2015, 11 pages. |
“International Search Report and the Written Opinion”, Application No. PCT/US2015/033545, Aug. 20, 2015, 11 pages. |
“International Search Report and the Written Opinion”, Application No. PCT/US2015/022887, Jun. 26, 2015, 12 pages. |
“International Search Report and the Written Opinion”, Application No. PCT/US2015/029334, Jul. 7, 2015, 12 pages. |
“International Search Report and the Written Opinion”, Application No. PCT/US2015/033872, Sep. 2, 2015, 12 pages. |
“International Search Report and the Written Opinion”, Application No. PCT/US2015/035219, Sep. 29, 2015, 12 pages. |
“International Search Report and the Written Opinion”, Application No. PCT/US2015/027689, Jul. 8, 2015, 13 pages. |
“International Search Report and the Written Opinion”, Application No. PCT/US2015/026971, Jul. 24, 2015, 15 pages. |
“International Search Report and the Written Opinion”, Application No. PCT/US2014/041023, Mar. 6, 2015, 17 pages. |
“International Search Report and the Written Opinion”, Application No. PCT/US2015/036767, Sep. 14, 2015, 19 pages. |
“International Search Report and the Written Opinion”, Application No. PCT/US2015/027688, Sep. 7, 2015, 9 pages. |
“International Search Report and the Written Opinion”, Application No. PCT/US2014/041014, Oct. 2, 2014, 9 pages. |
“International Search Report and Written Opinion”, Application No. PCT/US2015/031270, Sep. 4, 2015, 16 Pages. |
“Non-Final Office Action”, U.S. Appl. No. 13/923,917, May 28, 2015, 9 pages. |
“Non-Final Office Action”, U.S. Appl. No. 13/923,969, May 6, 2015, 7 pages. |
“Non-Final Office Action”, U.S. Appl. No. 14/201,704, Jul. 1, 2015, 6 pages. |
“Non-Final Office Action”, U.S. Appl. No. 14/266,795, Oct. 7, 2015, 10 pages. |
“Non-Final Office Action”, U.S. Appl. No. 14/273,100, Oct. 1, 2015, 20 pages. |
“Non-Final Office Action”, U.S. Appl. No. 14/275,724, Sep. 23, 2015, 8 pages. |
“Non-Final Office Action”, U.S. Appl. No. 14/275,761, Sep. 24, 2015, 8 pages. |
“Notice of Allowance”, U.S. Appl. No. 14/275,806, Oct. 8, 2015, 10 pages. |
“Notice of Allowance”, U.S. Appl. No. 14/312,562, Sep. 18, 2015, 13 pages. |
“Restriction Requirement”, U.S. Appl. No. 14/279,146, Sep. 3, 2015, 6 pages. |
Ajwani,“Breadth First Search on Massive Graphs”, In Proceedings of the 9th DIMACS Implementation Challenge: The Shortest Path Problem, Nov. 2006, 15 pages. |
Barrett,“Implementations of Routing Algorithms for Transportation Networks”, In Proceedings of the 9th DIMACS Implementation Challenge: The Shortest Path Problem, Nov. 2006, 19 pages. |
Belhumeur,“Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Jul. 1997, pp. 711-720. |
Bohus,“Olympus: An Open-Source Framework for Conversational Spoken Language Interface Research”, In Proceedings of the Workshop on Bridging the Gap: Academic and Industrial Research in Dialog Technologies, Apr. 2007, 8 pages. |
Cao,“Face Recognition with Learning-based Descriptor”, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2010, 8 pages. |
Chandrasekaran,“Sparse and Low-Rank Matrix Decompositions”;, IFAC Symposium on System Identification, 2009, 6 pages. |
Chen,“Bayesian Face Revisited: A Joint Formulation”, In Proceedings of the 12th European Conference on Computer Vision (ECCV), Oct. 2012, 14 pages. |
Chen,“Supplemental Material for “Bayesian Face Revisited: A Joint Formulation””, Apr. 2013, 5 pages. |
Cootes,“Modeling Facial Shape and Appearance”, Handbook of Face Recognition, Springer, New York, US, 2005, pp. 39-63. |
Davis,“Information-Theoretic Metric Learning”, In Proceedings of the 24th International Conference on Machine Learning (ICML), Jun. 2007, 8 pages. |
Delano,“Integrated Development Environments for Natural Language Processing”, Available at: http://www.textanalysis.com/TAI-IDE-WP.pdf, Oct. 2001, 13 pages. |
Delling,“Customizable Route Planning”, U.S. Appl. No. 13/152,313, filed Jun. 3, 2011, 23 pages. |
Delling,“Customizable Route Planning”, U.S. Appl. No. 13/868,135, filed Apr. 23, 2013, 33 pages. |
Delling,“Customizing Driving Directions With GPUs”, In Proceedings of the 20th Euro-Par International Conference on Parallel Processing, Aug. 2014, 12 pages. |
Delling,“High-Performance Multi-Level Graphs”, In Proceedings of the 9th DIMACS Implementation Challenge: The Shortest Path Problem, Nov. 2006, 13 pages. |
Delling,“Highway Hierarchies Star”, In Proceedings of the 9th DIMACS Implementation Challenge: The Shortest Path Problem, Nov. 2006, 29 pages. |
Demetrescu,“The Shortest Path Problem: Ninth DIMACS Implementation Challenge”, In Proceedings of DIMACS Series in Discrete Mathematics and Theoretical Computer Science, Jul. 28, 2009, 3 pages. |
Diez,“Optimization of a Face Verification System Using Bayesian Screening Techniques”, In Proceedings of the 23rd IASTED International Multi-Conference on Artificial Intelligence and Applications, Feb. 2005, pp. 427-432. |
Ding,“Handbook of Face Recognition, Chapter 12: Facial Landmark Localization”, Jan. 1, 2011, 19 pages. |
dos“LUP: A Language Understanding Platform”, A Dissertation for the Degree of Master of Information Systems and Computer Engineering, Jul. 2012, 128 pages. |
Eagle,“Common Sense Conversations: Understanding Casual Conversation using a Common Sense Database”, In Proceedings of the Artificial Intelligence, Information Access, and Mobile Computing Workshop, Aug. 2003, 6 pages. |
Edmonds,“Single-Source Shortest Paths With the Parallel Boost Graph Library”, In Proceedings of the 9th DIMACS Implementation Challenge: The Shortest Path Problem, Nov. 4, 2006, 20 pages. |
Geisberger,“Exact Routing in Large Road Networks using Contraction Hierarchies”, In Proceedings of Transportation Science, vol. 46, No. 3, Aug. 2012, 17 pages. |
Goldberg,“Better Landmarks within Reach”, In Proceedings of the 6th International Conference on Experimental Algorithms, Jun. 6, 2007, 14 Pages. |
Guillaumin,“Is that you? Metric Learning Approaches for Face Identification”, In Proceedings of 12th IEEE International Conference on Computer Vision (ICCV), Sep. 2009, 8 pages. |
He,“What is Discriminative Learning”, Discriminative Learning for Speech Recognition Theory and Practice, Achorn International, Jun. 25, 2008, 25 pages. |
Hoffmeister,“Log-linear Model Combination with Word-dependent Scaling Factors”, Human Language Technology and Pattern Recognition Computer Science Department, 2009, 4 pages. |
Huang,“Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments”, In Proceedings of the 10th European Conference on Computer Vision (ECCV), Oct. 2008, 11 pages. |
Huang,“Unified Stochastic Engine (USE) for Speech Recognition”, School of Computer Science, 1993, 4 pages. |
Ioffe,“Probabilistic Linear Discriminant Analysis”, International Journal of Computer Vision, Jun. 2001, 12 pages. |
Karpinski,“Multi-GPU Parallel Memetic Algorithm for Capacitated Vehicle Routing Problem”, Lecture Noes in Computer Science, May 8, 2014, 12 pages. |
Keshtkar,“A Corpus-based Method for Extracting Paraphrases of Emotion Terms”, Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text, 2010, 10 pages. |
Ko,“Cammia—A Context-Aware Spoken Dialog System for Mobile Environments”, In Automatic Speech Recognition and Understanding, Jul. 29, 2011, 2 pages. |
Kumar,“Attribute and Simile Classifiers for Face Verification”, In Proceedings of the 12th IEEE International Conference on Computer Vision (ICCV), Sep. 2009, 8 pages. |
Kumar,“Describable Visual Attributes for Face Verification and Image Research”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Oct. 2011, 17 pages. |
Kumar,“Face Recognition Using Gabor Wavelets”, In Proceedings of the 40th IEEE Asilomar Conference on Signals, Systems and Computers, Oct. 2006, 5 pages. |
Lanitis,“Toward Automatic Simulation of Aging Effects on Face Images”, IEEE Trans. PAML, vol. 24, No. 4, Apr. 2002, 14 pages. |
Lauther,“An Experimental Evaluation for Point-To-Point Shortest Path Calculation on Roadnetworks with Precalculated Edge-Flags”, In Proceedings of the 9th DIMACS Implementation Challenge: The Shortest Path Problem, Nov. 2006, 18 pages. |
Lee,“Intention-Based Corrective Feedback Generation using Context-Aware Model”, In Proceedings of the Second International Conference on Computer Supported Education, Apr. 7, 2010, 8 pages. |
Lei,“Face Recognition by Exploring Information Jointly in Space, Scale and Orientation”, IEEE Transactions on Image Processing, Jan. 2011, pp. 247-256. |
Li,“Bayesian Face Recognition Using Support Vector Machine and Face Clustering”, In Proceedings of the IEEE Computer Society on Computer Vision Pattern and Recognition (CVPR), Jun. 2004, 7 pages. |
Li,“Comparison of Discriminative Input and Output Transformations for Speaker Adaptation in the Hybrid NN/ HMM Systems”, In Proceedings of 11th Annual Conference of the International Speech Communication Association, Sep. 26, 2010, 4 pages. |
Li,“Probabilistic Models for Inference about Identity”, IEEE Transactions on Pattern Recognition and Machine Intelligence, Jan. 2012, 16 pages. |
Liang,“Face Alignment via Component-Based Discriminative Search”, Computer Vision, ECCV 2008, Lecture Notes in Computer Science vol. 5303, 2008, 14 pages. |
Martin,“CUDA Solutions for the SSSP Problem”, In Proceedings of 9th International Conference Baton Rouge, May 25, 2009, 10 pages. |
Moghaddam,“Bayesian Face Recognition”, The Journal of Pattern Recognition, Nov. 2000, pp. 1771-1782. |
Moreira,“Towards the Rapid Development of a Natural Language Understanding Module”, In Proceedings of the 10th International Conference on Intelligent Virtual Agents, Jan. 2011, 7 pages. |
Nguyen,“Cosine Similarity Metric Learning for Face Verification”, In Proceedings of the 10th Asian Conference on Computer Vision (ACCV), Nov. 2010, 12 pages. |
Ojala,“A Generalized Local Binary Pattern Operator for Multiresolution Gray Scale and Rotation Invariant Texture Classification”, In Proceedings of the 2nd International Conference on Advances in Pattern Recognition (ICAPR), Mar. 2001, 10 pages. |
Pascoal,“Implementations and Empirical Comparison of K Shortest Loopless Path Algorithms”, In Proceedings of the 9th DIMACS Implementation Challenge: The Shortest Path Problem, Nov. 2006, 16 pages. |
Phillips,“The Feret Evaluation Methodology for Face-Recognition Algorithms”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Oct. 2000, pp. 1090-1104. |
Powell,“Increased Accuracy Corner Cube Arrays for High Resolution Retro-Reflective Imaging Applications”, U.S. Appl. No. 62/062,732, filed Oct. 10, 2014, 46 pages. |
Raghuvanshi,“Parametric Wave Field Coding for Precomputed Sound Propagation”, Jul. 2014, 11 pages. |
Ramanan,“Local Distance Functions: A Taxonomy, New Algorithms, and an Evaluation”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Apr. 2011, 8 pages. |
Rodrig,“Command User Interface for Displaying and Scaling Selectable Controls and Commands”, U.S. Appl. No. 14/254,681, filed Apr. 16, 2014, 51 pages. |
Sanders,“Robust, Almost Constant Time Shortest-Path Queries in Road Networks”, In Proceedings of the 9th DIMACS Implementation Challenge: The Shortest Path Problem, Nov. 2006, 19 pages. |
Santos,“K Shortest Path Algorithms”, In Proceedings of the 9th DIMACS Implementation Challenge: The Shortest Path Problem, Nov. 2006, 13 pages. |
Sarukkai,“Word Set Probability Boosting for Improved Spontaneous Dialog Recognition”, IEEE Transactions on Speech and Audio Processing, vol. 5, No. 5, Sep. 1997, 13 pages. |
Seneff,“Galaxy-II: A Reference Architecture for Conversational System Development”, In Proceedings of the 5th International Conference on Spoken Language Processing, Nov. 2008, 4 pages. |
Seo,“Face Verification Using the LARK Representation”, IEEE Transactions on Information Forensics and Security, Dec. 2011, 12 pages. |
Sing,“Domain Metric Knowledge Model for Embodied Conversation Agents”, In 5th International Conference on Research, Innovation & Vision for the Future, Mar. 5, 2007, 7 pages. |
Susskind,“Modeling the joint density of two images under a variety of transformations”, In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2011, 8 pages. |
Taigman,“Leveraging Billions of Faces to Overcome Performance Barriers in Unconstrained Face Recognition”, Aug. 4, 2011, 7 pages. |
Taigman,“Multiple One-Shots for Utilizing Class Label Information”, In Proceedings of the British Machine Vision Conference (BMVC), Sep. 2009, 12 pages. |
Tian,“Facial Expression Analysis”, Handbook of Face Recognition, pp. 247-275. |
Wang,“A Unified Framework for Subspace Face Recognition”, retrieved at <<http://ieeexplore.ieee.org/Xplore/login.jsp?url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F34%2F29188%2F01316855.pdf&authDecision=−203>>, Sep. 2004, pp. 1222-1228. |
Wang,“Bayesian Face Recognition Using Gabor Features”, In Proceedings of the ACM SIGMM Workshop on Biometrics Methods and Applications (WBMA), Nov. 8, 2003, pp. 70-73. |
Wang,“Boosted Multi-Task Learning for Face Verification with Applications to Web Image and Video Search”, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Jun. 2009, 8 pages. |
Wang,“Subspace Analysis Using Random Mixture Models”, In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2005, 7 pages. |
Weinberger,“Distance Metric Learning for Large Margin Nearest Neighbor Classification”, In Proceedings of the Conference on Advances in Neural Information Processing Systems (NIPS), Dec. 2008, 8 pages. |
Xue,“Singular Value Decomposition Based Low-Footprint Speaker Adaptation and Personalization for Deep Neural Network”, In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, May 4, 2014, 5 pages. |
Ying,“Distance Metric Learning with Eigenvalue Optimization”, Journal of Machine Learning Research, Jan. 3, 2012, 26 pages. |
Zhang,“Two-Dimensional Bayesian Subspace Analysis for Face Recognition”, In Proceedings of the 4th International Symposium on Neutral Networks (ISNN), Jun. 2007, 7 pages. |
Zhu,“A Rank-Order Distance based Clustering Algorithm for Face Tagging”, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2011, pp. 481-488. |
“Final Office Action”, U.S. Appl. No. 12/970,949, Jun. 10, 2015, 25 pages. |
“Final Office Action”, U.S. Appl. No. 13/327,794, Nov. 20, 2014, 13 pages. |
“Final Office Action”, U.S. Appl. No. 13/530,015, Nov. 19, 2014, 48 pages. |
“GPU-Accelerated Route Planning”, https://www.cs.unc.edu/cms/research/summaries/GPUAcceleratedRoutePlanning.pdf, Aug. 2005, 2 pages. |
“International Search Report and Written Opinion”, Application No. PCT/US2015/030113, Aug. 7, 2015, 10 Pages. |
“International Search Report and Written Opinion”, Application No. PCT/US2015/030104, Aug. 7, 2015, 11 Pages. |
“International Search Report and Written Opinion”, Application No. PCT/US2015/030096, Aug. 19, 2015, 11 Pages. |
“International Search Report and Written Opinion”, Application No. PCT/US2015/032089, Jul. 31, 2015, 12 pages. |
“International Search Report and Written Opinion”, Application No. PCT/US2015/027409, Jul. 22, 2015, 13 pages. |
“International Search Report and Written Opinion”, Application No. PCT/US2015/028383, Jul. 24, 2015, 13 pages. |
“International Search Report and Written Opinion”, Application No. PCT/US2015/030153, Aug. 7, 2015, 13 Pages. |
“Non-Final Office Action”, U.S. Appl. No. 12/970,949, Jan. 2, 2015, 24 pages. |
“Non-Final Office Action”, U.S. Appl. No. 13/530,015, Apr. 28, 2015, 32 pages. |
“Non-Final Office Action”, U.S. Appl. No. 13/903,944, Mar. 27, 2015, 24 pages. |
“Non-Final Office Action”, U.S. Appl. No. 13/920,323, Feb. 27, 2015, 13 pages. |
“Non-Final Office Action”, U.S. Appl. No. 14/264,012, Jul. 31, 2015, 7 pages. |
“Non-Final Office Action”, U.S. Appl. No. 14/275,785, Aug. 26, 2015, 10 pages. |
“Non-Final Office Action”, U.S. Appl. No. 14/304,911, Jul. 17, 2015, 6 pages. |
“Non-Final Office Action”, U.S. Appl. No. 14/456,679, Jun. 19, 2015, 22 pages. |
“Notice of Allowance”, U.S. Appl. No. 12/970,939, Dec. 19, 2014, 10 pages. |
“Notice of Allowance”, U.S. Appl. No. 12/970,943, Dec. 19, 2014, 10 pages. |
“Notice of Allowance”, U.S. Appl. No. 13/026,058, Nov. 7, 2014, 5 pages. |
“Notice of Allowance”, U.S. Appl. No. 13/367,377, Feb. 7, 2012, 10 pages. |
“Restriction Requirement”, U.S. Appl. No. 14/275,785, Jun. 5, 2015, 6 pages. |
Abraham,“Hierarchical Hub Labelings for Shortest Paths”, In Technical Report MSR-TR-MSR-TR-2012-46, Apr. 2012, 15 pages. |
Bast,“Fast Routing in Road Networks with Transit Nodes”, In Proceedings of Science, vol. 316, No. 5824, Apr. 27, 2007, p. 566. |
Bast,“Route Planning in Transportation Networks”, In Technical Report MSR-TR-2014-4, Jan. 8, 2014, 57 pages. |
Bleiweiss,“GPU Accelerated Pathfinding”, In Proceedings of the 23rd ACM Siggraph/Eurographics symposium on Graphics hardware, Jun. 20, 2008, pp. 65-74. |
Cormen,“Introduction to Algorithms”, The MIT Press, Jul. 31, 2009, 43 pages. |
Delling,“Customizable Route Planning in Road Networks”, In Proceedings of the Sixth Annual Symposium on Combinatorial Search, Jul. 2011, pp. 1-31. |
Delling,“Customizable Route Planning”, In Proceedings of the 10th International Symposium on Experimental Algorithms, May 2011, pp. 1-12. |
Delling,“Faster Customization of Road Networks”, In Proceedings of the 12th International Symposium on Experimental Algorithms, Jun. 5, 2013, pp. 1-12. |
Delling,“Graph Partitioning with Natural Cuts”, In Proceedings of the IEEE International Parallel & Distributed Processing Symposium, May 16, 2011, 15 pages. |
Delling,“Phast: Hardware-Accelerated Shortest Path Trees”, In Journal of Parallel and Distributed Computing, vol. 73, No. 7, Jul. 2013, 11 pages. |
Delling,“Query Scenarios for Customizable Route Planning”, U.S. Appl. No. 13/649,114, Oct. 11, 2012, 27 pages. |
Dong,“Image Retargeting by Content-Aware Synthesis”, IEEE Transactions on Visualization and Computer Graphics, vol. XX, No. XX, Jun. 2014, Mar. 26, 2014, 14 pages. |
Efentakis,“Optimizing Landmark-Based Routing and Preprocessing”, In Proceedings of the Sixth ACM SIGSPATIAL International Workshop on Computational Transportation Science, Nov. 5, 2013, 6 pages. |
Geisberger,“Efficient Routing in Road Networks with Turn Costs”, In Proceedings of the 10th International Conference on Experimental Algorithms, May 5, 2011, 12 pages. |
Gooch,“Color2Gray: Salience-Preserving Color Removal”, In Journal of ACM Transactions on Graphics, vol. 24 Issue 3, Jul. 2006. |
Holzer,“Engineering Multilevel Overlay Graphs for Shortest-Path Queries”, In ACM Journal of Experimental Algorithmics, vol. 13, Sep. 2008, 26 pages. |
Kohler,“Fast Point-to-Point Shortest Path Computations with Arc-Flags”, In Proceedingsof Shortest Path Computations: Ninth DIMACS Challenge, vol. 24 of DIMACS Book. American Mathematical Society, Nov. 13, 2006, pp. 1-27. |
Lilly,“Robust Speech Recognition Using Singular Value Decomposition Based Speech Enhancement”, IEEE Tencon, 1997, 4 pages. |
Lu,“Context Aware Textures”, In Journal of ACM Transactions on Graphics, vol. 26 Issue 1, Jan. 2007, 31 pages. |
Madduri,“Parallel Shortest Path Algorithms for Solving Large-Scale Instances”, In Proceedings of 9th DIMACS Implementation Challenge—The Shortest Path Problem, Aug. 30, 2006, 39 pages. |
Malony,“Compensation of Measurement Overhead in Parallel Performance Profiling”, The International Journal of High Performance Computing Applications, May 1, 2007, 23 pages. |
Meyer,“D-Stepping: A Parallelizable Shortest Path Algorithm”, In Journal of Algorithms, vol. 49, Issue 1, Oct. 2003, pp. 114-152. |
Ortega-Arranz,“A New GPU-based Approach to the Shortest Path Problem”, In Proceedings of International Conference on High Performance Computing and Simulation, Jul. 1, 2013, 7 pages. |
Perumalla,“GPU-based Real-Time Execution of Vehicular Mobility Models in Large-Scale Road Network Scenarios”, In ACM/IEEE/SCS 23rd Workshop on Principles of Advanced and Distributed Simulation, Jun. 22, 2009, 9 pages. |
Shan,“Image Based Surface Detail Transfer”, in IEEE Computer Graphics and Applications, vol. 24 Issue 3, May 2004, 6 pages. |
Shen,“Agent-based Traffic Simulation and Traffic Signal Timing Optimization with GPU”, 2011 14th International IEEE Conference on Intelligent Transportation Systems, Oct. 5, 2011, pp. 145-150. |
Sommer,“Shortest-Path Queries in Static Networks”, In Proceedingsof ACM Computing Surveys, Apr. 7, 2014, 35 pages. |
Song,“Centralized Control of Wireless Sensor Networks for Real-Time Applications”, Retrieved from the Internet: URL:http://citeseerx.ist.psu.edu/viewdoc/download?doi=l0.1.1.187.8761&rep=rep1&type=pdf, Retrieved on Jul. 9, 2015, Nov. 7, 2007, 8 Pages. |
Wodecki,“Multi-GPU Parallel Memetic Algorithm for Capacitated Vehicle Routing Problem”, In Proceedings of Distributed, Parallel, and Cluster Computing, Jan. 21, 2014, pp. 207-214. |
“Corrected Notice of Allowance”, U.S. Appl. No. 14/275,806, Nov. 3, 2015, 2 pages. |
“Final Office Action”, U.S. Appl. No. 14/304,911, Nov. 13, 2015, 7 pages. |
“Final Office Action”, U.S. Appl. No. 14/456,679, Nov. 2, 2015, 26 pages. |
“International Search Report and Written Opinion”, Application No. PCT/US2015/036587, Oct. 8, 2015, 11 Pages. |
“International Search Report and Written Opinion”, Application No. PCT/US2015/029805, Oct. 15, 2015, 20 pages. |
“Non-Final Office Action”, U.S. Appl. No. 14/279,146, Dec. 8, 2015, 9 pages. |
“Non-Final Office Action”, U.S. Appl. No. 14/312,501, Dec. 16, 2015, 14 pages. |
“Second Written Opinion”, Application No. PCT/US2015/030104, Dec. 4, 2015, 7 pages. |
“Second Written Opinion”, Application No. PCT/US2015/030153, Dec. 4, 2015, 6 pages. |
Cvetkovic,“Image enhancement circuit using nonlinear processing curve and constrained histogram range equalization”, Visual Communications and Image Processing 2004, 2004, 12 pages. |
Grasset,“Image-Driven View Management for Augmented Reality Browsers”, IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Nov. 5, 2012, 10 pages. |
Rosten,“Real-time Video Annotations for Augmented Reality”, Advances in Visual Computing Lecture Notes in Computer Science, Jan. 1, 2005, 8 pages. |
Yin, “An Associate-Predict Model for Face Recognition”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Jun. 2011, 8 pages. |
“Advisory Action”, U.S. Appl. No. 14/304,911, Jan. 14, 2016, 2 pages. |
“Final Office Action”, U.S. Appl. No. 13/923,917, Sep. 29, 2015, 6 pages. |
“Final Office Action”, U.S. Appl. No. 14/275,274, Jan. 29, 2016, 6 pages. |
“Final Office Action”, U.S. Appl. No. 14/275,761, Dec. 18, 2015, 6 pages. |
“Final Office Action”, U.S. Appl. No. 14/275,785, Feb. 9, 2016, 11 pages. |
“Flexible Schema for Language Model Customization”, U.S. Appl. No. 14/227,492, filed Mar. 27, 2014, 20 pages. |
“International Preliminary Report on Patentability”, Application No. PCT/US2014/041014, Sep. 15, 2015, 6 pages. |
“International Search Report and Written Opinion”, Application No. PCT/US2015/022886, Aug. 31, 2015, 17 pages. |
“International Search Report and Written Opinion”, Application No. PCT/US2015/036859, Dec. 22, 2015, 17 pages. |
“Non-Final Office Action”, U.S. Appl. No. 14/227,492, Aug. 13, 2015, 36 pages. |
“Non-Final Office Action”, U.S. Appl. No. 14/281,518, Feb. 26, 2016, 23 pages. |
“Non-Final Office Action”, U.S. Appl. No. 14/311,208, Jan. 7, 2016, 6 pages. |
“Notice of Allowance”, U.S. Appl. No. 13/923,969, Oct. 1, 2015, 7 pages. |
“Notice of Allowance”, U.S. Appl. No. 13/923,969, Nov. 30, 2015, 5 pages. |
“Notice of Allowance”, U.S. Appl. No. 14/254,681, Dec. 4, 2015, 9 pages. |
“Notice of Allowance”, U.S. Appl. No. 14/264,012, Dec. 18, 2015, 7 pages. |
“Notice of Allowance”, U.S. Appl. No. 14/275,761, Mar. 2, 2016, 5 pages. |
“Notice of Allowance”, U.S. Appl. No. 14/275,806, Feb. 25, 2016, 9 pages. |
“Notice of Allowance”, U.S. Appl. No. 14/309,911, Feb. 19, 2016, 7 pages. |
“Notice of Allowance”, U.S. Appl. No. 14/312,562, Jan. 7, 2016, 9 pages. |
“Ribbon Layout and Resizing”, Retrieved on Mar. 12, 2014 at: https://msdn.microsoft.com/en-us/library/ff701790, 6 pages. |
“Second Written Opinion”, Application No. PCT/US2015/022887, Jan. 7, 2016, 5 pages. |
“Second Written Opinion”, Application No. PCT/US2015/027688, Feb. 9, 2016, 6 pages. |
“Step by Step Microsoft Word 2013”, Available at: https://dbgyan.files.wordpress.com/2013/02/0735669120—wor.pdf, Mar. 1, 2013, 576 pages. |
“The Ribbon Bar”, Available at: http://bioinf.scri.ac.uk/tablet/help/ribbon.shtml, Dec. 1, 2012, 36 pages. |
Gajos, “Automatically Generating Personalized User Interfaces with Supple”, In Proceedings of Artificial Intelligence, vol. 174, Issue, Aug. 1, 2010, 49 pages. |
Gajos, “Exploring the Design Space for Adaptive Graphical User Interfaces”, In Proceedings of the Working Conference on Advanced Visual Interfaces, May 6, 2006, 8 pages. |
Liu, “Language Model Combination and Adaptation using Weighted Finite State Transducers”, In Proceedings of IEEE International Conference on Acoustics Speech and Signal Processing, Mar. 14, 2010, 4 pages. |
Peng, “Joint and Implicit Registration for Face Recognition”, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'09), Jun. 2009, 8 pages. |
Scarr, “Improving Command Selection with Command Maps”, In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, May 2012, 10 pages. |
Number | Date | Country | |
---|---|---|---|
20150363339 A1 | Dec 2015 | US |