Abstract: Comprehensive patient-facing screening may provide diagnostics, real-time alerts, and feedback relating to a wide range of health and medical-related issues. The methods and systems for comprehensive patient-facing screening described provide feasible, user-friendly use, and may improve operations, processes, and connection to clinical care for users, such as veterans.

Abstract: Embodiments are directed to systems and methods to intelligently reduce the dynamic range of a signal. Using a histogram analysis of the signal, significant and insignificant portions of the original dynamic range can be identified. Compaction can then be focused on the insignificant portions of the dynamic range, resulting in significant dynamic range reduction with less signal loss. By compacting the little used portions of the original signal, the dynamic range of the rest of the signal can be largely maintained which results in little loss to signal fidelity, and thus mitigates saturation, quantization, signal mutual suppression, and other issues observed in prior art methods.

Abstract: Embodiments are directed to systems and methods to intelligently reduce the dynamic range of a signal. Using a histogram analysis of the signal, significant and insignificant portions of the original dynamic range can be identified. Compaction can then be focused on the insignificant portions of the dynamic range, resulting in significant dynamic range reduction with less signal loss. By compacting the little used portions of the original signal, the dynamic range of the rest of the signal can be largely maintained which results in little loss to signal fidelity, and thus mitigates saturation, quantization, signal mutual suppression, and other issues observed in prior art methods.

Abstract: Embodiments are directed to systems and methods to intelligently reduce the dynamic range of a signal. Using a histogram analysis of the signal, significant and insignificant portions of the original dynamic range can be identified. Compaction can then be focused on the insignificant portions of the dynamic range, resulting in significant dynamic range reduction with less signal loss. By compacting the little used portions of the original signal, the dynamic range of the rest of the signal can be largely maintained which results in little loss to signal fidelity, and thus mitigates saturation, quantization, signal mutual suppression, and other issues observed in prior art methods.

Abstract: Embodiments are directed to systems and methods to intelligently reduce the dynamic range of a signal. Using a histogram analysis of the signal, significant and insignificant portions of the original dynamic range can be identified. Compaction can then be focused on the insignificant portions of the dynamic range, resulting in significant dynamic range reduction with less signal loss. By compacting the little used portions of the original signal, the dynamic range of the rest of the signal can be largely maintained which results in little loss to signal fidelity, and thus mitigates saturation, quantization, signal mutual suppression, and other issues observed in prior art methods.

Abstract: A system and method for labeling radicals in East Asian characters is described. The identity of the radical and the location of the radical in a character may be stored for future reference.

Abstract: A kit is provided for carrying golf clubs. The kit comprises a golf club carrier and a user interface. The golf club carrier includes two receptacles each for receiving a golf club. The golf club carrier further includes a club selection aid comprising a highlighting means, wherein the highlighting means is controlled to highlight the golf club stowed within either the first receptacle or the second receptacle. The club selection aid highlights the club by drawing a user's attention to the club. The club selection aid includes a receiver for receiving a control signal. The receiver controls the highlighting means to highlight the desired club.

Abstract: Various technologies and techniques are disclosed that generate a teaching data set for use by a handwriting recognizer. Ink input is received from various ink sources, such as implicit field data, scripted untruthed ink, scripted truth ink, and/or ink from at least one other language in the same script as the target language for the recognizer. The ink input is used with various machine learning methods and/or other algorithmic methods to generate a teaching ink data set. Examples of the various machine learning methods include a character and/or word n-gram distribution leveling method, an allograph method, a subject diversity method, and a print and cursive data selection method. The teaching ink data is used by a handwriting trainer to produce the handwriting recognizer for the target language.

Abstract: New neural networks for handwriting recognition may be build from existing neural networks. An existing neural network pre-trained for a starting language is chosen based on a desired target language. The neural network is modified so that it may be used to recognize characters of the target language, and the modified neural network is used in a handwriting recognizer for the target language. Modification includes copying one or more of the primary outputs of the existing neural network. An appropriate starting language may be chosen based on the desired target language. In addition, a “super network” may be provided that is a relatively large neural network configured to recognize characters from a number of different languages. One may customize a handwriting recognizer using such a super network by programming a mask to block outputs from the super network that are not necessary for the language desired to be recognized.

Abstract: Various technologies and techniques are disclosed that generate a teaching data set for use by a handwriting recognizer. Ink input is received from various ink sources, such as implicit field data, scripted untruthed ink, scripted truth ink, and/or ink from at least one other language in the same script as the target language for the recognizer. The ink input is used with various machine learning methods and/or other algorithmic methods to generate a teaching ink data set. Examples of the various machine learning methods include a character and/or word n-gram distribution leveling method, an allograph method, a subject diversity method, and a print and cursive data selection method. The teaching ink data is used by a handwriting trainer to produce the handwriting recognizer for the target language.

Abstract: The heated air mattress includes an inflatable air mattress, a cover and a heating pad. The cover is joined to a top surface of the inflatable air mattress to form a pocket for receiving the heating pad. The inflatable air mattress includes a cavity for receiving a portable air pump, which may be carried with the air mattress for inflating the inflatable air mattress, and further includes an air valve for selective inflation and deflation of the inflatable air mattress. The inflatable air mattress has lateral recesses for receiving a wheel well compartment of a vehicle flatbed, allowing the air mattress to be mounted in a vehicle flatbed, such as in the rear of a pickup truck or sports utility vehicle. The lateral recesses may be releasably filled with filler members, allowing the mattress to be stably supported on a floor or on the ground.

Abstract: New neural networks for handwriting recognition may be build from existing neural networks. An existing neural network pre-trained for a starting language is chosen based on a desired target language. The neural network is modified so that it may be used to recognize characters of the target language, and the modified neural network is used in a handwriting recognizer for the target language. Modification includes copying one or more of the primary outputs of the existing neural network. An appropriate starting language may be chosen based on the desired target language. In addition, a “super network” may be provided that is a relatively large neural network configured to recognize characters from a number of different languages. One may customize a handwriting recognizer using such a super network by programming a mask to block outputs from the super network that are not necessary for the language desired to be recognized.

Abstract: A system and method for labeling radicals in East Asian characters is described. The identity of the radical and the location of the radical in a character may be stored for future reference.

Abstract: Method and apparatus for handwriting recognition system for ideographic characters and other characters based on subcharacter hidden Markov models. The ideographic characters are modeled using a sequence of subcharacter models and by using two-dimensional geometric layout models of the subcharacters. The subcharacter hidden Markov models are created according to one embodiment by following a set of design rules. The combination of the sequence and geometric layout of the subcharacter models is used to recognize the handwriting character.

Abstract: Method and apparatus for handwriting recognition system for ideographic characters and other characters based on subcharacter hidden Markov models. The ideographic characters are modeled using a sequence of subcharacter models and by using two-dimensional geometric layout models of the subcharacters. The subcharacter hidden Markov models are created according to one embodiment by following a set of design rules. The combination of the sequence and geometric layout of the subcharacter models is used to recognize the handwriting character.

Abstract: Method and apparatus for handwriting recognition system for ideographies characters and other characters based on subcharacter hidden Markov models. The ideographies characters are modeled using a sequence of subcharacter models and by using two-dimensional geometric layout models of the subcharacters. The subcharacter hidden Markov models are created according to one embodiment by following a set of design rules. The combination of the sequence and geometric layout of the subcharacter models is used to recognize the handwriting character.

Abstract: A system (1), for shot blasting of a surface, collecting used shot blast media and debris, and separating the debris from the shot blast, has at least one shot blast nozzle (105) with a hood (100) connected to a vacuum hose (110). The system further has a displacement chamber (200) with an inlet connected to the hood by the vacuum hose, an inlet baffle (220), a solid matter collecting and discharging area (205) for receiving solid matter which falls from the gas stream in the displacement chamber, an outlet baffle (225), an outlet (226) for the outgoing gas stream, and a rotary valve (510) for allowing discharge of the solid matter. A first filter unit (300) and a second filter unit (310) are connected to the displacement chamber via a first duct (230). A shot blast media container (600) is connected to a shot blast media feeding hose (120), which is connected to the shot blast nozzle.

Abstract: A method and system for recognizing user input information including cursive handwriting and spoken words. A time-delayed neural network having an improved architecture is trained at the word level with an improved method, which, along with preprocessing improvements, results in a recognizer with greater recognition accuracy. Preprocessing is performed on the input data and, for example, may include resampling the data with sample points based on the second derivative to focus the recognizer on areas of the input data where the slope change per time is greatest. The input data is segmented, featurized and fed to the time-delayed neural network which outputs a matrix of character scores per segment. The neural network architecture outputs a separate score for the start and the continuation of a character.

Abstract: Apparatus for vacuum collection of material, where a vacuum source is used for creating a vacuum to draw air into a displacement chamber, and at least two hoses are connected to the displacement chamber for vacuum collection of materials from various locations. Pressure sensors are connected to sense pressure in each hose, dampers are operable in response to the relative pressures between the hoses so as to vary the effective area of the respective connections between the hoses and the displacement chamber in order to equalize and optimize the relative pressures, and an automatic control such as a programmable logic controller is employed to operate the dampers in response to said sensed pressures.

Abstract: A multi-layered pattern recognition neural network (30) is disclosed that comprises an input layer (50) that is operable to be mapped onto an input space that includes a scan window (32). Two hidden layers (54) and (58) map the input space to an output layer (34). The hidden layers utilize a local receptor field architecture and store representations of objects within the scan window (32) for mapping into one of a plurality of output nodes. Further, the output layer (34) is also operable to store representations of desired distances between the center of the scan window (32) and the next adjacent object thereto and also the distance between the center of the scan window (32) and the center of the current object. A scanning system can then utilize the information regarding the distance to the next adjacent object, which is stored in an output vector (40) to incrementally jump to the center of the next adjacent character rather than scan the entire distance therebetween.