Abstract: A computer implemented method of detecting excessive customer wait times is provided. The method includes taking a headcount in a digital image obtained by a digital video camera of a monitored area, counting the number of bodies in the digital image, and rectifying the number of heads with the number of bodies to obtain a total count of persons. The method further includes determining which persons are moving and subtracting the moving persons from the total count of persons to obtain a still count, and determining which persons are workers and subtracting the workers from the still count to identify customers in the monitored area and obtain a customer count. The method further includes identifying the number of queues present in the monitored area, assigning each customer to a queue, and determining the wait time for each of the identified customers in each of the identified queues.

Abstract: A method includes obtaining a first set of parameters corresponding to a first video, such parameters including a first skip number and a first segment length. The method includes obtaining a first set of image feature values corresponding to the first video and storing the first set of parameters and the first set of image feature values as reference data. The method includes calculating a second set of image feature values corresponding to a second video and comparing the second set of image feature values to the reference data, and determining, based on the comparing, that the second set of image feature values exceeds a threshold. The method includes calculating, in response to the determining, a variance. The method includes generating, based on the variance, a second set of parameters corresponding to the second video, the second set of parameters including a second skip number and a second segment length.

Abstract: Techniques for monitoring particulate matter (PM) mass concentration using relatively low cost devices are described. A computer-implemented method comprises determining, by a device operatively coupled to a processor, relationships between: first PM mass data determined by a monitor station device for a first atmospheric area over a period of time; first PM count data determined by a reference PM count device for the first atmospheric area over the period of time; and first conditional information comprising first values for defined conditional parameters, wherein the first values are associated with the first atmospheric area over the period of time. The method further includes generating an initial conversion model based on the relationships, wherein the conversion model converts a PM count to a PM mass based on one or more conditional parameters of the defined conditional parameters and features for updating the conversion model.

Abstract: The present disclosure provides a computer-implemented method, computer system and computer program product for object detection. According to the computer-implemented method, a first object can be classified to be a first category based on detection data acquired in a detection area. Then, a confidence score for the first category can be calculated based on historical detection data of the detection area, wherein the confidence score presents possibility degree of at least one object of the first category existing in the detection area. Whether classification of the first object is abnormal can be determined based on the confidence score.

Abstract: The disclosure discloses a method for transmitting image data and an intelligent TV set. The method includes transmitting, by a primary chip, image data to a second chip. The image data comprises pixel data including a pixel type for indicating that a pixel in the image to be displayed is a menu On-Screen Display (OSD) pixel or a video pixel. The method includes receiving, by the second chip, the image data, and determining the pixel type in the image data. The method further includes performing, by the second chip, a Motion Estimate and Motion Compensation (MEMC) function on the pixel in response to the pixel type being the video pixel, and not performing the MEMC function on the pixel in response to the pixel type of the pixel being the menu OSD pixel.

Abstract: A computer implemented method of detecting excessive customer wait times is provided. The method includes taking a headcount in a digital image obtained by a digital video camera of a monitored area, counting the number of bodies in the digital image, and rectifying the number of heads with the number of bodies to obtain a total count of persons. The method further includes determining which persons are moving and subtracting the moving persons from the total count of persons to obtain a still count, and determining which persons are workers and subtracting the workers from the still count to identify customers in the monitored area and obtain a customer count. The method further includes identifying the number of queues present in the monitored area, assigning each customer to a queue, and determining the wait time for each of the identified customers in each of the identified queues.

Abstract: A method for sending early warning information, a storage medium and a terminal are provided. The method includes: calculating a target similarity between a first face image and a target face image when the first face image captured by an imaging device is acquired; and generating and sending early warning information corresponding to the first face image if the target similarity reaches a similarity threshold at the current moment; wherein, the similarity threshold is determined by a fluctuation degree value of a plurality of similarities in a similarity sample, the similarity in the similarity sample is a target similarity corresponding to a generated warning information, and the similarity sample is updated over. As a result, the accuracy in early warning may be improved.

Abstract: The disclosure discloses a method for transmitting image data and an intelligent TV set. The method includes transmitting, by a primary chip, image data to a second chip. The image data comprises pixel data including a pixel type for indicating that a pixel in the image to be displayed is a menu On-Screen Display (OSD) pixel or a video pixel. The method includes receiving, by the second chip, the image data, and determining the pixel type in the image data. The method further includes performing, by the second chip, a Motion Estimate and Motion Compensation (MEMC) function on the pixel in response to the pixel type being the video pixel, and not performing the MEMC function on the pixel in response to the pixel type of the pixel being the menu OSD pixel.

Abstract: A method, system and computer program product for accelerating a deep neural network (DNN) in a field-programmable gate array (FPGA) are disclosed. The method includes receiving a DNN net file and weights, converting the received DNN net file to one or more source files, generating an executable FPGA bit file using the one or more source files, and downloading the executable FPGA bit file from the DNN conversion platform to the FPGA. Converting of the received DNN net file and the weights to the one or more source files can further include analyzing the DNN net file to identify a plurality of neural layers, decomposing one or more neural layers of the plurality of neural layers to one or more operation blocks, instantiating the one or more source files, based on the one or more operation blocks.

Abstract: The present disclosure relates to methods, systems, and computer program products for implementing a deep neural network in a field-programmable gate array (FPGA). In response to receiving a network model describing a deep neural network, a plurality of layers associated with the deep neural network may be determined. With respect to a layer in the plurality of layers, a parallelism factor for processing operations associated with the layer simultaneously by processing elements in an FPGA may be determined based on a workload associated with the layer and a configuration of the FPGA.

Abstract: Techniques for monitoring particulate matter (PM) mass concentration using relatively low cost devices are described. A computer-implemented method comprises determining, by a device operatively coupled to a processor, relationships between: first PM mass data determined by a monitor station device for a first atmospheric area over a period of time; first PM count data determined by a reference PM count device for the first atmospheric area over the period of time; and first conditional information comprising first values for defined conditional parameters, wherein the first values are associated with the first atmospheric area over the period of time. The method further includes generating an initial conversion model based on the relationships, wherein the conversion model converts a PM count to a PM mass based on one or more conditional parameters of the defined conditional parameters and features for updating the conversion model.

Abstract: Techniques for monitoring particulate matter (PM) mass concentration using relatively low cost devices are described. A computer-implemented method comprises determining, by a device operatively coupled to a processor, relationships between: first PM mass data determined by a monitor station device for a first atmospheric area over a period of time; first PM count data determined by a reference PM count device for the first atmospheric area over the period of time; and first conditional information comprising first values for defined conditional parameters, wherein the first values are associated with the first atmospheric area over the period of time. The method further includes generating an initial conversion model based on the relationships, wherein the conversion model converts a PM count to a PM mass based on one or more conditional parameters of the defined conditional parameters and features for updating the conversion model.

Abstract: A method, computer system, and computer program product for model selection for training a new dataset is provided. The present invention may include choosing a model from a set of models to be evaluated for training the new dataset, selecting a sample input from a subset of the new dataset, calculating a model activation score for each of the sample inputs in the chosen model, calculating an accumulated model activation score for the chosen model, depending on the model activation score of each of the sample inputs in the chosen model, calculating an accumulated model activation score for each model from the set of models to be evaluated for training the new dataset, and selecting the model for training the new dataset with the highest accumulated model activation score.

Abstract: According to a method, an access request for a configuration module in a Field Programmable Gate Array (FPGA) may be received. The configuration module may be operable to configure functionality of the FPGA based on configuration information stored thereon. It may be determined whether the access request conforms to a specification specifying access control related to the configuration module. In response to determining that the access request conforms to the specification, the access request may be transmitted to the configuration module for access of the configuration information.

Abstract: Synchronization method and apparatus for a wireless wide band system in an interference environment. The method includes: obtaining interference information of a network; selecting at least one channel based at least in part on the interference information; and transmitting resource information through the at least one channel, wherein the resource information indicates a resource allocation determined at least in part on the interference information; and wherein a position of the at least one channel is indicated by a synchronization sequence. The present invention also provides another method and apparatus for synchronization.

Abstract: Techniques for monitoring particulate matter (PM) mass concentration using relatively low cost devices are described. A computer-implemented method comprises determining, by a device operatively coupled to a processor, relationships between: first PM mass data determined by a monitor station device for a first atmospheric area over a period of time; first PM count data determined by a reference PM count device for the first atmospheric area over the period of time; and first conditional information comprising first values for defined conditional parameters, wherein the first values are associated with the first atmospheric area over the period of time. The method further includes generating an initial conversion model based on the relationships, wherein the conversion model converts a PM count to a PM mass based on one or more conditional parameters of the defined conditional parameters and features for updating the conversion model.

Abstract: A method, system and computer program product for accelerating a deep neural network (DNN) in a field-programmable gate array (FPGA) are disclosed. The method includes receiving a DNN net file and weights, converting the received DNN net file to one or more source files, generating an executable FPGA bit file using the one or more source files, and downloading the executable FPGA bit file from the DNN conversion platform to the FPGA. Converting of the received DNN net file and the weights to the one or more source files can further include analyzing the DNN net file to identify a plurality of neural layers, decomposing one or more neural layers of the plurality of neural layers to one or more operation blocks, instantiating the one or more source files, based on the one or more operation blocks.

Abstract: Methods and systems for producing one or more alkanes from biomass by hydrodeoxygenation are disclosed. Biomass may be converted to one or more alkanes by heating the biomass with a catalyst mixture that includes a noble metal and at least one of a transition metal and derivative thereof. The catalyst mixture may further include a solid acid. Heating may be performed at a single temperature and pressure.

Abstract: Synchronization method and apparatus for a wireless wide band system in an interference environment. The method includes: obtaining interference information of a network; selecting at least one channel based at least in part on the interference information; and transmitting resource information through the at least one channel, wherein the resource information indicates a resource allocation determined at least in part on the interference information; and wherein a position of the at least one channel is indicated by a synchronization sequence. The present invention also provides another method and apparatus for synchronization.

Abstract: A lower lockpin rotation shaft assembly includes a lower lockpin rotation shaft body, an outer end portion thereof having a first coupler lifting bar hole, an intermediate portion thereof having a connecting key; and a lower lockpin rotation shaft bush, an outer end portion of the lower lockpin rotation shaft bush having a second coupler lifting bar hole, and an inner end portion of the lower lockpin rotation shaft bush being operatively connected to an inner end portion of the lower lockpin rotation shaft body. Further, the present invention further provides a double-side operating coupler and a coupler draft gear having the above lower lockpin rotation shaft assembly. The coupler draft gear further includes two coupler lifting bars and two coupler lifting bar seats.