Abstract: A one-shot neural architecture search method referred to as MergeNAS by merging different types of convolutions into a single operation. This mergence approach reduces the search cost to roughly half a GPU-day as well as alleviates the over-fitting problem caused by a traditional differentiable architecture search (DARTS) approach by reducing the number of redundant parameters.

Abstract: An alarm system an alarm method for a medical emergency are provided. The alarm method includes: obtaining a physiological signal of a user by a sensor of a portable electronic device; receiving the physiological signal from the portable electronic device, determining whether an abnormal event has occurred according to the physiological signal, and transmitting first feedback information corresponding to the physiological signal to a server in response to the abnormal event by the terminal device; and outputting an alarm message according to the first feedback information by the server.

Abstract: A wall mountable sensor module includes a housing defining an internal space that is segmented into a first internal space and a second internal space. The first internal space defines an air channel that extends from an air inlet to an air outlet. Two or more sensors are configured to be exposed to the air flow channel. A first sensor is configured to detect a first air parameter and a second sensor is configured to detect a second different air parameter, wherein the second sensor is situated downstream of the first sensor in the air flow channel. The sensor module includes a fan housed by the housing, the fan configured to cause an airflow to flow in through the air inlet, through the air flow channel thereby exposing each of the sensors to the airflow, and out through the air outlet.

Abstract: Aspects of the invention include systems and methods to obtain meta features of a dataset for training in a deep learning application. A method includes selecting an initial search space that defines a type of deep learning architecture representation that specifies hyperparameters for two or more neural network architectures. The method also includes applying a search strategy to the initial search space. One of the two or more neural network architectures are selected based on a result of an evaluation according to the search strategy. A new search space is generated with new hyperparameters using an evolutionary algorithm and a mutation type that defines one or more changes in the hyperparameters specified by the initial search space, and, based on the mutation type, the new hyperparameters are applied to the one of the two or more neural networks or the search strategy is applied to the new search space.

Abstract: Techniques for unattended object detection using machine learning are disclosed. A machine learning policy, for use in identifying unattended objects in a captured image depicting one or more objects, is generated. The generating includes determining a level of occlusion in the captured image relating to the objects, and determining the machine learning policy based on the determined level of occlusion. A machine learning model is selected, from among a plurality of pre-defined machine learning models, based on the generated machine learning policy. An unattended object is detected in the captured image using the selected machine learning model.

Abstract: A one-shot neural architecture search method referred to as MergeNAS by merging different types of convolutions into a single operation. This mergence approach reduces the search cost to roughly half a GPU-day as well as alleviates the over-fitting problem caused by a traditional differentiable architecture search (DARTS) approach by reducing the number of redundant parameters.

Abstract: Aspects of the invention include systems and methods to obtain meta features of a dataset for training in a deep learning application. A method includes selecting an initial search space that defines a type of deep learning architecture representation that specifies hyperparameters for two or more neural network architectures. The method also includes applying a search strategy to the initial search space. One of the two or more neural network architectures are selected based on a result of an evaluation according to the search strategy. A new search space is generated with new hyperparameters using an evolutionary algorithm and a mutation type that defines one or more changes in the hyperparameters specified by the initial search space, and, based on the mutation type, the new hyperparameters are applied to the one of the two or more neural networks or the search strategy is applied to the new search space.

Abstract: Techniques for unattended object detection using machine learning are disclosed. A machine learning policy, for use in identifying unattended objects in a captured image depicting one or more objects, is generated. The generating includes determining a level of occlusion in the captured image relating to the objects, and determining the machine learning policy based on the determined level of occlusion. A machine learning model is selected, from among a plurality of pre-defined machine learning models, based on the generated machine learning policy. An unattended object is detected in the captured image using the selected machine learning 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: 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: 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: An embodiment of a computer implemented method for transferring cryptocurrency amounts includes receiving, by a processing device, a request to transfer an amount of a cryptocurrency from a first storage location. The method also includes, in response to the request, automatically generating a credit value and a debit value as a related pair, each of the credit value and the debit value having an identifier that relates the credit value and the debit value to the amount of the cryptocurrency, one of the credit value and the debit value being a positive value and another of the credit value and the debit value being a negative value, and transferring the amount of the cryptocurrency by the transaction module from a wallet connected to the transaction module to a second storage location.

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: Methods, computer systems and computer program products for service packages porting are provided. Aspects include a computer implemented method for a service package porting is provided. One or more processors provision a component of a first layer based on a plurality of component descriptions and build the service package on the first layer. Hence the one or more processors collect first log information that relates to build failures of the service package. According to another embodiment of the present invention, the method further comprises determine whether a build failure is related to the first layer based on the first log information and remove the component of the first layer if it is determined that the build failure is related to the first layer.

Abstract: An embodiment of a computer implemented method for transferring cryptocurrency amounts includes receiving, by a processing device, a request to transfer an amount of a cryptocurrency from a first storage location. The method also includes, in response to the request, automatically generating a credit value and a debit value as a related pair, each of the credit value and the debit value having an identifier that relates the credit value and the debit value to the amount of the cryptocurrency, one of the credit value and the debit value being a positive value and another of the credit value and the debit value being a negative value, and transferring the amount of the cryptocurrency by the transaction module from a wallet connected to the transaction module to a second storage location.

Abstract: Embodiments of the present invention provide methods, computer systems and computer program products for service packages porting. In one embodiment of the present invention, a computer implemented method for a service package porting is provided. One or more processors provision a component of a first layer based on a plurality of component descriptions and build the service package on the first layer. Hence the one or more processors collect first log information that relates to build failures of the service package. According to another embodiment of the present invention, the method further comprises determine whether a build failure is related to the first layer based on the first log information and remove the component of the first layer if it is determined that the build failure is related to the first layer.

Abstract: In one embodiment, a system includes a first tracked device and a second tracked device. The first tracked device includes first known device data, describing one or more previous connections known to the first tracked device. The second tracked device includes second known device data, describing one or more previous connections known to the second tracked device. The first tracked device is configured to connect to the second tracked device, transfer to the second tracked device at least a portion of the first known device data, and receive from the second tracked device at least a portion of the second known device data. The first tracked device is further configured to modify the first known device data to incorporate the second known device data. The second known device data includes data related to a previous connection involving a third tracked device outside a signal range of the first tracked device.

Abstract: In one embodiment, a system includes a first tracked device and a second tracked device. The first tracked device includes first known device data, describing one or more previous connections known to the first tracked device. The second tracked device includes second known device data, describing one or more previous connections known to the second tracked device. The first tracked device is configured to connect to the second tracked device, transfer to the second tracked device at least a portion of the first known device data, and receive from the second tracked device at least a portion of the second known device data. The first tracked device is further configured to modify the first known device data to incorporate the second known device data. The second known device data includes data related to a previous connection involving a third tracked device outside a signal range of the first tracked device.

Abstract: A method and apparatus for managing remote devices. In one embodiment of the present invention, there is provided a method of managing a remote device, comprising: obtaining a first identifier based on a name sequence in state information of the remote device, the first identifier being for indicating a template that provides the state information; obtaining a second identifier based on a numerical value sequence in the state information; sending a state access notification that comprises at least the first identifier and the second identifier; and providing the state information based on the first identifier and the second identifier in response to having received a result of activating the state access notification. In one embodiment of the present invention, there is provided an apparatus for managing a remote device.

Abstract: In one embodiment, a system includes a first tracked device and a second tracked device. The first tracked device includes first known device data, describing one or more previous connections known to the first tracked device. The second tracked device includes second known device data, describing one or more previous connections known to the second tracked device. The first tracked device is configured to connect to the second tracked device, transfer to the second tracked device at least a portion of the first known device data, and receive from the second tracked device at least a portion of the second known device data. The first tracked device is further configured to modify the first known device data to incorporate the second known device data. The second known device data includes data related to a previous connection involving a third tracked device outside a signal range of the first tracked device.