Abstract: A flexible two-phase conversion heat transfer device includes a main body enclosing a chamber. A working liquid is received in the chamber. A capillary structure body is disposed in the chamber. The main body has at least one bellows section. The bellows section has multiple waved stripes. The waved stripes at least have a waved stripe feature including a waved stripe height or a waved stripe width or a waved stripe pitch between each two adjacent waved stripes. By means of the different waved stripe features, the main body is bendable by an angle ranging from 0-180 degrees without interference between the waved stripes.

Abstract: Disclosed are a computer-implemented method, a system and a computer program product for feature processing. In the computer-implemented method for feature processing, two input features selected from multiple features of each sample in a sample set are projected to one resulting feature by one or more processing units based on a specified curve. The sample set is updated by replacing the two input features with the one resulting feature for each sample in the sample set by one or more processing units. The projecting and the updating for the sample set are repeated by one or more processing units until the number of features of each sample in the sample set reaches a predetermined criterion.

Abstract: A computer-implemented method for data augmentation is provided according an embodiment of the present disclosure. In the method, a first feature vector for input data may be obtained based on a first model. The input data may be clustered to a plurality of clusters. For each of the clusters, a second feature vector may be obtained based on the first model. Then, a similarity between the first feature vector and the second feature vector may be estimated for each of the clusters. At least one cluster of the plurality of clusters for which the similarity is lower than a threshold may be determined. Moreover, data augmentation may be performed to the at least one cluster.

Abstract: A flexible heat dissipation device includes an evaporator, a vapor tube, a liquid tube and a condenser. The evaporator has at least one vapor chamber. A capillary structure and a working fluid are received in the vapor chamber. Two ends of the vapor tube is respectively in communication with one end of the evaporator and the condenser. Two ends of the liquid tube are respectively in communication with the evaporator and the condenser, whereby the evaporator, the vapor tube, the condenser and the liquid tube form a loop for the working fluid to flow through. At least one bellows section is disposed on one or both of the vapor tube and the liquid tube. The bellows section has multiple waved stripes. More than one of the heights, widths and pitches of the multiple waved stripes are equal to or unequal to each other.

Abstract: Embodiments of the invention are directed to a computer-implemented method that includes using a reinforcement learning (RL) system to generate a first set of displayed region candidates based on inputs received from online users while watching video. A recommendation system is used to rank the first set of displayed region candidates based on inputs received from a local user watching video. The recommendation system is further used to select a first highest ranked one of the first set of displayed region candidates. Based on the first highest ranked one of the first set of displayed region candidates, a first section of a first raw video frame is fetched that matches the first highest ranked one of the first set of displayed candidate regions, wherein the first section of the first raw video frame includes a first predicted display region of the video frame.

Abstract: An image processing method, apparatus, and device, and a storage medium are provided. The method is performed by a computing device, and includes: determining a first image feature of a first size of an input image, the first image feature having at least two channels; performing weight adjustment on each channel in the first image feature by using a first weight adjustment parameter, to obtain an adjusted first image feature, the first weight adjustment parameter including at least two parameter components, and each parameter component being used for adjusting a pixel of a channel corresponding to each parameter component; downsampling the adjusted first image feature to obtain a second image feature having a second size; combining the first image feature and the second image feature to obtain a combined image feature; and determining an image processing result according to the combined image feature.

Abstract: Traffic jam patterns can be identified and, based on historical traffic data, pre-traffic jam patterns that are likely to result in the traffic jam patterns can be identified as well. Real-time traffic data regarding a driving road of a community can be received and analyzed to determine whether the real-time traffic data match with a pre-traffic jam pattern. If the data matches a pre-traffic jam pattern, an alerting signal for predicting a traffic jam can be transmitted.

Abstract: A method can include obtaining, from a video having a first resolution, a set of frames having a second resolution. The first resolution can be higher than the second resolution. The set of frames can include a first frame and a second frame. The method can include generating a difference feature map. The method can include obtaining a third frame having the first resolution. The method can include detecting, based on the difference feature map, a first location of a first object in the third frame. The method can include cropping, from the third frame, a first cropped area. The first cropped area can be smaller than a third frame area. The method can include generating, based on a feature map and the difference feature map, a spatial attention layer. The method can include detecting, by the spatial attention layer, the first object in the first cropped area.

Abstract: Techniques for candidate evaluation and filtering are provided. Enrollment criteria for a clinical trial are received, where the enrollment criteria include a plurality of conditions. A plurality of cost vectors is constructed for the plurality of conditions. A set of values for one or more of the plurality of conditions is determined for a candidate, where the set of values does not include a value for at least a first condition of the plurality of conditions. A utilized cost is generated for the candidate, based on the first set of values and the plurality of cost vectors. The candidate is then ranked based on the utilized cost.

Abstract: A method for detecting deviations between an event log and a process model includes converting the process model into a probability process model, the probability process model comprising multiple nodes in multiple hierarchies and probability distribution associated with the multiple nodes, a leaf node among the multiple nodes corresponding to an activity in the process model; detecting differences between at least one event sequence contained in the event log and the probability process model according to a correspondence relationship; and identifying the differences as the deviations in response to the differences exceeding a predefined threshold; wherein the correspondence relationship describes a correspondence relationship between an event in one event sequence of the at least one event sequence and a leaf node in the probability process model.

Abstract: A dynamic graph embedding method for transaction data analysis includes obtaining transaction data associated with an account during a plurality of time windows, extracting spatial-temporal information of the transaction data by using a graph convolutional network and a transformer framework, and generating a feature representation for the account based on the spatial-temporal information.

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 flexible heat dissipation device includes an evaporator, a vapor tube, a liquid tube and a condenser. The evaporator has at least one vapor chamber. A capillary structure and a working fluid are received in the vapor chamber. Two ends of the vapor tube is respectively in communication with one end of the evaporator and the condenser. Two ends of the liquid tube are respectively in communication with the evaporator and the condenser, whereby the evaporator, the vapor tube, the condenser and the liquid tube form a loop for the working fluid to flow through. At least one bellows section is disposed on one or both of the vapor tube and the liquid tube. The bellows section has multiple waved stripes. More than one of the heights, widths and pitches of the multiple waved stripes are equal to or unequal to each other.

Abstract: A flexible two-phase conversion heat transfer device includes a main body enclosing a chamber. A working liquid is received in the chamber. A capillary structure body is disposed in the chamber. The main body has at least one bellows section. The bellows section has multiple waved stripes. The waved stripes at least have a waved stripe feature including a waved stripe height or a waved stripe width or a waved stripe pitch between each two adjacent waved stripes. By means of the different waved stripe features, the main body is bendable by an angle ranging from 0-180 degrees without interference between the waved stripes.

Abstract: A computer-implemented method for attention generation is provided. In this method, a plurality of image frames can be obtained from a video stream. An original attention for a first image frame of the plurality of image frames can be generated. Then, at least one interested area can be identified in the first image frame. A local attention for each of the at least one interested area can be generated. Moreover, a total attention for the first image frame can be generated based on the original attention of the first image frame and the local attention of each of the at least one interested area.

Abstract: A method can include obtaining, from a video having a first resolution, a set of frames having a second resolution. The first resolution can be higher than the second resolution. The set of frames can include a first frame and a second frame. The method can include generating a difference feature map. The method can include obtaining a third frame having the first resolution. The method can include detecting, based on the difference feature map, a first location of a first object in the third frame. The method can include cropping, from the third frame, a first cropped area. The first cropped area can be smaller than a third frame area. The method can include generating, based on a feature map and the difference feature map, a spatial attention layer. The method can include detecting, by the spatial attention layer, the first object in the first cropped area.

Abstract: A suspicious pattern can be detected within a transaction network of nodes. Nodes of the network are walked by determining if any adjacent node to a current node is within the suspicious pattern. If an adjacent node is within the suspicious pattern, that node is walked to. Based on the walk, a node sequence can be generated.

Abstract: Embodiments of the invention are directed to a computer-implemented method that includes using a reinforcement learning (RL) system to generate a first set of displayed region candidates based on inputs received from online users while watching video. A recommendation system is used to rank the first set of displayed region candidates based on inputs received from a local user watching video. The recommendation system is further used to select a first highest ranked one of the first set of displayed region candidates. Based on the first highest ranked one of the first set of displayed region candidates, a first section of a first raw video frame is fetched that matches the first highest ranked one of the first set of displayed candidate regions, wherein the first section of the first raw video frame includes a first predicted display region of the video frame.

Abstract: A method for detecting deviations between an event log and a process model includes converting the process model into a probability process model, the probability process model comprising multiple nodes in multiple hierarchies and probability distribution associated with the multiple nodes, a leaf node among the multiple nodes corresponding to an activity in the process model; detecting differences between at least one event sequence contained in the event log and the probability process model according to a correspondence relationship; and identifying the differences as the deviations in response to the differences exceeding a predefined threshold; wherein the correspondence relationship describes a correspondence relationship between an event in one event sequence of the at least one event sequence and a leaf node in the probability process model.

Abstract: Described are techniques for using a dynamic ensemble model. The techniques including training a plurality of machine learning models on training data. The techniques further include identifying a similar subset of the training data that is similar to a dataset for evaluation. The techniques further include assembling a subset of models from the plurality of machine learning models based on performance of the subset of models on the similar subset of the training data. The techniques further include generating an output from the subset of models for the dataset for evaluation.