Abstract: The present teaching relates to methods, systems, and programming for data assignment in a distributed system. In one example, a plurality of tables is obtained. Each of the plurality of tables includes a plurality of buckets. Each of the plurality of tables is generated based on a same set of keys and a different function. The buckets in the plurality of tables are projected into different partitions. Data in the plurality of tables are assigned to a plurality of nodes in the distributed system such that data in buckets that are projected into a same partition are assigned to a same node in the distributed system.

Abstract: An inrush current test device is adapted to receive an alternating current. The inrush current test device includes: a first isolation coupling component, a positive crossing point pulse generation circuit, an output circuit, and a control circuit. The first isolation coupling component includes a primary side and a secondary side, and is responsive to the alternating current on the primary side and conducts the secondary side. When the secondary side transits from an off state to an on state, the positive crossing point pulse generation circuit generates a positive crossing point pulse. When the control circuit is actuated and the positive crossing point pulse is detected, after delaying for a delay time, the control circuit outputs a control pulse for actuating the output circuit for a first operating time. The output circuit is configured to receive the alternating current and output the alternating current when the output circuit is actuated.

Abstract: An inrush current test device is adapted to receive an alternating current. The inrush current test device includes: a first isolation coupling component, a positive crossing point pulse generation circuit, an output circuit, and a control circuit. The first isolation coupling component includes a primary side and a secondary side, and is responsive to the alternating current on the primary side and conducts the secondary side. When the secondary side transits from an off state to an on state, the positive crossing point pulse generation circuit generates a positive crossing point pulse. When the control circuit is actuated and the positive crossing point pulse is detected, after delaying for a delay time, the control circuit outputs a control pulse for actuating the output circuit for a first operating time. The output circuit is configured to receive the alternating current and output the alternating current when the output circuit is actuated.

Abstract: Method and system for electronic commerce are provided. An image of a user is obtained. A plurality of features based on the image of the user is determined. A group of products based on the plurality of features are selected. A recommendation to the user is provided based on the group of products.

Abstract: A computer implemented method includes capturing, via a camera, one or more digital images of a face of a person representative of blood circulation of the person, collecting context information via one or more processors corresponding to the person contemporaneously with the capturing of the one or more digital images, labeling, via a trained individual health model executing on the one or more processors, the one or more digital images based on the blood circulation represented in the image and the collected context information via the trained individual health model that has been trained on prior such digital images and context information; and analyzing, via the one or more processors, the one or more labeled digital images to generate a health index of the person.

Abstract: Disclosed herein is item recommender that uses a model trained using a combination of at least visual item similarity training data and social activity training data. The model may be used, for example, to identify a set of recommended products having similar visual features as a given product. The set of recommended products may be presented to the user along with the given product. The model may be continuously updated using feedback from users to identify the features considered to be important to the users relative to other features.

Abstract: Embodiments are directed to detecting and uploading measurement data of a non-connected medical measuring device. Embodiments include capturing an image of an identification object and a beginning event image of a medical measuring device and extracting identification data from the image of the identification object. Based on detecting that the identification object has been removed, an ending event image of the medical measuring device is captured. Embodiments include determining if a measurement event has occurred by comparing the ending event image and the beginning event image. Based on determining that the measurement event occurred, a measurement data of the ending event image is extracted and upload to a personal health record database.

Abstract: Method and system for electronic commerce are provided. An image of a user is obtained. A plurality of features based on the image of the user is determined. A group of products based on the plurality of features are selected. A recommendation to the user is provided based on the group of products.

Abstract: In an embodiment, a method comprises obtaining a frequency domain representation associated with an image; obtaining one or more frequency domain representations of one or more object detection filters; generating a composite frequency domain representation based on the frequency domain representation associated with the image and the one or more frequency domain representations of the one or more object detection filters; and detecting one or more objects in the image based on the composite frequency domain representation. The frequency domain representation associated with the image may be obtained based on a forward transform performed on an image feature description. The image feature description may be obtained based on a feature extraction performed on the image. The one or more frequency domain representations of the one or more object detection filters may be obtained based on one or more Fourier transforms performed on the one or more object detection filters.

Abstract: The present teaching relates to methods, systems, and programming for data assignment in a distributed system. In one example, a plurality of tables is obtained. Each of the plurality of tables includes a plurality of buckets. Each of the plurality of tables is generated based on a same set of keys and a different function. The buckets in the plurality of tables are projected into different partitions. Data in the plurality of tables are assigned to a plurality of nodes in the distributed system such that data in buckets that are projected into a same partition are assigned to a same node in the distributed system.

Abstract: In an embodiment, a method comprises obtaining a frequency domain representation associated with an image; obtaining one or more frequency domain representations of one or more object detection filters; generating a composite frequency domain representation based on the frequency domain representation associated with the image and the one or more frequency domain representations of the one or more object detection filters; and detecting one or more objects in the image based on the composite frequency domain representation. The frequency domain representation associated with the image may be obtained based on a forward transform performed on an image feature description. The image feature description may be obtained based on a feature extraction performed on the image. The one or more frequency domain representations of the one or more object detection filters may be obtained based on one or more Fourier transforms performed on the one or more object detection filters.

Abstract: Disclosed herein is item recommender that uses a model trained using a combination of at least visual item similarity training data and social activity training data. The model may be used, for example, to identify a set of recommended products having similar visual features as a given product. The set of recommended products may be presented to the user along with the given product. The model may be continuously updated using feedback from users to identify the features considered to be important to the users relative to other features.

Abstract: In an embodiment, a method comprises obtaining a frequency domain representation associated with an image; obtaining one or more frequency domain representations of one or more object detection filters; generating a composite frequency domain representation based on the frequency domain representation associated with the image and the one or more frequency domain representations of the one or more object detection filters; and detecting one or more objects in the image based on the composite frequency domain representation. The frequency domain representation associated with the image may be obtained based on a forward transform performed on an image feature description. The image feature description may be obtained based on a feature extraction performed on the image. The one or more frequency domain representations of the one or more object detection filters may be obtained based on one or more Fourier transforms performed on the one or more object detection filters.

Abstract: A method of determining an optimal treatment includes determining a frequency for each health care provider indicating how frequently each treats a selected disease, determining for each health care provider, their average patient outcome APO for treating the selected disease, determining a score for each health care provider based on the corresponding frequency and APO, determining which of the health care providers are experts from the scores that exceed a predefined threshold, and selecting a treatment proscribed by at least one of the identified experts as the optimal treatment.

Abstract: A method of determining an optimal treatment includes determining a frequency for each health care provider indicating how frequently each treats a selected disease, determining for each health care provider, their average patient outcome APO for treating the selected disease, determining a score for each health care provider based on the corresponding frequency and APO, determining which of the health care providers are experts from the scores that exceed a predefined threshold, and selecting a treatment proscribed by at least one of the identified experts as the optimal treatment.

Abstract: A method and a system for preserving privacy of a dataset are provided. In the method, a k-anonymity value with respect to a sensitive data field is determined according to at least one first quasi-identifier. Data entries in each group have the same value in the one or more fields of the first quasi-identifier and data entries in different groups have different values in the one or more fields of the first quasi-identifier. A first group and a second group among the plurality of groups are determined according to the reference number Kr, where the first group and the second group are merged into a merging group. The number of data entries in the merging group is not less than a reference number Kr. One or more fields of at least one first quasi-identifier is masked for the merging group.

Abstract: Embodiments are directed to detecting and uploading measurement data of a non-connected medical measuring device. Embodiments include capturing an image of an identification object and a beginning event image of a medical measuring device and extracting identification data from the image of the identification object. Based on detecting that the identification object has been removed, an ending event image of the medical measuring device is captured. Embodiments include determining if a measurement event has occurred by comparing the ending event image and the beginning event image. Based on determining that the measurement event occurred, a measurement data of the ending event image is extracted and upload to a personal health record database.

Abstract: A method and a system for preserving privacy of a dataset are provided. In the method, a k-anonymity value with respect to a sensitive data field is determined according to at least one first quasi-identifier. Data entries in each group have the same value in the one or more fields of the first quasi-identifier and data entries in different groups have different values in the one or more fields of the first quasi-identifier. A first group and a second group among the plurality of groups are determined according to the reference number Kr, where the first group and the second group are merged into a merging group. The number of data entries in the merging group is not less than a reference number Kr. One or more fields of at least one first quasi-identifier is masked for the merging group.