Abstract: An approach is provided that automatically computes a number of feature combinations based on a set of subject matter fields that are selected from a set of subject matter fields and further based on qualifiers that correspond to the selected set of subject matter fields. A model in an artificial intelligence (AI) system is then trained using the computed plurality of feature combinations.

Abstract: The present disclosure discloses a method, device and computer readable storage medium for estimating SOC of a lithium battery. State data and corresponding SOC values of lithium batteries under different working conditions are collected to establish a sample set, and clustering analysis is performed on the sample set to obtain a plurality of sample subsets; obtain sub-model functions of the plurality of sample subsets; the state data of a sample to be tested is respectively added into the state data of each of the sample subsets to calculate a change value of the state data of each of the sample subsets before and after the adding operation, and at least one sub-model close to the sample to be tested is selected as the selected sub-model according to the change value; a weight is assigned to the selected sub-model to calculate the SOC value of the sample to be tested.

Abstract: A system, platform, program product, and/or method for generating new composite insight templates that includes: running a machine learning model on a data set to obtain for each of a plurality of entities a risk score and feature-based insights; generating a list of top “n” features input to the machine learning model that contributes to the risk score for each entity; grouping entities based upon similar features input to the machine learning model that contributes to the risk score for each entity; generating a decision tree for at least one of the group of entities; extracting, from the decision tree generated for the at least one of the group of entities, one or more feature-based insights; generating, by applying subject matter input, a new composite insight based upon the one or more feature-based insights; and adding the new composite insight to insight templates.

Abstract: A connector includes a housing provided with an accommodating cavity and a first opening communicating with the accommodating cavity; a circuit board disposed in the accommodating cavity and provided with a first signal connection point; a connection head disposed on the housing and including a second signal connection point for external device connection; and a switch disposed in the first opening, being respectively connected to the first signal connection point and the second signal connection point. The switch is used for controlling the connection or disconnection between the first signal connection point and the second signal connection point. In the above-mentioned manner, the connector and a heavy load may be disconnected by the switch when the connector is pulled out, so that risks of instant ignition and short circuit caused by the connector pulled out may be avoided, and safety accidents may be reduced.

Abstract: An energy storage apparatus includes a cabinet, cyclic cooling units, a support, battery modules, and an air supply duct. The support is fastened in an inner cavity of the cabinet, the battery modules are fastened on the support, and the support and the battery modules jointly separate the inner cavity into an air intake region and an air return region. A heat dissipation duct communicating with the air intake region and the air return region is disposed in the battery module. The cyclic cooling unit is located outside the cabinet and includes an air inlet vent and an air return vent. One end of the air supply duct communicates with the air inlet vent, and the other end of the air supply duct communicates with the air intake region. The air return vent communicates with the air return region.

Abstract: An entity resolution system performs a method of resolving one or more candidate entities based on a data set. The entity resolution system has a machine learning module and a narrative module. The machine learning module generates a synthesized data set, the synthesized data set comprising similarity ratings for each entity feature. The narrative module applies a clustering analysis to determine one or more distances between the group of similarity ratings for each entity feature and one or more clusters associated with known relationships between entities, generates a narrative output based on one or more distances. The narrative output states at least one identified relationship between at least two entities of the plurality of candidate entities and a confidence score. The narrative engine also provides the narrative output to a user interface.

Abstract: An entity resolution system performs a method of resolving one or more candidate entities based on a data set. The entity resolution system has a rules-based module, a machine learning module, a narrative module, and an evaluation module. The rules-based module compares the first entity features to the second entity features and determines whether a rule identifies a relationship between the first entity and the second entity. The machine learning module rates a similarity of the first entity features and the second entity features. The narrative module generates a narrative output based on one or more of the rules-based module and the machine learning module, the narrative output stating an identified relationship between the first entity and the second entity. The evaluation module determines one or more metrics to apply feedback to the system.

Abstract: A vacuum degree detection device with buried electrodes in a vacuum interrupter and a method thereof are provided. The vacuum degree wireless detection device includes two parts, wherein a first part is provided inside the vacuum interrupter, including buried electrodes, etc., wherein the buried electrodes are welded on an end cover of the vacuum interrupter; a second part is the external detection device after the arc interrupter is processed, including: detection and calculation components, wireless transmitters, rechargeable energy storage batteries, wireless charging coils, etc. The external detection device and the buried electrode structure is designed separately, and the buried structure such as the buried electrodes can be processed as a whole with the vacuum interrupter. During the detection, the external detection device is installed above the buried electrode structure.

Abstract: A system, program product, and/or method for evaluating the condition of data for using data analytics options that includes: collecting data to evaluate its condition for supporting a plurality of data analytics options; determining, for each data analytics option, a plurality of a group of data indices, the group consisting of: a volume index measuring the amount of data, a history index for measuring the amount of historical data, a variety index for measuring the variety and type of data, a veracity index for measuring the quality of the data, a value index for measuring the information gain provided by the data; and determining a data readiness score that encompasses scaling, for each of the data analytics options, the plurality of the data indices group. Utilizing a data requirements matrix, providing domain-specific business objectives, and calculating for each of the data analytics options the information gain is also disclosed.

Abstract: A pulse voltage conditioning method of a vacuum interrupter with automatic conditioning energy adjustment based on a trend of a breakdown voltage of the vacuum interrupter during a conditioning process. A current-limiting resistor and a parallel capacitor are automatically adjusted to ensure the conditioning energy reaching a critical value without deconditioning effect. The critical value refers to a maximum conditioning energy without damaging the electrode surfaces, namely an optimal conditioning energy, which can better remove insulation defects on the electrode surface and improve insulation performance of a vacuum gap. The problems of insufficient conditioning and deconditioning effect during conventional voltage conditioning process of the vacuum interrupter can be solved. Therefore, insulation strength of the vacuum interrupter can be raised to a higher level through conditioning.

Abstract: In a quality control method applied in manufacturing, product information of a product is obtained. Manufacturing parameters corresponding to the product information are queried. The manufacturing parameters are input into a product quality prediction model which is trained to obtain the value of at least one quality inspection of each product. If such quality inspection value is not equal to a standard value or is not within a standard value range, an incorrect manufacturing parameter is identified from all the manufacturing parameters applicable to each product, the incorrect manufacturing parameter being output when identified.

Abstract: An isolated antigen-binding protein, having one or more of the following properties: 1) capable of binding to human and monkey-derived GITR proteins at a KD value of 7×10?12 or below, wherein the KD value is measured by BLI method; 2) capable of stimulating immune cell proliferation; 3) capable of stimulating immune cells to secrete IFN-?, wherein the secretion is measured in T cell viability assay; 4) capable of inhibiting tumor growth and/or tumor cell proliferation; 5) capable of activating GITR signaling pathway; 6) capable of inhibiting the binding of GITR to GITRL.

Abstract: A processing method of an adaptation layer of an integrated access and backhaul node and an adaptation layer are provided. The method includes: mapping, by the adaptation layer of the integrated access and backhaul node, a received first data packet to a first bearer or channel between the integrated access and backhaul node and a first node; transmitting, by the adaptation layer of the integrated access and backhaul node, the first data packet to the first node; wherein the first node is a downstream integrated access and backhaul node relative to the integrated access and backhaul node and/or a UE accessing the integrated access and backhaul node, or the first node is an upstream integrated access and backhaul node relative to the integrated access and backhaul node or a donor node of the integrated access and backhaul node.

Abstract: A method, system, and computer program product for computer vision modeling are provided. The method identifies a set of transactions. A set of categorical behavior transaction types are determined for the set of transactions. The set of categorical behavior transaction types are mapped to a set of colors in a color coordinate system. The method scales color component values of the set of colors in the color coordinate system to generate a pattern of colorized units at intervals along a timespan of the set of transactions. The method generates a fraud detection model based on the set of transactions and the color component values.

Abstract: Technical solutions are described for improving the performance of natural language processing systems and other such human-computer interaction systems by facilitating analyzing unstructured computer text by converting such unstructured computer text to domain-specific groups using network graphs. The technical solutions use a graph to connect similar terms with attributes and structural information to facilitate the grouping of different terms that may be used to describe the same entity. Technical solutions facilitate analyzing different input data to generate a graph that can be further used to find data similarity in the input data. The generated graph captures attributes associated with each term and assigns groupings for all the terms at the same time, improving the performance of the natural language processing (NLP) system that is analyzing the input data.

Abstract: A method, computer system, and a computer program product for labeling optimization is provided. The present invention may include receiving a plurality of labeled historical transaction timeline image clusters based on a plurality of historical transaction timeline images clustered using unsupervised machine learning. The present invention may further include training an image recognition model using supervised machine learning based on the received plurality of labeled historical transaction timeline image clusters. The present invention may also include receiving, by the trained image recognition model, a current transaction timeline image. The present invention may further include assigning a corresponding label to the received current transaction timeline image based on matching the received current transaction timeline image to one of the received plurality of labeled historical transaction timeline image clusters.

Abstract: Disclosed is a catalyst for preparing 2,3,3,3-tetrafluoropropene by gas-phase hydrodechlorination, which solves the problem of the high costs and easy deactivation of traditional chlorofluorocarbon hydrodechlorination catalysts. The disclosed catalyst is characterized in consisting of an active component and a carrier, wherein the active component is a combination of one or more of the metals: Ni, Mo, W, Co, Cr, Cu, Ce, La, Mn and Fe. The catalyst in the present invention has excellent performance, high activity, good stability and a low reaction temperature, effectively reduces reaction energy consumption, and has industrial application value.

Abstract: Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises receiving transactional data from at least two users in a plurality of users; determining a pattern within the received transactional data based on a frequency-based domain conversion, wherein the pattern is associated with a determined periodicity; determining a delay within the received transactional data by identifying contextual factors associated with the received transactional data and measuring an amount of time between each identified contextual factors within a plurality of identified contextual factors using a signal processing algorithm; aligning the received transactional data from the at least two users by placing at least two signal forms associated based on the determined delay within the received transactional data at a same point; and generating a line graph depicting the aligned transactional data.

Abstract: Embodiments of the present invention provide a computer system a computer program product, and a method that comprises converting received data from a time-based domain to a frequency-based domain using a signal processing algorithm; identifying transactional noise within the converted data by identifying contextual factors based on a determined pattern, wherein the transactional noise is data associated with an identified fraudulent transaction; filtering the identified transactional noise by removing datapoints within the converted data that reaches a predetermined threshold of signal strength using the signal processing algorithm; and generating a line graph depicting removal of the data that is indicative of the identified transactional noise from the converted data.

Abstract: A system, computer program product, and method are presented for facilitating determinations of risk including behavior classifications and predictions through timeline reshaping and rescoring of structured data. One embodiment of the method includes receiving, for one or more target focal objects, at least a portion of a transaction history including a plurality of sequential transactions, where the portion of the transaction history is associated with a first temporal range. The method also includes generating a first transaction timeline image representative of the portion of the transaction history, where the first temporal range includes a first temporal scaling. The method further includes labeling, through a machine learning (ML) model, the first transaction timeline image. The method also includes reshaping the first transaction timeline image, including rescaling the first temporal range, thereby generating a rescaled transaction timeline image, and labeling the rescaled transaction timeline image.