Abstract: The invention provides a battery managing system, which includes: a charging/discharging unit, configured to operably charge/discharge the battery; a sensing unit, configured to operably sense a voltage, a discharging current and a discharging duration time of the battery during discharging the battery; and a calculating unit, determining a charge/discharge capability of the battery according to the voltage, the discharge current, the discharge duration time, and temperature of the battery. According to the present invention, the battery managing system can be included in a chip insides each cell of the battery for early indication of poor reliability, so that the chip can be used to determine the charge/discharge capability or to prevent explosion.

Abstract: A computer system identifies threads in a communication session. A feature vector is generated for a message in a communication session, wherein the feature vector includes elements for features and contextual information of the message. The message feature vector and feature vectors for a plurality of threads are processed using machine learning models each associated with a corresponding thread to determine a set of probability values for classifying the message into at least one thread, wherein the threads include one or more pre-existing threads and a new thread. A classification of the message into at least one of the threads is indicated based on the set of probability values. Classification of one or more prior messages is adjusted based on the message's classification. Embodiments of the present invention further include a method and program product for identifying threads in a communication session in substantially the same manner described above.

Abstract: A first photoresist material is formed. The first photoresist material is exposed through a phase shift mask. The first photoresist material is developed to form a first photoresist layer, wherein the first photoresist layer comprises a plurality of first photoresist patterns and a plurality of first openings between the plurality of first photoresist patterns. A first conductive material is formed in the plurality of first openings. A second photoresist layer is formed over the first conductive material, wherein the second photoresist layer comprises at least one second opening. A second conductive material is formed in the at least one second opening. The first photoresist layer and the second photoresist layer are removed, to form a plurality of first conductive patterns and at least one second conductive pattern. A dielectric layer is formed, wherein the at least one second conductive pattern is disposed in the dielectric layer.

Abstract: A computing device receives a natural language input from a user. The computing device routes the natural language input from an active domain node of multiple domain nodes of a multi-domain context-based hierarchy to a leaf node of the domain nodes by selecting a parent domain node in the hierarchy until an off-topic classifier labels the natural language input as in-domain and then selecting a subdomain node in the hierarchy until an in-domain classifier labels the natural language input with a classification label, each of the plurality of domain nodes comprising a respective off-topic classifier and a respective in-domain classifier trained for a respective domain node. The computing device outputs the classification label determined by the leaf node.

Abstract: A mechanism is provided for implementing a bias detection mechanism that mitigates unintended bias in a conversational agent by leveraging conversational agent definitions, a conversational agent chat logs, and user satisfaction statistics. One or more protected attributes are identified within an utterance from the conversational agent chat logs. Using the identified protected attributes, a replacement utterance with a replacement term is generated for at least one of the identified protected attributes in the utterance. A score is generated for the utterance and the replacement utterance using utterance level relative term importance for protected attributes and regular terms in the utterance and the replacement utterance. Utilizing the scoring, a determination is made as to whether unintended bias exists within the utterance. Responsive to unintended bias being detected, an action is implemented that causes a change to a machine learning model used by the conversational agent.

Abstract: The invention, is directed to devices and methods for low cost and convenient separation, of plasma from whole blood. In some embodiments, devices of the invention comprise an integrated collection of channels and chambers m a body that permit acquisition of a blood sample by capillary action, centrifugal separation of cells from plasma, and manual dispensing of purified plasma by simple pinching of a bellows chamber to force air into plasma-holding channels which thereby expels a predetermined volume of the purified plasma.

Abstract: Techniques facilitating detection of conversation threads in unstructured channels are provided. A system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an extraction component that employs a model to detect conversation messages based on a defined confidence level and assigns the conversation messages to respective conversation thread categories. The computer executable components also can comprise a model component that trains the model on conversation messages that comprise respective text data, wherein the model is trained to detect the respective text data to the defined confidence level.

Abstract: Methods and apparatus for complementary evidence identification in natural language inference. A given question is obtained and a set of N passages is obtained from a database. A probability is determined, for each passage of the set of N passages, of a corresponding passage being a supportive passage for the given question and the set of N passages is ranked based on the determined probabilities. M passages that are ranked 1 to M of the set of N passages are selected. A set of L passages is selected based on a plurality of scores, each score assigned to a set of candidate passages of the set of N passages, each score being based on the determined probabilities, the selected M passages, and a weighted regulation parameter. The set of L passages is provided to a computerized machine learning system to answer the question based on the set of L passages.

Abstract: An above ground frame pool (10) includes a frame assembly (20) and a liner (40) supported by the frame assembly (20). The frame assembly (20) includes a plurality of horizontal pipes (22), a plurality of vertical pipes (24), and a plurality of T-shaped joints (30). The joints (30) may lack mechanical fasteners with adjacent pipes or corresponding apertures. The joints (30) may be one-piece or multi-piece structures. Such joints (30) maybe water-resistant and convenient to manufacture, assemble, disassemble, and store.

Abstract: Systems and methods provide for automated messaging summarization and ranking. The systems and methods may use an integrated machine learning model to perform thread detection, thread summarization, and summarization ranking. The messages may be received from a team chat application, organized, summarized and ranked by the machine learning model, and the results may be returned to the team chat application. In some cases, the ranking may be different for different users of the team chat application.

Abstract: Systems and techniques that facilitate few-shot temporal action localization based on graph convolutional networks are provided. In one or more embodiments, a graph component can generate a graph that models a support set of temporal action classifications. Nodes of the graph can correspond to respective temporal action classifications in the support set. Edges of the graph can correspond to similarities between the respective temporal action classifications. In various embodiments, a convolution component can perform a convolution on the graph, such that the nodes of the graph output respective matching scores indicating levels of match between the respective temporal action classifications and an action to be classified. In various embodiments, an instantiation component can input into the nodes respective input vectors based on a proposed feature vector representing the action to be classified.

Abstract: A photoresist apparatus and a method are provided. The photoresist apparatus includes a pre-baking apparatus. The pre-baking apparatus includes: a hot-plate, a first cover over the hot-plate, a second cover over the first cover, a first heating element extending along a topmost surface of the first cover, and a second heating element extending along a topmost surface of the second cover.

Abstract: A mechanism is provided to implement a text classifier training augmentation mechanism for incorporating unlabeled data into the generation of a text classifier. For each term of a plurality of terms in each document of a plurality of documents in a set of unlabeled data, a term frequency value is determined. The term is normalized by dividing the term frequency value by a total number of terms in the document. An inverse document frequency (idf) value is determined for each term based on the term frequency value. A subset of terms is filtered from the plurality of terms based the determined idf values. The idf values for the remaining terms are transformed into feature weights. Terms from a set of labeled data are re-weighted based on the feature weights determined from the set of unlabeled data. The text classifier is then generated using the re-weighted labeled data.

Abstract: An intelligent computer platform to introduce adversarial training to natural language processing (NLP). An initial training set is modified with synthetic training data to create an adversarial training set. The modification includes use of natural language understanding (NLU) to parse the initial training set into components and identify component categories. As input is presented, a classifier evaluates the input and leverages the adversarial training set to identify the intent of the input. An identified classification model generates accurate and reflective response data based on the received input.

Abstract: Methods of manufacturing redistribution circuit structures are disclosed and one of the methods includes the following steps. A seed layer is formed over a die and an encapsulant encapsulating the die. A photoresist material is formed over the seed layer. The photoresist material is exposed through a phase shift mask to an I-line wavelength within an I-line stepper using a numerical aperture equal to or less than 0.18. The photoresist material is developed to form a photoresist layer including photoresist patterns and openings therebetween. A conductive material is formed in the openings. The photoresist patterns are removed to form conductive patterns. By using the conductive patterns as a mask, the seed layer is partially removed, to form seed layer patterns under the conductive patterns, wherein redistribution conductive patterns include the seed layer patterns and the conductive patterns respectively.

Abstract: Systems and techniques that facilitate few-shot temporal action localization based on graph convolutional networks are provided. In one or more embodiments, a graph component can generate a graph that models a support set of temporal action classifications. Nodes of the graph can correspond to respective temporal action classifications in the support set. Edges of the graph can correspond to similarities between the respective temporal action classifications. In various embodiments, a convolution component can perform a convolution on the graph, such that the nodes of the graph output respective matching scores indicating levels of match between the respective temporal action classifications and an action to be classified. In various embodiments, an instantiation component can input into the nodes respective input vectors based on a proposed feature vector representing the action to be classified.

Abstract: A mechanism is provided to implement a text classifier training augmentation mechanism for incorporating unlabeled data into the generation of a text classifier. For each term of a plurality of terms in each document of a plurality of documents in a set of unlabeled data, a term frequency value is determined. The term is normalized by dividing the term frequency value by a total number of terms in the document. An inverse document frequency (idf) value is determined for each term based on the term frequency value. A subset of terms is filtered from the plurality of terms based the determined idf values. The idf values for the remaining terms are transformed into feature weights. Terms from a set of labeled data are re-weighted based on the feature weights determined from the set of unlabeled data. The text classifier is then generated using the re-weighted labeled data.

Abstract: A device includes a molding compound encapsulating a first integrated circuit die and a second integrated circuit die; a dielectric layer over the molding compound, the first integrated circuit die, and the second integrated circuit die; and a metallization pattern over the dielectric layer and electrically connecting the first integrated circuit die to the second integrated circuit die. The metallization pattern comprises a plurality of conductive lines. Each of the plurality of conductive lines extends continuously from a first region of the metallization pattern through a second region of the metallization pattern to a third region of the metallization pattern; and has a same type of manufacturing anomaly in the second region of the metallization pattern.

Abstract: A mechanism is provided to implement suggestion of new entity types with discriminative importance analysis. The mechanism obtains a list of predefined intents from a chatbot designer. The mechanism receives an input sentence having a target intent within the list of predefined intents. The mechanism performs intent-specific importance analysis on the input sentence to generate an importance score for each token in the input sentence. The mechanism ranks the tokens in the input sentence by importance score and outputs a token with a highest importance score as a candidate entity type.

Abstract: An optical lithography system for patterning semiconductor devices and a method of using the same are disclosed. In an embodiment, an apparatus includes an optical path; a prism disposed on the optical path; a lens disposed on the optical path; and a tunable mirror disposed on the optical path, the tunable mirror including a mirror having a concave surface at a front-side thereof; a rear support attached to a backside of the mirror; and a plurality of fine-adjustment screws extending from the rear support to the backside of the mirror.