Abstract: Embodiments of the present invention are directed to facilitating concurrent forecasting associating with multiple time series data sets. In accordance with aspects of the present disclosure, a request to perform a predictive analysis in association with multiple time series data sets is received. Thereafter, the request is parsed to identify each of the time series data sets to use in predictive analysis. For each time series data set, an object is initiated to perform the predictive analysis for the corresponding time series data set. Generally, the predictive analysis predicts expected outcomes based on the corresponding time series data set. Each object is concurrently executed to generate expected outcomes associated with the corresponding time series data set, and the expected outcomes associated with each of the corresponding time series data sets are provided for display.

Abstract: Provided is an encoder, system and method for metaphor detection in natural language processing. The system comprises an encoding module configured to convert words included in a sentence into BiLSTM representation vectors; a first encoder configured to generate a first entire representation vector of a WSD resolving task; a second encoder configured to generate a second entire representation vector of an MD task; and a multi-task learning module configured to perform knowledge transfer between the first and second encoders. Wherein, each of the first and second encoders includes a graph convolutional neural network (GCN) module configured to encode a link between a target word and a core word to generate GCN representation vectors; a control module configured to regulate the GCN representation vectors to generate an entire representation vector.

Abstract: The system includes a cell framework for defining a manufacturing area. The system includes at least one workplace within the manufacturing area. The system includes at least one manufacturing component within the manufacturing area and configured to be movable along three axes in relation to the at least one workplace. The system includes a conveying mechanism configured to move a part into the at least one workplace to be worked on by the at least one manufacturing component.

Abstract: Inert matrices for use with a-synuclein seed amplification assays (“?S-SAA”s) are provided. The inert matrices accurately reflect the absence of misfolded ?S protein when used as a negative control, in the form of no, perceptively low, or delayed ?S substrate self-aggregation, yet will readily permit aggregation of the ?S substrate with seeds when used as a positive control. The inert matrices may be used to screen for ?S-SAA reagent competence. The inert matrices may be used to dilute samples taken from peripheral biological matrices. Finally, the inert matrices may be used as a diluent for serial dilutions of ?S-SAA samples, to enable semi-quantitative versions of ?S-SAAs.

Abstract: A compute-in-memory array is provided that implements a filter for a layer in a neural network. The filter multiplies a plurality of activation bits by a plurality of filter weight bits for each channel in a plurality of channels through a charge accumulation from a plurality of capacitors. The accumulated charge is digitized to provide the output of the filter.

Abstract: Briefly stated, the invention is directed to retrieving a semantically matched knowledge structure. A question and answer pair is received, wherein the answer is received from a query of a search engine. A question is constraint-matched with the answer based on maximizing a plurality of constraints, wherein at least one of the plurality of the constraints is a similarity score between question and answer, wherein the constraint matching generates a matched sequence. For one or more answer sequences, a subsequence is found that are not parsed as answer slots. Query results are obtained from another search engine based on a combination of the answer or question, and the non-answer subsequence. And a KB based is refined on the query results and the constraint matching and based on a neural network training, for a further subsequent semantic matching, wherein the KB includes a dense semantic vector indication of concepts.

Abstract: Bayesian continuous user authentication can be obtained by receiving observed behavior data that collectively characterizes interaction of an active user with at least one computing device or software application. A sequence of events within the observed behavior data can be identified and scored using a universal background model that generates first scores that characterize an extent to which each event or history of events is anomalous for a particular population of users. Further, the events are scored using a user model that generates second scores that characterizes an extent to which each event or history of events is anomalous for the particular user who owns the account. The first scores and the second scores are smoothed using a smoothing function. A probability that the active user is the account owner associated with the user model is determined based on the smoothed first scores and the smoothed second scores.

Abstract: The present disclosure relates to recombinant microorganisms having an improved ethylene producing ability, methods of producing the same, and methods of producing ethylene. A benefit of the recombinant microorganisms and the methods disclosed herein can include increased production of ethylene from microbial cultures. An additional benefit can be the use of carbon dioxide to produce bio-ethylene useful as a feedstock for the production of plastics, textiles, and chemical materials, and for use in other applications. Another benefit of the methods and systems disclosed herein can include reduction of excess carbon dioxide from the environment.

Abstract: A computerized method of diagnosing a mislabeling of a source type of a received event. The method comprising operations of receiving an event by a source type analysis logic with a data index and query system, wherein the event includes a portion of raw machine data and is associated with a specific point in time, obtaining an original source type assigned to the event and one or more predicted source types. The one or more predicted source types are determined by analysis of a data representation of the event in view of training data and the training data includes a plurality of data representations corresponding to known source types. Additionally, the computerized method also includes an operation of, determining whether the event has been mislabeled and in response to determining the event has been mislabeled, diagnosing a source of the mislabeling.

Abstract: The present invention relates to a structure for attachment/detachment of an energy pack for an electric vehicle and, more specifically, a structure for attachment/detachment of an energy pack for an electric vehicle, wherein: the energy capacity of a main energy supply device is reduced, and thereby fuel economy/efficiency can be increased through weight reduction; and an energy pack capable of additional energy supply is separately provided and detachably attached inside the vehicle depending on the travel distance of the vehicle, and thereby the driving conditions of the electric vehicle can be optimized without a need to change driving qualifications.

Abstract: An injection molding apparatus and hot runner system are disclosed. The injection molding apparatus includes a plurality of mold plates in which the hot runner system is received. A manifold receives molding material and has a manifold channel that extends between an inlet and an outlet. A nozzle delivers moldable material to a mold cavity. The nozzle has a nozzle channel in fluid communication between the manifold channel and the mold cavity. A valve pin seal is located at the upstream end of the nozzle, and a valve pin that is connected to an actuator extends through the manifold and nozzle is slidably received in the valve pin seal. The hot runner system further includes a thermal bridge that is in conductive thermal communication with the valve pin seal and a cooled one of the plurality of mold plates.

Abstract: A connector includes a body having gear teeth. A first sleeve is rotatably coupled to the body. A moveable member is positioned in a hole of the first sleeve. A second sleeve is movable with respect to the first sleeve between a locked and unlocked positions. A releasable locking member is positioned between the moveable member and the gear teeth. In the unlocked position of the second sleeve, a recess formed in the second sleeve is aligned with the opening. Upon rotation of the first sleeve, the moveable member is translated into the recess as the releasable locking member travels along the gear teeth. In the locked position of the second sleeve, the recess is rotationally spaced from the opening, and, the releasable locking member is sandwiched between the gear teeth and the moveable member to prevent rotation of the first sleeve with respect to the connector body.

Abstract: Provided herein are compounds, including enantiomerically pure forms thereof, and pharmaceutically acceptable salts or co-crystals and prodrugs thereof which have glucagon receptor antagonist or inverse agonist activity. Further, provided herein are pharmaceutical compositions comprising the same as well as methods of treating, preventing, delaying the time to onset or reducing the risk for the development or progression of a disease or condition for which one or more glucagon receptor antagonist is indicated, including Type I and II diabetes, insulin resistance and hyperglycemia. Moreover, provided herein are methods of making or manufacturing compounds disclosed herein, including enantiomerically pure forms thereof, and pharmaceutically acceptable salts or Co-crystals and prodrugs thereof.

Abstract: Bayesian continuous user authentication can be obtained by receiving observed behavior data that collectively characterizes interaction of an active user with at least one computing device or software application. A sequence of events within the observed behavior data can be identified and scored using a universal background model that generates first scores that characterize an extent to which each event or history of events is anomalous for a particular population of users. Further, the events are scored using a user model that generates second scores that characterizes an extent to which each event or history of events is anomalous for the particular user who owns the account. The first scores and the second scores are smoothed using a smoothing function. A probability that the active user is the account owner associated with the user model is determined based on the smoothed first scores and the smoothed second scores.

Abstract: An Internet of Things (IoT) system is disclosed which includes: a network; a plurality of IoT servers coupled together and serviced by the network; a plurality of IoT agents coupled to each other and to the plurality of IoT servers; and a plurality of IoT devices electrically coupled to the plurality of IoT agents, wherein the IoT servers and the IoT agents further includes a deep reinforcement neural network operative to generate an action map {at} so as to satisfy an arg ? ? max ? a t ? Q ? ( s , a , ? ) wherein Q(s,a)=E[Rt|(s, a)].

Abstract: A smart parking system and method are disclosed which includes a plug-and-play and point to multipoint (PnP&P2MP) based internet of things (IoT) parking sensors, gateway managers, and user devices that can share information via a network. The information is used to preserve parking spaces, calculate minimum parking search time, and establish a dynamic queuing system to achieve high throughput, avoid traffic congestion and time losses.

Abstract: Systems and methods are described herein for computer user authentication using machine learning. Authentication for a user is initiated based on an identification confidence score of the user. The identification confidence score is based on one or more characteristics of the user. Using a machine learning model for the user, user activity of the user is monitored for anomalous activity to generate first data. Based on the monitoring, differences between the first data and historical utilization data for the user determine whether the user's utilization of the one or more resources is anomalous. When the user's utilization of the one or more resource is anomalous, the user's access to the one or more resource is removed.

Abstract: Systems and methods are described herein for computer user authentication using machine learning. Authentication for a user is initiated based on an identification confidence score of the user. The identification confidence score is based on one or more characteristics of the user. Using a machine learning model for the user, user activity of the user is monitored for anomalous activity to generate first data. Based on the monitoring, differences between the first data and historical utilization data for the user determine whether the user's utilization of the one or more resources is anomalous. When the user's utilization of the one or more resource is anomalous, the user's access to the one or more resource is removed.

Abstract: A dual-mode memory is provided that includes a self-timed clock circuit for asserting a sense enable signal for a sense amplifier. In a low-bandwidth read mode, the self-timed clock circuit asserts the sense enable signal only once during a memory clock cycle. The sense amplifier then senses only a single bit from a group of multiplexed columns. In a high-bandwidth read mode, the self-timed clock circuit successively asserts the sense enable signal so that the sense amplifier successively senses bits from the multiplexed columns.

Abstract: An image caption apparatus includes an encoder which encodes an input image; and a decoder which receives an output of the encoder. The decoder comprises a first long short-term memory (LSTM) configured to operate in cooperation with a second LSTM to respectively generate a first hidden vector and a second hidden vector, wherein the second hidden vector is used to generate a word for an output caption, a LSTM cell configured to be used for both the first LSTM and the second LSTM to generate the first hidden vector or the second hidden vector, wherein an personality embedding vector fed into the LSTM cell is employed to modulate an input signal of visual and language features of the internal gates of the LSTM cell, and a personality controller configured to decay the personality embedding vector at each word generation step before the personality embedding vector is fed into the LSTM cell.