International Business Machines Corporation

Gm Global Technolgoy Operations, Inc.

Lumination LLC

Beihang University

Entropic Communications, Inc.

Yu Pan

Zhong Fang Yuan

Matthew S Mrakovich

Tong Liu

Koushik Babi Saha

David S Yang

Xiang Yu Yang

Wu Tao

Ronald K Brengartner, Jr

Paul Southard

Jeffrey Marc Nall

Ye Wy Wang

Deng Xin Luo

Li Juan Gao

Paolo A Novelletto

Mark Scarlato

Li Ni Zhang

Blair E Carlson

Yong Wang

Yi Chen Zhong

Dan Wu

Hui-ping Wang

Zhuo Jp Cai

Joshua L Solomon

Weisheng Zhao

Peng Ouyang

Miao Guo

Yuanli Wang

William P Payne

Justin Allen Wolsker

Qiong Wu

Qiang He

Youguang Zhang

Jian Long Li

Bowei Song

Michael F Augustine

Reducing an average give-away rate of a weighing device by determining a weight of a product of a weighing device that includes an article, determining one or more conditions of an environment of the weighing device, determining a state of the environment of the weighing device, wherein the state relates to an average give-away rate of the environment of the weighing device, determining a reward value for the state of the environment of the weighing device, wherein the reward value is based at least in part on the weight of the product, and generating a set of parameters for the weighing device based at least in part on the environment, the state, and the reward.

Adjusting parameters of weighing device for reducing average giveaway rate when packaging an article

A computer-implemented method, according to one embodiment, includes: receiving an image having characters that correspond to a language, and using a text recognition algorithm to determine a first language believed to correspond to the characters. A first confidence level associated with the first language is also computed, and a determination is made as to whether the first confidence level associated with the first language is outside a predetermined range. In response to determining that the first confidence level associated with the first language is not outside the predetermined range, the first language is output as the given language. The text recognition algorithm is trained using a simple shallow neural network and a generated mixed language corpus. The generated mixed language corpus is formed by: randomly sampling libraries having vocabulary and/or characters therein, and combining the randomly sampled vocabulary and/or characters to form the generated mixed language corpus.

Rapid language detection for characters in images of documents

Methods, computer program products, and/or systems are provided that perform the following operations: obtaining pre-check data associated with specified data nodes; calculating outliers for each specified data node, wherein the outliers are calculated based on a unit of the pre-check data associated with each specified data node; backtracking the calculated outliers for each specified data node through an associated generating data link; selecting one or more data nodes associated with a set of largest outliers; selecting one or more data links associated with the set of largest outliers; and generating potential anomaly indications based on the one or more data nodes selected and the one or more data links selected.

Cognitive data outlier pre-check based on data lineage

In an approach for a text block recognition in a document, a processor detects characters in the document using an object detection technique. A processor identifies positions of the detected characters in the document. A processor analyzes semantic connectivity among the detected characters based on the positions and semantic connectivity of the characters. A processor recognizes text blocks of related characters based on the semantic connectivity analysis. A processor outputs the text blocks associated with the related characters.

Text block recognition based on discrete character recognition and text information connectivity

A method, system, and computer program product for segmenting and processing documents for optical character recognition is provided. The method includes receiving a document and detecting different types of text data. The document is divided into a plurality of text regions associated with the different types of said text data. Optical noise is removed from each text region and differing optical character recognition software code is selected for application to each text region. The differing optical character recognition software code is executed with respect to each text region resulting in extractable computer readable text located within each said text region.

Optical character recognition segmentation

A method for joining together metal workpiece (or) includes forming a laser weld joint () in a workpiece stack-up () that fusion welds two or more overlapping metal workpiece (oror) together. The laser weld joint () has an initial top surface (). Once the laser weld joint () is formed, the method calls for impinging the laser weld joint () with a laser beam () and moving the laser beam () along the initial joint () including the initial top surface (). The laser beam () is eventually removed from the laser weld joint () to allow the melted upper portion () of the joint () to resolidify and provide the laser weld joint () with a modified top surface () that is smoother than the initial top surface (). By providing the laser weld joint with a smoother modified top surface, residual stress concentration points are removed and the laser weld joint is less liable to damage seal strips.

Method for smoothing the surface of a laser weld joint

A computing in-memory system and computing in-memory method based on a skyrmion race memory are provided. The system comprises a circuit architecture of SRM-CIM. The circuit architecture of the SRM-CIM comprises a row decoder, a column decoder, a voltage-driven, a storage array, a modified sensor circuit, a counter Bit-counter and a mode controller. The voltage-driven includes two NMOSs, and the two NMOSs are respectively connected with a selector MUX. The modified sensor circuit compares the resistance between a first node to a second node and a third node to a fourth node by using a pre-charge sense amplifier. The storage array is composed of the skyrmion racetrack memories. The computing in-memory architecture is designed by utilizing the skyrmion racetrack memory, so that storage is realized in the memory, and computing operation can be carried out in the memory.

Computing in-memory system and method based on skyrmion racetrack memory

A method of laser welding a workpiece stack-up () of overlapping steel workpieces () involves heat-treating a region () of the stack-up () followed by forming a laser weld joint () that is located at least partially within the heat-treated region (). During heat-treating, one or more pre-welding laser beams () are sequentially directed at a top surface () of the workpiece stack-up () and advanced along a pre-welding beam travel pattern () so as to reduce an amount of vaporizable zinc within the stack-up (). Thereafter, the laser weld joint () is formed by directing a welding laser beam () at the top surface () of the workpiece stack-up () and advancing the welding laser beam () along a welding beam travel pattern () that at least partially overlaps with a coverage area of a pre-welding beam travel pattern () or a shared coverage area portion of multiple pre-welding beam travel patterns (). The method can help reduce an amount of vaporizable zinc within the stack-up ().

Method for laser welding steel workpieces

A method of laser welding a workpiece stack-up that includes two or more overlapping metal workpieces is disclosed. The disclosed method includes directing a laser beam at a top surface of the workpiece stack-up to create a molten metal weld pool and, optionally, a keyhole, and further gyrating the laser beam to move a focal point of the laser beam along a helical path having a central helix axis oriented transverse to the top and bottom surfaces of the workpiece stack-up. The gyration of the laser beam may even be practiced to move the focal point of the laser beam along a plurality of helical paths so as to alternately convey the focal point back-and-forth in a first overall axial direction and a second overall axial direction while advancing the laser beam relative to the top surface of the workpiece stack-up along a beam travel pattern.

Remote laser welding of overlapping metal workpieces using helical path(s)

The invention regards to Carrier recovery device, especially estimator device for carrier recovery, for pseudo random noise based systems, comprising a coarse estimator (), a fine estimator (), a switch () to select estimator output, and a sweeper () to sweep input data carrier frequency offset within a certain range, wherein the coarse estimator () is arranged to estimate a residual frequency offset by using a correlation of pseudo random noise (PN), and the fine estimator () is arranged to estimate the residual frequency offset by using an estimated channel information, and wherein the switch () is controlled to select data outputted out of the coarse estimator (), the fine estimator () or the sweeper () as the estimator output.

Carrier recovery method and carrier recovery device for pseudo random noise based system

A string light engine includes a plurality of LEDs, a plurality of IDC connectors, and an insulated flexible conductor. Each IDC connector is in electrical communication with at least one of the plurality of LEDs and is operatively mechanically connected to at least one of the plurality of LEDs. The IDC connectors attach to the conductor.

LED string light engine and devices that are illuminated by the string light engine

A connector electrically connects corresponding conductors of at least first and second cables. The connector comprises a connecting portion into which the conductors of the first and second cables are inserted opposing one another to electrically connect corresponding conductors of each cable. A positive terminal and a negative terminal terminate and electrically connect corresponding conductors of each cable.

IDC splice connector

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Shanghai, China

Yu Pan