International Business Machines Corporation

Delta Electronics, Inc.

Delta Electronics (shanghai) Co., Ltd

China University of Mining and Technology

Shanghai Yuda Industrial Co., Ltd.

Northwestern University

China Petroleum & Chemical Corporation

Shandong University

Shanghai Research Institute of Petrochemical Technology, Sinopec

Jian Min Jiang

Zhong Su

Jing Li

Ke Fei Wang

Guo Tong Xie

Jin Song Ji

Jian Wang

Hongyang Wu

Si Yuan Zhang

Li Ni Zhang

Bin Wang

Shi Wan Zhao

Xiao Feng Guan

Yuan Ni

Bibo Hao

Guo Yu Tang

Xiaoni Xin

Zi Ming Huang

Fang Wang

Jing Min Xu

Wei Zhu Chen

Tao Liu

Si Bin Fan

Wen Sun

Gang Hu

Yue Pan

Jiang Wu

Jing Mei

Changhua Sun

Pei Ni Liu

Dongxu Duan

Marlin R Deckert

En Liang Xu

Songfang Huang

Chau-Chun Wen

Xiaojun Qi

De Zhi Mou

Hui Lei

Yaoping Ruan

Jian-Ping Ying

Shiwan Zhao

Li Ping Yang

Wei Chen

Yong Qin

Hong Iris Zhu

Jian-Hong Zeng

Honglei Guo

Keke Cai

Yi Qin Yu

Rui Li

Zhi Peng Liu

Donald T Tang

Wei Guan

Zhen Zhang

Hong Lei Guo

Ke Ke Cai

Jingtao Tan

Ke Wen Lin

Michael C Smith

Harold H Kung

Chunjin Lin

Eryu Xia

Zhao Ming Qiu

Chang Hua Sun

Bo Hu

Guoyu Tang

Mayfair C Kung

Guangyuan Yu

Xin Ni

Jiong Wang

Qikun Wu

Yu Xiao

Kaitian Yan

Yunfeng Zhang

Mengtian Li

Bagao Li

Yaping Yang

Shouyan Wang

Bing Xue

Jiajia Yu

Jihong Ye

Zhichao Li

Changxi Miao

Bradley W Crawford

Cao Lei

Qifeng Ye

Rujiao Yao

Ying Xue Li

Yongyong Zhu

Wanqing Liu

Dongyu Jiang

Zhen Guo

Wuchao Zhao

A processor obtains a pair including a question and an answer in natural language; determines at least one entity in the question and an entity type of each of the at least one entity consistent with the schema of a knowledge graph (KG); identifies a subset of candidate query templates based on the entity type of each of the at least one entity, wherein the candidate query templates are generated based on the schema of the KG; composes a set of queries by populating the at least one entity into each of the subset of candidate query templates; executes the set of queries on the KG to generate respective answers; identifies a first answer from the respective answers that is matching with the answer in the pair; and determines a candidate query template, from the subset of candidate query templates, corresponding to the first answer as a query template.

Generation of query templates for knowledge-graph based question answering system

The present disclosure relates to a technical field of coal mining, in particular to a surrounding rock stability control method adapted for a coal mining area main roadway. The method comprises the following steps: reinforcing support on a roof and two sides of the mining area main roadway on a basis of an original support form; digging a safety roadway along a stop line of a present working face required by coal mine design, and supporting the safety roadway, wherein a protective coal pillar is formed between the safety roadway and the mining area main roadway; performing slitting blasting on the roof in the safety roadway, wherein blast holes are arranged on a roadway corner line on one side of the present working face to form a pre-splitting slit; and performing stoping at a next working face after completing coal mining at the present working face when stoping at the present working face advances to the safety roadway. By cutting the roof and relieving pressure at the stop mining line of the working face, an influence of mining disturbance on stability of the mining area main roadway in the stoping process of the working face is reduced, and by reinforcing support, a yielding deformation capacity of the mining area main roadway is improved, and the stability of the surrounding rock of the mining area main roadway is further improved.

Surrounding rock stability control method adapted for coal mining area main roadway

Techniques for generating a natural language question template for an artificial intelligence question and answer (QA) system are disclosed. A graph database query relating to a QA system is parsed using a predefined schema. The parsing includes extracting a first plurality of values from the graph database query relating to a where clause in the graph database query, extracting a second plurality of values from the graph database query relating to a return clause in the graph database query, identifying a QA template rule relating to the graph database query, based on a match clause in the graph database query. A natural language question template is generated based on the first plurality of values, the second plurality of values, and the identified QA template rule. The natural language question template is suitable for use by the QA system as part of generating a response to a natural language question.

Generating question templates in a knowledge-graph based question and answer system

A precharge system and method are provided. The precharge system comprises a load circuit, a precharge circuit and a control circuit. The load circuit comprises an input terminal, an input switch and a bus capacitor. The precharge circuit comprises a precharge resistor and a precharge switch. The precharge method comprises: during the load circuit being in a precharge mode, controlling the input switch to be in an off state, and controlling the precharge switch to switch between the on and off state for multiple times; and during the load circuit being in a work mode, controlling the input switch to be in an on state. During the load circuit being in the precharge mode, when the precharge switch is in the on state, a consuming power of the precharge resistor is larger than a threshold power and is smaller than or equal to a limit power of the precharge resistor.

Precharge system and method

The disclosure provides a method for data instance processing. The method includes obtaining a set of data instances collected from a plurality of organizations. Each of the data instances includes at least one record formed in an organization that stores values of a plurality of attributes of the data instance. The method also includes dividing the set of data instances into groups, wherein data instances with conflicting values for the same attribute are divided into different groups. The method further includes subdividing data instances in each of the groups into clusters.

Cross-organization data instance matching

Methods and apparatus for generating medical records from a doctor-patient dialogue are provided. A main content portion of a written doctor-patient conversation is identified. The main content portion of the conversation is extracted from the conversation. The main content of the conversation is divided into sections according to a pre-defined set of sections, and, based on the sections and their respective content, a medical record is generated according to a pre-defined template. The pre-defined template is one of a hard medical record format or a soft medical record format.

Generation of medical records based on doctor-patient dialogue

A multi-dimensional space load and fire test system for a tunnel structure, which includes a multi-point loading self-balancing reaction force system having a rigid platform, two furnace body side-sealing apparatuses () and a model assembly and transport apparatus () for transporting and situating a tunnel model are on a track on the rigid platform (), the two furnace body side-sealing apparatuses () are respectively used for sealing two end openings of the tunnel model, a tower-type combustion vehicle can be placed within an inner cavity of the tunnel model, a plurality of sets of evenly distributed self-adaptive loading apparatuses () used for exerting loading forces on an outer wall of the tunnel model are connected between two reaction force frames () of the multi-point loading self-balancing reaction force system. The present system is able to perform loading on tunnel models having different cross section shapes, can be adapted to testing requirements of tunnel structures having different cross section shapes, and with respect to tunnel structure fire testing in particular, a camera of the present system has a large imaging angle of view, the present invention has good heat resistance, possesses both terminal imaging and distance measurement, and can amply satisfy a use requirement for the high temperature environment of a tunnel fire.

Multi-dimensional space load and fire test system for tunnel structure, and method for implementing same

A computer-implemented method for clinical decision support is provided according to an embodiment of the present disclosure. In the method, patient information can be obtained that comprises at least one clinical condition. A graph can be searched for at least one rule matching the at least one clinical condition. The graph represents a plurality of rule sets. The rule set comprises one or more rule. The rule can be indicated with a path comprising at least one first node and a second node. The first node can indicate a clinical condition, and the second node can indicate a clinical conclusion. Then, a clinical conclusion can be determined based on the at least one path in response that the at least one path matching the at least one clinical condition is searched out.

Clinical decision support

Method and apparatus are presented for receiving a medical or medical condition related input term or phrase in a source language, and translating the term or phrase from the source language into at least one target language to obtain a set of translated terms of the input term. For each translated term in the set of translations, the method and apparatus further translate the set of translations back into the source language to obtain an output list of standard versions of the input term, scoring each entry of the output list as to probability of being the most standard version of the input term, and providing the entry of the output list that has the highest score to a user.

Normalization of medical terms with multi-lingual resources

Methods and systems for using machine learning to determine electronic document similarity include extracting entities and corresponding relationships from each of two electronic documents of a corpus of electronic documents based on word embedding, computing an entity distance between the extracted entities and a relationship distance between the extracted relationships based on knowledge graph embedding, combining the entity and relationship distances to generate a similarity score between the electronic documents, and implementing the similarity score to perform a task associated with the electronic documents.

Using machine learning to determine electronic document similarity

Methods, systems, and computer program products are provided for language entity identification. In one embodiment, a computer-implemented method is disclosed. In the method, respective pinyin codes may be determined for respective Chinese characters comprised in a string that is to be processed. Then, respective pinyin features may be generated from the respective pinyin codes. Next, a candidate language entity may be identified from the string based on the respective pinyin features and a mapping describing an association between pinyin features and language entity. In other embodiments, a computer-implemented system and a computer program product for security management are disclosed.

Language entity identification

Systems, computer-implemented methods and/or computer program products that facilitate automatically mapping different data types are provided. In one embodiment, a computer-implemented method comprises: constructing, by a system operatively coupled to a processor, an index from one or more classifier models for one or more data types; scoring and ranking, by the system, one or more candidate pairs for the one or more data types based on confidence score; and analyzing, by the system, how the one or more candidate pairs are scored and automatically generating the one or more classifier models used to construct the index.

Facilitating data-driven mapping discovery

A computer implemented method identifies guidelines through use of a neural network by a remote guideline server. A client computer transmits instructions to the remote guideline server to retrieve and evaluate multiple candidate guidelines. The remote guideline server utilizes a neural network to identify a string of terms found in each of the multiple candidate guidelines that match one or more strings of terms from a model guideline; to identify a semantic concept of each of the multiple candidate guidelines that matches one or more semantic concepts from the model guideline; and to identify a structural pattern of each of the multiple candidate guidelines that matches one or more structural patterns of the model guideline. The candidate guidelines that match the model guideline are then sent from the remote guideline server to the client computer.

Remote neural network processing for guideline identification

An amplification system includes a first amplification module, a second amplification module, a third amplification module I, a fourth amplification module I, a first load, a third amplification module II, a fourth amplification module II and a second load. An output terminal of the first amplification module is connected to an input terminal of the second amplification module; output terminals of the second amplification module are connected to an input terminal of the third amplification module I and an input terminal of the third amplification module II. An output terminal of the third amplification module I is connected to an input terminal of the first load through the fourth amplification module I. An output terminal of the third amplification module II is connected to an input terminal of the second load through the fourth amplification module II.

Amplification system for continuously adjusting amplification gain of a high frequency weak signal for mass spectrometers

A method is provided for data matching between a set of source data structures and a set of target data structures. The method includes obtaining, using a processor device configured to perform machine learning, source to target matching results with matching scores, based on the sets of source and target data structures. The method further includes calculating, by the processor device, context information for data structure pairs based on a structure similarity and an ontology similarity between constituent data structures thereof. Each of data structure pairs include as the constituent data structures a respective source data structure and a respective target data structure from the sets of source and target data structures. The method also includes updating, by the processor device, the matching scores based on the context information. The method additionally includes controlling, by the processor device, a hardware device responsive to at least one updated matching score.

Data matching accuracy based on context features

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Beijing, China

Jian Min Jiang