With the implementation of the“Internet+”strategy,electronic medi-cal records are generally applied in the medicalfield.Deep mining of electronic medical record content data is an effective means to obtain medical kn...With the implementation of the“Internet+”strategy,electronic medi-cal records are generally applied in the medicalfield.Deep mining of electronic medical record content data is an effective means to obtain medical knowledge and analyse patients’states,but the existing methods for extracting entities from electronic medical records have problems of redundant information,overlapping entities,and low accuracy rates.Therefore,this paper proposes an entity extrac-tion method for electronic medical records based on the network framework of BERT-BiLSTM,which incorporates a multichannel self-attention mechanism and location relationship features.First,the text input sequence was encoded using the BERT-BiLSTM network framework,and the global semantic information of the sentence was mined more deeply using the multichannel self-attention mech-anism.Then,the position relation characteristic was used to extract the local semantic message of the text,and the position relation characteristic of the word and the position embedding matrix of the whole sentence were obtained.Next,the extracted global semantic information was stitched with the positional embedding matrix of the sentence to obtain the current entity classification matrix.Finally,the proposed method was validated on the dataset of Chinese medical text entity relationship extraction and the 2010i2b2/VA relationship corpus,and the exper-imental results indicate that the proposed method surpasses existing methods in terms of precision,recall,F1 value and training time.展开更多
Target tracking is one typical application of visual servoing technology. It is still a difficult task to track high speed target with current visual servo system. The improvement of visual servoing scheme is strongly...Target tracking is one typical application of visual servoing technology. It is still a difficult task to track high speed target with current visual servo system. The improvement of visual servoing scheme is strongly required. A position-based visual servo parallel system is presented for tracking target with high speed. A local Frenet frame is assigned to the sampling point of spatial trajectory. Position estimation is formed by the differential features of intrinsic geometry, and orientation estimation is formed by homogenous transformation. The time spent for searching and processing can be greatly reduced by shifting the window according to features location prediction. The simulation results have demonstrated the ability of the system to track spatial moving object.展开更多
Program comprehension is a key activity throughout software maintenance and reuse. The knowledge acquired through comprehending programs can guide engineers to perform various kinds of software maintenance and reuse t...Program comprehension is a key activity throughout software maintenance and reuse. The knowledge acquired through comprehending programs can guide engineers to perform various kinds of software maintenance and reuse tasks. The effective comprehension strategy and the associated efficient approach, as well as the sophisticated tool support, are the indispensable elements for an entire solution to program comprehension to reduce the high costs of this nontrivial activity. This paper presents an objective-oriented comprehension strategy, contrasting to the traditional comprehensive understanding strategy in the literature. It is a kind of on-demand understanding for specific tasks and more effective in practice. In addition, using multiple information sources to understand programs is proposed with the corresponding framework. From these two points of views, we propose a feature-oriented program comprehension approach using requirement documentation. This approach aims at a specific category of feature-related software maintenance and reuse tasks. Case studies are conducted to evaluate the proposed solution. Results from the studied cases show that the experimental prototype provides more explicit advices for software engineers when performing these tasks.展开更多
基金This work is partly supported by the General Project of Scientific Research Funds of Liaoning Provincial Department of Education under Grant Nos.LJKZ0085,and LJKMZ20220447the Project of PublicWelfareResearch Fund for Science(Soft Science Research Program)of Liaoning Province under Grant No.2023JH4/10700056the Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education,Jilin University under Grant No.93K172018K01.
文摘With the implementation of the“Internet+”strategy,electronic medi-cal records are generally applied in the medicalfield.Deep mining of electronic medical record content data is an effective means to obtain medical knowledge and analyse patients’states,but the existing methods for extracting entities from electronic medical records have problems of redundant information,overlapping entities,and low accuracy rates.Therefore,this paper proposes an entity extrac-tion method for electronic medical records based on the network framework of BERT-BiLSTM,which incorporates a multichannel self-attention mechanism and location relationship features.First,the text input sequence was encoded using the BERT-BiLSTM network framework,and the global semantic information of the sentence was mined more deeply using the multichannel self-attention mech-anism.Then,the position relation characteristic was used to extract the local semantic message of the text,and the position relation characteristic of the word and the position embedding matrix of the whole sentence were obtained.Next,the extracted global semantic information was stitched with the positional embedding matrix of the sentence to obtain the current entity classification matrix.Finally,the proposed method was validated on the dataset of Chinese medical text entity relationship extraction and the 2010i2b2/VA relationship corpus,and the exper-imental results indicate that the proposed method surpasses existing methods in terms of precision,recall,F1 value and training time.
基金This project is supported by National Electric Power Corporation Foundation of China(No.SPKJ010-27).
文摘Target tracking is one typical application of visual servoing technology. It is still a difficult task to track high speed target with current visual servo system. The improvement of visual servoing scheme is strongly required. A position-based visual servo parallel system is presented for tracking target with high speed. A local Frenet frame is assigned to the sampling point of spatial trajectory. Position estimation is formed by the differential features of intrinsic geometry, and orientation estimation is formed by homogenous transformation. The time spent for searching and processing can be greatly reduced by shifting the window according to features location prediction. The simulation results have demonstrated the ability of the system to track spatial moving object.
基金the National 973 Key Basic Research and Development Program (Grant No.2002CB312003)the National Natural Science Foundation of China (Grant Nos.90412011 and 60403015)
文摘Program comprehension is a key activity throughout software maintenance and reuse. The knowledge acquired through comprehending programs can guide engineers to perform various kinds of software maintenance and reuse tasks. The effective comprehension strategy and the associated efficient approach, as well as the sophisticated tool support, are the indispensable elements for an entire solution to program comprehension to reduce the high costs of this nontrivial activity. This paper presents an objective-oriented comprehension strategy, contrasting to the traditional comprehensive understanding strategy in the literature. It is a kind of on-demand understanding for specific tasks and more effective in practice. In addition, using multiple information sources to understand programs is proposed with the corresponding framework. From these two points of views, we propose a feature-oriented program comprehension approach using requirement documentation. This approach aims at a specific category of feature-related software maintenance and reuse tasks. Case studies are conducted to evaluate the proposed solution. Results from the studied cases show that the experimental prototype provides more explicit advices for software engineers when performing these tasks.
