Remote driving,an emergent technology enabling remote operations of vehicles,presents a significant challenge in transmitting large volumes of image data to a central server.This requirement outpaces the capacity of t...Remote driving,an emergent technology enabling remote operations of vehicles,presents a significant challenge in transmitting large volumes of image data to a central server.This requirement outpaces the capacity of traditional communication methods.To tackle this,we propose a novel framework using semantic communications,through a region of interest semantic segmentation method,to reduce the communication costs by transmitting meaningful semantic information rather than bit-wise data.To solve the knowledge base inconsistencies inherent in semantic communications,we introduce a blockchain-based edge-assisted system for managing diverse and geographically varied semantic segmentation knowledge bases.This system not only ensures the security of data through the tamper-resistant nature of blockchain but also leverages edge computing for efficient management.Additionally,the implementation of blockchain sharding handles differentiated knowledge bases for various tasks,thus boosting overall blockchain efficiency.Experimental results show a great reduction in latency by sharding and an increase in model accuracy,confirming our framework's effectiveness.展开更多
In the context of power generation companies, vast amounts of specialized data and expert knowledge have been accumulated. However, challenges such as data silos and fragmented knowledge hinder the effective utilizati...In the context of power generation companies, vast amounts of specialized data and expert knowledge have been accumulated. However, challenges such as data silos and fragmented knowledge hinder the effective utilization of this information. This study proposes a novel framework for intelligent Question-and-Answer (Q&A) systems based on Retrieval-Augmented Generation (RAG) to address these issues. The system efficiently acquires domain-specific knowledge by leveraging external databases, including Relational Databases (RDBs) and graph databases, without additional fine-tuning for Large Language Models (LLMs). Crucially, the framework integrates a Dynamic Knowledge Base Updating Mechanism (DKBUM) and a Weighted Context-Aware Similarity (WCAS) method to enhance retrieval accuracy and mitigate inherent limitations of LLMs, such as hallucinations and lack of specialization. Additionally, the proposed DKBUM dynamically adjusts knowledge weights within the database, ensuring that the most recent and relevant information is utilized, while WCAS refines the alignment between queries and knowledge items by enhanced context understanding. Experimental validation demonstrates that the system can generate timely, accurate, and context-sensitive responses, making it a robust solution for managing complex business logic in specialized industries.展开更多
The“Opinions on Comprehensively Deepening Curriculum Reform to Fulfill the Fundamental Task of Strengthening Moral Education”,issued by China’s Ministry of Education in 2015,explicitly identified Project-Based Lear...The“Opinions on Comprehensively Deepening Curriculum Reform to Fulfill the Fundamental Task of Strengthening Moral Education”,issued by China’s Ministry of Education in 2015,explicitly identified Project-Based Learning(PBL)as a key strategy for cultivating students’core competencies.Since then,PBL has been widely implemented as a pilot initiative in primary and secondary schools,gaining increasing influence.Analyzing the intellectual foundations of PBL research in China can offer valuable insights into its theoretical and practical dimensions.This study uses CiteSpace to examine 156 PBL-related articles from the CSSCI database,revealing that the knowledge base of PBL research is primarily built on two major domains.The first is the theoretical foundation,characterized by frequently cited literature focusing on the conceptual framework,educational value,interdisciplinary approaches,core competency cultivation,and instructional objectives of PBL.The second is empirical research,where highly cited studies include case analyses across K–12 settings,general high schools,and higher education institutions.Moving forward,future research on PBL should explore its meaning and value from a dual-subject and integrated perspective,expand case studies to include vocational education,and further promote the interdisciplinary development of core competencies through PBL.展开更多
To increase efficiency in fierce competition,it is necessary and urgent to improve the standard of production planning for shipbuilding.The construction of curved blocks is the bottleneck to improve the efficiency of ...To increase efficiency in fierce competition,it is necessary and urgent to improve the standard of production planning for shipbuilding.The construction of curved blocks is the bottleneck to improve the efficiency of shipbuilding.Thus it is a key breakthrough for higher shipbuilding productivity to study the curved block production.By analyzing the scheduling problem in curved blocks production,we propose an intelligent curved block production scheduling method and its system based on a knowledge base,and show the main process of the system.The functions of the system include data management,assembly plan generation,plan adjustment,and plan evaluation.In order to deal with the actual situation and inherit the empirical knowledge,the system extracts some rules to control block selecting,algorithm selection,and evaluation thresholds to build a production decision-making knowledge base in the curved block scheduling system.The proposed knowledge base could be referred and modified by users,especially after a few interactions between the users and the knowledge base.The final assembly plan can be visualized and evaluated to facilitate the observation of plan implementation and effects of the decisions in the process.Finally,the system is verified by a large shipyard in Shanghai using real data and the results illustrate that the proposed method can perform the knowledge-based scheduling for curved blocks construction effectively.展开更多
As legal cases grow in complexity and volume worldwide,integrating machine learning and artificial intelligence into judicial systems has become a pivotal research focus.This study introduces a comprehensive framework...As legal cases grow in complexity and volume worldwide,integrating machine learning and artificial intelligence into judicial systems has become a pivotal research focus.This study introduces a comprehensive framework for verdict recommendation that synergizes rule-based methods with deep learning techniques specifically tailored to the legal domain.The proposed framework comprises three core modules:legal feature extraction,semantic similarity assessment,and verdict recommendation.For legal feature extraction,a rule-based approach leverages Black’s Law Dictionary and WordNet Synsets to construct feature vectors from judicial texts.Semantic similarity between cases is evaluated using a hybrid method that combines rule-based logic with an LSTM model,analyzing the feature vectors of query cases against a legal knowledge base.Verdicts are then recommended through a rule-based retrieval system,enhanced by predefined legal statutes and regulations.By merging rule-based methodologies with deep learning,this framework addresses the interpretability challenges often associated with contemporary AImodels,thereby enhancing both transparency and generalizability across diverse legal contexts.The system was rigorously tested using a legal corpus of 43,000 case laws across six categories:Criminal,Revenue,Service,Corporate,Constitutional,and Civil law,ensuring its adaptability across a wide range of judicial scenarios.Performance evaluation showed that the feature extraction module achieved an average accuracy of 91.6%with an F-Score of 95%.The semantic similarity module,tested using Manhattan,Euclidean,and Cosine distance metrics,achieved 88%accuracy and a 93%F-Score for short queries(Manhattan),89%accuracy and a 93.7%F-Score for medium-length queries(Euclidean),and 87%accuracy with a 92.5%F-Score for longer queries(Cosine).The verdict recommendation module outperformed existing methods,achieving 90%accuracy and a 93.75%F-Score.This study highlights the potential of hybrid AI frameworks to improve judicial decision-making and streamline legal processes,offering a robust,interpretable,and adaptable solution for the evolving demands of modern legal systems.展开更多
In this paper, the knowledge based enterprise is considered as an organism, which possesses a set of capabilities. The organizational structure model of knowledge based enterprise organism is described in order to pos...In this paper, the knowledge based enterprise is considered as an organism, which possesses a set of capabilities. The organizational structure model of knowledge based enterprise organism is described in order to possess the essential capacity set. A dynamic capacity set is defined and analyzed based on the definition of the growth and development for knowledge based enterprise organism. The structure of the capacity base, a subset of the capacity set, is optimized for different periods of the organism ...展开更多
In this paper, the structure characteristics of open complex giant systems are concretely analysed in depth, thus the view and its significance to support the meta synthesis engineering with manifold knowledge models...In this paper, the structure characteristics of open complex giant systems are concretely analysed in depth, thus the view and its significance to support the meta synthesis engineering with manifold knowledge models are clarified. Furthermore, the knowledge based multifaceted modeling methodology for open complex giant systems is emphatically studied. The major points are as follows: (1) nonlinear mechanism and general information partition law; (2) from the symmetry and similarity to the acquisition of construction knowledge; (3) structures for hierarchical and nonhierarchical organizations; (4) the integration of manifold knowledge models; (5) the methodology of knowledge based multifaceted modeling.展开更多
The aim, characteristics and requirements of stampability evaluation are identified. As sampability evaluation is highly skill intensive and requires a wide variety of design expertise and knowledge, a knowledge based...The aim, characteristics and requirements of stampability evaluation are identified. As sampability evaluation is highly skill intensive and requires a wide variety of design expertise and knowledge, a knowledge based system is proposed for implementing the stampability evaluation. The stampability evaluation knowledge representation, and processing phases are illustrated. A case study demonstrates the feasibility of the knowledge based approach to stampability evaluation.展开更多
Aiming at the relation linking task for question answering over knowledge base,especially the multi relation linking task for complex questions,a relation linking approach based on the multi-attention recurrent neural...Aiming at the relation linking task for question answering over knowledge base,especially the multi relation linking task for complex questions,a relation linking approach based on the multi-attention recurrent neural network(RNN)model is proposed,which works for both simple and complex questions.First,the vector representations of questions are learned by the bidirectional long short-term memory(Bi-LSTM)model at the word and character levels,and named entities in questions are labeled by the conditional random field(CRF)model.Candidate entities are generated based on a dictionary,the disambiguation of candidate entities is realized based on predefined rules,and named entities mentioned in questions are linked to entities in knowledge base.Next,questions are classified into simple or complex questions by the machine learning method.Starting from the identified entities,for simple questions,one-hop relations are collected in the knowledge base as candidate relations;for complex questions,two-hop relations are collected as candidates.Finally,the multi-attention Bi-LSTM model is used to encode questions and candidate relations,compare their similarity,and return the candidate relation with the highest similarity as the result of relation linking.It is worth noting that the Bi-LSTM model with one attentions is adopted for simple questions,and the Bi-LSTM model with two attentions is adopted for complex questions.The experimental results show that,based on the effective entity linking method,the Bi-LSTM model with the attention mechanism improves the relation linking effectiveness of both simple and complex questions,which outperforms the existing relation linking methods based on graph algorithm or linguistics understanding.展开更多
In order to enhance the intelligent level of system and improve the interaetivity with other systems, a knowledge and XML based computer aided process planning （CAPP） system is implemented. It includes user manageme...In order to enhance the intelligent level of system and improve the interaetivity with other systems, a knowledge and XML based computer aided process planning （CAPP） system is implemented. It includes user management, bill of materials（BOM） management, knowledge based process planning, knowledge management and database maintaining sub-systems. This kind of nesting knowledge representation method the system provided can represent complicated arithmetic and logical relationship to deal with process planning tasks. With the representation and manipulation of XML based technological file, the system solves some important problems in web environment such as information interactive efficiency and refreshing of web page. The CAPP system is written in ASP VBScript, JavaScript, Visual C＋＋ languages and Oracle database. At present, the CAPP system is running in Shenyang Machine Tools. The functions of it meet the requirements of enterprise production.展开更多
Based on the knowledge representation and knowledge reasoning, this paper addresses the creation of the multi-attribute knowledge base on the basis of hybrid knowledge representation, with the help of object-oriented ...Based on the knowledge representation and knowledge reasoning, this paper addresses the creation of the multi-attribute knowledge base on the basis of hybrid knowledge representation, with the help of object-oriented programming language and relational database. Compared with general knowledge base, multi-attribute knowledge base can enhance the ability of knowledge processing and application; integrate the heterogeneous knowledge, such as model, symbol, case-based sample knowledge; and support the whole decision process by integrated reasoning.展开更多
The present work deals with the development of an Ontology-Based Knowledge Network of soil/water physicochemical & biological properties (soil/water concepts), derived from ASTM Standard Methods (ASTMi,n) and rele...The present work deals with the development of an Ontology-Based Knowledge Network of soil/water physicochemical & biological properties (soil/water concepts), derived from ASTM Standard Methods (ASTMi,n) and relevant scientific/applicable references (published papers—PPi,n) to fill up/bridge the gap of the information science between cited Standards and infiltration discipline conceptual vocabulary providing accordingly a dedicated/internal Knowledge Base (KB). This attempt constitutes an innovative approach, since it is based on externalizing domain knowledge in the form of Ontology-Based Knowledge Networks, incorporating standardized methodology in soil engineering. The ontology soil/water concepts (semantics) of the developed network correspond to soil/water physicochemical & biological properties, classified in seven different generations that are distinguished/located in infiltration/percolation process of contaminated water through soil porous media. The interconnections with arcs between corresponding concepts/properties among the consecutive generations are defined by the relationship of dependent and independent variables. All these interconnections are documented according to the below three ways: 1) dependent and independent variables interconnected by using the logical operator “<em>depends on</em>” quoting existent explicit functions and equations;2) dependent and independent variables interconnected by using the logical operator “<em>depends on</em>” quoting produced implicit functions, according to Rayleigh’s method of indices;3) dependent and independent variables interconnected by using the logical operator “<em>related to</em>” based on a logical dependence among the examined nodes-concepts-variables. The aforementioned approach provides significant advantages to semantic web developers and web users by means of prompt knowledge navigation, tracking, retrieval and usage.展开更多
Named Entity Recognition(NER)stands as a fundamental task within the field of biomedical text mining,aiming to extract specific types of entities such as genes,proteins,and diseases from complex biomedical texts and c...Named Entity Recognition(NER)stands as a fundamental task within the field of biomedical text mining,aiming to extract specific types of entities such as genes,proteins,and diseases from complex biomedical texts and categorize them into predefined entity types.This process can provide basic support for the automatic construction of knowledge bases.In contrast to general texts,biomedical texts frequently contain numerous nested entities and local dependencies among these entities,presenting significant challenges to prevailing NER models.To address these issues,we propose a novel Chinese nested biomedical NER model based on RoBERTa and Global Pointer(RoBGP).Our model initially utilizes the RoBERTa-wwm-ext-large pretrained language model to dynamically generate word-level initial vectors.It then incorporates a Bidirectional Long Short-Term Memory network for capturing bidirectional semantic information,effectively addressing the issue of long-distance dependencies.Furthermore,the Global Pointer model is employed to comprehensively recognize all nested entities in the text.We conduct extensive experiments on the Chinese medical dataset CMeEE and the results demonstrate the superior performance of RoBGP over several baseline models.This research confirms the effectiveness of RoBGP in Chinese biomedical NER,providing reliable technical support for biomedical information extraction and knowledge base construction.展开更多
Most of KBE systems applied by previous researchers are dependent on some CAD software, which makes knowledge hard to be reused to other CAD software. Independent knowledge based system is independent of CAD software;...Most of KBE systems applied by previous researchers are dependent on some CAD software, which makes knowledge hard to be reused to other CAD software. Independent knowledge based system is independent of CAD software; therefore knowledge can be reused freely. This paper describes independent knowledge based system for mechanical design. A detailed discussion about typical design is put forward including design process implementation based on knowledge engineering, independent knowledge based design architecture. The main principal of knowledge driven engineering is explained. The implementation of KBE on the design of worm reducer is studied as a case. Independent knowledge based reducer design system is realized. The usage of independent knowledge based system makes KBE system work independent of CAD software, which enhances their portability and fertilizes the collaborative work of heterogeneous CAD systems.展开更多
With the deep research of knowledge engineering and the widespread applications of CAD technology, the joining of knowledge engineering with CAD is the focus of advanced manufacturing. An intelligent approach is prese...With the deep research of knowledge engineering and the widespread applications of CAD technology, the joining of knowledge engineering with CAD is the focus of advanced manufacturing. An intelligent approach is presented for configurating the typical structural components of radar. Case based reasoning, rule based reasoning, geometric, constraint solving and domain ontology are merged into a compound knowledge model. The main frame and workflow of radar typical structural component design system are illustrated. Experiments show this approach is efficient and effective.展开更多
Search engines have greatly helped us to find the desired information from the Internet. Most search engines use keywords matching technique. This paper discusses a Dynamic Knowledge Base based Search Engine （DKBSE）...Search engines have greatly helped us to find the desired information from the Internet. Most search engines use keywords matching technique. This paper discusses a Dynamic Knowledge Base based Search Engine （DKBSE）, which can expand the user＇s query using the keywords＇ concept or meaning. To do this, the DKBSE needs to construct and maintain the knowledge base dynamically via the system＇s searching results and the user＇s feedback information. The DKBSE expands the user＇s initial query using the knowledge base, and returns the searched information after the expanded query.展开更多
This paper presents a novel application of metaheuristic algorithmsfor solving stochastic programming problems using a recently developed gaining sharing knowledge based optimization (GSK) algorithm. The algorithmis b...This paper presents a novel application of metaheuristic algorithmsfor solving stochastic programming problems using a recently developed gaining sharing knowledge based optimization (GSK) algorithm. The algorithmis based on human behavior in which people gain and share their knowledgewith others. Different types of stochastic fractional programming problemsare considered in this study. The augmented Lagrangian method (ALM)is used to handle these constrained optimization problems by convertingthem into unconstrained optimization problems. Three examples from theliterature are considered and transformed into their deterministic form usingthe chance-constrained technique. The transformed problems are solved usingGSK algorithm and the results are compared with eight other state-of-the-artmetaheuristic algorithms. The obtained results are also compared with theoptimal global solution and the results quoted in the literature. To investigatethe performance of the GSK algorithm on a real-world problem, a solidstochastic fixed charge transportation problem is examined, in which theparameters of the problem are considered as random variables. The obtainedresults show that the GSK algorithm outperforms other algorithms in termsof convergence, robustness, computational time, and quality of obtainedsolutions.展开更多
A new structure of ESKD (expert system based on knowledge discovery system KD (D&K)) is first presented on the basis of KD (D&K)-a synthesized knowledge discovery system based on double-base (database and know...A new structure of ESKD (expert system based on knowledge discovery system KD (D&K)) is first presented on the basis of KD (D&K)-a synthesized knowledge discovery system based on double-base (database and knowledge base) cooperating mechanism. With all new features, ESKD may form a new research direction and provide a great probability for solving the wealth of knowledge in the knowledge base. The general structural frame of ESKD and some sub-systems among ESKD have been described, and the dynamic knowledge base based on double-base cooperating mechanism has been emphased on. According to the result of demonstrative experi- ment, the structure of ESKD is effective and feasible.展开更多
MedTrad＋ is an expert system for African Traditional Medicine where actors are often illiterate. Its originality lies in the use of icons instead of textual content of facts. It has been created by GExpert＋ which is...MedTrad＋ is an expert system for African Traditional Medicine where actors are often illiterate. Its originality lies in the use of icons instead of textual content of facts. It has been created by GExpert＋ which is An Expert system Generator based on the use of icons in a Web environment. With its iconic interface GExpert＋ allows any user to overcome any intermediary for the management and the use of its knowledge base. Traditional healers from Yamoussoukro region are working toward its validation.展开更多
A knowledge based company is the microcosmic foundation of the knowledge economy, the design of its organization structure should amplify the company competence to be agile to the knowledge elements. This paper expoun...A knowledge based company is the microcosmic foundation of the knowledge economy, the design of its organization structure should amplify the company competence to be agile to the knowledge elements. This paper expounds an interior market network structure which is fit for the company intellectual capital operation, and analyses this organization pattern about the reasons of existence, the effectiveness of growing up in scale, the economies of knowledge distribution and the efficiency of operation, and it will provide some beneficial theoretical guidance about how can a company improve its competition competence in the knowledge environment through organization innovation.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant No.62062031in part by the MIC/SCOPE#JP235006102+2 种基金in part by JST ASPIRE Grant Number JPMJAP2325in part by ROIS NII Open Collaborative Research under Grant 24S0601in part by collaborative research with Toyota Motor Corporation,Japan。
文摘Remote driving,an emergent technology enabling remote operations of vehicles,presents a significant challenge in transmitting large volumes of image data to a central server.This requirement outpaces the capacity of traditional communication methods.To tackle this,we propose a novel framework using semantic communications,through a region of interest semantic segmentation method,to reduce the communication costs by transmitting meaningful semantic information rather than bit-wise data.To solve the knowledge base inconsistencies inherent in semantic communications,we introduce a blockchain-based edge-assisted system for managing diverse and geographically varied semantic segmentation knowledge bases.This system not only ensures the security of data through the tamper-resistant nature of blockchain but also leverages edge computing for efficient management.Additionally,the implementation of blockchain sharding handles differentiated knowledge bases for various tasks,thus boosting overall blockchain efficiency.Experimental results show a great reduction in latency by sharding and an increase in model accuracy,confirming our framework's effectiveness.
文摘In the context of power generation companies, vast amounts of specialized data and expert knowledge have been accumulated. However, challenges such as data silos and fragmented knowledge hinder the effective utilization of this information. This study proposes a novel framework for intelligent Question-and-Answer (Q&A) systems based on Retrieval-Augmented Generation (RAG) to address these issues. The system efficiently acquires domain-specific knowledge by leveraging external databases, including Relational Databases (RDBs) and graph databases, without additional fine-tuning for Large Language Models (LLMs). Crucially, the framework integrates a Dynamic Knowledge Base Updating Mechanism (DKBUM) and a Weighted Context-Aware Similarity (WCAS) method to enhance retrieval accuracy and mitigate inherent limitations of LLMs, such as hallucinations and lack of specialization. Additionally, the proposed DKBUM dynamically adjusts knowledge weights within the database, ensuring that the most recent and relevant information is utilized, while WCAS refines the alignment between queries and knowledge items by enhanced context understanding. Experimental validation demonstrates that the system can generate timely, accurate, and context-sensitive responses, making it a robust solution for managing complex business logic in specialized industries.
基金Provincial-Level Quality Engineering Project,Preschool Education Teacher Training Base of Fuyang Normal University(Project No.:2023cyts023)University-Level Research Team Project,Collaborative Innovation Center for Basic Education in Northern Anhui(Project No.:kytd202418)。
文摘The“Opinions on Comprehensively Deepening Curriculum Reform to Fulfill the Fundamental Task of Strengthening Moral Education”,issued by China’s Ministry of Education in 2015,explicitly identified Project-Based Learning(PBL)as a key strategy for cultivating students’core competencies.Since then,PBL has been widely implemented as a pilot initiative in primary and secondary schools,gaining increasing influence.Analyzing the intellectual foundations of PBL research in China can offer valuable insights into its theoretical and practical dimensions.This study uses CiteSpace to examine 156 PBL-related articles from the CSSCI database,revealing that the knowledge base of PBL research is primarily built on two major domains.The first is the theoretical foundation,characterized by frequently cited literature focusing on the conceptual framework,educational value,interdisciplinary approaches,core competency cultivation,and instructional objectives of PBL.The second is empirical research,where highly cited studies include case analyses across K–12 settings,general high schools,and higher education institutions.Moving forward,future research on PBL should explore its meaning and value from a dual-subject and integrated perspective,expand case studies to include vocational education,and further promote the interdisciplinary development of core competencies through PBL.
基金the China High-Tech Ship Project of the Ministry of Industry and Information Technology(No.2021-51(MC-202032-Z08))。
文摘To increase efficiency in fierce competition,it is necessary and urgent to improve the standard of production planning for shipbuilding.The construction of curved blocks is the bottleneck to improve the efficiency of shipbuilding.Thus it is a key breakthrough for higher shipbuilding productivity to study the curved block production.By analyzing the scheduling problem in curved blocks production,we propose an intelligent curved block production scheduling method and its system based on a knowledge base,and show the main process of the system.The functions of the system include data management,assembly plan generation,plan adjustment,and plan evaluation.In order to deal with the actual situation and inherit the empirical knowledge,the system extracts some rules to control block selecting,algorithm selection,and evaluation thresholds to build a production decision-making knowledge base in the curved block scheduling system.The proposed knowledge base could be referred and modified by users,especially after a few interactions between the users and the knowledge base.The final assembly plan can be visualized and evaluated to facilitate the observation of plan implementation and effects of the decisions in the process.Finally,the system is verified by a large shipyard in Shanghai using real data and the results illustrate that the proposed method can perform the knowledge-based scheduling for curved blocks construction effectively.
基金funded by the Deanship of Scientific Research at Jouf University under Grant number DSR-2022-RG-0101。
文摘As legal cases grow in complexity and volume worldwide,integrating machine learning and artificial intelligence into judicial systems has become a pivotal research focus.This study introduces a comprehensive framework for verdict recommendation that synergizes rule-based methods with deep learning techniques specifically tailored to the legal domain.The proposed framework comprises three core modules:legal feature extraction,semantic similarity assessment,and verdict recommendation.For legal feature extraction,a rule-based approach leverages Black’s Law Dictionary and WordNet Synsets to construct feature vectors from judicial texts.Semantic similarity between cases is evaluated using a hybrid method that combines rule-based logic with an LSTM model,analyzing the feature vectors of query cases against a legal knowledge base.Verdicts are then recommended through a rule-based retrieval system,enhanced by predefined legal statutes and regulations.By merging rule-based methodologies with deep learning,this framework addresses the interpretability challenges often associated with contemporary AImodels,thereby enhancing both transparency and generalizability across diverse legal contexts.The system was rigorously tested using a legal corpus of 43,000 case laws across six categories:Criminal,Revenue,Service,Corporate,Constitutional,and Civil law,ensuring its adaptability across a wide range of judicial scenarios.Performance evaluation showed that the feature extraction module achieved an average accuracy of 91.6%with an F-Score of 95%.The semantic similarity module,tested using Manhattan,Euclidean,and Cosine distance metrics,achieved 88%accuracy and a 93%F-Score for short queries(Manhattan),89%accuracy and a 93.7%F-Score for medium-length queries(Euclidean),and 87%accuracy with a 92.5%F-Score for longer queries(Cosine).The verdict recommendation module outperformed existing methods,achieving 90%accuracy and a 93.75%F-Score.This study highlights the potential of hybrid AI frameworks to improve judicial decision-making and streamline legal processes,offering a robust,interpretable,and adaptable solution for the evolving demands of modern legal systems.
文摘In this paper, the knowledge based enterprise is considered as an organism, which possesses a set of capabilities. The organizational structure model of knowledge based enterprise organism is described in order to possess the essential capacity set. A dynamic capacity set is defined and analyzed based on the definition of the growth and development for knowledge based enterprise organism. The structure of the capacity base, a subset of the capacity set, is optimized for different periods of the organism ...
文摘In this paper, the structure characteristics of open complex giant systems are concretely analysed in depth, thus the view and its significance to support the meta synthesis engineering with manifold knowledge models are clarified. Furthermore, the knowledge based multifaceted modeling methodology for open complex giant systems is emphatically studied. The major points are as follows: (1) nonlinear mechanism and general information partition law; (2) from the symmetry and similarity to the acquisition of construction knowledge; (3) structures for hierarchical and nonhierarchical organizations; (4) the integration of manifold knowledge models; (5) the methodology of knowledge based multifaceted modeling.
文摘The aim, characteristics and requirements of stampability evaluation are identified. As sampability evaluation is highly skill intensive and requires a wide variety of design expertise and knowledge, a knowledge based system is proposed for implementing the stampability evaluation. The stampability evaluation knowledge representation, and processing phases are illustrated. A case study demonstrates the feasibility of the knowledge based approach to stampability evaluation.
基金The National Natural Science Foundation of China(No.61502095).
文摘Aiming at the relation linking task for question answering over knowledge base,especially the multi relation linking task for complex questions,a relation linking approach based on the multi-attention recurrent neural network(RNN)model is proposed,which works for both simple and complex questions.First,the vector representations of questions are learned by the bidirectional long short-term memory(Bi-LSTM)model at the word and character levels,and named entities in questions are labeled by the conditional random field(CRF)model.Candidate entities are generated based on a dictionary,the disambiguation of candidate entities is realized based on predefined rules,and named entities mentioned in questions are linked to entities in knowledge base.Next,questions are classified into simple or complex questions by the machine learning method.Starting from the identified entities,for simple questions,one-hop relations are collected in the knowledge base as candidate relations;for complex questions,two-hop relations are collected as candidates.Finally,the multi-attention Bi-LSTM model is used to encode questions and candidate relations,compare their similarity,and return the candidate relation with the highest similarity as the result of relation linking.It is worth noting that the Bi-LSTM model with one attentions is adopted for simple questions,and the Bi-LSTM model with two attentions is adopted for complex questions.The experimental results show that,based on the effective entity linking method,the Bi-LSTM model with the attention mechanism improves the relation linking effectiveness of both simple and complex questions,which outperforms the existing relation linking methods based on graph algorithm or linguistics understanding.
基金This project is supported by National Hi-tech Research and Development Program of China(863 Program, No. 2001AA412020, No. 2001AA412210).
文摘In order to enhance the intelligent level of system and improve the interaetivity with other systems, a knowledge and XML based computer aided process planning （CAPP） system is implemented. It includes user management, bill of materials（BOM） management, knowledge based process planning, knowledge management and database maintaining sub-systems. This kind of nesting knowledge representation method the system provided can represent complicated arithmetic and logical relationship to deal with process planning tasks. With the representation and manipulation of XML based technological file, the system solves some important problems in web environment such as information interactive efficiency and refreshing of web page. The CAPP system is written in ASP VBScript, JavaScript, Visual C＋＋ languages and Oracle database. At present, the CAPP system is running in Shenyang Machine Tools. The functions of it meet the requirements of enterprise production.
基金Supported by National Natural Science Foundation of China(No.70271002)
文摘Based on the knowledge representation and knowledge reasoning, this paper addresses the creation of the multi-attribute knowledge base on the basis of hybrid knowledge representation, with the help of object-oriented programming language and relational database. Compared with general knowledge base, multi-attribute knowledge base can enhance the ability of knowledge processing and application; integrate the heterogeneous knowledge, such as model, symbol, case-based sample knowledge; and support the whole decision process by integrated reasoning.
文摘The present work deals with the development of an Ontology-Based Knowledge Network of soil/water physicochemical & biological properties (soil/water concepts), derived from ASTM Standard Methods (ASTMi,n) and relevant scientific/applicable references (published papers—PPi,n) to fill up/bridge the gap of the information science between cited Standards and infiltration discipline conceptual vocabulary providing accordingly a dedicated/internal Knowledge Base (KB). This attempt constitutes an innovative approach, since it is based on externalizing domain knowledge in the form of Ontology-Based Knowledge Networks, incorporating standardized methodology in soil engineering. The ontology soil/water concepts (semantics) of the developed network correspond to soil/water physicochemical & biological properties, classified in seven different generations that are distinguished/located in infiltration/percolation process of contaminated water through soil porous media. The interconnections with arcs between corresponding concepts/properties among the consecutive generations are defined by the relationship of dependent and independent variables. All these interconnections are documented according to the below three ways: 1) dependent and independent variables interconnected by using the logical operator “<em>depends on</em>” quoting existent explicit functions and equations;2) dependent and independent variables interconnected by using the logical operator “<em>depends on</em>” quoting produced implicit functions, according to Rayleigh’s method of indices;3) dependent and independent variables interconnected by using the logical operator “<em>related to</em>” based on a logical dependence among the examined nodes-concepts-variables. The aforementioned approach provides significant advantages to semantic web developers and web users by means of prompt knowledge navigation, tracking, retrieval and usage.
基金supported by the Outstanding Youth Team Project of Central Universities(QNTD202308)the Ant Group through CCF-Ant Research Fund(CCF-AFSG 769498 RF20220214).
文摘Named Entity Recognition(NER)stands as a fundamental task within the field of biomedical text mining,aiming to extract specific types of entities such as genes,proteins,and diseases from complex biomedical texts and categorize them into predefined entity types.This process can provide basic support for the automatic construction of knowledge bases.In contrast to general texts,biomedical texts frequently contain numerous nested entities and local dependencies among these entities,presenting significant challenges to prevailing NER models.To address these issues,we propose a novel Chinese nested biomedical NER model based on RoBERTa and Global Pointer(RoBGP).Our model initially utilizes the RoBERTa-wwm-ext-large pretrained language model to dynamically generate word-level initial vectors.It then incorporates a Bidirectional Long Short-Term Memory network for capturing bidirectional semantic information,effectively addressing the issue of long-distance dependencies.Furthermore,the Global Pointer model is employed to comprehensively recognize all nested entities in the text.We conduct extensive experiments on the Chinese medical dataset CMeEE and the results demonstrate the superior performance of RoBGP over several baseline models.This research confirms the effectiveness of RoBGP in Chinese biomedical NER,providing reliable technical support for biomedical information extraction and knowledge base construction.
文摘Most of KBE systems applied by previous researchers are dependent on some CAD software, which makes knowledge hard to be reused to other CAD software. Independent knowledge based system is independent of CAD software; therefore knowledge can be reused freely. This paper describes independent knowledge based system for mechanical design. A detailed discussion about typical design is put forward including design process implementation based on knowledge engineering, independent knowledge based design architecture. The main principal of knowledge driven engineering is explained. The implementation of KBE on the design of worm reducer is studied as a case. Independent knowledge based reducer design system is realized. The usage of independent knowledge based system makes KBE system work independent of CAD software, which enhances their portability and fertilizes the collaborative work of heterogeneous CAD systems.
基金Supported by China Hi-tech Program (863) (2007AA04Z125)
文摘With the deep research of knowledge engineering and the widespread applications of CAD technology, the joining of knowledge engineering with CAD is the focus of advanced manufacturing. An intelligent approach is presented for configurating the typical structural components of radar. Case based reasoning, rule based reasoning, geometric, constraint solving and domain ontology are merged into a compound knowledge model. The main frame and workflow of radar typical structural component design system are illustrated. Experiments show this approach is efficient and effective.
文摘Search engines have greatly helped us to find the desired information from the Internet. Most search engines use keywords matching technique. This paper discusses a Dynamic Knowledge Base based Search Engine （DKBSE）, which can expand the user＇s query using the keywords＇ concept or meaning. To do this, the DKBSE needs to construct and maintain the knowledge base dynamically via the system＇s searching results and the user＇s feedback information. The DKBSE expands the user＇s initial query using the knowledge base, and returns the searched information after the expanded query.
基金The research is funded by Researchers Supporting Program at King Saud University,(Project#RSP-2021/305).
文摘This paper presents a novel application of metaheuristic algorithmsfor solving stochastic programming problems using a recently developed gaining sharing knowledge based optimization (GSK) algorithm. The algorithmis based on human behavior in which people gain and share their knowledgewith others. Different types of stochastic fractional programming problemsare considered in this study. The augmented Lagrangian method (ALM)is used to handle these constrained optimization problems by convertingthem into unconstrained optimization problems. Three examples from theliterature are considered and transformed into their deterministic form usingthe chance-constrained technique. The transformed problems are solved usingGSK algorithm and the results are compared with eight other state-of-the-artmetaheuristic algorithms. The obtained results are also compared with theoptimal global solution and the results quoted in the literature. To investigatethe performance of the GSK algorithm on a real-world problem, a solidstochastic fixed charge transportation problem is examined, in which theparameters of the problem are considered as random variables. The obtainedresults show that the GSK algorithm outperforms other algorithms in termsof convergence, robustness, computational time, and quality of obtainedsolutions.
文摘A new structure of ESKD (expert system based on knowledge discovery system KD (D&K)) is first presented on the basis of KD (D&K)-a synthesized knowledge discovery system based on double-base (database and knowledge base) cooperating mechanism. With all new features, ESKD may form a new research direction and provide a great probability for solving the wealth of knowledge in the knowledge base. The general structural frame of ESKD and some sub-systems among ESKD have been described, and the dynamic knowledge base based on double-base cooperating mechanism has been emphased on. According to the result of demonstrative experi- ment, the structure of ESKD is effective and feasible.
文摘MedTrad＋ is an expert system for African Traditional Medicine where actors are often illiterate. Its originality lies in the use of icons instead of textual content of facts. It has been created by GExpert＋ which is An Expert system Generator based on the use of icons in a Web environment. With its iconic interface GExpert＋ allows any user to overcome any intermediary for the management and the use of its knowledge base. Traditional healers from Yamoussoukro region are working toward its validation.
基金This paper is supported by the Philosophy and Social Science Foundation ofGuangxi （No.05FJY034）.
文摘A knowledge based company is the microcosmic foundation of the knowledge economy, the design of its organization structure should amplify the company competence to be agile to the knowledge elements. This paper expounds an interior market network structure which is fit for the company intellectual capital operation, and analyses this organization pattern about the reasons of existence, the effectiveness of growing up in scale, the economies of knowledge distribution and the efficiency of operation, and it will provide some beneficial theoretical guidance about how can a company improve its competition competence in the knowledge environment through organization innovation.
