Under the paradigm of Industry 5.0,intelligent manufacturing transcends mere efficiency enhancement by emphasizing human-machine collaboration,where human expertise plays a central role in assembly processes.Despite a...Under the paradigm of Industry 5.0,intelligent manufacturing transcends mere efficiency enhancement by emphasizing human-machine collaboration,where human expertise plays a central role in assembly processes.Despite advancements in intelligent and digital technologies,assembly process design still heavily relies on manual knowledge reuse,and inefficiencies and inconsistent quality in process documentation are caused.To address the aforementioned issues,this paper proposes a knowledge push method of complex product assembly process design based on distillation model-based dynamically enhanced graph and Bayesian network.First,an initial knowledge graph is constructed using a BERT-BiLSTM-CRF model trained with integrated human expertise and a fine-tuned large language model.Then,a confidence-based dynamic weighted fusion strategy is employed to achieve dynamic incremental construction of the knowledge graph with low resource consumption.Subsequently,a Bayesian network model is constructed based on the relationships between assembly components,assembly features,and operations.Bayesian network reasoning is used to push assembly process knowledge under different design requirements.Finally,the feasibility of the Bayesian network construction method and the effectiveness of Bayesian network reasoning are verified through a specific example,significantly improving the utilization of assembly process knowledge and the efficiency of assembly process design.展开更多
Xi Jinping,general secretary of the Communist Party of China(CPC)Central Committee,stressed that we should adhere to the“two integrations”(namely,integrating the basic tenets of Marxism with China’s specific realit...Xi Jinping,general secretary of the Communist Party of China(CPC)Central Committee,stressed that we should adhere to the“two integrations”(namely,integrating the basic tenets of Marxism with China’s specific realities and fine traditional culture),root ourselves in Chinese soil,carry forward the Chinese cultural heritage,and strengthen the academic foundation.We should accelerate the building of an independent knowledge system for Chinese philosophy and social sciences,and formulate original concepts and develop systems of academic discipline,research and discourse,drawing on China’s rich experience of advancing human rights.In the face of changes of a magnitude not seen in a century,in the historic process of advancing the great rejuvenation of the Chinese nation on all fronts through Chinese modernization,we should and must strengthen our theoretical self-consciousness and confidence in the path of Chinese modernization.We need to enhance human rights research,develop the human rights theoretical system and paradigm that are based on Chinese realities and express Chinese voice,and an independent Chinese knowledge system for human rights.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
Recent advancements in large language models(LLMs)have driven remarkable progress in text process-ing,opening new avenues for medical knowledge discovery.In this study,we present ERQA,a mEdical knowledge Retrieval and...Recent advancements in large language models(LLMs)have driven remarkable progress in text process-ing,opening new avenues for medical knowledge discovery.In this study,we present ERQA,a mEdical knowledge Retrieval and Question-Answering framework powered by an enhanced LLM that integrates a semantic vector database and a curated literature repository.The ERQA framework leverages domain-specific incremental pretraining and conducts supervised fine-tuning on medical literature,enabling retrieval and question-answering(QA)tasks to be completed with high precision.Performance evaluations implemented on the coronavirus disease 2019(COVID-19)and TripClick data-sets demonstrate the robust capabilities of ERQA across multiple tasks.On the COVID-19 dataset,ERQA-13B achieves state-of-the-art retrieval metrics,with normalized discounted cumulative gain at top 10(NDCG@10)0.297,recall values at top 10(Recall@10)0.347,and mean reciprocal rank(MRR)=0.370;it also attains strong abstract summarization performance,with a recall-oriented understudy for gisting evaluation(ROUGE)-1 score of 0.434,and QA performance,with a bilingual evaluation understudy(BLEU)-1 score of 7.851.The comparable performance achieved on the TripClick dataset further under-scores the adaptability of ERQA across diverse medical topics.These findings suggest that ERQA repre-sents a significant step toward efficient biomedical knowledge retrieval and QA.展开更多
The global rise in animal protein consumption has significantly amplified the demand for fodder.A comprehensive understanding of the diversity and characteristics of existing fodder resources is essential for balanced...The global rise in animal protein consumption has significantly amplified the demand for fodder.A comprehensive understanding of the diversity and characteristics of existing fodder resources is essential for balanced nutritional fodder production.This study investigates the diversity and composition of fodder plants and identifies key species for cattle in Zhaotong City,Yunnan,China,while documenting indigenous knowledge on their usage and selection criteria.Ethnobotanical surveys were conducted in 19 villages across seven townships with 140 informants.Data were collected through semi-structured interviews,free listing,and participatory observation,and analyzed using Relative Frequency Citation.A total of 125 taxa(including 106 wild and 19 cultivated)were reported.The most cited family is Poaceae(27 taxa,21.43%),followed by Asteraceae(17 taxa,13.49%),Fabaceae(14 taxa,11.11%),Polygonaceae(9 taxa,7.14%)and Lamiaceae(4 taxa,3.17%).The whole plant(66.04%)and herbaceous plants(84.80%)were the most used parts and life forms.The most cited species were Zea mays,Brassica rapa,Solanum tuberosum,Eragrostis nigra,and Artemisia dubia.Usage of diverse fodder resources reflects local wisdom in managing resource availability and achieving balanced nutrition while coping with environmental and climatic risks.Preferences for certain taxonomic groups are due to their quality as premier fodder resources.To promote integrated crop-livestock farming,we suggest further research into highly preferred fodder species,focusing on nutritional assessment,digestibility,meat quality impacts,and potential as antibiotic alternatives.Establishing germplasm and gene banks for fodder resources is also recommended.展开更多
Water scarcity poses a significant challenge globally,with South Africa exemplifying the severe socio-economic and environmental impacts of limited water access.Despite advances in modern water management systems,the ...Water scarcity poses a significant challenge globally,with South Africa exemplifying the severe socio-economic and environmental impacts of limited water access.Despite advances in modern water management systems,the integration of indigenous knowledge(IK)into formal frameworks remains underutilized.This study systematically reviews the role of indigenous water conservation practices in South Africa,analyzing over 50 high-quality sources using the PRISMA methodology.The findings highlight the effectiveness of IK in addressing water scarcity through techniques such as rainwater harvesting,terracing,and wetland management,which are low-cost,environmentally sustainable,and deeply rooted in cultural practices.Indigenous methods also enhance climate resilience by enabling communities to adapt to droughts and floods through practices such as weather prediction and adaptive farming techniques.Furthermore,these practices foster social inclusivity and community empowerment,ensuring equitable water access and intergenerational knowledge transfer.The study underscores the potential of integrating IK with modern water technologies to create holistic solutions that are scalable,sustainable,and aligned with South Africa’s goal of achieving water security by 2030.Policy recommendations emphasize the need for institutional support,data collection,and financial incentives to sustain and mainstream indigenous approaches.By bridging the gap between traditional and contemporary systems,this research provides a roadmap for leveraging diverse knowledge systems to address water scarcity and build resilient communities.展开更多
Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representati...Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representation,modeling,fusion,computation,and storage.Within this framework,knowledge extraction,as the core component,directly determines KG quality.In military domains,traditional manual curation models face efficiency constraints due to data fragmentation,complex knowledge architectures,and confidentiality protocols.Meanwhile,crowdsourced ontology construction approaches from general domains prove non-transferable,while human-crafted ontologies struggle with generalization deficiencies.To address these challenges,this study proposes an OntologyAware LLM Methodology for Military Domain Knowledge Extraction(LLM-KE).This approach leverages the deep semantic comprehension capabilities of Large Language Models(LLMs)to simulate human experts’cognitive processes in crowdsourced ontology construction,enabling automated extraction of military textual knowledge.It concurrently enhances knowledge processing efficiency and improves KG completeness.Empirical analysis demonstrates that this method effectively resolves scalability and dynamic adaptation challenges in military KG construction,establishing a novel technological pathway for advancing military intelligence development.展开更多
Large-scale U.S.-sponsored protests and armed militants are targeting major cities across Iran,destroying property as well as killing security personnel and civilians alike.The Western media has deliberately mischarac...Large-scale U.S.-sponsored protests and armed militants are targeting major cities across Iran,destroying property as well as killing security personnel and civilians alike.The Western media has deliberately mischaracterized the violence as a one-sided government crackdown,omitting any mention of armed opposition in the streets and merely conceding that.展开更多
The reliable operation of power grid secondary equipment is an important guarantee for the safety and stability of the power system.However,various defects could be produced in the secondary equipment during longtermo...The reliable operation of power grid secondary equipment is an important guarantee for the safety and stability of the power system.However,various defects could be produced in the secondary equipment during longtermoperation.The complex relationship between the defect phenomenon andmulti-layer causes and the probabilistic influence of secondary equipment cannot be described through knowledge extraction and fusion technology by existing methods,which limits the real-time and accuracy of defect identification.Therefore,a defect recognition method based on the Bayesian network and knowledge graph fusion is proposed.The defect data of secondary equipment is transformed into the structured knowledge graph through knowledge extraction and fusion technology.The knowledge graph of power grid secondary equipment is mapped to the Bayesian network framework,combined with historical defect data,and introduced Noisy-OR nodes.The prior and conditional probabilities of the Bayesian network are then reasonably assigned to build a model that reflects the probability dependence between defect phenomena and potential causes in power grid secondary equipment.Defect identification of power grid secondary equipment is achieved by defect subgraph search based on the knowledge graph,and defect inference based on the Bayesian network.Practical application cases prove this method’s effectiveness in identifying secondary equipment defect causes,improving identification accuracy and efficiency.展开更多
With the widespread use of social media,the propagation of health-related rumors has become a significant public health threat.Existing methods for detecting health rumors predominantly rely on external knowledge or p...With the widespread use of social media,the propagation of health-related rumors has become a significant public health threat.Existing methods for detecting health rumors predominantly rely on external knowledge or propagation structures,with only a few recent approaches attempting causal inference;however,these have not yet effectively integrated causal discovery with domain-specific knowledge graphs for detecting health rumors.In this study,we found that the combined use of causal discovery and domain-specific knowledge graphs can effectively identify implicit pseudo-causal logic embedded within texts,holding significant potential for health rumor detection.To this end,we propose CKDG—a dual-graph fusion framework based on causal logic and medical knowledge graphs.CKDG constructs a weighted causal graph to capture the implicit causal relationships in the text and introduces a medical knowledge graph to verify semantic consistency,thereby enhancing the ability to identify the misuse of professional terminology and pseudoscientific claims.In experiments conducted on a dataset comprising 8430 health rumors,CKDG achieved an accuracy of 91.28%and an F1 score of 90.38%,representing improvements of 5.11%and 3.29%over the best baseline,respectively.Our results indicate that the integrated use of causal discovery and domainspecific knowledge graphs offers significant advantages for health rumor detection systems.This method not only improves detection performance but also enhances the transparency and credibility of model decisions by tracing causal chains and sources of knowledge conflicts.We anticipate that this work will provide key technological support for the development of trustworthy health-information filtering systems,thereby improving the reliability of public health information on social media.展开更多
In 2024,China’s human rights research has assumed a distinct“autonomy-oriented shift,”with scholars beginning to refine and construct uniquely Chinese and locally identifiable human rights concepts,categories,and d...In 2024,China’s human rights research has assumed a distinct“autonomy-oriented shift,”with scholars beginning to refine and construct uniquely Chinese and locally identifiable human rights concepts,categories,and discourses.Building an independent human rights knowledge system has become a core academic focus in China’s human rights research field.Upholding fundamental principles and breaking new ground are the key methodological principles for the process.China’s human rights research should be rooted in the“cultural lineage”by preserving the essence of fine traditional Chinese culture,guided by the“moral lineage”by adhering to the Marxist view on human rights,and anchored in the“Four-sphere Confidence”by upholding a distinct human rights development path,so as to define the historical coordinates and value stance of China’s independent human rights knowledge system.Meanwhile,it should maintain a high degree of openness in knowledge,theory,and methodology to address emerging rights demands and contribute to building a new global human rights governance order,so as to underscore the mission of China’s independent human rights knowledge system in the contemporary era and China’s responsibility as a major global actor.China’s human rights research should uphold the dialectical unity between the fundamental principles and innovations,and advance the systemic and theoretical interpretation of its independent human rights knowledge.展开更多
With the aim to address the problems presented in knowledge utilization in knowledge-intensive enterprises, the ontology-based proactive knowledge system （OPKS） is put forward to improve knowledge utilization. Proac...With the aim to address the problems presented in knowledge utilization in knowledge-intensive enterprises, the ontology-based proactive knowledge system （OPKS） is put forward to improve knowledge utilization. Proactive knowledge service is taken as the basic idea in the OPKS. The user knowledge requirement is taken as the driving factor and described by the user knowledge requirement. Ontologies are used to present the semantic of heterogeneous knowledge sources and ontology mapping is used to realize the interoperation of heterogeneous knowledge sources. The required knowledge is found by matching the user knowledge requirement with knowledge sources and is provided to the user proactively. System analysis and design of OPKS is carded on by adopting UML. The OPKS is implemented in Java language. Application in a certain institute shows that the OPKS can raise efficiency of knowledge utilization in knowledge-intensive enterprises.展开更多
To deal with a lack of semantic interoperability of traditional knowledge retrieval approaches, a semantic-based networked manufacturing （NM） knowledge retrieval architecture is proposed, which offers a series of to...To deal with a lack of semantic interoperability of traditional knowledge retrieval approaches, a semantic-based networked manufacturing （NM） knowledge retrieval architecture is proposed, which offers a series of tools for supporting the sharing of knowledge and promoting NM collaboration. A 5-tuple based semantic information retrieval model is proposed, which includes the interoperation on the semantic layer, and a test process is given for this model. The recall ratio and the precision ratio of manufacturing knowledge retrieval are proved to be greatly improved by evaluation. Thus, a practical and reliable approach based on the semantic web is provided for solving the correlated concrete problems in regional networked manufacturing.展开更多
Aim To analyse the influence of knowledge base on the performance of the fuzzy controller of the electrohydraulic position control system,and to determine their selection cri- teria. Methods Experiments based on diffe...Aim To analyse the influence of knowledge base on the performance of the fuzzy controller of the electrohydraulic position control system,and to determine their selection cri- teria. Methods Experiments based on different membership functions,scaling factors and con-trol rules were done separately.The experiment results and the influence of different know- ledge base on the control performance were analysed in theory so that criteria of selcting knowledge base can be summarized correctly.Results Knowledge base,including membershipfunctions, scaling factors and control rules,has a crucial effect on the fuzzy control system.Suitably selected knowledge base can lead to good control performance of fuzzy control sys-tem. Conclusion Being symmetric,having an intersection ratio of 1 and satisfying width con- dition are three necessities for selecting membership functions.Selecting scaling factors dependson both the system requirement and a comprehensive analysis in the overshoot,oscillation, rising time and stability. Integrity and continuity must be guaranteed when determining control rules.展开更多
Ontology is the formal representation of concepts and their mutual relations. It has wide application potential in the classification of agricultural information, the construction of information and knowledge database...Ontology is the formal representation of concepts and their mutual relations. It has wide application potential in the classification of agricultural information, the construction of information and knowledge database, the research and development of intelligent search engine, as well as the realization of cooperative information service, etc. In this research, an ontology-based agricultural knowledge management system framework is proposed, which includes modules of ontology-based knowledge acquisition, knowledge representation, knowledge organization, and knowledge mining, etc. The key technologies, building tools and applications of the framework are explored. Future researches on the theoretical refinement and intelligent simulation knowledge service are also envisioned.展开更多
Entering 21st century, knowledge has already become the most important strategic resource for enterprises. The key factors of keeping continuous competitive advantages for an enterprise are the abilities of knowledge ...Entering 21st century, knowledge has already become the most important strategic resource for enterprises. The key factors of keeping continuous competitive advantages for an enterprise are the abilities of knowledge management and knowledge innovations. Enterprise knowledge management is a new subject with great theoretical meaning and actual meaning. From a new angle, guided by systematic viewpoint, this paper analyses deeply and explores synthetically enterprise knowledge management as a complicated system problem by doing the following:Defining the implication of enterprise knowledge management;Analyzing three kinds of the key elements in enterprise knowledge management and the interaction relations among the elements;Proposing and probing into the structure of enterprise knowledge management. Considers the structure as the open dynamic network structure with multidimensional space. Through drawing the state chart of key elements, analyzes the functions of enterprise knowledge management; Proposing and studying the interaction mechanisms between three kinds of the key elements and enterprise knowledge management. On the basis of all above analyses, aiming at the conditions and problems of enterprise knowledge management in our country, this paper probes into the main countermeasures of knowledge management that should be adopted by the enterprises of our country.展开更多
After analyzing the welding procedure knowledge in Chinese national standards for welding procedure qualification of steel pressure vessel from the point of establishing expert system, it can be divided into five type...After analyzing the welding procedure knowledge in Chinese national standards for welding procedure qualification of steel pressure vessel from the point of establishing expert system, it can be divided into five types of knowledge, i. e. practice, definition, regularity, process and description knowledge. The knowledge expression methods are established according to the different type of welding procedure knowledge. The reasoning process based on rule is adopted. And the reasoning engine is embedded among objects integrated with the knowledge base.展开更多
By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and ...By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and management indices to variety types, ecological environments and production levels were analysed and extracted, and a dynamic knowledge model with temporal and spatial characters for wheat management(WheatKnow)was developed. By adopting the soft component characteristics as non language relevance , re-utilization and portable system maintenance. and by further integrating the wheat growth simulation model(WheatGrow)and intelligent system for wheat management, a comprehensive and digital knowledge model, growth model and component-based decision support system for wheat management(MBDSSWM)was established on the platforms of Visual C++ and Visual Basic. The MBDSSWM realized the effective integration and coupling of the prediction and decision-making functions for digital crop management.展开更多
A knowledge model with temporal and spatial characteristics for the quantitative design of a cultural pattern in wheat production, using systems analysis and dynamic modeling techniques, was developed for wheat manage...A knowledge model with temporal and spatial characteristics for the quantitative design of a cultural pattern in wheat production, using systems analysis and dynamic modeling techniques, was developed for wheat management, as a decision-making tool in digital farming. The fundamental relationships and algorithms of wheat growth indices and management criteria to cultivars, ecological environments, and production levels were derived from the existing literature and research data to establish a knowledge model system for quantitative wheat management using Visual C^＋＋. The system designed a cultural management plan for general management guidelines and crop regulation indices for timecourse control criteria during the wheat-growing period. The cultural management plan module included submodels to determine target grain yield and quality, cultivar choice, sowing date, population density, sowing rate, fertilization strategy, and water management, whereas the crop regulation indices module included submodels for suitable development stages, dynamic growth indices, source-sink indices, and nutrient indices. Ewluation of the knowledge model by design studies on the basis of data sets of different eco-sites, cultiwrs, and soil types indicated a favorable performance of the model system in recommending growth indices and management criteria under diverse conditions. Practical application of the knowledge model system in comparative field experiments produced yield gains of 2.4% to 16.5%. Thus, the presented knowledge model system overcame some of the difficulties of the traditional wheat management patterns and expert systems, and laid a foundation for facilitating the digitization of wheat management.展开更多
This study proposes the establishment of a knowledge-system ontology in the nursing field. It uses advanced data mining techniques,digital publishing technologies, and new media concepts to comprehensively integrate a...This study proposes the establishment of a knowledge-system ontology in the nursing field. It uses advanced data mining techniques,digital publishing technologies, and new media concepts to comprehensively integrate and deepen nursing knowledge and to aggregate sources of knowledge in specialized technical fields. This study applies all forms of media and transmission channels, such as personal computers and mobile devices, to establish a knowledge-transmission system that provides knowledge services such as knowledge search, update retrieval, evaluation, questions and answers(Q&As), online viewing, information subscription, expert services, push notifications, review forums, and online learning. In doing so, this study creates an authoritative and foundational knowledge service engine for the nursing field, which provides convenient, flexible, and comprehensive knowledge services to members of the nursing industry in a digital format.展开更多
基金Supported by National Key Research and Development Program(Grant No.2024YFB3312700)National Natural Science Foundation of China(Grant No.52405541)the Changzhou Municipal Sci&Tech Program(Grant No.CJ20241131)。
文摘Under the paradigm of Industry 5.0,intelligent manufacturing transcends mere efficiency enhancement by emphasizing human-machine collaboration,where human expertise plays a central role in assembly processes.Despite advancements in intelligent and digital technologies,assembly process design still heavily relies on manual knowledge reuse,and inefficiencies and inconsistent quality in process documentation are caused.To address the aforementioned issues,this paper proposes a knowledge push method of complex product assembly process design based on distillation model-based dynamically enhanced graph and Bayesian network.First,an initial knowledge graph is constructed using a BERT-BiLSTM-CRF model trained with integrated human expertise and a fine-tuned large language model.Then,a confidence-based dynamic weighted fusion strategy is employed to achieve dynamic incremental construction of the knowledge graph with low resource consumption.Subsequently,a Bayesian network model is constructed based on the relationships between assembly components,assembly features,and operations.Bayesian network reasoning is used to push assembly process knowledge under different design requirements.Finally,the feasibility of the Bayesian network construction method and the effectiveness of Bayesian network reasoning are verified through a specific example,significantly improving the utilization of assembly process knowledge and the efficiency of assembly process design.
文摘Xi Jinping,general secretary of the Communist Party of China(CPC)Central Committee,stressed that we should adhere to the“two integrations”(namely,integrating the basic tenets of Marxism with China’s specific realities and fine traditional culture),root ourselves in Chinese soil,carry forward the Chinese cultural heritage,and strengthen the academic foundation.We should accelerate the building of an independent knowledge system for Chinese philosophy and social sciences,and formulate original concepts and develop systems of academic discipline,research and discourse,drawing on China’s rich experience of advancing human rights.In the face of changes of a magnitude not seen in a century,in the historic process of advancing the great rejuvenation of the Chinese nation on all fronts through Chinese modernization,we should and must strengthen our theoretical self-consciousness and confidence in the path of Chinese modernization.We need to enhance human rights research,develop the human rights theoretical system and paradigm that are based on Chinese realities and express Chinese voice,and an independent Chinese knowledge system for human rights.
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supported by the Innovation Fund for Medical Sciences of the Chinese Academy of Medical Sciences(2021-I2M-1-033)the National Key Research and Development Program of China(2022YFF0711900).
文摘Recent advancements in large language models(LLMs)have driven remarkable progress in text process-ing,opening new avenues for medical knowledge discovery.In this study,we present ERQA,a mEdical knowledge Retrieval and Question-Answering framework powered by an enhanced LLM that integrates a semantic vector database and a curated literature repository.The ERQA framework leverages domain-specific incremental pretraining and conducts supervised fine-tuning on medical literature,enabling retrieval and question-answering(QA)tasks to be completed with high precision.Performance evaluations implemented on the coronavirus disease 2019(COVID-19)and TripClick data-sets demonstrate the robust capabilities of ERQA across multiple tasks.On the COVID-19 dataset,ERQA-13B achieves state-of-the-art retrieval metrics,with normalized discounted cumulative gain at top 10(NDCG@10)0.297,recall values at top 10(Recall@10)0.347,and mean reciprocal rank(MRR)=0.370;it also attains strong abstract summarization performance,with a recall-oriented understudy for gisting evaluation(ROUGE)-1 score of 0.434,and QA performance,with a bilingual evaluation understudy(BLEU)-1 score of 7.851.The comparable performance achieved on the TripClick dataset further under-scores the adaptability of ERQA across diverse medical topics.These findings suggest that ERQA repre-sents a significant step toward efficient biomedical knowledge retrieval and QA.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDA26050301-02)。
文摘The global rise in animal protein consumption has significantly amplified the demand for fodder.A comprehensive understanding of the diversity and characteristics of existing fodder resources is essential for balanced nutritional fodder production.This study investigates the diversity and composition of fodder plants and identifies key species for cattle in Zhaotong City,Yunnan,China,while documenting indigenous knowledge on their usage and selection criteria.Ethnobotanical surveys were conducted in 19 villages across seven townships with 140 informants.Data were collected through semi-structured interviews,free listing,and participatory observation,and analyzed using Relative Frequency Citation.A total of 125 taxa(including 106 wild and 19 cultivated)were reported.The most cited family is Poaceae(27 taxa,21.43%),followed by Asteraceae(17 taxa,13.49%),Fabaceae(14 taxa,11.11%),Polygonaceae(9 taxa,7.14%)and Lamiaceae(4 taxa,3.17%).The whole plant(66.04%)and herbaceous plants(84.80%)were the most used parts and life forms.The most cited species were Zea mays,Brassica rapa,Solanum tuberosum,Eragrostis nigra,and Artemisia dubia.Usage of diverse fodder resources reflects local wisdom in managing resource availability and achieving balanced nutrition while coping with environmental and climatic risks.Preferences for certain taxonomic groups are due to their quality as premier fodder resources.To promote integrated crop-livestock farming,we suggest further research into highly preferred fodder species,focusing on nutritional assessment,digestibility,meat quality impacts,and potential as antibiotic alternatives.Establishing germplasm and gene banks for fodder resources is also recommended.
文摘Water scarcity poses a significant challenge globally,with South Africa exemplifying the severe socio-economic and environmental impacts of limited water access.Despite advances in modern water management systems,the integration of indigenous knowledge(IK)into formal frameworks remains underutilized.This study systematically reviews the role of indigenous water conservation practices in South Africa,analyzing over 50 high-quality sources using the PRISMA methodology.The findings highlight the effectiveness of IK in addressing water scarcity through techniques such as rainwater harvesting,terracing,and wetland management,which are low-cost,environmentally sustainable,and deeply rooted in cultural practices.Indigenous methods also enhance climate resilience by enabling communities to adapt to droughts and floods through practices such as weather prediction and adaptive farming techniques.Furthermore,these practices foster social inclusivity and community empowerment,ensuring equitable water access and intergenerational knowledge transfer.The study underscores the potential of integrating IK with modern water technologies to create holistic solutions that are scalable,sustainable,and aligned with South Africa’s goal of achieving water security by 2030.Policy recommendations emphasize the need for institutional support,data collection,and financial incentives to sustain and mainstream indigenous approaches.By bridging the gap between traditional and contemporary systems,this research provides a roadmap for leveraging diverse knowledge systems to address water scarcity and build resilient communities.
文摘Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representation,modeling,fusion,computation,and storage.Within this framework,knowledge extraction,as the core component,directly determines KG quality.In military domains,traditional manual curation models face efficiency constraints due to data fragmentation,complex knowledge architectures,and confidentiality protocols.Meanwhile,crowdsourced ontology construction approaches from general domains prove non-transferable,while human-crafted ontologies struggle with generalization deficiencies.To address these challenges,this study proposes an OntologyAware LLM Methodology for Military Domain Knowledge Extraction(LLM-KE).This approach leverages the deep semantic comprehension capabilities of Large Language Models(LLMs)to simulate human experts’cognitive processes in crowdsourced ontology construction,enabling automated extraction of military textual knowledge.It concurrently enhances knowledge processing efficiency and improves KG completeness.Empirical analysis demonstrates that this method effectively resolves scalability and dynamic adaptation challenges in military KG construction,establishing a novel technological pathway for advancing military intelligence development.
文摘Large-scale U.S.-sponsored protests and armed militants are targeting major cities across Iran,destroying property as well as killing security personnel and civilians alike.The Western media has deliberately mischaracterized the violence as a one-sided government crackdown,omitting any mention of armed opposition in the streets and merely conceding that.
基金supported by the State Grid Southwest Branch Project“Research on Defect Diagnosis and Early Warning Technology of Relay Protection and Safety Automation Devices Based on Multi-Source Heterogeneous Defect Data”.
文摘The reliable operation of power grid secondary equipment is an important guarantee for the safety and stability of the power system.However,various defects could be produced in the secondary equipment during longtermoperation.The complex relationship between the defect phenomenon andmulti-layer causes and the probabilistic influence of secondary equipment cannot be described through knowledge extraction and fusion technology by existing methods,which limits the real-time and accuracy of defect identification.Therefore,a defect recognition method based on the Bayesian network and knowledge graph fusion is proposed.The defect data of secondary equipment is transformed into the structured knowledge graph through knowledge extraction and fusion technology.The knowledge graph of power grid secondary equipment is mapped to the Bayesian network framework,combined with historical defect data,and introduced Noisy-OR nodes.The prior and conditional probabilities of the Bayesian network are then reasonably assigned to build a model that reflects the probability dependence between defect phenomena and potential causes in power grid secondary equipment.Defect identification of power grid secondary equipment is achieved by defect subgraph search based on the knowledge graph,and defect inference based on the Bayesian network.Practical application cases prove this method’s effectiveness in identifying secondary equipment defect causes,improving identification accuracy and efficiency.
基金funded by the Hunan Provincial Natural Science Foundation of China(Grant No.2025JJ70105)the Hunan Provincial College Students’Innovation and Entrepreneurship Training Program(Project No.S202411342056)The article processing charge(APC)was funded by the Project No.2025JJ70105.
文摘With the widespread use of social media,the propagation of health-related rumors has become a significant public health threat.Existing methods for detecting health rumors predominantly rely on external knowledge or propagation structures,with only a few recent approaches attempting causal inference;however,these have not yet effectively integrated causal discovery with domain-specific knowledge graphs for detecting health rumors.In this study,we found that the combined use of causal discovery and domain-specific knowledge graphs can effectively identify implicit pseudo-causal logic embedded within texts,holding significant potential for health rumor detection.To this end,we propose CKDG—a dual-graph fusion framework based on causal logic and medical knowledge graphs.CKDG constructs a weighted causal graph to capture the implicit causal relationships in the text and introduces a medical knowledge graph to verify semantic consistency,thereby enhancing the ability to identify the misuse of professional terminology and pseudoscientific claims.In experiments conducted on a dataset comprising 8430 health rumors,CKDG achieved an accuracy of 91.28%and an F1 score of 90.38%,representing improvements of 5.11%and 3.29%over the best baseline,respectively.Our results indicate that the integrated use of causal discovery and domainspecific knowledge graphs offers significant advantages for health rumor detection systems.This method not only improves detection performance but also enhances the transparency and credibility of model decisions by tracing causal chains and sources of knowledge conflicts.We anticipate that this work will provide key technological support for the development of trustworthy health-information filtering systems,thereby improving the reliability of public health information on social media.
基金a phased result funded by the Special Funds for Basic Scientific Research Expenses of Universities under the Central Government(24CXTD01).
文摘In 2024,China’s human rights research has assumed a distinct“autonomy-oriented shift,”with scholars beginning to refine and construct uniquely Chinese and locally identifiable human rights concepts,categories,and discourses.Building an independent human rights knowledge system has become a core academic focus in China’s human rights research field.Upholding fundamental principles and breaking new ground are the key methodological principles for the process.China’s human rights research should be rooted in the“cultural lineage”by preserving the essence of fine traditional Chinese culture,guided by the“moral lineage”by adhering to the Marxist view on human rights,and anchored in the“Four-sphere Confidence”by upholding a distinct human rights development path,so as to define the historical coordinates and value stance of China’s independent human rights knowledge system.Meanwhile,it should maintain a high degree of openness in knowledge,theory,and methodology to address emerging rights demands and contribute to building a new global human rights governance order,so as to underscore the mission of China’s independent human rights knowledge system in the contemporary era and China’s responsibility as a major global actor.China’s human rights research should uphold the dialectical unity between the fundamental principles and innovations,and advance the systemic and theoretical interpretation of its independent human rights knowledge.
基金The National Natural Science Foundation of China(No50674086)Specialized Research Fund for the Doctoral Program of Higher Education (No20060290508)
文摘With the aim to address the problems presented in knowledge utilization in knowledge-intensive enterprises, the ontology-based proactive knowledge system （OPKS） is put forward to improve knowledge utilization. Proactive knowledge service is taken as the basic idea in the OPKS. The user knowledge requirement is taken as the driving factor and described by the user knowledge requirement. Ontologies are used to present the semantic of heterogeneous knowledge sources and ontology mapping is used to realize the interoperation of heterogeneous knowledge sources. The required knowledge is found by matching the user knowledge requirement with knowledge sources and is provided to the user proactively. System analysis and design of OPKS is carded on by adopting UML. The OPKS is implemented in Java language. Application in a certain institute shows that the OPKS can raise efficiency of knowledge utilization in knowledge-intensive enterprises.
基金The National High Technology Research and Devel-opment Program of China (863Program) (No2003AA1Z2560,2002AA414060)the Key Science and Technology Program of Shaanxi Province (No2006K04-G10)
文摘To deal with a lack of semantic interoperability of traditional knowledge retrieval approaches, a semantic-based networked manufacturing （NM） knowledge retrieval architecture is proposed, which offers a series of tools for supporting the sharing of knowledge and promoting NM collaboration. A 5-tuple based semantic information retrieval model is proposed, which includes the interoperation on the semantic layer, and a test process is given for this model. The recall ratio and the precision ratio of manufacturing knowledge retrieval are proved to be greatly improved by evaluation. Thus, a practical and reliable approach based on the semantic web is provided for solving the correlated concrete problems in regional networked manufacturing.
文摘Aim To analyse the influence of knowledge base on the performance of the fuzzy controller of the electrohydraulic position control system,and to determine their selection cri- teria. Methods Experiments based on different membership functions,scaling factors and con-trol rules were done separately.The experiment results and the influence of different know- ledge base on the control performance were analysed in theory so that criteria of selcting knowledge base can be summarized correctly.Results Knowledge base,including membershipfunctions, scaling factors and control rules,has a crucial effect on the fuzzy control system.Suitably selected knowledge base can lead to good control performance of fuzzy control sys-tem. Conclusion Being symmetric,having an intersection ratio of 1 and satisfying width con- dition are three necessities for selecting membership functions.Selecting scaling factors dependson both the system requirement and a comprehensive analysis in the overshoot,oscillation, rising time and stability. Integrity and continuity must be guaranteed when determining control rules.
基金supported by the National Natural Science Foundation of China (2006AA10Z239)the National Key Technology Research and Development Program of China (2006BAD10A0501)
文摘Ontology is the formal representation of concepts and their mutual relations. It has wide application potential in the classification of agricultural information, the construction of information and knowledge database, the research and development of intelligent search engine, as well as the realization of cooperative information service, etc. In this research, an ontology-based agricultural knowledge management system framework is proposed, which includes modules of ontology-based knowledge acquisition, knowledge representation, knowledge organization, and knowledge mining, etc. The key technologies, building tools and applications of the framework are explored. Future researches on the theoretical refinement and intelligent simulation knowledge service are also envisioned.
文摘Entering 21st century, knowledge has already become the most important strategic resource for enterprises. The key factors of keeping continuous competitive advantages for an enterprise are the abilities of knowledge management and knowledge innovations. Enterprise knowledge management is a new subject with great theoretical meaning and actual meaning. From a new angle, guided by systematic viewpoint, this paper analyses deeply and explores synthetically enterprise knowledge management as a complicated system problem by doing the following:Defining the implication of enterprise knowledge management;Analyzing three kinds of the key elements in enterprise knowledge management and the interaction relations among the elements;Proposing and probing into the structure of enterprise knowledge management. Considers the structure as the open dynamic network structure with multidimensional space. Through drawing the state chart of key elements, analyzes the functions of enterprise knowledge management; Proposing and studying the interaction mechanisms between three kinds of the key elements and enterprise knowledge management. On the basis of all above analyses, aiming at the conditions and problems of enterprise knowledge management in our country, this paper probes into the main countermeasures of knowledge management that should be adopted by the enterprises of our country.
文摘After analyzing the welding procedure knowledge in Chinese national standards for welding procedure qualification of steel pressure vessel from the point of establishing expert system, it can be divided into five types of knowledge, i. e. practice, definition, regularity, process and description knowledge. The knowledge expression methods are established according to the different type of welding procedure knowledge. The reasoning process based on rule is adopted. And the reasoning engine is embedded among objects integrated with the knowledge base.
基金supported by the National Natural Science Foundation of China(30030090)the National 863 Program,China(2001AA115420,2001AA245041).
文摘By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and management indices to variety types, ecological environments and production levels were analysed and extracted, and a dynamic knowledge model with temporal and spatial characters for wheat management(WheatKnow)was developed. By adopting the soft component characteristics as non language relevance , re-utilization and portable system maintenance. and by further integrating the wheat growth simulation model(WheatGrow)and intelligent system for wheat management, a comprehensive and digital knowledge model, growth model and component-based decision support system for wheat management(MBDSSWM)was established on the platforms of Visual C++ and Visual Basic. The MBDSSWM realized the effective integration and coupling of the prediction and decision-making functions for digital crop management.
基金Project supported by the National High-Technology Research and Development Program of China (863 Program) (No. 2003AA209030)the National Natural Science Foundation of China (No. 30030090)and the Hi-Tech Research and Development Program of Jiangsu Province (No. BG2004320).
文摘A knowledge model with temporal and spatial characteristics for the quantitative design of a cultural pattern in wheat production, using systems analysis and dynamic modeling techniques, was developed for wheat management, as a decision-making tool in digital farming. The fundamental relationships and algorithms of wheat growth indices and management criteria to cultivars, ecological environments, and production levels were derived from the existing literature and research data to establish a knowledge model system for quantitative wheat management using Visual C^＋＋. The system designed a cultural management plan for general management guidelines and crop regulation indices for timecourse control criteria during the wheat-growing period. The cultural management plan module included submodels to determine target grain yield and quality, cultivar choice, sowing date, population density, sowing rate, fertilization strategy, and water management, whereas the crop regulation indices module included submodels for suitable development stages, dynamic growth indices, source-sink indices, and nutrient indices. Ewluation of the knowledge model by design studies on the basis of data sets of different eco-sites, cultiwrs, and soil types indicated a favorable performance of the model system in recommending growth indices and management criteria under diverse conditions. Practical application of the knowledge model system in comparative field experiments produced yield gains of 2.4% to 16.5%. Thus, the presented knowledge model system overcame some of the difficulties of the traditional wheat management patterns and expert systems, and laid a foundation for facilitating the digitization of wheat management.
基金supported by National Natural Science Foundation of China(No.71573162)Shanxi Province Soft Science Research Program(No.2018041029-3)
文摘This study proposes the establishment of a knowledge-system ontology in the nursing field. It uses advanced data mining techniques,digital publishing technologies, and new media concepts to comprehensively integrate and deepen nursing knowledge and to aggregate sources of knowledge in specialized technical fields. This study applies all forms of media and transmission channels, such as personal computers and mobile devices, to establish a knowledge-transmission system that provides knowledge services such as knowledge search, update retrieval, evaluation, questions and answers(Q&As), online viewing, information subscription, expert services, push notifications, review forums, and online learning. In doing so, this study creates an authoritative and foundational knowledge service engine for the nursing field, which provides convenient, flexible, and comprehensive knowledge services to members of the nursing industry in a digital format.
