In order to solve the problem of modeling product configuration knowledge at the semantic level to successfully implement the mass customization strategy, an approach of ontology-based configuration knowledge modeling...In order to solve the problem of modeling product configuration knowledge at the semantic level to successfully implement the mass customization strategy, an approach of ontology-based configuration knowledge modeling, combining semantic web technologies, was proposed. A general configuration ontology was developed to provide a common concept structure for modeling configuration knowledge and rules of specific product domains. The OWL web ontology language and semantic web rule language （SWRL） were used to formally represent the configuration ontology, domain configuration knowledge and rules to enhance the consistency, maintainability and reusability of all the configuration knowledge. The configuration knowledge modeling of a customizable personal computer family shows that the approach can provide explicit, computerunderstandable knowledge semantics for specific product configuration domains and can efficiently support automatic configuration tasks of complex products.展开更多
Knowledge-based modeling is a trend in complex system modeling technology. To extract the process knowledge from an information system, an approach of knowledge modeling based on interval-valued fuzzy rough set is pre...Knowledge-based modeling is a trend in complex system modeling technology. To extract the process knowledge from an information system, an approach of knowledge modeling based on interval-valued fuzzy rough set is presented in this paper, in which attribute reduction is a key to obtain the simplified knowledge model. Through defining dependency and inclusion functions, algorithms for attribute reduction and rule extraction are obtained. The approximation inference plays an important role in the development of the fuzzy system. To improve the inference mechanism, we provide a method of similaritybased inference in an interval-valued fuzzy environment. Combining the conventional compositional rule of inference with similarity based approximate reasoning, an inference result is deduced via rule translation, similarity matching, relation modification, and projection operation. This approach is applied to the problem of predicting welding distortion in marine structures, and the experimental results validate the effectiveness of the proposed methods of knowledge modeling and similarity-based inference.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
Background:The advent of the self-media age,digital humanities,and artificial intelligence(AI)technologies is gradually reshaping the narrative frameworks of the history of science and technology in general and the hi...Background:The advent of the self-media age,digital humanities,and artificial intelligence(AI)technologies is gradually reshaping the narrative frameworks of the history of science and technology in general and the history of medicine in particular,as it transforms the specific shape of contemporary medical science and health communication practice with the help of interactive,scenario-based communication ecosystems.Methods:This paper focuses on the interactive relationship between the history of science and science communication,employing historical tracing and case study comparison as research methods to explore the pathways and innovative models for reintegrating the history of science and technology including the history of medicine into contemporary scientific discourse.Results:The study finds that in the Chinese context,three key pathways facilitate the engagement of the history of science and technology including the history of medicine in science communication:administrative intervention,value reconstruction,and personalized adaptation.Specifically,administrative intervention promotes the integration of the history of science education into talent development through policy design;value reconstruction,centered on the scientific spirit,enhances societal cultural recognition of technological progress;and personalized adaptation leverages big data and social media technologies to enable precise and tailored knowledge dissemination.Conclusion:The rise of the“web-based knowledge brokering model”in the era of social media has introduced professional knowledge brokers,ensuring the accuracy and accessibility of science communication.These innovations not only serve as decision-making simulation tools for medical science and health communication,linking historical insights with contemporary practice,but also provide theoretical foundations and practical paradigms for realizing the value of the history of science and technology in the digital era.展开更多
Objective:To investigate the effect of an information-knowledge-attitude-practice(IKAP)nursing intervention on the caregiving capacity of family caregivers of elderly dementia patients.Methods:Sixty-nine family caregi...Objective:To investigate the effect of an information-knowledge-attitude-practice(IKAP)nursing intervention on the caregiving capacity of family caregivers of elderly dementia patients.Methods:Sixty-nine family caregivers of elderly dementia patients attending the neurology outpatient clinic of a hospital between October 2024 and March 2025 were selected.They were randomly divided into a control group(n=35)and an observation group(n=34).The control group received routine health education,while the observation group additionally underwent a systematic Information-Knowledge-Attitude-Practice(IKAP)nursing intervention.Care competence and self-efficacy scores were compared between groups before intervention and after 12 weeks.Results:Pre-intervention,no statistically significant difference existed in care competence or self-efficacy scores between groups(p>0.05).Following the 12-week intervention,all scores significantly increased in both groups,with the observation group demonstrating superior outcomes compared to the control group(p<0.001).Conclusion:The care intervention program based on the IKAP model effectively enhances caregivers’care competence and self-efficacy,thereby positively promoting the quality of life for patients with dementia.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
By analyzing and extracting the research progress on nitrogen fertilization in wheat, a dynamic knowledge model for management decision-making on total nitrogen rate, ratios of organic to inorganic and of basal to dre...By analyzing and extracting the research progress on nitrogen fertilization in wheat, a dynamic knowledge model for management decision-making on total nitrogen rate, ratios of organic to inorganic and of basal to dressing nitrogen under different environments and cultivars in wheat was developed with principle of nutrient balance and by integrating the quantitative effects of grain yield and quality targets, soil characters, variety traits and water management levels. Case studies on the nitrogen fertilization model with the data sets of different eco-sites, cultivars, soil fertility levels, grain yield and quality targets and water management levels indicate a good performance of the model system in decision-making and wide applicability.展开更多
Based on research concerning dynamic relationships of winter wheat growth to environments and production conditions, a winter wheat model for selecting suitable sowing date, population density and sowing rate under di...Based on research concerning dynamic relationships of winter wheat growth to environments and production conditions, a winter wheat model for selecting suitable sowing date, population density and sowing rate under different varieties, spatial and temporal environments was developed. Case studies on sowing date with the data sets of five different eco-sites, three climatic years and soil fertility levels, and on population density and sowing rate with the data sets of two different variety types, three different soil types, soil fertility levels, sowing dates and grain yield levels indicate a good model performance for decision-making.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
Open data initiatives have promoted governmental agencies and scientific organizations to publish data online for reuse.Research of geoscience focuses on processing georeferenced quantitative data(e.g.,rock parameters...Open data initiatives have promoted governmental agencies and scientific organizations to publish data online for reuse.Research of geoscience focuses on processing georeferenced quantitative data(e.g.,rock parameters,geochemical tests,geophysical surveys and satellite imagery)for discovering new knowledge.Geological knowledge is the cognitive result of human knowledge of the spatial distribution,evolution and interaction patterns of geological objects or processes.Knowledge graphs(KGs)can formalize unstructured knowledge into structured form and have been used in supporting decision-making recently.In this paper,we propose a novel framework that can extract the geological knowledge graph(GKG)from public reports relating to a modelling study.Based on the analysis of basic questions answered by geology,we summarize and abstract geological knowledge elements and then explore a geological knowledge representation model with three levels of“geological conceptsgeological entities-geological relations”to describe semantic units of geological knowledge and their logic relations.Finally,based on the characteristics of mineral resource reports,the geological knowledge representation model oriented to“object relationships”and the hierarchical geological knowledge representation model oriented to“process relationships”are proposed with reference to the commonly used geological knowledge graph representation.The research in this paper can provide some implications for the formalization and structured representation of geological knowledge graphs.展开更多
The modular design technology is of importance increasingly,as product structure is more and more complex.Modular design systems face challenging problems as the design information tends to be dynamic,redundant,and ve...The modular design technology is of importance increasingly,as product structure is more and more complex.Modular design systems face challenging problems as the design information tends to be dynamic,redundant,and very large.This paper describes a novel approach for handling them.In this approach,a partition is firstly performed for the complex structural components by mapping functions to the structures layer by layer.Based on this partition,a comprehensive design matrix is then developed to identify the key design mode which is driven by a special function.The design process is also programmed by analyzing the coupled information on both the functional and structural hierarchies.Then,the integrated knowledge model based on object-oriented method and hybrid inference method is constructed.In this model,knowledge can be organized at hierarchical classification and expressed with different forms.Finally,the methodology developed has been applied to a real application in automobile cylinder block design and the results are presented.展开更多
BACKGROUND Cerebrovascular disease(CVD)poses a serious threat to human health and safety.Thus,developing a reasonable exercise program plays an important role in the long-term recovery and prognosis for patients with ...BACKGROUND Cerebrovascular disease(CVD)poses a serious threat to human health and safety.Thus,developing a reasonable exercise program plays an important role in the long-term recovery and prognosis for patients with CVD.Studies have shown that predictive nursing can improve the quality of care and that the information–knowledge–attitude–practice(IKAP)nursing model has a positive impact on patients who suffered a stroke.Few studies have combined these two nursing models to treat CVD.AIM To explore the effect of the IKAP nursing model combined with predictive nursing on the Fugl–Meyer motor function(FMA)score,Barthel index score,and disease knowledge mastery rate in patients with CVD.METHODS A total of 140 patients with CVD treated at our hospital between December 2019 and September 2021 were randomly divided into two groups,with 70 patients in each.The control group received routine nursing,while the observation group received the IKAP nursing model combined with predictive nursing.Both groups were observed for self-care ability,motor function,and disease knowledge mastery rate after one month of nursing.RESULTS There was no clear difference between the Barthel index and FMA scores of the two groups before nursing(P>0.05);however,their scores increased after nursing.This increase was more apparent in the observation group,and the difference was statistically significant(P<0.05).The rates of disease knowledge mastery,timely medication,appropriate exercise,and reasonable diet were significantly higher in the observation group than in the control group(P<0.05).The satisfaction rate in the observation group(97.14%)was significantly higher than that in the control group(81.43%;P<0.05).CONCLUSION The IKAP nursing model,combined with predictive nursing,is more effective than routine nursing in the care of patients with CVD,and it can significantly improve the Barthel index and FMA scores with better knowledge acquisition,as well as produce high satisfaction in patients.Moreover,they can be widely used in the clinical setting.展开更多
Without sufficient real training data,the data driven classification algorithms based on boosting method cannot solely be utilized to applications such as the mini unmanned helicopter landmark image detection.In this ...Without sufficient real training data,the data driven classification algorithms based on boosting method cannot solely be utilized to applications such as the mini unmanned helicopter landmark image detection.In this paper,we propose an approach which uses a boosting algorithm with the prior knowledge for the mini unmanned helicopter landmark image detection.The stage forward stagewise additive model of boosting is analyzed,and the approach how to combine it with the prior knowledge model is presented.The approach is then applied to landmark image detection,where the multi-features are boosted to solve a series of problems,such as rotation,noises affected,etc.Results of real flight experiments demonstrate that for small training examples the boosted learning system using prior knowledge is dramatically better than the one driven by data only.展开更多
Resources are the base and core of education information, but current web education resources have no structure and it is still difficult to reuse them and make them can be self assembled and developed continually. Ac...Resources are the base and core of education information, but current web education resources have no structure and it is still difficult to reuse them and make them can be self assembled and developed continually. According to the knowledge structure of course and text, the relation among knowledge points, knowledge units from three levels of media material, we can build education resource components, and build TKCM （Teaching Knowledge Combination Model） based on resource components. Builders can build and assemble knowledge system structure and make knowledge units can be self assembled, thus we can develop and consummate them continually. Users can make knowledge units can be self assembled and renewed, and build education knowledge system to satisfy users＇ demand under the form of education knowledge system.展开更多
On the basis of studying general comprehension model of information, this paper puts forward the Four Dimensions Set Information Comprehension Model （FDSICM） based on regarding the new knowledge acquired by cognitiv...On the basis of studying general comprehension model of information, this paper puts forward the Four Dimensions Set Information Comprehension Model （FDSICM） based on regarding the new knowledge acquired by cognitive subject as the fourth dimension set. Making use of the Four Dimension Set Information Comprehension Model （FDSICM）, this paper analyzes the information attributes and expatiates from three levels the comprehension of the information meaning.展开更多
This paper views knowledge management （KM） investment from the angle of real options, and demonstrates the utility of the real options approach to KM investment analysis. First, KM project has characteristics of unc...This paper views knowledge management （KM） investment from the angle of real options, and demonstrates the utility of the real options approach to KM investment analysis. First, KM project has characteristics of uncertainty, irreversibility and choice of timing, which suggests that we can appraise KM investment by real options theory. Second, the paper analyses corresponding states of real options in KM and finance options. Then, this paper sheds light on the way to the application of binomial pricing method to KM investment model, which includes modeling and conducting KM options. Finally, different results are shown of using DCF method and binomial model of option evaluation via a case.展开更多
A prodouct modeling and a process planning that are two essential basses of realizing concurrent engineering are investigated , a logical modeling technique , grammar representation scheme of technology knowledge and...A prodouct modeling and a process planning that are two essential basses of realizing concurrent engineering are investigated , a logical modeling technique , grammar representation scheme of technology knowledge and architecture of expert system for process planning within con- current engineering environment are proposed. They have been utilized in a real reaserch project.展开更多
The objective of this study is to construct a multi-department symptom-based automatic diagnosis model.However,it is dificult to establish a model to classify plenty of diseases and collect thousands of disease-sympto...The objective of this study is to construct a multi-department symptom-based automatic diagnosis model.However,it is dificult to establish a model to classify plenty of diseases and collect thousands of disease-symptom datasets simultaneously.Inspired by the thought of"knowledge graph is model",this study proposes to build an experience-infused knowledge model by continuously learning the experiential knowledge from data,and incrementally injecting it into the knowledge graph.Therefore,incremental learning and injection are used to solve the data collection problem,and the knowledge graph is modeled and containerized to solve the large-scale multi-classification problems.First,an entity linking method is designed and a heterogeneous knowledge graph is constructed by graph fusion.Then,an adaptive neural network model is constructed for each dataset,and the data is used for statistical initialization and model training.Finally,the weights and biases of the learned neural network model are updated to the knowledge graph.It is worth noting that for the incremental process,we consider both the data and class increments.We evaluate the diagnostic effectiveness of the model on the current dataset and the anti-forgetting ability on the historical dataset after class increment on three public datasets.Compared with the classical model,the proposed model improves the diagnostic accuracy of the three datasets by 5%,2%,and 15%on average,respectively.Meanwhile,the model under incremental learning has a better ability to resist forgetting.展开更多
基金The National Natural Science Foundation of China(No.70471023).
文摘In order to solve the problem of modeling product configuration knowledge at the semantic level to successfully implement the mass customization strategy, an approach of ontology-based configuration knowledge modeling, combining semantic web technologies, was proposed. A general configuration ontology was developed to provide a common concept structure for modeling configuration knowledge and rules of specific product domains. The OWL web ontology language and semantic web rule language （SWRL） were used to formally represent the configuration ontology, domain configuration knowledge and rules to enhance the consistency, maintainability and reusability of all the configuration knowledge. The configuration knowledge modeling of a customizable personal computer family shows that the approach can provide explicit, computerunderstandable knowledge semantics for specific product configuration domains and can efficiently support automatic configuration tasks of complex products.
基金supported by 2013 Comprehensive Reform Pilot of Marine Engineering Specialty(No.ZG0434)
文摘Knowledge-based modeling is a trend in complex system modeling technology. To extract the process knowledge from an information system, an approach of knowledge modeling based on interval-valued fuzzy rough set is presented in this paper, in which attribute reduction is a key to obtain the simplified knowledge model. Through defining dependency and inclusion functions, algorithms for attribute reduction and rule extraction are obtained. The approximation inference plays an important role in the development of the fuzzy system. To improve the inference mechanism, we provide a method of similaritybased inference in an interval-valued fuzzy environment. Combining the conventional compositional rule of inference with similarity based approximate reasoning, an inference result is deduced via rule translation, similarity matching, relation modification, and projection operation. This approach is applied to the problem of predicting welding distortion in marine structures, and the experimental results validate the effectiveness of the proposed methods of knowledge modeling and similarity-based inference.
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.
基金The National Key R&D project granted by the Ministry of Science and Technology(2024YFA0917200)Digital Museum Construction Project of Chinese Centre for Disease Control and Prevention(BB2110240080)Science Communication Project of Chinese Academy of Sciences(CX2090000008).
文摘Background:The advent of the self-media age,digital humanities,and artificial intelligence(AI)technologies is gradually reshaping the narrative frameworks of the history of science and technology in general and the history of medicine in particular,as it transforms the specific shape of contemporary medical science and health communication practice with the help of interactive,scenario-based communication ecosystems.Methods:This paper focuses on the interactive relationship between the history of science and science communication,employing historical tracing and case study comparison as research methods to explore the pathways and innovative models for reintegrating the history of science and technology including the history of medicine into contemporary scientific discourse.Results:The study finds that in the Chinese context,three key pathways facilitate the engagement of the history of science and technology including the history of medicine in science communication:administrative intervention,value reconstruction,and personalized adaptation.Specifically,administrative intervention promotes the integration of the history of science education into talent development through policy design;value reconstruction,centered on the scientific spirit,enhances societal cultural recognition of technological progress;and personalized adaptation leverages big data and social media technologies to enable precise and tailored knowledge dissemination.Conclusion:The rise of the“web-based knowledge brokering model”in the era of social media has introduced professional knowledge brokers,ensuring the accuracy and accessibility of science communication.These innovations not only serve as decision-making simulation tools for medical science and health communication,linking historical insights with contemporary practice,but also provide theoretical foundations and practical paradigms for realizing the value of the history of science and technology in the digital era.
文摘Objective:To investigate the effect of an information-knowledge-attitude-practice(IKAP)nursing intervention on the caregiving capacity of family caregivers of elderly dementia patients.Methods:Sixty-nine family caregivers of elderly dementia patients attending the neurology outpatient clinic of a hospital between October 2024 and March 2025 were selected.They were randomly divided into a control group(n=35)and an observation group(n=34).The control group received routine health education,while the observation group additionally underwent a systematic Information-Knowledge-Attitude-Practice(IKAP)nursing intervention.Care competence and self-efficacy scores were compared between groups before intervention and after 12 weeks.Results:Pre-intervention,no statistically significant difference existed in care competence or self-efficacy scores between groups(p>0.05).Following the 12-week intervention,all scores significantly increased in both groups,with the observation group demonstrating superior outcomes compared to the control group(p<0.001).Conclusion:The care intervention program based on the IKAP model effectively enhances caregivers’care competence and self-efficacy,thereby positively promoting the quality of life for patients with dementia.
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 the National Natural Science Foundation of China(30030090)National High Tech R&D Program(863 Program)of China(2001AA245041,2001AA115420).
文摘By analyzing and extracting the research progress on nitrogen fertilization in wheat, a dynamic knowledge model for management decision-making on total nitrogen rate, ratios of organic to inorganic and of basal to dressing nitrogen under different environments and cultivars in wheat was developed with principle of nutrient balance and by integrating the quantitative effects of grain yield and quality targets, soil characters, variety traits and water management levels. Case studies on the nitrogen fertilization model with the data sets of different eco-sites, cultivars, soil fertility levels, grain yield and quality targets and water management levels indicate a good performance of the model system in decision-making and wide applicability.
基金the National Natural Science Foundation of China(30030090) National“863”Plans of China(2001AA245041,2001AA115420).
文摘Based on research concerning dynamic relationships of winter wheat growth to environments and production conditions, a winter wheat model for selecting suitable sowing date, population density and sowing rate under different varieties, spatial and temporal environments was developed. Case studies on sowing date with the data sets of five different eco-sites, three climatic years and soil fertility levels, and on population density and sowing rate with the data sets of two different variety types, three different soil types, soil fertility levels, sowing dates and grain yield levels indicate a good model performance for decision-making.
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the IUGS Deep-time Digital Earth(DDE)Big Science Programfinancially supported by the National Key R&D Program of China(No.2022YFF0711601)+4 种基金the Natural Science Foundation of Hubei Province of China(No.2022CFB640)the Opening Fund of Hubei Key Laboratory of Intelligent Vision-Based Monitoring for Hydroelectric Engineering(No.2022SDSJ04)the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(No.GLAB 2023ZR01)the Fundamental Research Funds for the Central UniversitiesFunded by Joint Fund of Collaborative Innovation Center of Geo-Information Technology for Smart Central Plains,Henan Province and Key Laboratory of Spatiotemporal Perception and Intelligent processing,Ministry of Natural Resources(No.212205)。
文摘Open data initiatives have promoted governmental agencies and scientific organizations to publish data online for reuse.Research of geoscience focuses on processing georeferenced quantitative data(e.g.,rock parameters,geochemical tests,geophysical surveys and satellite imagery)for discovering new knowledge.Geological knowledge is the cognitive result of human knowledge of the spatial distribution,evolution and interaction patterns of geological objects or processes.Knowledge graphs(KGs)can formalize unstructured knowledge into structured form and have been used in supporting decision-making recently.In this paper,we propose a novel framework that can extract the geological knowledge graph(GKG)from public reports relating to a modelling study.Based on the analysis of basic questions answered by geology,we summarize and abstract geological knowledge elements and then explore a geological knowledge representation model with three levels of“geological conceptsgeological entities-geological relations”to describe semantic units of geological knowledge and their logic relations.Finally,based on the characteristics of mineral resource reports,the geological knowledge representation model oriented to“object relationships”and the hierarchical geological knowledge representation model oriented to“process relationships”are proposed with reference to the commonly used geological knowledge graph representation.The research in this paper can provide some implications for the formalization and structured representation of geological knowledge graphs.
基金the National Natural Science Foundation of China （No. 50935006）； the National High Technology Research and Development Program （863） of China （No. 2009AA04Z147）；the Science- Technology Research and Development Program of Shaanxi Province （No. 2008KW-07）
文摘The modular design technology is of importance increasingly,as product structure is more and more complex.Modular design systems face challenging problems as the design information tends to be dynamic,redundant,and very large.This paper describes a novel approach for handling them.In this approach,a partition is firstly performed for the complex structural components by mapping functions to the structures layer by layer.Based on this partition,a comprehensive design matrix is then developed to identify the key design mode which is driven by a special function.The design process is also programmed by analyzing the coupled information on both the functional and structural hierarchies.Then,the integrated knowledge model based on object-oriented method and hybrid inference method is constructed.In this model,knowledge can be organized at hierarchical classification and expressed with different forms.Finally,the methodology developed has been applied to a real application in automobile cylinder block design and the results are presented.
基金Supported by Basic scientific research industry of Heilongjiang Provincial undergraduate universities in 2019,No.2019-KYYWF-1213.
文摘BACKGROUND Cerebrovascular disease(CVD)poses a serious threat to human health and safety.Thus,developing a reasonable exercise program plays an important role in the long-term recovery and prognosis for patients with CVD.Studies have shown that predictive nursing can improve the quality of care and that the information–knowledge–attitude–practice(IKAP)nursing model has a positive impact on patients who suffered a stroke.Few studies have combined these two nursing models to treat CVD.AIM To explore the effect of the IKAP nursing model combined with predictive nursing on the Fugl–Meyer motor function(FMA)score,Barthel index score,and disease knowledge mastery rate in patients with CVD.METHODS A total of 140 patients with CVD treated at our hospital between December 2019 and September 2021 were randomly divided into two groups,with 70 patients in each.The control group received routine nursing,while the observation group received the IKAP nursing model combined with predictive nursing.Both groups were observed for self-care ability,motor function,and disease knowledge mastery rate after one month of nursing.RESULTS There was no clear difference between the Barthel index and FMA scores of the two groups before nursing(P>0.05);however,their scores increased after nursing.This increase was more apparent in the observation group,and the difference was statistically significant(P<0.05).The rates of disease knowledge mastery,timely medication,appropriate exercise,and reasonable diet were significantly higher in the observation group than in the control group(P<0.05).The satisfaction rate in the observation group(97.14%)was significantly higher than that in the control group(81.43%;P<0.05).CONCLUSION The IKAP nursing model,combined with predictive nursing,is more effective than routine nursing in the care of patients with CVD,and it can significantly improve the Barthel index and FMA scores with better knowledge acquisition,as well as produce high satisfaction in patients.Moreover,they can be widely used in the clinical setting.
基金Project (No. 2006AA10Z204) supported by the National Hi-Tech Research and Development Program (863) of China
文摘Without sufficient real training data,the data driven classification algorithms based on boosting method cannot solely be utilized to applications such as the mini unmanned helicopter landmark image detection.In this paper,we propose an approach which uses a boosting algorithm with the prior knowledge for the mini unmanned helicopter landmark image detection.The stage forward stagewise additive model of boosting is analyzed,and the approach how to combine it with the prior knowledge model is presented.The approach is then applied to landmark image detection,where the multi-features are boosted to solve a series of problems,such as rotation,noises affected,etc.Results of real flight experiments demonstrate that for small training examples the boosted learning system using prior knowledge is dramatically better than the one driven by data only.
基金Supported by the National High Technology Research and Development Program of China (863 Program) (2002AA111010 2003AA001032)
文摘Resources are the base and core of education information, but current web education resources have no structure and it is still difficult to reuse them and make them can be self assembled and developed continually. According to the knowledge structure of course and text, the relation among knowledge points, knowledge units from three levels of media material, we can build education resource components, and build TKCM （Teaching Knowledge Combination Model） based on resource components. Builders can build and assemble knowledge system structure and make knowledge units can be self assembled, thus we can develop and consummate them continually. Users can make knowledge units can be self assembled and renewed, and build education knowledge system to satisfy users＇ demand under the form of education knowledge system.
文摘On the basis of studying general comprehension model of information, this paper puts forward the Four Dimensions Set Information Comprehension Model （FDSICM） based on regarding the new knowledge acquired by cognitive subject as the fourth dimension set. Making use of the Four Dimension Set Information Comprehension Model （FDSICM）, this paper analyzes the information attributes and expatiates from three levels the comprehension of the information meaning.
基金This paper is supported by National Natural Science Foundation of China （NSFC） and Ph.D. Research Fund.
文摘This paper views knowledge management （KM） investment from the angle of real options, and demonstrates the utility of the real options approach to KM investment analysis. First, KM project has characteristics of uncertainty, irreversibility and choice of timing, which suggests that we can appraise KM investment by real options theory. Second, the paper analyses corresponding states of real options in KM and finance options. Then, this paper sheds light on the way to the application of binomial pricing method to KM investment model, which includes modeling and conducting KM options. Finally, different results are shown of using DCF method and binomial model of option evaluation via a case.
文摘A prodouct modeling and a process planning that are two essential basses of realizing concurrent engineering are investigated , a logical modeling technique , grammar representation scheme of technology knowledge and architecture of expert system for process planning within con- current engineering environment are proposed. They have been utilized in a real reaserch project.
基金the National Key Research and Development Program(No.2018YFB1307005)the Smart Medical Project of Shanghai Municipal Commission of Health and Family Planning(No.2018ZHYL0226)。
文摘The objective of this study is to construct a multi-department symptom-based automatic diagnosis model.However,it is dificult to establish a model to classify plenty of diseases and collect thousands of disease-symptom datasets simultaneously.Inspired by the thought of"knowledge graph is model",this study proposes to build an experience-infused knowledge model by continuously learning the experiential knowledge from data,and incrementally injecting it into the knowledge graph.Therefore,incremental learning and injection are used to solve the data collection problem,and the knowledge graph is modeled and containerized to solve the large-scale multi-classification problems.First,an entity linking method is designed and a heterogeneous knowledge graph is constructed by graph fusion.Then,an adaptive neural network model is constructed for each dataset,and the data is used for statistical initialization and model training.Finally,the weights and biases of the learned neural network model are updated to the knowledge graph.It is worth noting that for the incremental process,we consider both the data and class increments.We evaluate the diagnostic effectiveness of the model on the current dataset and the anti-forgetting ability on the historical dataset after class increment on three public datasets.Compared with the classical model,the proposed model improves the diagnostic accuracy of the three datasets by 5%,2%,and 15%on average,respectively.Meanwhile,the model under incremental learning has a better ability to resist forgetting.
