Knowledge Automatic Indexing Based on Concept Lexicon and Segm-entation Algorithm

This paper is based on two existing theories about automatic indexing of thematic knowledge concept. The prohibit-word table with position information has been designed. The improved Maximum Matching-Minimum Backtracking method has been researched. Moreover it has been studied on improved indexing algorithm and application technology based on rules and thematic concept word table.

Arguing the capacity of ＂word knowledge framework＂ to explain the nature of vocabulary

The acquisition of word knowledge, in terms of breadth and depth, has a fundamental impact on language learning. A comprehensive framework of word knowledge is therefore needed to help language learners master all the aspects of word knowledge. This paper proposed a framework of word knowledge based on the literature review of the field. The pedagogical implications of the word knowledge framework were then proposed and discussed critically. Finally, it is proposed that syllabus designers need to consider the possibility of incorporating ＂word knowledge framework＂ into syllabus.

Incorporating Domain Knowledge into Data Mining Process:An Ontology Based Framework

With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. First, some valid mining task schedules are generated, and then au tonomous and local mining are executed periodically, finally, previous results are merged and refined. The framework based on the model creates a communication mechanism to in corporate domain knowledge into continuous process through ontology service. The local and merge mining are transparent to the end user and heterogeneous data ,source by ontology. Experiments suggest that the framework should be useful in guiding the continuous mining process.

Large-Scale Ontology Development and Agricultural Application Based on Knowledge Domain Framework

The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge management- the knowledge domain framework （KDF）, and introduces an integrated development environment （IDE） named large-scale ontology development environment （LODE）, which implements the proposed theoretical framework. We also compared LODE with other popular ontology development environments in this paper. The practice of using LODE on management and development of agriculture ontologies shows that knowledge domain framework can handle the development activities of large scale ontologies. Application studies based on the described briefly. principle of knowledge domain framework and LODE was

A Proposed Knowledge Management Implementation Framework for the Ghanaian Construction Industry

This study aims at developing a Knowledge Management Implementation Framework for adoption by firms in the Ghanaian construction industry. Recent developments in the field of Knowledge management in the construction sector have led to a renewed competition in driving organizational performance. However, the construction industry in Ghana lacks a knowledge management implementation framework that addresses the needs of the Ghanaian construction supply chain while a comprehensive approach to managing knowledge remains nebulous. The study adopted an extensive literature review of existing knowledge management models to provide the basis for the development of the proposed framework for Ghana. The proposed knowledge management implementation framework was subjected to testing and validation by project managers drawn from nineteen indigenous construction firms in Ghana. The technology acceptance model (TAM) was used as the criteria to validate the proposed knowledge management implementation framework. The proposed Guribie & Tengan knowledge management implementation framework was perceived to be useful, and easy to use and the intention to adopt and use was high among indigenous Ghanaian construction firms. The study recommends further validation using wider population to enhance the efficacy of the framework for wider industry acceptance to enhance organizational competitiveness and performance delivery.

Designing and Evaluating a Collaborative Knowledge Management Framework for Leaf Disease Detection

Knowledge Management(KM)has become a dynamic concept for inquiry in research.The management of knowledge from multiple sources requires a systematic approach that can facilitate capturing all important aspects related to a particular discipline,several KM frameworks have been designed to serve this purpose.This research aims to propose a Collaborative Knowledge Management(CKM)Framework that bridges gaps and overcomes weaknesses in existing frameworks.The paper also validates the framework by evaluating its effectiveness for the agriculture sector of Pakistan.A software LCWU aKMS was developed which serves as a practical implementation of the concepts behind the proposed CKMF framework.LCWU aKMS served as an effective system for rice leaf disease detection and identification.It aimed to enhance CKM through knowledge sharing,lessons learned,feedback on problem resolutions,help from co-workers,collaboration,and helping communities.Data were collected from 300 rice crop farmers by questionnaires based on hypotheses.Jennex Olfman model was used to estimate the effectiveness of CKMF.Various tests were performed including frequency measures of variables,Cronbach’s alpha reliability,and Pearson’s correlation.The research provided a KMS depicting KM and collaborative features.The disease detection module was evaluated using the precision and recall method and found to be 94.16%accurate.The system could replace the work of extension agents,making it a cost and time-effective initiative for farmer betterment.

Using the KISO's Framework to Integrate Knowledge Sources

In complicated application environment such as CIMS (Computer Integrated Manufacture System) enterprise, it will bring great benefits to integrate distributed knowledge sources. But the difficulties of knowledge sharing and reuse seriously encumbrance the implementation of knowledge integration. In this paper, we describe how a framework of knowledge-integrated system based on ontology (KISO) can be used to support integrating distributed knowledge sources.

Research on construction knowledge resources framework of real estate enterprises

Many studies have shown that knowledge resources have been the real source of innovation and competitiveness of real estate enterprises. Therefore, it is the basic work to establish the real estate enterprise knowledge resources framework for implementing knowledge management（KM）,and it should be given enough attention. A sort of the real estate enterprise knowledge resources framework system has been built in this paper based on the thought of Clark ＆ Henderson＇s enterprise knowledge classification, and the contents have been analyzed and expounded. Thus, the real estate enterprises can grasp clearly the basic contents of its knowledge resources, then depict the knowledge system, in the end the solid foundation should be settled for implementing knowledge management.

Exploring the Three-dimensional Framework of Knowledge Service in the field of Library and Information Science(LIS)

The evolution of the society and economy has stimulated the development of Knowledge Service(KS), making it an indispensable solution to address future challenges facing libraries and information institutions. However at present, academic research on knowledge service is falling short and its definition is far from clear and complete. As such,this article proposes the Three-dimensional Framework Knowledge Service(TdFKS) for libraries and information institutions based on the knowledge value chain model. By making reliability analysis and mean value analysis of a questionnaire survey result, the article clarifies the structure of the three-dimensional framework and verifies the rationality of the TdFKS.

CAD Framework中基于知识的设计流管理

设计流管理是CAD Framework(框架结构)中一个新的研究领域。本文在给出与设计流有关的基本概念的基础上,采用结构约束和数据约束的方法实现对设计流的知识表示,并通过设计经验的获取途径、进一步的知识生成以及设计流的执行、一致性的处理和设计流的评估,详细讨论CAD Framework 中基于知识的设计流管理。文中还给出了相应的设计流管理系统的总体设计。

Intelligent search on integrated knowledge base of traditional Chinese medicine

To semantically integrate heterogeneous resources and provide a unified intelligent access interface, semantic web technology is exploited to publish and interlink machineunderstandable resources so that intelligent search can be supported. TCMSearch, a deployed intelligent search engine for traditional Chinese medicine （TCM）, is presented. The core of the system is an integrated knowledge base that uses a TCM domain ontology to represent the instances and relationships in TCM. Machine-learning techniques are used to generate semantic annotations for texts and semantic mappings for relational databases, and then a semantic index is constructed for these resources. The major benefit of representing the semantic index in RDF/OWL is to support some powerful reasoning functions, such as class hierarchies and relation inferences. By combining resource integration with reasoning, the knowledge base can support some intelligent search paradigms besides keyword search, such as correlated search, semantic graph navigation and concept recommendation.

A Knowledge Model System for Wheat Production Management

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.

Research Progress on Evaluation Frameworks of Regional Ecological Sustainability

As natural ecosystems provide the material basis and fundamental support for regional sustainable devel-opment,the sustainability of natural ecosystems is an important prerequisite and a viable approach for the achievement of regional sustainable development.It is also the final criteria to assess whether sustainable development paradigm is successful.Along with the increasing impacts of human activities on natural ecosystems,the evaluation of regional ecological sustainability has become one of the key issues for research on macro ecology and sustainable development.Based on different unit of indicators,this study firstly groups the evaluation frameworks of regional ecological sus-tainability into three major types:comprehensive index evaluation with dimensionless unit,monetary valuation,and biophysical quantity measurement.We then discuss and compare these types in terms of basic principles,scope of ap-plications,advantages and shortcomings.Finally,drawn on the discussion about characteristics of ecological sustain-ability,we outline the current trend and future directions of regional ecological sustainability evaluation,for instance,transition from sustainable development evaluation to sustainability science,integration of goal-oriented and problem-solving approaches,combination of spatial pattern analysis and ecological sustainability evaluation,and en-hancement of ecological sustainability evaluation at landscape scale.

Effects of the information–knowledge–attitude–practice nursing model combined with predictability intervention on patients with cerebrovascular disease

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.

A Methodology for Estimating Leaf Area Index by Assimilating Remote Sensing Data into Crop Model Based on Temporal and Spatial Knowledge

In this paper,a methodology for Leaf Area Index(LAI) estimating was proposed by assimilating remote sensed data into crop model based on temporal and spatial knowledge.Firstly,sensitive parameters of crop model were calibrated by Shuffled Complex Evolution method developed at the University of Arizona(SCE-UA) optimization method based on phenological information,which is called temporal knowledge.The calibrated crop model will be used as the forecast operator.Then,the Taylor′s mean value theorem was applied to extracting spatial information from the Moderate Resolution Imaging Spectroradiometer(MODIS) multi-scale data,which was used to calibrate the LAI inversion results by A two-layer Canopy Reflectance Model(ACRM) model.The calibrated LAI result was used as the observation operator.Finally,an Ensemble Kalman Filter(EnKF) was used to assimilate MODIS data into crop model.The results showed that the method could significantly improve the estimation accuracy of LAI and the simulated curves of LAI more conform to the crop growth situation closely comparing with MODIS LAI products.The root mean square error(RMSE) of LAI calculated by assimilation is 0.9185 which is reduced by 58.7% compared with that by simulation(0.3795),and before and after assimilation the mean error is reduced by 92.6% which is from 0.3563 to 0.0265.All these experiments indicated that the methodology proposed in this paper is reasonable and accurate for estimating crop LAI.

Expanding the Definition and Measurement of Knowledge Economy： Integrating Triple Bottom Line Factors into Knowledge Economy Index Models and Methodologies

The application of knowledge is a primary source of growth in the knowledge economy. The World Bank Group has developed a rigorous assessment methodology for assessing a country＇s ability to access and use knowledge to become more competitive in the knowledge economy of the 21st century. The World Bank＇s annual knowledge economy index is grounded on a four-pillar model： （1） economic incentives and institutional regime; （2） education and skills; （3） information and communication infrastructure; and （4） innovation systems. An argument can be made that the model lacks coverage of some key factors that pertain to intellectual capital and the production and consumption of knowledge. The model＇s heavy focus on economic incentives and open institutional regimes comes at a societal cost. This paper proposes an alternative knowledge economy index which is grounded in a more holistic and balanced view of a knowledge society. Adopting the perspective of triple bottom line shifts the purpose and design of a knowledge economy from one of aggregation and reporting to action and involvement. The World Bank＇s scorecard and indexing methodology are adaptable to this new perspective and a new set of indicators.

Occupational Safety Culture Index (OSCI)——measuring the community and employees awareness,attitude and knowledge towards workplace safety and health in Hong Kong SAR

Promoting occupational safety and health in Hong Kong,Special Administrative Region of China is an important and ongoing mission. As the major organization with statutory responsibilities,the Occupational Safety and Health Council understand the importance to strengthen and cultivate our safety culture. It is widely believed that numbers of occupational related diseases and injuries could be prevented with the improvement of the awareness and attitudes of the employees and the public. Therefore,a comprehensive and in-depth study to monitor the occupational health and safety level and status of the community and working population is needed. Objectives: Our Council has developed the Occupational Safety Culture Index ( OSCI) to measure the current level of community and workplace safety and health awareness,knowledge and attitude. Benchmarking measures of the key safety performance indicators are to be derived thereof. Methods: A territory-wide random telephone survey was conducted to assess the community and employees'awareness,attitude and knowledge in 2008. A structured questionnaire was designed with the content validity and reliability assessed before the survey administration. A series of quality control approaches were also applied to assure the quality of the fieldwork and the reliability of the data. Results: 1,531 eligible participants'data were collected and computed into 2 types of composite indices,Occupational Safety Culture Index ( Community) ( OSCIC) and Occupational Safety Culture Index (Workplace) (OSCIW) . With the maximum score of index at 100,the overall score of OSCIC is 66. 9 and the OSCIW is 61. 3 in Hong Kong. Achievements: OSCI served as an effective management tool to measure the safety culture in Hong Kong. With a representative sample and high quality study control and validated assessment approaches,the OSCI and the sub-indices are reliable indicators to assess the effectiveness of safety culture enhancement strategy and the OSH intervention measures.

Assessment of Knowledge and Attitude in a Sample of Patients with Rheumatoid Arthritis and Its Association with Disease Activity and Severity: A Cross-Sectional Study

Background: Rheumatoid arthritis (RA) is a chronic and disabling disease that has a major impact on the lives of patients. Objectives: To test the patients’ knowledge about their disease, its treatment, its complications, and if this affects severity of the disease as measured by the disease activity index (DAS 28). Patients and Methods: A sample of 100 patients with RA who met the Criteria of American College of Rheumatology for RA agreed to participate in this study over the period September 2011-March 2012. Patients’ data were obtained by personal interview. The questionnaire included demographic characteristics and the patients’ knowledge about their disease. The disease activity was measured using standard (DAS28). Results: Thirty three percent of the patients didn’t have an idea about their disease, 20% didn’t know the reason for the investigations, 49% didn’t know the treatment and 40% didn’t know the side effects of their medications. Most patients had a high disease activity index, and there was a poor correlation between patients’ educational level and the disease activity. Conclusions: Neither the educational level nor the frequency of hospital admissions had effects on the knowledge about this disease. As most patients had a high disease activity, a better knowledge may improve disease control and prevent complications.

Research on Performance Measurement System of Knowledge Strategy for Firms

Knowledge has become the most important strategic resource of firms, and the competition among firms is more based on knowledge than before. To deal with this challenge, some firms are trying to develop knowledge strategies to direct their knowledge management activities, but current strategic performance measurement systems can＇t evaluate the performance of knowledge strategies appropriately. This article develops a performance measurement system for knowledge strategies based on Balanced Scorecard, and simulates the system with an improved Data Envelopment Analysis （DEA） model.

Amino acids industry knowledge service platform

Purpose： This paper introduces an amino acids industry knowledge service platform, which integrates industry data, science literature, and technology knowledge from patents.Design/methodology/approach： From the perspective of knowledge organization, the amino acids industry knowledge service platform comprises a basic data layer, a knowledge representation layer, and a knowledge service layer. The platform integrates heterogeneous information sources by means of a multi-dimensional integration index. It enables users to find technology knowledge from patents by employing the semantic Theory of Inventive Problem Solving （TRIZ）.Findings： This paper constructs an integrated amino acids industry database, which offers a general service oriented to the public, and a technical innovation knowledge base, which offers a value-added service oriented to enterprises.Research limitations： The technical innovation knowledge base only includes parts of amino acids technology knowledge, making it suitable to meet certain specific needs.Practical implications： Semantic annotation of technical innovation knowledge from patents requires manual work by domain experts.Originality/value： The amino acids industry knowledge service platform offers not only an integrated search service for amino acids industry information, but also a deep tech mining service for technical innovation knowledge of amino acids. It will offer a more personalized knowledge service in the future.