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.

On the development of modern service industry under mismatched Blotto game of knowledge flow

In order to highlight and analyze the influence of heterogeneous knowledge flows to enterprises in the modern service industry,based on a review of the Colonel Blotto game,some presumptions such as the game's utility function are modified,and a mechanism to change tacit knowledge into explicit knowledge is constructed to carry out an analysis of a two-player knowledge flow management.The characteristics of the players' optimal reactions of knowledge flow management are studied,and the results bear evidence of the facts that a gap always exists under the spillover effect.Meanwhile,tacit knowledge seems more important to the development of enterprises than explicit knowledge.So it implies that the foremost task for the development of the modern service industry is to strengthen the settings and institutions for the flux of tacit knowledge and enterprise knowledge management.

Ontology Engineering and Knowledge Services for Agriculture Domain

This paper presents a knowledge service system for the domain of agriculture. Three key issues for providing knowledge services are how to improve the access of unstructured and scattered information for the non-specialist users, how to provide adequate information to knowledge workers and how to provide the information requiring highly focused and related information. Cyber-Brain has been designed as a platform that combines approaches based on knowledge engineering and language engineering to gather knowledge from various sources and to provide the effective knowledge service. Based on specially designed ontology for practical service scenarios, it can aggregate knowledge from Internet, digital archives, expert, and other resources for providing one-stop-shop knowledge services. The domain specific and task oriented ontology also enables advanced search and allows the system ensures that knowledge service could improve the user benefit. Users are presented with the necessary information closely related to their information need and thus of potential high interest. This paper presents several service scenarios for different end-users and reviews ontology engineering and its life cycle for supporting AOS （Agricultural Ontology Services） Vocbench which is the heart of knowledge services in agriculture domain.

Prioritizing sustainable development goals and linking them to ecosystem services:A global expert’s knowledge evaluation

The implementation of strategies to achieve the Sustainable Development Goals(SDGs)is frequently hindered by potential trade-offs between priorities for either environmental protection or human well-being.However,ecosystem services(ES)-based solutions can offer possible co-benefits for SDGs implementation that are often overlooked or underexploited.In this study,we cover this gap and investigate how experts from different countries value the SDGs and relate them with ES.A total of 66 countries participated to the survey,and answers were grouped into three macro-regions:Asia;Europe,North America,and Oceania(ENO);Latin America,Caribbean and Africa(LA).Results show that the most prioritized SDGs in the three macro-regions are usually those related to essential material needs and environmental conditions,such as SDG2(Zero Hunger),SDG1(No Poverty),and SDG6(Clean Water).At a global scale,the number of prioritized synergies between SDGs and ES largely exceeded trade-offs.The highest amount of synergies was observed for SDG1(No Poverty),mainly with SDG2,SDG3(Good Health),SDG5(Gender Equality),and SDG8(Economic Growth).Other major synergies among SDGs include SDG14-15(Life below water-Life on land),SDG5-10(Gender Equity-Reduced Inequality),and SDG1-2(No poverty-Zero Hunger).At a global scale,SDG15,SDG13,SDG14,and SDG6 were closely related to ES like climate regulation,freshwater,food,water purification,biodiversity,and education.SDG11(Sustainable Cities)and SDG3 were also relevant in Asia and in LA,respectively.Overall,this study shows the potential to couple future policies that can implement SDGs’strategies while adopting ES-based solutions in different regions of the world.

Intelligent Recommendation and Matching Method for Agricultural Knowledge Based on Context-Aware Models

The personalized recommendation of the cloud platform for agricultural knowledge and agricultural intelligent service is one of the core technologies for the development of smart agriculture.Revealing the implicit laws and dynamic characteristics of agricultural knowledge demand is a key problem to be solved urgently.In order to enhance the matching ability of knowledge recommendation and service in human-computer interaction of cloud platform,the mechanism of agricultural knowledge intelligent recommendation service integrated with context-aware model was analyzed.By combining context data acquisition,data analysis and matching,and personalized knowledge recommendation,a framework for agricultural knowledge recommendation service is constructed to improve the ability to extract multidimensional information features and predict sequence data.Using the cloud platform for agricultural knowledge and agricultural intelligent service,this research aims to deliver interesting video service content to users in order to solve key problems faced by farmers,including planting technology,disease control,expert advice,etc.Then the knowledge needs of different users can be met and user satisfaction can be improved.

Fuzzy Logic Inference System for Managing Intensive Care Unit Resources Based on Knowledge Graph

With the rapid growth in the availability of digital health-related data,there is a great demand for the utilization of intelligent information systems within the healthcare sector.These systems can manage and manipulate this massive amount of health-related data and encourage different decision-making tasks.They can also provide various sustainable health services such as medical error reduction,diagnosis acceleration,and clinical services quality improvement.The intensive care unit(ICU)is one of the most important hospital units.However,there are limited rooms and resources in most hospitals.During times of seasonal diseases and pandemics,ICUs face high admission demand.In line with this increasing number of admissions,determining health risk levels has become an essential and imperative task.It creates a heightened demand for the implementation of an expert decision support system,enabling doctors to accurately and swiftly determine the risk level of patients.Therefore,this study proposes a fuzzy logic inference system built on domain-specific knowledge graphs,as a proof-of-concept,for tackling this healthcare-related issue.The system employs a combination of two sets of fuzzy input parameters to classify health risk levels of new admissions to hospitals.The proposed system implemented utilizes MATLAB Fuzzy Logic Toolbox via several experiments showing the validity of the proposed system.

Leveraging Robust Artificial Intelligence for Mechatronic Product Development—A Literature Review

Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineering. The integration of artificial intelligence technologies is revolutionizing this domain, offering opportunities to enhance design processes, optimize performance, and leverage vast amounts of knowledge. However, human expertise remains essential in contextualizing information, considering trade-offs, and ensuring ethical and societal implications are taken into account. This paper therefore explores the existing literature regarding the application of artificial intelligence as a comprehensive database, decision support system, and modeling tool in mechatronic product development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert knowledge, improving prediction quality, and enhancing intelligent control systems. For this purpose, a consideration of the V-cycle takes place, a standard in mechatronic product development. Along this, an initial assessment of the AI potential is shown and important categories of AI support are formed. This is followed by an examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in mechatronic product development opens new possibilities and transforms the way innovative mechatronic systems are conceived, designed, and deployed. However, the approaches are only taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive artificial intelligence along them is still needed.

A Health State Prediction Model Based on Belief Rule Base and LSTM for Complex Systems

In industrial production and engineering operations,the health state of complex systems is critical,and predicting it can ensure normal operation.Complex systems have many monitoring indicators,complex coupling structures,non-linear and time-varying characteristics,so it is a challenge to establish a reliable prediction model.The belief rule base(BRB)can fuse observed data and expert knowledge to establish a nonlinear relationship between input and output and has well modeling capabilities.Since each indicator of the complex system can reflect the health state to some extent,the BRB is built based on the causal relationship between system indicators and the health state to achieve the prediction.A health state prediction model based on BRB and long short term memory for complex systems is proposed in this paper.Firstly,the LSTMis introduced to predict the trend of the indicators in the system.Secondly,the Density Peak Clustering(DPC)algorithmis used todetermine referential values of indicators for BRB,which effectively offset the lack of expert knowledge.Then,the predicted values and expert knowledge are fused to construct BRB to predict the health state of the systems by inference.Finally,the effectiveness of the model is verified by a case study of a certain vehicle hydraulic pump.

Knowledge of Cervical Cancer and Prevalence of the Screening Services among HIV-Infected Women in Blantyre, Malawi

HIV-infected women are at high risk of developing cervical cancer and are encouraged to undergo cervical cancer screening regularly. However, very little has been documented about the knowledge of cervical cancer and the utilization of the screening services by these women. This study aimed to investigate the knowledge of cervical cancer, prevalence of cervical cancer screening uptake and predictive factors that affect utilization of cervical cancer screening services among HIV-infected women. The study employed quantitative methods for data collection and analysis. It was conducted at Queen Elizabeth Central Hospital (QECH) from December 2017 to February 2018 where HIV-positive patients accessing QECH Antiretroviral Therapy (ART) clinic were recruited. Systematic random sampling was employed to select HIV-positive women for the survey. Data were collected using semi-structured questionnaires. STATA version 12 was used to analyze the data. Out of the 196 recruited women, the majority (98%;n = 192) indicated having heard of cervical cancer and of the 192 women, only 57% (n = 109) were able to know at least a single sign/symptom of cervical cancer, furthermore, only 47% (n = 91) indicated ever been screened, finally, getting information from health facilities and knowing at least a single sign/symptom of cervical cancer influenced HIV-infected women to go for cervical cancer screening services. The study revealed that knowledge of cervical cancer and the utilization of its screening services among HIV-infected women is low. Therefore, there is need to increase knowledge and strengthen cervical cancer screening services among HIV-infected women in the country.

Application of an expert knowledge system in the study of forest spatial patterns

For the sake of exploring how the pattern of Chinese pine （Pinus massoniana Lamb） community changed after the invasion of the pine wood nematode （Bursaphelenchus xylophilus （Steiner ＆ Buhrer） Niclde） in Zhoushan, Zhejiang Province, we established a test area in the local Chinese pine community. Landsat5 TM images from 1991 and 2006 were integrated with auxiliary data from field investigation and spectral data as additional sources of information. A method of expert knowledge classifier was applied to establish the expert knowledge dataset of the main vegetation cover types from which we obtained a forest type distribution map. The spatial patterns and stability of the forest, before and after the invasion of the pine wood nematode, were analyzed in terms of community patterns. The results indicated that the predominant coniferous forest type changed to a mixed forest. As a result, the forest structure became complex and the interaction between coniferous forest patches became weakened over the period from 1991 to 2006. Therefore, the resistance of the forest eco-system to plant diseases and insect pests and the stability of forest eco-system enhanced.

Developing Better Services for Intimate Partner Violence： Hearing the Voice of Disabled People

This article deals with collaborative development work between the public sector and the third sectorin an area of Southern Savo, Finland, from the perspective of disabled victims. The purpose was to create structures for IPV （intimate partner violence） work, developing professionals＇ skills in both tackling IPV and service-user involvement. Five NGOs （non-goverumental organizations） for disabled people were involved. Professionals were trained to ask about IPV and to gainamore in-depth understanding of the issue （including thespecial features relating to disabled people） andof how to intervene. Care pathways, linking both basic and special services, were also modeled. A permanent and regional NEIPV （Network of Excellence in IPV） was established and is coordinated by both the public and third sectors, including Experts by Experience. Strong basic structures and care pathways are needed so that the special needs of disabled people can be recognized. Raising awareness of violence, routine enquiries modified according to the needs of organizations, and simple care pathways are needed--both in the public sector and for NGOs representing the disabled. Information gained through training will not necessarily be transferred into direct practice without a strong commitment from the managerial level. Establishing organizational guidelines is necessary. This will also promote professionals＇ openness toward user knowledge.

Study on Cultivating the Loyalty of Knowledge Workers in Service Enterprises

Knowledge workers are important human resources in service enterprises.How to cultivate the loyalty of knowledge workers in service enterprises is an important problem that managers must pay attention to.Beginning from the defines of basic concepts, the author analyzes factors influencing loyalty of knowledge workers. Finally, it puts forward effective measures including building people-oriented corporate culture; loyalty oriented recruianent and allocation; emphasis on compensation management; establishing a scientific career management system; paying attention to emotional management and so on.

A discussion of the emotive element of knowledge service practice:An empirical study at the Chinese Academy of Sciences

With the arrival of the information age, research activities focused on the practice and approaches of knowledge services are on a marked increase as evidenced in the publications of social sciences. According to a social network analysis on knowledge service related literature, it reveals that information and knowledge workers often fail to take such an important element as the functional role of an emotive engagement into consideration in their study of knowledge services. It has increasingly become an issue of high profile with the rapid development of digital libraries and their web-based knowledge services in China and anywhere else in the world. In order to have a clearer understanding about issues involved in knowledge servicing so as to maximize the effectiveness and efficiency of digital libraries in their knowledge service performance, the author has conducted surveys for seven times on the online information seeking behavior of graduate students at the Chinese Academy of Sciences with such research methods as questionnaires, interviews and natural observations during September 2006-June 2009. The research result has showed the emotive element has an important role in the user's information seeking behavior and in knowledge services practice. Therefore, knowledge services rendered may be more effective by adding the emotiveness-oriented communication element into such practice. This paper recommends that such an emotiveness-oriented communication approach should be carefully studied and factored into libraries' knowledge services practice.

Construction of a domain knowledge service system based on the STKOS

Purpose: The study was carried out to construct a domain knowledge service system based on the Scientific & Technological Knowledge Organization Systems(STKOS). Design/methodology/approach: The framework of a domain knowledge service system is designed on the basis of the STKOS, and the STKOS science and technology vocabularies, category systems, and ontology networks are applied to realize the knowledge organization and semantic linking of the scientific and technological information resources. Meanwhile, related knowledge-mining analysis algorithms and models are improved, and some tools such as Solr and D3 are used for developing the system. This system integrates various knowledge service modules, including unified search of domain information resources and knowledge-linked navigation, domain hotspot and burst topics monitoring analysis, knowledge structure and evolution analysis, literature citation network, and research agents’ cooperative relationship network analysis. Findings: The system can help to refine descriptions, knowledge organization, and the semantic linking of various kinds of information resources closely related to science and technology. Such resources include domain literature, institutions, scientists, projects, and more. Research limitations: Trial assessment and performance improvement should be carried out for the knowledge service application on the basis of more types of and larger quantities of domain information resources.Practical implications: The domain knowledge service system provides an integrated knowledge discovery tool, as well as several kinds of knowledge mining analysis services for researchers.Originality/value: Our practice can be used as a valuable guide for libraries and information institutions that plan to provide deep domain knowledge services.

To design and construct an embedded knowledge integration service platform:Taking ISCAS subject group platform as an example

Purpose:As scientific resources are widely distributed,researchers often have difficulties in acquiring information from different individual sources.This paper intends to present a new approach to construct a subject-knowledge-based integration platform which was carried out by the Institute of Software,Chinese Academy of Sciences(ISCAS).Our aim is to use technique tools to strengthen the library service by combining a variety of information service resources with knowledge tools.Design/methodology/approach:Based on the analysis of users’ needs,we established a collaborative team across ISCAS Library,National Science Library of CAS(NSL CAS),and ISCAS’ research groups or research labs.With the service tools developed by ISCAS Library,we embedded other multipurpose utility tools of knowledge integration into the platform as to make full use of software tools in knowledge integration,knowledge fusion,and intelligent push of library services to end users.Findings:With a hard effort of the construction team,the ISCAS subject group platform(hereinafter as ISCAS Platform) has integrated such information resources as institutional repository(IR) of ISCAS,open resources from websites and subject resources of computer sciences.Up to date,ISCAS platform can provide integrated information services including data collection for computer science and intelligent generation of citation reports,by means of embedding self-developed discovering tools for domain experts and subject content,and generation tools for scientific citation reports.Research limitations:Knowledge organization need be further improved in the ISCAS subject group platform.In addition,functions for academic exchanges need be maximized as to meet the individual demands of researchers for library services at the Platform.Practical implications:Since we Platform has been put into use through the Library website of the ISCAS in June 2012,many academic libraries from both domestic universities and CAS institutes have showed their strong interest for our self-developed tools,among which more than 10 cooperation partnerships have been formed.Originality/value:Through self-developed service tools and the integration of multiple-type resources,our Platform has solved such key problems as timely access and update of the trusted resources from a third party,and the rapid fusion and extension of library resources while establishing subject knowledge environment.So the ISCAS library can provide a flexible customization of library services according to the need of different users.

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.

A new service model of document and information sharing among consortium members: The collaborative innovation practice of the NSLC and PASs

Purpose： This paper documents an exploration of an innovative approach to the sharing of documents and information among the members of the National Alliance of Academies of Sciences （NAAS） in China, based on the practice initiated by the National Science Library of the Chinese Academy of Sciences （NSLC）.Design/methodology/approach： Through interviews and user surveys, we analyzed the general information demands of users from provincial academies of sciences （PASs） and problems of their document and information service teams. Based on our findings, we designed targeted services to help Alliance members support their document resources, information services for science and technology （S＆T） decisions, and their knowledge transfer achievements. Furthermore, we offered training courses for provincial service teams, researchers, and administrators, to improve their information skills. These activities represent a new collaborative model for professional library consortia.Findings： To date, our service has been extended to all Alliance members, covering 19 provinces in China, and the NSLC service covers all aspects of knowledge services of Alliance members, from basic document delivery services to subject information analyses.Research limitations： Different PASs have different understandings of the role of the document and information services in the process of scientific research. These differences limit information service sharing of the NSLC with the PASs, and affect the service performance. For the sake of convenience, the original survey was conducted in only three provinces, which may not fully reflect the information needs of users in each Alliance institution. In addition, quantitative and qualitative analyses have been limited by the coverage of the sample.Practical implications： Document and information sharing has not only taken advantage of the NSLC knowledge service system and cooperation model, it has also enhanced the range of services of the NAAS in China.Originality/value： Based on knowledge service enhancements, the NAAS in China has formed a new kind of library consortium, which has broken the traditional library alliance model that was based mainly on the sharing of resources and services.

Crossing the Growth Threshold： Service-Based Economy, Knowledge Process and Reshaping of Efficiency Model

The transition from middle-income to high-income stage is fraught with risks of growth divergence. Economic transition is clouded by the following possibilities： （1）falling share of industrial seetor through industrial depression and weakening growth momentum caused by the large urbanization costs; （2） the subordination of service sector as a result of nearly irreversibly industrial professional, which falters the process of service sector transition and upgrading,＂ （3） inefficient knowledge production allocation and human capital upgrade due to the absence of incentivized compensation of knowledge consumption. We suggest that a country should reshape its efficiency model by upgrading knowledge factor and human capital as the pre-requisite. Given the dilemmas of transition, China should take the faetorization trend of service sector and reshape efficiency model through institutional reform, ensuring that service sector will develop in tandem with industrial sector.

Knowledge-Based Systems for the Assessment and Management of Bridge Structures: A Review

It is becoming an important social problem to make maintenance and rehabilitation of existing infrastructures such as bridges, buildings, etc. in the world. The kernel of such structure management is to develop a method of safety assessment on items which include remaining life and load carrying capacity. The purpose of this paper is to summarize the finding of up-to-date research articles concerning the application of knowledge-based systems to assessment and management of structures and to illustrate the potential of such systems in the structural engineering. In here, knowledge-based systems include knowledge-based expert systems incorporation with artificial neural networks, fuzzy reasoning and genetic or immune algorithms. Specifically, two modern bridge management systems (BMS’s) are presented in the paper. The first is a BMS to assess the performance and derive optimal strategies for inspection and maintenance of concrete bridge structures using reliability based and knowledge-based systems. The second is the concrete bridge rating expert system (J-BMS BREX) to evaluate the performance of existing bridges by incorporating with artificial neural networks and fuzzy reasoning.