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.

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.

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.

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.

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.

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.

Knowledge expression and reasoning process in an expert system for welding procedure qualification

After analyzing the welding procedure knowledge in Chinese national standards for welding procedure qualification of steel pressure vessel from the point of establishing expert system, it can be divided into five types of knowledge, i. e. practice, definition, regularity, process and description knowledge. The knowledge expression methods are established according to the different type of welding procedure knowledge. The reasoning process based on rule is adopted. And the reasoning engine is embedded among objects integrated with the knowledge base.

What Do Educators Need to Teach for Prospective Knowledge Engineers?

As expert systems technology has matured and migrated into mainstream computing, there arestill areas which are overlooked in education prospective knowledge engineers. This paper addresses this issue, and provides a message to educators that expert and knowledge-based systems should be an importantstrategic science and technology for many organizations.

Application of Pruning Algorithm on Voice Service Platform of Cow Disease Diagnosis Expert System

Expert System （ES） is considered effective and efficient in agricultural production, as agricultural informationization becomes a main trend in agricultural development. ES, however, is applied unsatisfactorily in most rural areas of China and it has considerably affected and restricted the development of the agricultural informationization. This paper proposed a solution to voice service system of ES, which was suitable for the information transmission, and it especially could help the peasants in remote regions obtain knowledge from ES through the voice service system. As for the disadvantages of massive knowledge data and slow deduction, in this system the classification method could be adopted based on the decision tree. Designing pruning algorithm to ＂trim off＂ the unrelated knowledge to the users in query course would simplify the structure of the decision tree and accelerate the speed of deduction before the inference engine deduced the knowledge required by users.

Formalized Description of Distributed Denial of Service Attack

The distributed denial of service (DDoS) attack is one of the dangers in intrusion modes. It's difficult to defense and can cause serious damage to the system. Based on a careful study of the attack principles and characteristics, an object-oriented formalized description is presented, which contains a three-level framework and offers full specifications of all kinds of DDoS modes and their features and the relations between one another. Its greatest merit lies in that it contributes to analyzing, checking and judging DDoS. Now this formalized description has been used in a special IDS and it works very effectively.(

Ontology Based Ocean Knowledge Representation for Semantic Information Retrieval

The drastic growth of coastal observation sensors results in copious data that provide weather information.The intricacies in sensor-generated big data are heterogeneity and interpretation,driving high-end Information Retrieval(IR)systems.The Semantic Web(SW)can solve this issue by integrating data into a single platform for information exchange and knowledge retrieval.This paper focuses on exploiting the SWbase systemto provide interoperability through ontologies by combining the data concepts with ontology classes.This paper presents a 4-phase weather data model:data processing,ontology creation,SW processing,and query engine.The developed Oceanographic Weather Ontology helps to enhance data analysis,discovery,IR,and decision making.In addition to that,it also evaluates the developed ontology with other state-of-the-art ontologies.The proposed ontology’s quality has improved by 39.28%in terms of completeness,and structural complexity has decreased by 45.29%,11%and 37.7%in Precision and Accuracy.Indian Meteorological Satellite INSAT-3D’s ocean data is a typical example of testing the proposed model.The experimental result shows the effectiveness of the proposed data model and its advantages in machine understanding and IR.

Discussion on Subject Knowledge Service Pattern of Agricultural University Libraries

Taking Heilongjiang Bayi Agricultural University as an example, the discipline service practice was explored from the aspects such as free network resources and tool use, subject navigation, subject librarians, information sharing space and information literacy education. The typical cases were provided;the optimization of utilization method of network resources was put forward;the subject theme navigation was developed;and the information sharing space of specific discipline and other working strategies were carried out. The experience and enlightenment of active service for subject construction, priority service for key subjects, subject service by lay and step and seizing of the opportunity of subject service were summarized, which developed ideas and provided reference to the establishment of deep subject services of general libraries of colleges and universities.

Experts' Knowledge Fusion in Model-Based Diagnosis Based on Bayes Networks

In previous researches on a model-based diagnostic system, the components are assumed mutually independent. Howerver , the assumption is not always the case because the information about whether a component is faulty or not usually influences our knowledge about other components. Some experts may draw such a conclusion that 'if component m 1 is faulty, then component m 2 may be faulty too'. How can we use this experts' knowledge to aid the diagnosis? Based on Kohlas's probabilistic assumption-based reasoning method, we use Bayes networks to solve this problem. We calculate the posterior fault probability of the components in the observation state. The result is reasonable and reflects the effectiveness of the experts' knowledge.

Knowledge about Sexual and Reproductive Health Services and Practice of What Is Known among Ghanaian Youth, a Mixed Method Approach

Most young person will become sexually active before their 20th birthday having to battle with early and unplanned pregnancies, unsafe abortions, maternal deaths and injuries. This study examined young person’s sexual knowledge, attitudes and practices and their levels of utilization of sexual reproductive health. Our study progresses beyond current research of reporting only sexual behaviour among youth to have insight into sexual and reproductive health update drivers yielding new empirically robust results for the Ghanaian case for sexual and reproductive health service uptake. The descriptively cross sectional design was employed in sampling 170 youth (150 surveyed and 20 Interviewed) using the stratified sampling technique together with a purposive selection of one key informant. Test of significance and associations were performed with the Chisquare test. In all 45.2% (77/170) of youth (10 - 24) had had sexual experience in life time. In respect of in-school youth, 42% (63/150) had had sexual experience whiles 70% (14/20) out-of-school youth had had sexual intercourse in life time. A total of 28.8% (49/170) of all the youth had sexual intercourse in the last six months with only 40.1 (20/49) using condom for protection. Parental discussion of contraceptive methods (29.3%) and sexual and romantic relationship (28.0%) was the least sexual and reproductive health area discussed among in-school youth. Youth knowledge of the available sexual reproductive health service was statistically associated with reproductive health service utilization (X2 = 0.00, P ≤ 0.05). A concerted effort is required from government, NGO, Civil society organizations and religious bodies to help translate youth knowledge about sexual health into responsible sexual life and protective sex.

Knowledge-intensive Business Services in National Innovation Systems

In order to find the roles of knowledge-intensive business services （KIBS） in the innovation activities, This paper focus on three perspectives. First, we find that KIBS possess good prerequisites to function as vehicles in innovation distribution, the sources of innovation and the facilitators of innovation in their client firms. Second, we further discuss KIBS as the knowledge and innovation infrastructure of society in parallel with the research, educational and other public institutions. Third, we present some research policies and agenda to promote the development of KIBS. It is regarded that much remains to be studied both in the use of KIBS and in their own activities, including integrating and networking the knowledge-intensive services into the client companies, the convergence of various services and closer connection with the client companies＇ strategy, and the national policies to connect the KIBS to the different sectors.