Knowledge-based Information System Research Articles

A study on the knowledge-based information system for evacuation situation awareness in the case of fire

This study is on designing a knowledge-based information system for evacuation situation awareness in case of fire. First, in the design of this system, various progress of urban fires was stored and learned in the database so that multiple fire situations could be recognized. In addition, it is to be actively applied to fire disaster prevention through the knowledge-based Fire Dynamics Simulator information system so that it can be actively used for situational information of evacuees and property protection. Moreover, this system is designed to reduce damage to human life and property in the event of a fire in a building, etc. For this purpose, fire extinguishment can be predicted based on building information such as structure and building materials. Natural disasters leading to significant fires can be prevented by predicting fire evolution between buildings. Damage to human life and property due to fire can be contained. This system is a knowledge-based information system that optimizes ubiquitous technologies. It can respond to minimize damage by periodically recognizing the situation of evacuees in case of fire and notifying the central control center of the problem.

DEVELOPMENT OF THE STRUCTURE OF AN AUTOMATED SYSTEM FOR DIAGNOSING DISEASES

Today, the importance of information support for various medical technologies has increased significantly. The use of modern information technologies is becoming a critical factor in the development of most branches of knowledge and areas of practice, so the development and implementation of information systems is an urgent task. The clinical decision support system provides clinicians and stakeholders with individualized patient assessments and recommendations to assist in the clinical decision-making process.
 Knowledge-based information systems are widely used in medicine around the world. Modern technical capabilities make it possible to reach a qualitatively new level of presentation of the course of the disease, namely, based on appropriate mathematical models, to model the typical development of the pathological process in a particular disease, to speed up the process of diagnosing and receiving recommendations on treatment protocols.
 In Kazakhstan, there is no variety of decision support systems in medicine, especially in the process of diagnosing diseases. The purpose of this study is to develop the structure of an automated system for diagnosing diseases. The Unified Modeling Language (UML) is used as a design tool. The structure of the automated system is presented; the main components and key terms are considered. A mathematical model of diagnostics is shown (in the example of diseases of intestinal and pancreatic insufficiency) based on decision-making methods with fuzzy initial data. A diagram of the data flows of the system is presented. Thus, the paper proposes the structure of an automated system that will contribute to high-quality diagnostics due to an effective method of system organization and the use of fuzzy set theory methods.

Learning Disease Causality Knowledge From the Web of Health Data

Health information becomes importantly valuable for protecting public health in the current coronavirus situation. Knowledge-based information systems can play a crucial role in helping individuals to practice risk assessment and remote diagnosis. We introduce a novel approach that will develop causality-focused knowledge learning in a robust and transparent manner. Then, the machine gains the causality and probability knowledge for inference (thinking) and accurate prediction later. Besides, the hidden knowledge can be discovered beyond the existing understanding of the diseases. The whole approach is built on a Causal Probability Description Logic Framework that combines Natural Language Processing (NLP), Causality Analysis and extended Knowledge Graph (KG) technologies together. The experimental work has processed 801 diseases in total (from the UK NHS website linking with DBpedia datasets). As a result, the machine learnt comprehensive health causal knowledge and relations among the diseases, symptoms, and other facts efficiently.

Knowledge Based Decision Support System in Steel Industries

Knowledge-based information system (KBIS) is a structure which is based on understanding, which develops approaches to aid people in decision-making and to gain knowledge of best business practices. Anticipations from these approaches are to converse with human beings but the essence and manner of aid given are important issues. DSS i.e Decision Support Systems is a peculiar kind of information system that eases the growth of product designs of viable quality, functional practices and business decision-making. Developing and executing a decision support program for a steel plant is an asking job. Various business functional fields like production and supply chain, product planning, marketing, and finance, which is required to take several censorious decisions. A KBIS clubbed with DSS will be very useful tool for steel industries in decision making. A detailed discussion on the structure of KBIS and DSS is carried out in this paper. A significant portion of this article is dedicated to the execution of KBDSS i.e knowledge based decision support system in steel industries. The article summarizes with the advantages and shortcomings of KBDSS execution.

Knowledge based information system for detecting early eye diseases

The eyes are very important senses in human life. If the eyes experience interference, it will be fatal to human life. Although each type of eye disease has its own specific characteristics and symptoms, early detection with a deeper recognition of eye disease symptoms should be done. Knowledge-based information systems are systems that attempt to convert human knowledge into computers so that computers can solve problems as is usually done by experts. produce conclusions or goals. The aim of this study is to design applications for early detection of fourteen types of eye diseases. This detection uses a knowledge-based system that uses the Forward Chaining method. This study produced an output in the form of the possibility of the disease the user suffered based on fifty-three selected symptoms. This system indicates how much confidence the user has in the symptoms of possible eye diseases.

Big Data Guided Unconventional Digital Reservoir Energy Ecosystem and its Knowledge Management

Abstract Background: In shale basins, petroleum systems are complex; they hold data sources in Big Data scales. The motivation of research lies with the facts of exploring effective inherent connectivity between unconventional petroleum systems. The connectivity between energy reservoir systems is ambiguous within a distinctive petroleum ecosystem. Heterogeneity and multidimensionality of unstructured data sources are additional challenges, precluding systematic modelling of diverse petroleum systems and their data integration process, including growing demand for storage systems. The research aims to establish the knowledge-based connectivity between petroleum systems through Information System (IS) articulations, visual analytics and data management. Method: We investigate the knowledge-based IS guided exploration and production systems to explore the connectivity between diverse unconventional petroleum systems and forecast the reservoir energy. We articulate Design Science Information System (DSIS), bring various IS artefacts, unify multiple domains of petroleum provinces and analyze the associativity between petroleum systems. In addition, use, reuse, effectiveness and interoperability are utility properties of IS artefacts that we evaluate. We implement IS solutions in the oil and gas industries to facilitate database management and reservoir energy exploration. Results: We simulate DSIS as an Unconventional Digital Petroleum Ecosystem (UDPE) as it allows us to investigate and ascertain the interplay between petroleum systems’ elements and processes. Metadata cubes are computed for data views to visualize, interpret, and implement IS articulations in energy systems. We compute the structure and reservoir attribute views for interpreting energy-driven petroleum systems, prospect evaluation and business-knowledge management with a viable DSIS solution. Conclusions: The DSIS emerges as a knowledge-based digital ecosystem innovation, demonstrating how it can effectively interconnect geographically controlled petroleum systems. Its development, in the exploration of unconventional shale basins, is a knowledge-based reservoir-energy management solution. This research is beneficial to IS practitioners who wish to pursue energy research in reservoir ecosystem contexts.

Utilizing the New Technologies For Enhancing Healthcare Tourism in Egypt

This paper recognizes and identifies various new advances technologies and applications in Information Communication Technologies that gradually revolutionize the tourism industry and related business and industries. The Tourism business sector is the most aggressive and competitive business in the worldwide and one of the most complicated business sectors .The tourism industry primarily consists of businesses that provide accommodation, transformation, flight trips, attractions, food and beverage, and integrated combination of these activities. This research is focused on using the new technologies to develop healthcare tourism in Egypt by increasing the tourist awareness of healthcare tourism. This aim is achieved by using new technologies such as Big Data Analytic Technology and knowledge-based information system in order to forecast tourist’s demands, needs and requests in tourism industry sector. Any data concerning the future development of tourism flows is of extraordinary significance to hoteliers, travel agents and other industries related with tourism business. Precise prediction of traveler services needs will be coordinated for the business' activities and allotment of assets, for example, labor, money related administration, advertising the executives… and so on to accomplish adequacy of arrangement ahead of time and cost decrease. Showing that the Internet and sharp technological development have encouraged the increasing demand for tourism and using new technologies in forecasting the tourist demands and needs will naturally promote or potentiate an increase of tourism demand.

A Pragmatic Prototype to Enhance The Quality Pre-University Level Skills Towards Further Development of Human and Knowledge Attributes in the Region

The research based on knowledge-based information system, follows a pragmatic study of pre-university level educational learning outcomes and the skills gained by the students, to further assess and compare it with the required knowledge and skills needed at the entry gate of the university level education. It will identify the gaps between the two, consecutively synchronizing the attained efforts to further enhance the delivery of quality pre-university level education as desired, focused towards the core of human and knowledge development to sustain and further enhance country’s fiscal and structural growth over time. The research is needed to address the fact that most of the students received at the entrance gate of university level education, lack necessary basic knowledge and skills. If these deficient knowledge and skills are incorporated it could help develop their performance at the level of further higher education. The attainment of those deficient skills would also help boost the student’s ability and capability at the level of higher education, thereby contributing towards nation’s human and knowledge development across various sectors. Diverse factors that negatively affect the students and their performance during their higher education at the university level education are categorized and identified. In order to effectively address these factors, we propose a knowledge management system to efficiently scrutinize the core areas necessary to fill in the breach by incorporating appropriate attributes which would thereby contribute towards the country’s economic and structural growth. The outcomes and the end results of the research enforces a methodology to reform the structure of higher educational systems and consecutively the lower level educational systems to be sequentially aligned to the expectations and benchmarks of industry standards, through a top-down approach.

Knowledge Based Information System to Manage Transfer of Credits in An Outcome Based Higher Educational Setting

While shifting from one outcome based educational system to another one, a student needs to gain the benefit of credits transfer for all or most of his/her attained credits, followed by the policy and procedure of the granting institutions. Transfer of attained credits for a relocating student is quite normal and obvious in an outcome based higher educational system. With equal importance to transfer of credits, it is also vital to confirm that the knowledge and competency gained by the student does map the core skills needed for further progress in his/her education, in the receiving institution. In context to the field of Computer Science or Information Technology or any other related technical area, where programming languages and software platforms are imperative, the normal method of credits transfer could be a critical concern. On one hand, while the receiving institutions provide the transfer of credits for all or most of the courses successfully completed by a student, it is also a major concern whether the student occupies the core knowledge, competencies and skills needed to proceed with higher level courses, specific to software platforms or other specific requirements, in the receiving institution. This is because different institutions provide different curriculum for a similar program and thus, though the concepts may remain in general, the core software platforms or course related specific requirements may differ. In this case, with varying platforms from institution to institution, if a student is being received with transfer of credits but with lack of relevant knowledge, competencies and skills, he/she would face a critical challenge to cope up with the higher-level course, to succeed in the program. The competition within the institution may not allow the student to progress smoothly and could develop a sense of criticality or failure. With much needed effective solution to this problem, in our research, we have discussed the backdrops of normally executed credits transfer, addressed its complications as well repercussions and proposed a knowledge-based information system that would effectively tackle this problem. The outcome of the conducted research proposes to create a prototype of an information system tool to be identified as Knowledge Management Credit Transfer System in order to manage an efficient credits transfer process.

Wisdom extraction in knowledge-based information systems

PurposeThis paper aims to provide a number of distinct approaches towards this goal, i.e. to translate the information contained in the repositories into knowledge. For centuries, humans have gathered and generated data to study the different phenomena around them. Consequently, there are a variety of information repositories available in many different fields of study. However, the ability to access, integrate and properly interpret the relevant data sets in these repositories has mainly been limited by their ever expanding volumes. The goal of translating the available data to knowledge, eventually leading to wisdom, requires an understanding of the relations, ordering and associations among the data sets.Design/methodology/approachWhile the existing information repositories are rich in content, there are no easy means of understanding the relevance or influence of the different facts contained therein. Therefore, the interest of the general populace in terms of prioritizing some data items (or facts) over others is usually lost. In this paper, the goal is to provide approaches for transforming the available facts in the information repositories to wisdom. The authors target the lack of order in the facts presented in the repositories to create a hierarchical distribution based on the common understanding, expectations, opinions and judgments of the different users.FindingsThe authors present multiple approaches to extract and order the facts related to each concept, using both automatic and semi-automatic methods. The experiments show that the results of these approaches are similar and very close to the instinctive ordering of facts by users.Originality/valueThe authors believe that the work presented in this paper, with some additions, can be a feasible step to convert the available knowledge to wisdom and a step towards the future of online information systems.

Preface

Special Issue : Advances in Knowledge-Based and Intelligent Engineering and Information Systems Preface

Feature-based product modelling: an ontological approach

ABSTRACTFeature-based modelling is the leading approach for computer-based product design. The development of knowledge-based information systems brought to represent features in formalised ontologies. The lack of a clear ontological analysis of how features are understood in engineering led to formal models that treat features in an ambiguous manner, or reduce them to pure geometric elements. The purpose of the paper is to present a modular ontological architecture to support the explicit and machine treatment of features’ semantic. Differently from the state of art, we provide a general framework where features are contextualised within a larger system for product knowledge representation. We focus on the fundamental (ontological) properties that features satisfy independently from specific applications and contexts of usage. The paper presents modelling case studies where the proposed ontologies are used to represent and (automatically) reason over product knowledge, and to analyse, compare, and integrate existing features classifications.

Using Information Technology for Enhancing Sustainable Tourism in Egypt

This paper identifies a number of new technologies and applications in Information Communication Technologies that gradually revolutionize the tourism industry. Tourism industry is the most competitive business in the world and one of the most complicated industries. The tourism industry primarily consists of businesses that provide accommodation, transformation, flight trips, attractions, food and beverage, and integrated combination of these activities. This research is focused on using the new technologies to develop sustainable tourism in Egypt by increasing the tourist awareness of sustainability and sustainable tourism. This aim is achieved by using new technologies such as Big Data Analytic Technology and knowledge-based information system in order to forecast tourist’s needs and demands in tourism industry. Any information concerning the future evolution of tourism flows is of great importance to hoteliers, tour operators and other industries concerned with tourism. Accurate forecasting of tourist services needs will be integrated for the industry’s operations and allocation of resources such as manpower, financial management, marketing management… etc. to achieve effectiveness of advance planning and cost reduction. Showing that the Internet and sharp technological development have encouraged the increasing demand for tourism and using new technologies in forecasting the tourist demands and needs will naturally promote or potentiate an increase of tourism demand. Keywords: Information and Communication Technologies, ANNs, big data analytics, Tourist’s Demands and needs.

Systematic Design of Expert System Using Unified Modelling Language

An expert system as an expert knowledge-based information system has been widely used by interested parties to consult their problems. Therefore, an expert system should be well designed so as to meet the requirements for a software to store knowledge, explain problems, and recommend solutions. The purpose of the present study is to develop a systematic design of an expert system using Unified Modeling Language (UML), which is one of popular object-oriented modeling languages. The research method was a literature review as the main source for analyzing the expert system requirements. The developed design was then clarified, verified, and validated in a Focus Group Discussion (FGD). To evaluate the model, a review of some related studies was conducted. The research respondents were informatics lecturers at UIN Sunan Gunung Djati Bandung. The results of the study revealed that the systematic design of expert system was well-developed because it was user-friendly, flexible, easy to be modified, and able to propose solutions for various problems.

Membership function model for defining optimality of vapor pressure deficit in closed-field cultivation of tomato

Estimation of plant’s evapotranspiration (ET) or water loss to the atmosphere depends on the vapor pressure deficit (VPD) of the closed-field environment (greenhouse). The objective of this work was to develop a membership function model for defining optimal VPD of greenhouse air for tomato cultivation (Lycopersicon esculentum) at different growth stages (GS) and light conditions (sun, cloud, night). Mathematical descriptions of a peer-reviewed published growth response (GR) model for optimal greenhouse air temperature (T) and relative humidity (rH) were derived and implemented in a computer program. An incremental algorithm was written in MATLAB© based on definitive concepts in VPD equations and the GR model. Non-linear regression was applied to describe mathematical relationship between the incremented outputs of the model and the calculated VPD values (R2=0.999 to 1). Results were validated with three published literatures and were shown to be capable of exploring optimal levels of VPD by means of real numbers between 0 and 1. This study can contribute to knowledge-based information and decision support systems in greenhouse climate control and management by quantifying comfort level of microclimate.

Software System for Dynamic Athlete Health Monitoring

Workload increase in sport that leads to a greater stress level, both physical and psychoemotional, reflects on health indicators. Therefore, the early multi-component diagnostics and the establishment of prevention and treatment programmes that is based on dynamic analysis of current and previous information on health and abnormalities play a significant role in sport. The development of an intelligent knowledge-based information system is highly relevant. Such a system should include an electronic passport of sportsmen health and the database concerning the health of sportsmen that will provide an increase in efficiency of children, junior, mass, and professional sports in Russian Federation. Based on the authors’ experience of building similar types of systems, core requirements to this system, its structure and functional requirements are formed. A structure of the electronic passport of sportsman health, guidelines for maintenance and usage are suggested.

The Effect of Perceived Factors of Decision Support Systems on Actual Usage: Behavioral Intention of Using Decision Support Systems as a Mediating Variable: “An Empirical Study of Jordanian Higher Education Institutions”

Decision support systems (DSS) are interactive computer-based systems that provide information, modeling, and manipulation of data. DSS are clearly knowledge-based information systems to capture, Processing and analysis of information affecting or aims to influence the decision making process, performed by people in scope professional job appointed by a user. Hence, this study describes briefly the key concepts of decision support systems such as perceived factors with a focus on quality of information systems and quality of information variables, behavioral intention of using DSS, and actual DSS use by adopting and extending the technology acceptance model (TAM) of Davis (1989); and Davis, Bagozzi and Warshaw (1989).There are two main goals, which stimulate the study. The first goal is to combine Perceived DSS factors and behavioral intention to use DSS from both the social perspective and a technology perspective with regard to actual DSS usage, and an experimental test of relations provide strategic locations to organizations and providing indicators that should help them manage their DSS effectiveness. Managers face the dilemma in choosing and focusing on most important factors which contributing to the positive behavioral intention of use DSS by the decision makers, which, in turn, could contribute positively in the actual DSS usage by them and other users to effectively solve organizational problems. Hence, this study presents a model which should provide the useful tool for top management in the higher education institutions- in particular-to understand the factors that determine using behaviors for designing proactive interventions and to motivate the acceptance of TAM in order to use the DSS in a way that contributes to the higher education decision-making plan and IT policy.To accomplish or attain the above mentioned objectives, the researcher developed a research instrument (questionnaire) and distributed it amongst the higher education institutions in Jordan to collect data in order to empirically study hypothesis testing (related to the objectives of study). 341 questionnaires were returned from the study respondents. Data were analyzed by utilizing both SPSS (conducted descriptive analysis) and AMOS (conducting structural equation modelling).Findings of the study indicate that some hypotheses were supported while the others were not. Contributions of the study were presented. In addition, the researcher presented some recommendations. Finally, this study has identified opportunities for further study which has progressed greatly advanced understanding constantly of DSS usage, that can help formulate powerful strategies Involving differentiation between DSS perceived factors.

The Relationship between Knowledge-Based Information System Management and Creativity As well As Organizational Learning (Case Study: West Azerbaijan Province Salamat Insurance Administration)

The Relationship between Knowledge-Based Information System Management and Creativity As well As Organizational Learning (Case Study: West Azerbaijan Province Salamat Insurance Administration)

Implementation of a User-Oriented Model for Collaborative Product Development: An Example from The Medical Equipment Industry

In this study, we summarize the requirements for collaborative product development based on our investigation of the differences in the resources and tools that are needed for the various stages of collaborative product development and the needs of system users during these various stages. We developed a user-oriented model of collaborative product development for medical equipment and designed an interface module with the required functionalities to satisfy different areas according to their roles and workflow. In medical-equipment development, the issues related to marketing, design, and manufacturing must be considered; more importantly, the relevant regulatory needs must be thoroughly understood. Therefore, based on the unique features of the medical-equipment industry and the requirements for product development therein, we implemented a development system for collaborative product development in the intelligent medical-equipment industry, including a calendar function module, an announcements module, a knowledge-based information system, a project management system, a project operation and maintenance system, a file management system, an accessibility system, and a clinical test system. In addition, the results obtained with this system were verified with the following three possible cases: project operation and maintenance, clinical trial application, and medical equipment testing. The platform we developed can drastically simplify the original complex and dispersed process of product development for intelligent medical equipment, thereby allowing the project team to develop new medical-equipment products and promote interactions among the research and development staff, clinical specialists, and the test participants successfully, thereby resulting in a user-oriented collaborative product development process.

CPE: Novel method to shorten the lead time for laser micro-machining

Abstract Conceptual profit engines method is a novel design approach to shorten preparation and manufacturing times from the perspective of enterprise objectives. It illustrates conceptual steps of design operation for knowledge-based laser micro-machining information system and provides new insights into decision-making systems with reducing human interaction. This method facilitated laser micro-machining by setting unknown parameters, and it reduced the process time to 47 % with actively reducing operations preventing complex decisions.