• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.887-890
• /
• 1993

By introducing the notion of constraint-oriented fuzzy inference, we will show that it provides us ways of fuzzy control methods that has abilities of adaptation, learning and self-organization. The basic supporting techniques behind these abilities are“hard”processing by Artificial Intelligence or traditional computational framework and“soft”processing by Neural Network or Genetic Algorithm techniques. The reason that these techniques can be incorporated to fuzzy control systems is that the notion of“constraint”itself has two fundamental properties, that is, the“modularity”property due to its declarativeness and the“logicality”property due to its two-valuedness. From the former property, the modularity property, decomposing and integrating constraints can be done easily and efficiently, which enables us to carry out the above“soft”processing. From the latter property, the logicality property, Qualitative Reasoning and Instance Generalization by Symbolic Reasoning an be carried out, thus enabling the“hard”processing.

• Journal of Information Technology Services
• /
• v.11 no.4
• /
• pp.309-333
• /
• 2012

Recently, emergence of smart-phones and Social Networking Service(SNS) would offer the market environment changes and the opportunities for new business. For the case analysis comprehensive survey were implemented. And those data were analyzed along the research framework. The late-comer firms offered differential services, maintained creative and opened corporate culture, shoed learning capabilities which means absorption and organization of external knowledge, innovative efforts to control the insurgents than early-mover firms. When we analyze these phenomena along the developmental stages of late-comer, we can perceive that the stage of late-comers firms were moving from the "tracing the path" stage to "jumping the path" stage which means the creating capabilities were more or less enhanced and the firms become more stable in terms of business operation. In business model, early-mover firms showed clear definition for each business element, especially the revenue structure, while late-mover firms seemed unstable or unclear revenue structure.

• Asia pacific journal of information systems
• /
• v.16 no.3
• /
• pp.117-142
• /
• 2006

The purposes of this paper are to find out the characteristics of organizational members' cognitive structure for the effective acceptance of a six sigma innovative method in the organization. The author hypothesized the characteristics of individual cognitive structure is one of the most important factors on the acceptance of a six sigma method in the organizations for verifying through literature reviews, in-depth interviews and an analysis of questionnaire. This study is the first trial to corroborate the influence of characteristics of individual cognitive structure on the acceptance of a six sigma method. This can be utilized as an integrated appraisal model for the evaluation of acceptance of a six sigma method. The result not only helps the organizations that a six sigma method was recently introduced, to decrease the trial-and-errors experienced by the preceding groups, but can be used as fundamental data to establish an concrete strategy of a six sigma acceptance.

• International Journal of Computer Science & Network Security
• /
• v.21 no.12
• /
• pp.165-174
• /
• 2021

This study aimed to ascertain whether electronic courses at the deanship of electronic learning and distance education at Umm Al-Qura University meet the quality standards developed by the Quality Matters (QM) organization. This endeavor adopted a mixed method of an explanatory sequential research design for an in-depth understanding of the topic under scrutiny. The sample of the study consisted of ten courses designed at the deanship and reviewed using an evaluation form. The results showed that the courses in focus did not meet the criteria of QM. Based on this finding, a semi-structured interview was designed to collect relevant data from the syllabus designers at the deanship. The interviews yielded information on the difficulties the course designers faced when designing QM-criteria-based courses. The results obtained from the interviews showed that the designers experienced administrative, technical, and faculty-member-related challenges that, when producing online courses, intercepted their way to achieving the QM standards. The study closed with some recommendations, the most important of which is a call for re-developing online courses in alignment with the well-recognized QM standards.

• International Journal of Knowledge Content Development & Technology
• /
• v.8 no.4
• /
• pp.7-18
• /
• 2018

Information Literacy (IL) is considered as an important aspect of everybody's life. In today's information society possessing IL skills is more significant than ever as information is available in many forms and formats. Schools are the primary places where these skills are imbibed in students. Organizations like UNESCO, IFLA, ALA, AASL, & ACRL have formulated IL Standards and Guidelines/Models at the international arena. Though the Government of India is making efforts in providing information literacy skills yet there are no set of standards/guidelines devised by any agency/organization at the school level. This paper gives a brief account of IL initiatives and highlights the trends and developments of IL programmes in Indian School Libraries. It recommends the nation to form a national level advisory committee to develop IL framework for Indian school Libraries. Further, it suggests that librarians should work in close collaboration with teachers for better results. A moderate attempt has been made to provide feasible solutions for effective implementation of IL programmes in school libraries.

• Journal of information and communication convergence engineering
• /
• v.17 no.1
• /
• pp.21-40
• /
• 2019

This paper presents a comprehensive survey of various artificial intelligence (AI) techniques implemented in cognitive radio engine to improve cognition capability in cognitive radio networks (CRNs). AI enables systems to solve problems by emulating human biological processes such as learning, reasoning, decision making, self-adaptation, self-organization, and self-stability. The use of AI techniques is studied in applications related to the major tasks of cognitive radio including spectrum sensing, spectrum sharing, spectrum mobility, and decision making regarding dynamic spectrum access, resource allocation, parameter adaptation, and optimization problem. The aim is to provide a single source as a survey paper to help researchers better understand the various implementations of AI approaches to different cognitive radio designs, as well as to refer interested readers to the recent AI research works done in CRNs.

• Korean Journal of Artificial Intelligence
• /
• v.8 no.2
• /
• pp.7-10
• /
• 2020

In this paper, a study was conducted to find main factorsto Pima Indians Diabetes based on machine learning. Diabetes is a type of metabolic disease such as insufficient secretion of insulin or inability to function normally and is characterized by a high blood glucose concentration. According to a situation report from WHO(World Health Organization), Diabetes is a chronic, metabolic disease characterized by elevated levels of blood glucose (or blood sugar), which leads over time to serious damage to the heart, blood vessels, eyes, kidneys and nerves. And also about 422 million people worldwide have diabetes, the majority living in low-and middle-income countries, and 1.6 million deaths are directly attributed to diabetes each year. Both the number of cases and the prevalence of diabetes have been steadily increasing over the past few decades. Therefore, in this study, we used Support Vector Machine (SVM), Decision Tree, and correlation analysisto discover three important factorsthat predict Pima Indians diabetes with 70% accuracy. Applying the results suggested in this paper, doctors can quickly diagnose potential Pima Indians diabetics and prevent Pima Indians diabetes.

• Genomics & Informatics
• /
• v.19 no.4
• /
• pp.51.1-51.8
• /
• 2021

This study explored the trends of Genomics & Informatics during the period of 2003-2018 in comparison with 11 other scholarly journals: BMC Bioinformatics, Algorithms for Molecular Biology: AMB, BMC Systems Biology, Journal of Computational Biology, Briefings in Bioinformatics, BMC Genomics, Nucleic Acids Research, American Journal of Human Genetics, Oncogenesis, Disease Markers, and Microarrays. In total, 22,423 research articles were reviewed. Content analysis was the main method employed in the current research. The results were interpreted using descriptive analysis, a clustering analysis, word embedding, and deep learning techniques. Trends are discussed for the 12 journals, both individually and collectively. This is an extension of our previous study (PMCID: PMC6808643).

• Electronics and Telecommunications Trends
• /
• v.36 no.2
• /
• pp.56-64
• /
• 2021

Many computer vision algorithms are computationally expensive and require a lot of computing resources. Recently, owing to machine learning technology and high-performance embedded systems, vision processing applications, such as object detection, face recognition, and visual inspection, are widely used. However, on-devices need to use their resources to handle powerful vision works with low power consumption in heterogeneous environments. Consequently, global manufacturers are trying to lock many developers into their ecosystem, providing integrated low-power chips and dedicated vision libraries. Khronos Group-an international standard organization-has released the OpenVX standard for high-performance/low-power vision processing in heterogeneous on-device systems. This paper describes vision libraries for the embedded systems and presents the OpenVX standard along with related trends for on-device vision system.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2020.11a
• /
• pp.680-684
• /
• 2020

최근 국내에서는 식품에 대한 관심도가 높아짐에 따라 먹거리에 건강·환경·미래지향적 가치가 부여되고 있으며 식품 산업에서도 신규 식품 개발이 증가하는 추세이다. 식단을 구성할 때 기준이 되는 식품교환표는 개정과정에서 많은 인력과 시간이 소요되기 때문에 식품 섭취 변화를 신속하게 반영하기 어렵다. 본 논문에서는 식품교환표의 활용도를 높이기 위한 식품교환표 갱신 기법을 제안한다. 제안 기법은 의사결정트리 모델을 학습하여 새롭게 추가된 식품의 정보를 바탕으로 식품군을 분류하여 식품교환표를 갱신한다. 이는 영양 관리가 필요한 당뇨병 환자 등에게 실용적이며 기호성·다양성이 높은 식단을 구성하는 데 도움을 준다.