• Journal of the Korea Safety Management & Science
• /
• v.2 no.2
• /
• pp.1-10
• /
• 2000

This study deals with the application of knowledge engineering and a methodology for the assessment and measurement of reliability, availability, maintainability, and safety of industrial systems using fault-tree representation. A fuzzy methodology for fault-tree evaluation seems to be an alternative solution to overcome the drawbacks of the conventional approach (insufficient information concerning the relative frequence of hazard events). To improve the quality of results, the membership functions must be approximated based on heuristic considerations. The purpose of this study is to describe the knowledge engineering approach, directed to integrate the various sources of knowledge involved in a FTA.

• Smart Media Journal
• /
• v.12 no.9
• /
• pp.89-94
• /
• 2023

Recommender systems provide users with the most favorable items by analyzing explicit or implicit feedback of users on items. Recently, as the size of deep-learning-based models employed in recommender systems has increased, many studies have focused on reducing inference time while maintaining high recommendation accuracy. As one of them, a study on recommender systems with a knowledge distillation (KD) technique is actively conducted. By KD, a small-sized model (i.e., student) is trained through knowledge extracted from a large-sized model (i.e., teacher), and then the trained student is used as a recommendation model. Existing studies on KD for recommender systems have been mainly performed only for implicit feedback settings. Thus, in this paper, we try to investigate the performance and accuracy when applied to explicit feedback settings. To this end, we leveraged a total of five state-of-the-art KD methods and three real-world datasets for recommender systems.

• Journal of the Korean Data and Information Science Society
• /
• v.10 no.2
• /
• pp.359-367
• /
• 1999

We investigate a logical approach to represent medical knowledge, reason deductively and diagnostically. It is suggested that medical knowledge-bases can be formulated as a set of sentences stated in classical logic where each sentence reflects a doctor's knowledge about the human anatomy or his/her view of patient's symptoms. It is also suggested that a form of temporal reasoning can be captured within the same framework because each sentence can have a different truth value based on time. We apply our logical framework to formalize diagnostic reasoning, where the primary cause of illness is chosen among the set of minimal causation on the basis of abductive hypotheses. Most of our examples are given in the context of medical expert systems.

• Journal of Korea Multimedia Society
• /
• v.25 no.7
• /
• pp.895-902
• /
• 2022

Building segmentation using satellite imagery such as EO (Electro-Optical) and SAR (Synthetic-Aperture Radar) images are widely used due to their various uses. EO images have the advantage of having color information, and they are noise-free. In contrast, SAR images can identify the physical characteristics and geometrical information that the EO image cannot capture. This paper proposes a learning framework for efficient building segmentation that consists of a teacher-student-based privileged knowledge distillation and deformable convolution block. The teacher network utilizes EO and SAR images simultaneously to produce richer features and provide them to the student network, while the student network only uses EO images. To do this, we present objective functions that consist of Kullback-Leibler divergence loss and knowledge distillation loss. Furthermore, we introduce deformable convolution to avoid pixel-level noise and efficiently capture hard samples such as small and thin buildings at the global level. Experimental result shows that our method outperforms other methods and efficiently captures complex samples such as a small or narrow building. Moreover, Since our method can be applied to various methods.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2490-2495
• /
• 2005

The scheduling of plant should be determined based on the product demands correctly forecasted by reasonable methods. However, because most existing forecasting packages need user's knowledge about forecasting, it has been hard for plant engineers without forecasting knowledge to apply forecasted demands to scheduling. Therefore, a forecasting module has been developed for plant engineers without forecasting knowledge. In this study, for the development of the forecasting module, an automatic method using the ARIMA model that is framed from the modified Box-Jenkins process is proposed. And a new method for safety inventory determination is proposed to reduce the penalty cost by forecasting errors. Finally, using the two proposed methods, the web-based automatic module has been developed.

• Journal of Korean Society of Rural Planning
• /
• v.17 no.1
• /
• pp.89-98
• /
• 2011

Recently, the food industry has evolved into a new and innovative trend according to its globalization and change of food consumption patterns. However, it is hard for the traditional food industry in Korea to meet the changing consumers' needs because of its poorer quality control and lower industrialization technology than other advanced industries. Also the knowledges acquired through a lot of time and efforts would be lost after the human resources with tacit knowledges leave by their too much aging. Especially, the 21st century would be called as knowledge based society which means that knowledge be the important contributing factor in the economic growth. In this regard, this study aimed at proposing the knowledge based system for systematically managing or preserving knowledges of Mosisongpyun industry in Yeonggwang County to seek for the sustainable development of the traditional food industry in Korea. The knowledge based system of Mosisongpyun industry in Yeonggwang County is finally proposed as follows; First, hardware is composed with the necessary unit facilities such as interpretive center, learning and experience room, library, etc. And the integrating facilities such as Mosisongpyun theme park, traditional village, and knowledge industrialization support center are proposed. Second, software is composed with the necessary unit softwares such as the preservation manual of traditional knowledge and skill, web-site administrator, development of graded textbooks, development database software, etc. And the integrating softwares such as development of innovation and management ability in Mosisongpyun industry are proposed. Third, humanware is composed with the necessary unit programs such as exhibition, own training program, incubator support system, etc. And the integrating programs such as the farm association corporation, the testing and research institute, the institution of learning and training are proposed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.12a
• /
• pp.208-212
• /
• 2001

This paper is for the optimized management of the knowledge abstracted from the World-Wide Web(WWW) in which we assume the infinite knowledge-base. Though we can abstract various useful knowledge such as the facts and the rules from the WWW pages, they may include many noisy knowledge. Therefore we have to reasonably reject them from the knowledge-base which is composed of knowledge abstracted from the WWW. To do this, we propose the oblivious memorization concept. This concept is characterized by the memorization based on the oblivion mechanism of human being. We assume the memorization is the function of the concern for any knowledge, oblivion ability and time. That is, the more concern for my knowledge the ore memorizable. And, the more oblivious and the more tine spent the less memorizable by exponentially. Where, tie assume the oblivion is the function of the degree of previous memorization, memorization ability md the number of knowledge stimulation. That is, the more previously memorized, the greater memorizing ability and the more frequently stimulated by any knowledge the less knowledge oblivious.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.2
• /
• pp.171-177
• /
• 2004

In this paper, we propose a cognition-based navigational algorithm for mobile robots in dynamic environments. The proposed algorithm consists of two main stages: (i) the fuzzy logic-based perception stage that constructs knowledge from the sensory data for subsequent usage in reasoning, and (ii) the planning stage that identifies the path between a starting and a goal position within its environment on the basis of the knowledge base on the environment and information from the perception stage. A mobile robot reasons places and moves to goal using ambiguous information and ambiguous knowledge through ‘perception’ and ‘planning’. We provide computer simulation results for a mobile robot in order to show the validity of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.451-456
• /
• 1989

New image coding system for facial images called 'Knowledge-based image coding' is described, in which input image is analyzed and output image is synthesized using analysis results. Analysis and synthesis method of facial expressions are presented. Synthesis rules are determined on the basis of facial muscles and are also used in analysis process to produce a faithful reconstruction of the original image. A number of examples are shown.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.17 no.30
• /
• pp.153-160
• /
• 1994

In this paper, we present the application of knowledge-based system technique for generating of PLC ladder diagram The developed prototype system receives a time chart as an input and generates a ladder logic as its output This results in the computerization and intellegent processing of PLC programming. The system can be effectively applied to sequence control where the PLC programs need to be frequently changed and generated.