• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.307-310
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• 1995

In the conventional systems, a human must have knowledge of machines and of their special language in communicating with machines. In one side, it is desirable for a human but in another side, it is true that achieving it is very elaborate and is also a significant cause of human error. To reduce this sort of human load, an intelligent man-machine interface is desirable to exist between a human operator and machines to be operated. In the ordinary human communication, not only linguistic information but also visual information is effective, compensating for each others defect. From this viewpoint, problem of translating verbal expressions to some visual image is discussed here in this paper. The location relation between any two objects in a visual scene is a key in translating verbal information to visual information, as is the case in Fig.l. The present translation system advances in knowledge with experience. It consists of Japanese Language processing, image processing, and Japanese-scene translation functions.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.29.2-29
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• 2001

For the design of human-centered systems in which a human and machine such as a robot form a human-in system, human-friendly interaction/interface is essential. Human-friendly interaction is possible when the system is capable of recognizing human biosigns such as5 EMG Signal, hand gesture and facial expressions so the some humanintention and/or emotion can be inferred and is used as a proper feedback signal. In the talk, we report our experiences of applying the Soft computing techniques including Fuzzy, ANN, GA and rho rough set theory for efficiently recognizing various biosigns and for effective inference. More specifically, we first observe characteristics of various forms of biosigns and propose a new way of extracting feature set for such signals. Then we show a standardized procedure of getting an inferred intention or emotion from the signals. Finally, we present examples of application for our model of rehabilitation robot named.

• Journal of Mechanical Science and Technology
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• v.20 no.11
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• pp.1863-1872
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• 2006

In FMS (Flexible Manufacturing System) and CIM (Computer Integrated Manufacturing), machine-tools have been the target of integration in the last three decades. The conventional concept of integration is being changed into the autonomous manufacturing device based on the knowledge evolution by applying advanced information technology in which an open architecture controller, high-speed network and internet technology are included. In the advanced environment, the machine-tools is not the target of integration anymore, but has been the key subject of cooperation. In the near future, machine-tools will be more improved in the form of a knowledge-evolutionary intelligent device. The final goal of this study is to develop an intelligent machine having knowledge-evolution capability and a management system based on internet operability. The knowledge-evolutionary intelligent machine-tools is expected to gather knowledge autonomically, by producing knowledge, understanding knowledge, reasoning knowledge, making a new decision, dialoguing with other machines, etc. The concept of the knowledge-evolutionary intelligent machine is originated from the machine control being operated by human experts' sense, dialogue and decision. The structure of knowledge evolution in M2M (Machine to Machine) and the scheme for a dialogue agent among agent-based modules such as a sensory agent, a dialogue agent and an expert system (decision support agent) are presented in this paper, with intent to develop the knowledge-evolutionary machine-tools. The dialogue agent functions as an interface for inter-machine cooperation. To design the dialogue agent module in an M2M environment, FIPA (Foundation of Intelligent Physical Agent) standard platform and the ping agent based on FIPA are analyzed in this study. In addition, the dialogue agent is designed and applied to recommend cutting conditions and thermal error compensation in a tapping machine. The knowledge-evolutionary machine-tools are expected easily implemented on the basis of this study and shows a good assistance to sensory and decision support agents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.576-590
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• 2023

Machine learning is widely used in various academic fields, and recently it has been actively applied in the medical research. In the medical field, machine learning is used in a variety of ways, such as speeding up diagnosis, discovering new biomarkers, or discovering latent traits of a disease. In the respiratory field, a relative regional air volume change (RRAVC) map based on quantitative inspiratory and expiratory computed tomography (CT) imaging can be used as a useful functional imaging biomarker for characterizing regional ventilation. In this study, we seek to predict RRAVC using various regular machine learning models such as extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and multi-layer perceptron (MLP). We experimentally show that MLP performs best, followed by XGBoost. We also propose several relative coordinate systems to minimize intersubjective variability. We confirm a significant experimental performance improvement when we apply a subject's relative proportion coordinates over conventional absolute coordinates.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.642-650
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• 2000

The pilot (human actor) involved in the control loop of the highly automated aircraft systems (machine actor) must be able to monitor these systems just as the machine actor must also be able to monitor the human actor. For its safety and better performance of the human machine system, each of the two elements must be knowledgeable about the other's intentions or goals. In fact, several recent accidents occurred due to goal conflicts between human and machines in a modern avionic system. To facilitate the coordination of these actors, a computational aid was developed. The aid, which operates in a part-task simulator environment, attempts to facilitate the management of the goals and functions being performed to accomplish them. To provide an accurate knowledge of both actors' goals and their function statuses, the aid uses agent-based objects representing the elements of the cockpit operations. This paper describes the development of the flightdeck goals and functions called Agenda Management.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1430-1435
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• 1990

Using eye mark recorder and polygraph, basic laboratory experiments have been conducted to investigate the validity of psycho-physiological measures to the analysis of on-line cognitive information characteristics at man-machine interface (MMI). It is concluded that various psycho-physiological measures are useful to estimate various aspects of human cognitive characteristics and thus to the evaluation of MMI designing from the viewpoint of its harmony to the human cognitives.

• Journal of the Korean Society of Systems Engineering
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• v.17 no.2
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• pp.69-81
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• 2021

The human performance issues and increased automation issues in advanced Small Modular Reactors (SMRs) are critical to numerous stakeholders in the nuclear industry, due to the undesirable implications targeting the Man Machine Interface Systems (MMIS) complexity of (Generation IV) SMRs. It is imperative that the design of future SMRs must address these problems. Nowadays, Multi Agent Systems (MAS) are used in the industrial sector to solve multiple complex problems; therefore incorporating this technology in the proposed innovative SMR (I-SMR) design will contribute greatly in the decision making process during plant operations, also reduce the number MCR operating crew and human errors. However, it is speculated that an increased level of complexity will be introduced. Prior to achieving the objectives of this research, the tools used to analyze the system for complexity reduction, are the McCabe's Cyclomatic complexity metric and the Henry-Kafura Information Flow metric. In this research, the systems engineering approach is used to guide the engineering process of complexity reduction concept of the system in its entirety.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.847-850
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• 2008

On today, human is going to develop machine by using mutual communication to machine. Including vision - based HCI(Human Computer Interaction), the technique which to recognize finger and to track finger is important in HCI systems, in HCI systems. In order to divide finger, this paper uses more effectively dividing the technique using subtraction which is separation of background and foreground, as well as to divide finger from limited background and cluttered background. In order to divide finger, the finger is recognized to make "Template-Matching" by identified fingertip images. And, identified gestures be compared the tracked gesture after tracking recognized finger. In this paper, after obtaining interest area, not only using subtraction image and template-matching but to perform template-matching in the area. So, emphasis is placed on decreasing perform speed and reaction speed, and we propose technique which is more effectively recognizing gestures.

• Journal of the Korean Society for information Management
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• v.25 no.2
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• pp.199-221
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• 2008

The purpose of this study is to investigate the characteristics of indexes by human and machine, and differences between them in terms of term identification in a fulltext environment. A back-of-book index and two indexes produced by two term identifiers (LinkIt and Termer) as pseudo-indexing systems for a whole body of a monograph are examined. In the investigation, the traditional contrast between manual and automatic indexing is confirmed in fulltext environment, manual index is for browsing and human use, and automatic index is for searching and machine use. The border between them, however, becomes vague. Some considerations for the use of the term identifiers for browsing and for searching are discussed, and further research for the use of the term identifier is suggested.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.813-816
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• 2005

Ear detection is an important part of an non-invasive ear recognition system. In this paper we propose human ear detection from side face images. The proposed method is made by imitating the human recognition process using feature information and color information. First, we search face candidate area in an input image by using 'skin-color model' and try to find an ear area based on edge information. Then, to verify whether it is the ear area or not, we use the SVM (Support Vector Machine) based on a statistical theory. The method shows high detection ratio in indoors environment with stable illumination.