• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.5
• /
• pp.1008-1013
• /
• 2009

In this paper, we proposed the biological signal (body heat, pulse, breathe rate, and blood pressure) analysis system using wireless sensor. In order to analyze, we designed a back-propagation neural network system using expert group system. The proposed system is consist of hardware patt such as UStar-2400 ISP and Wireless sensor and software part such as Knowledge Base module, Inference Engine module and User Interface module which is inserted in Host PC. To improve the accuracy of the system, we implement a FEC (Forward Error Correction) block. For conducting simulation, we chose 100 data sets from Knowledge Base module to train the neural network. As a result, we obtained about 95% accuracy using 128 data sets from Knowledge Base module and acquired about 85% accuracy which experiments 13 students using wireless sensor.

• Journal of Korean Medical classics
• /
• v.26 no.3
• /
• pp.127-139
• /
• 2013

Objectives : In the traditional oriental medicine, efforts to utilize the knowledge system so called Ontology have been achieved for systemic researches and efficient propagation of knowledge on oriental medicine. So far, in Korea, studies on drug ontology, pathological ontology, Cold Damage ontology and diagnostic ontology had been implemented, however, any development of ontology in the field of Acupuncture &, Moxibustion has not been achieved. Methods : We used Microsoft Access to collect terms in ZhenJiuJiaYiJing. The terms are related to human body area and structure. And then we built relationship of 'part of' and 'criterion of acupuncture point location' between the terms. Result & Conclusions : The terms used to explain acupuncture points in order to describe the position of acupuncture point name in ZhenJiuJiaYiJing were 8 words concerning different name of acupuncture point(穴名) 109, body part name(人體部位名稱) 150, meridian(經脈) 6 and structure(構造物).

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.51 no.9
• /
• pp.413-422
• /
• 2002

In a power plant, disturbance detection and diagnosis are massive and complex problems. Once a disturbance occurs, it can be either persistent, self cleared, cleared by the automatic controllers or propagated into another disturbance until it subsides in a new equilibrium or a stable state. In addition to the Physical complexity of the power plant structure itself, these dynamic behaviors of the disturbances further complicate the fault monitoring and diagnosis tasks. A data structure called a disturbance interrelation analysis graph(DIAG) is proposed in this paper, trying to capture, organize and better utilize the vast and interrelated knowledge required for power plant disturbance detection and diagnosis. The DIAG is a multi-layer directed AND/OR graph composed of 4 layers. Each layer includes vertices that represent components, disturbances, conditions and sensors respectively With the implementation of the DIAG, disturbances and their relationships can be conveniently represented and traced with modularized operations. All the cascaded disturbances following an initial triggering disturbance can be diagnosed in the context of that initial disturbance instead of diagnosing each of them as an individual disturbance. DIAG is applied to a typical cooling water system of a thermal power plant and its effectiveness is also demonstrated.

• Proceedings of the KIEE Conference
• /
• 1989.07a
• /
• pp.241-245
• /
• 1989

A knowledge based expert system is a computer program that emulates the reasoning process of a human expert in a specific problem domain. This paper presents an expert system to diagnose the various faults in power system. The developed expert system is represented considering two points; the possibility of solution and the fast processing speed. As uncertainties exist in the facts and rules which comprise the knowledge base of the expert system, Certainty Factor, which is based on the confirmation theory is used for the inexact reasoning. Also, as the diagnosis problem requires the inductive reasoning process in nature, the solution is imperfect and not unique in general. So the expert system is designed to generate all the possible hypothesis in order of the possibility and also it can explain the propagation procedure of the faults for each solution using the built in backtracking mechanism. In realization of the expert system, the processing speed is greatly dependent upon the problem representation, reasoning scheme and search strategy. So, in this paper the fault diagnosis problem itself is analysed from the view point of Artificial Intelligence and as a result, the expert system has the following basic features. 1) The certainty factor is adopted in the inference engine for inexact reasoning. 2) Problem apace is represented using the problem reduction technique. 3) Bidirectional reasoning scheme is used. 4) Best first search strategy is adopted for rapid processing. The expert system was developed us ing PROLOG language.

• Asia pacific journal of information systems
• /
• v.25 no.1
• /
• pp.83-97
• /
• 2015

Recently, the exhibition industry has developed rapidly with the development of information technologies. Most exhibitors in an exhibition plan and deploy many events that may provide advantages to visitors as a method of effective promotion. The growth and propagation of wireless technologies is a powerful marketing tool for exhibitors. However, exhibitors still rely on domain experts who are costly and time consuming because of the manual knowledge input procedure. Moreover, it is prone to biases and errors and not suitable for managing fast-growing and tremendous amounts of data that far exceed a human's ability to comprehend. To overcome these problems, data mining technology may be a great alternative, but it needs to be fit to each exhibition. This study uses data mining technology with the Predictive Model Markup Language (PMML) to suggest a system that supports intelligent services and that improves stakeholder satisfaction. This system provides advantages to the exhibitor, show organizer, and system designer, and is first enhanced by integrating data mining technologies through the knowledge of exhibition experts. Second, using the PMML, the system can automate the process of applying data mining models to solve real-time processing problems in the exhibition environment.

• Journal of Korean Elementary Science Education
• /
• v.35 no.4
• /
• pp.389-405
• /
• 2016

The purpose of this study was to analyze elementary school teachers' understanding, certainty, and familiarity with 13 key concepts of wave physics that are presented in textbook and teacher's guidebook. 123 elementary school teachers answered concept tests and questionnaires. In the results to these tests and questionnaires, teachers demonstrated a high level of understanding and high certainty in understanding with regard to the concepts of sound generation, effect of medium on wave, timbre, wavelength, and trough and crest of wave. For the topics of sound velocity, wave reflection and wave transmission, teachers demonstrated a high level of understanding but low certainty in understanding. With regard to sound propagation, teachers demonstrated a low level of understanding and an improperly high certainty in that low understanding. Teachers lacked knowledge, i.e., displayed a low level of understanding and low certainty in sound strength, sound frequency, constructive interference and destructive interference. In constructive and destructive interference, the teachers also displayed a low level of familiarity. We analyzed the differences in teacher's understanding, certainty, and familiarity according to teacher demographics defined by the teacher's gender, teaching experience with concepts of sound, career, curriculum track while in high school, and major in university. There were no significant differences in understanding, certainty, or familiarity as defined by gender, teaching experience, and career. However, these displays of knowledge were affected by the teacher's curriculum track in high school and their major. These results suggest that the teacher's understanding of, familiarity with, and certainty in wave physics concepts are more influenced by their learning experience than by their teaching experience. Therefore, we suggest additional learning opportunities for teachers (such as teacher training programs) in order to improve teacher knowledge and correct teacher misconceptions in wave physics.

• ETRI Journal
• /
• v.40 no.2
• /
• pp.197-206
• /
• 2018

Multiple-input multiple-output (MIMO) systems offer significant enhancements in terms of their data rate and channel capacity compared to traditional systems. However, correlation degrades the system performance and imposes practical limits on the number of antennas that can be incorporated into portable wireless devices. The use of switched parasitic antennas (SPAs) is a possible solution, especially where it is difficult to obtain sufficient signal decorrelation by conventional means. The covariance matrix represents the correlation present in the propagation channel, and has significant impact on the MIMO channel capacity. The results of this work demonstrate a significant improvement in the MIMO channel capacity by using SPA with the knowledge of the covariance matrix for all pattern configurations. By employing the "water-pouring algorithm" to modify the covariance matrix, the channel capacity is significantly improved compared to traditional systems, which spread transmit power uniformly across all the antennas. A condition number is also proposed as a selection metric to select the optimal pattern configuration for MIMO-SPAs.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.283-286
• /
• 1996

This study suggests a new methodology for the fault diagnosis based on the signed digraph in developing the fault diagnosis system of a boiler plant. The suggested methodology uses the new model, fault-effect tree. The SDG has the advantage, which is simple and graphical to represent the causal relationship between process variables, and therefore is easy to understand. However, it cannot handle the broken path cases arisen from data uncertainty as it assumes consistent path. The FET is based on the SDG to utilize the advantages of the SDG, and also covers the above problem. The proposed FET model is constructed by clustering of measured variables, decomposing knowledge base and searching the fault propagation path from the possible faults. The search is performed automatically. The fault diagnosis system for a boiler plant, ENDS was constructed using the expert system shell G2 and the advantages of the presented method were confirmed through case studies.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.375-378
• /
• 1997

This research deals with a problem of reconstructing 3D surface structures from their 2D projections, which is an important research topic in computer vision. In order to provide robust reconstruction algorithm, that is reliable even in the presence of uncertainty in the range images, we first present a detailed model and analysis of several error sources and their effects on measuring three-dimensional surface properties using the space encoded range imaging technique. Our approach has two key elements. The first is the error modeling for the space encoding range sensor and its propagation to the 3D surface reconstruction problem. The second key element in our approach is the algorithm for removing outliers in the range image. Such analyses, to our knowledge, have never attempted before. Experimental results show that our approach is significantly reliable.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.10
• /
• pp.77-85
• /
• 1993

In this paper, we present a method to solve a convexly combined fuzzy relational equation with generalized connectives. For this, we propose a neural network whose structure represents the fuzzy relational equation. Then we derive a learning algorithm by using the concept of back-propagation learning. Since the proposed method can be used for a general form of fuzzy relational equations, such fuzzy max-min or min-max relational equations can be treated as its special cases. Moreover, the relational structure adopted in the proposed neurocomputational approach can work in a highly parallel manner so that real-time applications of fuzzy sets are possibles as in fuzzy logic controllers, knowledge-based systems, and pattern recognition systems.