• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제16권2호
• /
• pp.111-118
• /
• 2016

Artificial intelligence (AI) is making computer systems intelligent to do right thing. The AI is used today in a variety of fields, such as journalism, medical, industry as well as entertainment. The impact of AI is becoming larger day after day. In general, the AI system has to lead the optimal decision under uncertainty. But it is difficult for the AI system can derive the best conclusion. In addition, we have a trouble to represent the intelligent capacity of AI in numeric values. Statistics has the ability to quantify the uncertainty by two approaches of frequentist and Bayesian. So in this paper, we propose a methodology of the connection between statistics and AI efficiently. We compute a fixed value for estimating the population parameter using the frequentist learning. Also we find a probability distribution to estimate the parameter of conceptual population using Bayesian learning. To show how our proposed research could be applied to practical domain, we collect the patent big data related to Apple company, and we make the AI more intelligent to understand Apple's technology.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
• /
• pp.486-495
• /
• 2001

This paper describes an implementation of the interval based expert system for syndrome differential diagnosis of Oriental Traditional Medicine (OTM). An approximate reasoning model using fuzzy logic for syndrome differential diagnosis is proposed. Based on this model, we implemented the system for diagnosing Eight rule diagnosis, organ diagnosis and then final differential syndrome of OTM. After carrying out inference process, the system will provide patient\`s syndromes differentiation diagnosis in the intervals and will give the explanation, which helps the user to understand the obtained conclusions.

• 대한한의학회지
• /
• 제21권3호
• /
• pp.9-19
• /
• 2000

Objective : We proposed fundamental rules of prospective Korean Standard Classification of Diseases(Oriental Medicine). Methods : We analysed Korean Standard Classification of Diseases(Oriental Medicine)(established in 1994) in comparison with ICD-10 and Chinese Standard Classification of Disease(Traditional Chinese Medicine). Secondly, we analysed the diagnostic structure of Modem oriental medicine. Results : Korean Standard Classification of Diseases has an inappropriate writing structure, logical errors of classification, confusion of symptoms, 'bing', and 'zheng', inappropriate comparison of disease designations in oriental medicine and western medicine, and the ommission of important items. Secondly, we demonstrate the relations of 'bing' and 'zheng' in modem oriental medicine and disease designations in oriental medicine and western medicine. Conclusions : We propose the separate classification of 'bing' and 'zheng', the qualification of designated names, the structure of 'bing' and 'zheng' system, and a different writing method.

• 대한의용생체공학회:학술대회논문집
• /
• 대한의용생체공학회 1992년도 춘계학술대회
• /
• pp.155-160
• /
• 1992

Liver function test is one of the most common tests for diagnosis and follow-up of patients and for heal th screening. Automatic interpretation and suggestions on the diagnostic possibilities contribute to shorten the interpretation time of the test results and help to provide qualified health care. Fuzzy logic has been recently introduced and being spread for these purposes. The present study aims at model Ins the foray rule-based laboratory diagnosis system. The fuzzy rule-based laboratory diagnosis system was applied to the diagnosis regarding liver function test. The system was evaluated by comparing with the stepwise multivariate discriminant function analysis, which showed similar results, and the overall accuracy of the fuzzy diagnosis system was about 80%.

• 대한의용생체공학회:학술대회논문집
• /
• 대한의용생체공학회 1997년도 춘계학술대회
• /
• pp.156-160
• /
• 1997

In this paper, the control scheme is proposed that PI controller parameter used for TAH speed control is adapted by fuzzy logic method using only the motor current waveform. By scheduling PI parameters, minimization of the vibration and the energy consumption and overcoming AoP loads becomes possible. In in vitro tests experimental results show our approach is a good scheme that is adapted to changing afterloads well.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제1권1호
• /
• pp.104-112
• /
• 2001

Simply, Nonlinear dynamics theory means the complicated and noise-like phenomena originated form nonlinearity involved in deterministic dynamical system. An almost all the natural signals have nonlinear property. However, there exist few analysis software tool or package for a research and development of applications. We develop nonlinear time series analysis simulator is to provide a common and useful tool for this purpose and to promote research and development of nonlinear dynamics theory. This simulator is consists of the following four modules such as generation module, preprocessing module, analysis module and ICA module. In this paper, we applied to Electroencephalograph (EEG), as it turned out, our simulator is able to analyze nonlinear time series. Besides, we could get the useful results using the various parameters. These results are used to diagnostic the brain diseases.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제4권2호
• /
• pp.211-216
• /
• 2004

Fuzzy neural networks have been successfully applied to analyze/generate predictive rules for medical or diagnostic data. However, most approaches proposed so far have not considered the weights for the membership functions much. This paper presents a neural network with weighted fuzzy membership functions. In our approach, the membership functions can capture the concentrated and essential information that affects the classification of the input patterns. To verify the performance of the proposed model, well-known Iris data set is performed. According to the results, the weighted membership functions enhance the prediction accuracy. The architecture of the proposed neural network with weighted fuzzy membership functions and the details of experimental results for the data set is discussed in this paper.

• International Journal of Aeronautical and Space Sciences
• /
• 제5권2호
• /
• pp.28-34
• /
• 2004

One of the major problem encountered in nuclear plants and satellites design isEMI (Electro-Magnetic Interference) and EMC (Electro-Magnetic Compatibility).Here, our focus is to implement the test board for checking SEU (Single EventUpsets); the effects of protons on the electronic system. The SEU results from thelevel change of stored information due to photon radiation and temperature in thespace environment. The impact of SEU on PLD (Programmable Logic Devices)technology is most apparent in ROM/SRAM/DRAM devices wherein the state ofstorage cell can be upset. In this paper, a simple and powerful test techniques issuggested, and the results are presented for the analysis and future reference. In ourexperiment, the proton radiation facilitv (having the energy of 50 MeV with a beamcurrent of 60 uA of cyclotron) available at KIRAMS (Korea Institute of RadiologicalMedical Sciences) has been applied on a commercially available SRAM manufacturedby Hynix Semiconductor Company.

• 대한의용생체공학회:의공학회지
• /
• 제12권4호
• /
• pp.277-284
• /
• 1991

This study describes the ambulatory ECG monitoring system for the remote autom atic diagnosis. System: tlardware is based on one chip microcomputer(80c31) and its peripherals which consists of A/D, EPROM, RAM, LCD display and two preamplifiers, Power circuits, control logic circuits. A/D converted data were differentiated and low pass filtered. The detection of QRS complex and R point were accomplished by software algorithm based on adaptive threshold computed on low pass fi:leered signal. Rhythm analysis is performed by RR interval and average RR interval. The performance of QRS detection algorithm is evaluated by using MIT/BIH data base. Using this system, the trends of the arrythmia during the long term could be saved and displayed.

• 대한의용생체공학회:의공학회지
• /
• 제12권3호
• /
• pp.203-208
• /
• 1991

Balancing left/right cardiac output is essential for the automatic control of total artificial hearts(TAH). A fuzzy logic-based control method is presented. We use left atrial pressure( LAP) ann right a'rial pressure( RAP ) as indicators for left/right balancing. The fuzzy controller has four input variables which are measured LAP and RAP and their gradients. Desired variations in left cardiac output(LCO) and right cardiac output(RCO) are cal- culated to keep LAP and RAP within the Physiological limlts. Computer simulations were performed to adjust fuzzy membership functions for variables and verify this control method. Results from simulations showed that LAP and RAP returned to the physiological limits while AoP and PAP stayed within the physiological limits.