• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 춘계학술대회논문집
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• pp.945-948
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• 2005

Mobile computing devices are becoming increasingly prevalent in a huge range of physical area, offering a considerable market opportunity. The focus of this paper is on the development of a platform of fault diagnosis system integrating with personal digital assistant (PDA). An improvement of induction machine rotor fault diagnosis based on AI algorithms approach is presented. This network system consists of two parts; condition monitoring and fault diagnosis by using Artificial Intelligence algorithm. LabVIEW allows easy interaction between acquisition instrumentation and operators. Also it can easily integrate AI algorithm. This paper presents a development environment fur intelligent application for PDA. The introduced configuration is a LabVIEW application in PDA module toolkit which is LabVIEW software.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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• pp.145-154
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• 1999

An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes th hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.

• 한국인공지능학회지
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• 제6권1호
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• pp.16-20
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• 2018

The development of modern information technology has increased the amount of big data about patients' information and diseases. In this study, we developed a prediction model of diabetes using the health examination data provided by the public data portal in 2016. In addition, we graphically visualized diabetes incidence by sex, age, residence area, and income level. As a result, the incidence of diabetes was different in each residence area and income level, and the probability of accurately predicting male and female was about 65%. In addition, it can be confirmed that the influence of X on male and Y on female is highly to affect diabetes. This predictive model can be used to predict the high-risk patients and low-risk patients of diabetes and to alarm the serious patients, thereby dramatically improving the re-admission rate. Ultimately it will be possible to contribute to improve public health and reduce chronic disease management cost by continuous target selection and management.

• 한국지능시스템학회논문지
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• 제11권7호
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• pp.579-583
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• 2001

In the area of data clustering in high dimensional space, one of the difficulties is the time-consuming process for computing vector similarities. It becomes worse in the case of the agglomerative algorithm with the group-average link and mean centroid method, because the cluster similarity must be recomputed whenever the cluster center moves after the merging step. As a solution of this problem, we present an incremental method of similarity computation, which substitutes the scalar calculation for the time-consuming calculation of vector similarity with several measures such as the squared distance, inner product, cosine, and minimum variance. Experimental results show that it makes clustering speed significantly fast for very high dimensional data.

• 한국전자통신학회논문지
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• 제12권1호
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• pp.115-122
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• 2017

딥 러닝은 사람이 가르치지 않아도 컴퓨터가 스스로 사람처럼 학습할 수 있는 인공지능 기술이다. 딥 러닝은 세상을 이해하고 감지하는 인공지능을 개발하는데 가장 촉망받는 기술이 되고 있으며, 구글, 바이두, 페이스북 등이 가장 앞서서 개발을 하고 있다. 본 논문에서는 딥 러닝을 구현하는 딥 러닝 프레임워크의 종류에 대해 논의하고, 딥 러닝 프레임워크의 영상과 음성 인식 분야의 효율성에 대해 비교, 분석하고자 한다.

• Advances in materials Research
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• 제1권4호
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• pp.349-359
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• 2012

To reveal localized plastic deformation zones in a tough pitch copper, the etching characteristics of a copper sample have been examined. The etching was carried out on a sample surface using an etchant consisting of 25 ml nitric acid solution and 75 ml water. To clarify the plastic deformation zone, the sample deformed plastically was heated to between $250^{\circ}C$ and $300^{\circ}C$ before the etching process. This is due to a change of the microstructure and crystal orientation in the plastic deformation zone producing recrystallized small grains. In this case, the plastically deformed zone is severely etched, whereas the undeformed zone is only slightly etched. Identification of the details of the deformation zone from the etching is further discussed.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1167-1170
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• 1993

We look at the problem of defuzzification in situations in which in addition to the usual fuzzy output of the controller there exists some ancillary restriction on the allowable defuzzified values. We provide two basic approaches to address this problem. In the first approach we enforce the restriction by selecting the defuzzified value through a random experiment in which the values which have nonzero probabilities are in the allowable region, this method is based on the RAGE defuzzification procedure and makes use of a nonmonotonic conjunction operator. The second approach which in the spirit of the commonly used methods, a kind of expected value, converts the problem to a constraint optimization problem.

• International Journal of Advanced Culture Technology
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• 제6권4호
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• pp.165-171
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• 2018

As the artificial intelligence (AI) plays a crucial role in machine translation (MT) which has loomed large as a new translation paradigm, concerns have also arisen if MT can produce a quality product as human translation (HT) can. In fact, several MT experimental studies report cases in which the MT product called post-editing (PE) as equally as HT or often superior ([1],[2],[6]). As motivated from those studies on translation quality between HT and PE, this study set up an experimental situation in which Korean literature was translated into English, comparatively, by 3 translators and 3 post-editors. Afterwards, a group of 3 other Koreans checked for accuracy of HT and PE; a group of 3 English native speakers scored for fluency of HT and PE. The findings are (1) HT took the translation time, at least, twice longer than PE. (2) Both HT and PE produced similar error types, and Mistranslation and Omission were the major errors for accuracy and Grammar for fluency. (3) HT turned to be inferior to PE for both accuracy and fluency.

• 한국정보통신학회논문지
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• 제24권2호
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• pp.333-336
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• 2020

AI-powered robot news is drawing attention as artificial intelligence technology is fully spread in the news distribution field. Robot news still has many technical and ethical problems, but academic research on this is insufficient. This study analyzes the issue of robot writing in artificial intelligent based robot journalism industry using SWOT analysis. As a result, the advantages of big data processes, accurate information gathering, high efficiency and disadvantages such as lack of independent arguments and lack of evidence and opportunities for technical development, government support, academic development, and industrial applications, and threats such as uncritical acceptance and lack of talent have been found. This study suggests three future-oriented directions, such as human-machine collaboration, intelligent news, and chat-bot, through previous studies on the development direction of robot journalism-based article writing.

• 한국인공지능학회지
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• 제8권2호
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• pp.7-10
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• 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.