• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 춘계학술대회
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• pp.258-263
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• 2004

Mechanical property evaluation of micrometer-sized structures is necessary to help design reliable microelectromechanical systems(MEMS) devices. Most material properties are known to exhibit dependence on specimen size and such properties of microscale structures are not well characterized. This paper describes techniques developed for tensile testing of materials used in MEMS. Epi-polycrystalline silicon is currently the most widely used material, and its tensile strength has been measured as 1.52GPa. We have developed an uniaxial testing machine for testing microscale specimen using electro-magnetic actuator. The field magnet and the moving coil taken from an audio-speaker were utilized as the components of the actuator. Structure of specimen was designed and manufactured for easy handling and alignment. In addition to the static tensile tests, new techniques and procedures for measuring strength are described.

• ETRI Journal
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• 제43권4호
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• pp.694-701
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• 2021

Catastrophic events cause casualties, damage property, and lead to huge social impacts. To build common standards and facilitate international communications regarding disasters, the relevant authorities in social management rank them in subjectively imposed terms such as direct economic losses and loss of life. Terrorist attacks involving uncertain human factors, which are roughly graded based on the rule of property damage, are even more difficult to interpret and assess. In this paper, we collected 114 183 open-source records of terrorist attacks and used a machine learning method to grade them synthetically in an automatic and objective way. No subjective claims or personal preferences were involved in the grading, and each derived common factor contains the comprehensive and rich information of many variables. Our work presents a new automatic ranking approach and is suitable for a broad range of gradation problems. Furthermore, we can use this model to grade all such attacks globally and visualize them to provide new insights.

• Korean Journal of Mathematics
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• 제28권4호
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• pp.973-984
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• 2020

This paper is devoted to study the reproducing property on 2-inner product Hilbert spaces. We focus on a new structure to produce reproducing kernel Hilbert and Banach spaces. According to multi variable computing, this structures play the key role in probability, mathematical finance and machine learning.

• Journal of the Korean Data and Information Science Society
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• 제22권5호
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• pp.921-929
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• 2011

정보화시대에 대학에서의 교양 컴퓨터교육과정은 컴퓨터에 대한 소양을 쌓고 정보화 사회에 능동적으로 대처할 수 있는 능력을 배양하여 생산성 향상은 물론 국가 간의 경쟁력에서 뒤지지 않게 하는데 목표를 두고 있다. 본 논문에서는 대학생을 대상으로 컴퓨터교육 만족도에 영향을 미치는 결정적인 변인의 발견 및 만족도를 분석한다. 전처리과정으로 자바 기반의 학습 도구인 속성 부분집합의 선택기반을 사용하여 최적의 변인을 선택한 후 통계적 학습이론에 기반을 둔 다중 최소제곱 서포트벡터 기계를 사용하고자 한다. 대학의 교양 컴퓨터교육 만족도 분석을 위하여 새로운 알고리즘을 제시하기 보다는 기존의 다중 서포트벡터기계와 다중 최소제곱 서포트벡터기계를 비교 분석한다. 본 논문의 연구결과는 컴퓨터교육 만족도 자료의 분석에서 다중 최소제곱 서포트벡터기계가 다중 서포트벡터기계와 같이 우수한 성과를 나타내는 것을 확인하였다.

• 한국생산제조학회지
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• 제7권5호
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• pp.59-65
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• 1998

In order to utilize the information of well-know grinding database or grinding machine characteristics, a database needs to be designed by considering the delicate property of the machine tools for the high precision and quality of the demanding specification. Among the machine tools for the high precision and quality of the demanding specification. Among the machine tools, machining conditions of the grinding are various and knowledge repeatance obtained form the grinding process are less credable. therefore it is desirable for database, which is used to set the grinding conditions, to utilize the maximum machine tool capability. The present paper studied on the occurance limit of chatter vibration and burn considering the characteristics of machine tool. And also basic experiments were performed to establish the optimum grinding conditions which could maximize the grinding efficiency.

• 한국지능시스템학회논문지
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• 제17권3호
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• pp.291-296
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• 2007

최근에 여러 분야에서 구축되고 있는 온톨로지는 기계가 이해할 수 있는 지식을 축적하는 것을 목표로 하고 있다. 기계가 온톨로지를 이용하여 정보의 관리 및 해석을 스스로 하는 것이 가능할 것으로 본다. 본 논문에서는 온톨로지의 인스턴스를 구성하는 속성을 기존 웹 문서의 구조정보로부터 추출하는 알고리즘을 제안하였다. 특히, 속성 정보로 구성하는 도메인 지식을 계층화함으로써 속성 추출 알고리즘을 개선하고, 추출 결과의 품질을 향상시킨다. 2만 문서를 대상으로 제안된 알고리즘을 적용한 결과 약 83%의 신뢰도의 속성 정보를 추출할 수 있었다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.8-13
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• 1997

In order to utilize the information of well-known grinding data or grinding machine, a database needs to be designed by considering the delicate property of the machine tools for the high precision and quality of the demanding specification. Among the machine tools, machining conditions of the grinding are various and knowledge repeatance obtained form the grinding process are less credable.Therefore it is desirable for D/B, which is used to set the grinding conditions, to utilize the maximum machine tool capability. The present paper studied occurance limit of chatter vibration and burn considering the characteristics of machine tool. And also basic experiments were performed to establish optimum grinding canditions which can maximize the machining efficiency.

• 디지털산업정보학회논문지
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• 제15권2호
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• pp.19-28
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• 2019

The purpose of this study is to examine the trends on machine learning and deep learning research in the published journals from the Web of Science Database. To achieve the study purpose, we used the abstracts of 20,664 articles published between 1990 and 2017, which include the word 'machine learning', 'deep learning', and 'artificial neural network' in their titles. Twenty major research topics were identified from topic modeling analysis and they were inclusive of classification accuracy, machine learning, optimization problem, time series model, temperature flow, engine variable, neuron layer, spectrum sample, image feature, strength property, extreme machine learning, control system, energy power, cancer patient, descriptor compound, fault diagnosis, soil map, concentration removal, protein gene, and job problem. The analysis of the time-series linear regression showed that all identified topics in machine learning research were 'hot' ones.

• 한국도로학회:학술대회논문집
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• 한국도로학회 2001년도 학술발표회 논문집
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• pp.79-86
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• 2001

• Journal of Information Processing Systems
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• 제13권5호
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• pp.1103-1125
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• 2017

This paper aims to extract an ObjectProperty-UsageMethod relation, in particular the HerbalMedicinalProperty-UsageMethod relation of the herb-plant object, as a semantic relation between two related sets, a herbal-medicinal-property concept set and a usage-method concept set from several web documents. This HerbalMedicinalProperty-UsageMethod relation benefits people by providing an alternative treatment/solution knowledge to health problems. The research includes three main problems: how to determine EDU (where EDU is an elementary discourse unit or a simple sentence/clause) with a medicinal-property/usage-method concept; how to determine the usage-method boundary; and how to determine the HerbalMedicinalProperty-UsageMethod relation between the two related sets. We propose using N-Word-Co on the verb phrase with the medicinal-property/usage-method concept to solve the first and second problems where the N-Word-Co size is determined by the learning of maximum entropy, support vector machine, and naïve Bayes. We also apply naïve Bayes to solve the third problem of determining the HerbalMedicinalProperty-UsageMethod relation with N-Word-Co elements as features. The research results can provide high precision in the HerbalMedicinalProperty-UsageMethod relation extraction.