• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.2 s.332
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• pp.31-40
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• 2005

The Multi-Threshold CMOS (MTCMOS) technology provides a solution to the high performance and low power design requirements of mobile computing applications. In this paper, we (i) motivate the post-mask-tooling performance enhancement technique combined with the MTCMOS leakage current suppression technology, and (ii) develop a practical MTCMOS ASIC design methodology which fine-tunes and integrates best-in-class techniques and commercially available tools to fix the new design issues related to the MTCMOS technology. Towards validating the proposed techniques, a Personal Digital Assistant (PDA) processor has been implemented using the methodology, and a 0.18um Process. The fabricated PDA processor operates at 333MHz which has been improved about $23\%$ at no additional cost of redesign and masks, and consumes about 2uW of standby mode leakage power which could have been three orders of magnitude larger if the MTCMOS technology was not applied.

• The Journal of the Korea Contents Association
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• v.11 no.9
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• pp.372-383
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• 2011

Our study was carried out to develop the severity-adjustment model for length of stay in hospital for percutaneous coronary interventions so that we would analysis the factors on the variation in length of stay(LOS). The subjects were 1,011 percutaneous coronary interventions inpatients of the Korean National Hospital Discharge In-depth Injury Survey 2004-2006 data. The data were analyzed using t-test and ANOVA and the severity-adjustment model was developed using data mining technique. After yielding the standardized value of the difference between crude and expected length of stay, we analysed the variation of length of stay for percutaneous coronary interventions. There was variation of LOS in regional differences, size of sickbed and insurance type. The variation of length of stay controlling the case mix or severity of illness can be explained the factors of provider. This supply factors in LOS variations should be more studied for individual practice style or patient management practices and healthcare resources or environment. We expect that the severity-adjustment model using administrative databases should be more adapted in other diseases in practical.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.5
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• pp.427-433
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• 2017

In the case of high-strength or low thermal conductivity material milling, tool breakage occurs easily because of the high friction temperature. Therefore, the effectiveness of the coolant supply is very important for proper tool cooling. As the manually adjustable joint mechanism nozzle is generally used for coolant supply, the cooling efficiency is very low. It also has a bad influence on the workspace environment because of coolant scattering. In this study, the milling characteristics of STS316L were investigated according to the coolant spray position based on the automatic adjustable system. Tool wear and surface roughness were measured according to the coolant spray position. Through these experiments, the effectiveness of the fabricated system was explained.

• Journal of Information Technology and Architecture
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• v.9 no.2
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• pp.167-176
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• 2012

In Korean military measuring systems interoperability is based on LISI (Level of Information System Interoperability) model at the requirement generation and acquisition process. However, LISI model cannot be used for interoperability measurement of system of systems (SoS) because LISI model is focused on interoperability measurement of a given system or system pair. Also, LISI model cannot provide quantitative information for interoperability decision because of qualitative rather than quantitative approach. This paper proposes a quantitative interoperability measurement methodology of SoS. At the proposed methodology, mission threads and supporting systems are identified using architecture approach, and Interoperability of SoS is measured with systems multiplicity and resemblance coefficient. Finally, a case study is presented to show the usefulness of the methodology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.565-569
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• 2007

To find optimal path is killer application in the telematics system. The shortest path of conventional system, however, isn't always optimal path. That is, the path with minimum travelling time could be defined as optimal path in the road networks. There are techniques and algorithms for finding optimal path. Hierarchical path algorithm categorizes road networks into major layer and minor layer so that the performance of operational time increases. The path searched is accurate as much as optimal path. At above 2 system, a method to allocate minor roads to major road region influences the performance extremely. This paper proposes methods to determine search space for selecting major roads in the hierarchical path algorithm. In addition, methods which apply the proposed methods to hierarchical route algorithm is presented.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.238-239
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• 2010

주거 상업용 건물에 있어 최근 TV, LED 조명, 컴퓨터, IT 기기들과 같은 직류를 사용하는 부하가 점차 증가함에 따라 기존의 교류 배전 기반의 건물 전력구조에서 에너지절감을 위한 하나의 방안으로 직류기반의 건물 배전구조에 대한 도입에 대한 연구가 활발히 이뤄지고 있다. 또한 직류 형태의 전원인 태양광 발전, 연료전지 등의 신재생 에너지와 가정 및 전기자동차용 배터리의 등장은 직류 기반 전력구조가 가지는 강점을 더욱 부각시키고 있다. 직류 배전 시스템은 기존 교류 배전에서 직류부하를 위한 다중의 전력 변환 과정을 최소화함으로서 전원 및 부하에서 소모되는 에너지를 절감하여 전력시장 내 전체적인 탄소배출량 저감에 기여할 수 있을 것으로 고려되어지고 있다. 이는 직류배전 시스템의 에너지 저감 효용성 이외 기존 교류배전 대비 부하단 부품 수의 감소에 따른 신뢰성 향상 및 가격 저감, 무효전력 고려사항의 제거 등 많은 장점을 가지기 때문이다. 본 논문에서는 소용량 건물에 직류배전 구조가 도입될 경우 실현 가능성이 높은 대표적 직류 배전 구조들을 Functional Modeling 기법을 통해 모델링하며, 시뮬레이션을 통해 기존의 교류 배전 건물과 함께 각각의 전력계 구조에 대한 효율 및 장단점들을 정성적으로 비교하고, 구현에 필요한 고려사항들을 제시한다.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.245-258
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• 2016

This paper aims to present the way to bring about significant results through performance improvement of learning algorithm in the research applying to machine learning. Research papers showing the results from machine learning methods were collected as data for this case study. In addition, suitable machine learning methods for each field were selected and suggested in this paper. As a result, SVM for engineering, decision-making tree algorithm for medical science, and SVM for other fields showed their efficiency in terms of their frequent use cases and classification/prediction. By analyzing cases of machine learning application, general characterization of application plans is drawn. Machine learning application has three steps: (1) data collection; (2) data learning through algorithm; and (3) significance test on algorithm. Performance is improved in each step by combining algorithm. Ways of performance improvement are classified as multiple machine learning structure modeling, $+{\alpha}$ machine learning structure modeling, and so forth.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9A
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• pp.801-808
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• 2011

We propose MBAP(Multi-rate Broadcast Active Probing) technique to get the right measurements for link quality in Wireless Mesh Network (WMN). Most routing protocols for WMN make use of link quality-aware routing metrics, such as ETX(Expected Transmission Count) and ETT(Expected Transmission Time), while the hop count is usually used in MANET (Mobile Ad-hoc NETwork). A broadcast based active proving technique is adopted in the previous studies to get the ETX or ETT of a link. However this technique does not reflect the multi-rate feature of WLAN because it uses a single fixed transmission rate for broadcast which usually differs from the actual rate used in data transmissions. MBAP overcomes this shortage by exploiting various rate broadcast frames for probing. We implement MBAP on linux system by modifying WLAN driver and related kernel sub-systems. Experimental results show that MBAP can capture link quality more accurately than the existing techniques.

• Journal of Digital Convergence
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• v.18 no.4
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• pp.177-191
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• 2020

This study examines the effect of the self-overviewing attributes derived from agency problem on the cost behavior in franchise industry. To solve the research problem, we developed the proxies for self-overviewing attributes of domestic franchise CEO and used Anderson et al. (2003)'s cost behavior model to test hypothesis. Moreover, we grouped the self-overviewing variables for additional test. We find that operating costs are more sticky for firms which present higher CEO's self-overviewing attributes in franchise industry. Second, we find that the greater the self-overviewing tendency, more strengthened cost stickiness when sales decrease. This study is meaningful in that we developed proxies for self-overviewing propensity, such as the hypodermic behaviors of franchise CEO, which have not been performed in previous studies, to enhance future studies of franchise CEO. Futhermore, we empirically provide the effects of CEO's self-overviewing attributes on the operating costs behaviors, suggesting useful information to franchise stakeholders such as prospective start-ups, franchisee and investors.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.197-199
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• 2000

연속음성인식을 수행하기 위해서는 발음사전과 언어모델이 필요하다. 이 둘 사이에는 디코딩 단위가 일치하여야 하므로 발음사전 구축시 디코딩 단위로 표제어 단위를 선정하며 표제어 사이의 음운변화 현상을 반영한 발음사전을 구축하여야 한다. 한국어에 부합하는 음운변화현상을 분석하여 학습용 자동 발음열을 생성하고, 이를 통하여 발음사전을 구축한다. 전처리 단계로 기호, 단위, 숫자 등 전처리 과정 및 형태소 분석 과정을 수행하며, 디코딩 단위인 의사 형태소 단위를 생성하기 위해 규칙을 이용한 태깅 과정을 거친다. 이를 통해 나온 결과를 발음열 생성기 입력으로 하며, 결과는 학습용 발음열 또는 발음사전 구성을 위한 형태로 출력한다. 표제어간 음운변화 현상이 반영된 상태의 표제어 단위이므로 실제 음운변화가 반영되지 않은 상태의 표제어와는 그 형태가 상이하다. 이는 연속 발음시 생기는 현상으로 실제 인식에는 이 음운변화 현상이 반영된 사전이 필요하게 된다. 생성된 발음사전의 효용성을 확인하기 위해 다음과 같은 실험을 통해 성능을 평가하였다. 음향학습을 위하여 PBS(Phonetically Balanced Sentence) 낭독체 17200문장을 녹음하고 그 전사파일을 사용하여 학습을 수행하였고, 발음사전의 평가를 위하여 이 중 각각 3100문장을 사용하여 다음과 같은 실험을 수행하였다. 형태소 태그정보를 이용하여 표제어간 음운변화 현상을 반영한 최적의 발음사전과 다중 발음사전, 언어학적 기준에 의한 수작업으로 생성한 표준 발음사전, 그리고 표제어간의 음운변화 현상을 고려하지 않고 독립된 단어로 생성한 발음사전과의 비교 실험을 수행하였다. 실험결과 표제어간 음운변화 현상을 반영하지 않은 경우 단어 인식률이 43.21%인 반면 표제어간 음운변화 현상을 반영한 1-Best 사전의 경우 48.99%, Multi 사전의 경우 50.19%로 인식률이 5~6%정도 향상되었음을 볼 수 있었고, 수작업에 의한 표준발음사전의 단어 인식률 45.90% 보다도 약 3~4% 좋은 성능을 보였다.