• 센서학회지
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• 제25권1호
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• pp.13-19
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• 2016

Nowadays, most major automobile manufacturers are very interested, and actively involved, in developing driver alcohol detection system for safety (DADSS) that serves to prevent driving under the influence. DADSS measures the blood alcohol concentration (BAC) from the driver's breath and limits the ignition of the engine of the vehicle if the BAC exceeds the reference value. In this study, to optimize the sensor array of the DADSS, we selected sensors by using three different methods, configured the sensor arrays, and then compared their performance. The Wilks' lambda, stepwise elimination and filter method (using a principal component) were used as the sensor selection methods [2,3]. We compared the performance of the arrays, by using the selectivity and sensitivity as criteria, and Sammon mapping for the analysis of the cluster type of each gas. The sensor array configured by using the stepwise elimination method exhibited the highest sensitivity and selectivity and yielded the best visual result after Sammon mapping.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2007년도 한국지능정보시스템학회
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• pp.218-225
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• 2007

Recommendation system is one way of implementing personalized service. The collaborative filtering is one of the major techniques that have been employed for recommendation systems. It has proven its effectiveness in the recommendation systems for such domain as motion picture or music. However, it has some limitations, i.e., sparsity and scalability. In this research, as one way of overcoming such limitations, we proposed the stepwise collaborative filtering method. To show the practicality of our proposed method, we designed and implemented a movie recommendation system which we shall call Step_CF, and its performance was evaluated using MovieLens data. The performance of Step_CF was better than that of Basic_CF that was implemented using the original collaborative filtering method.

• Communications for Statistical Applications and Methods
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• 제23권1호
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• pp.57-70
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• 2016

Type-II progressive censoring is one of the censoring methods frequently used in clinical studies, reliability trials, quality control of products and industrial experiments. Sometimes in Type-II progressive censoring experiments, the failure rate is low so the waiting time to observe the $m^{th}$ failure will be very long; however, the experimenter may have to terminate the experiment before a predetermined time. In this article, if two generalized types of Type-II progressive censoring are reminded, we then make some changes in the removal method of Type-II progressive censoring such that without reducing the deduction quality, the termination time of the experiment decreases. This can be done with decreasing withdraws throughout the steps of the experiment with a special reasonable method. A simulation study is done and the results are tabulated at the end of this article for a comparison between introduced method and Type-II progressive censoring.

• Mass Spectrometry Letters
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• 제9권1호
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• pp.30-36
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• 2018

A quantitation method for free amino acids in human serum was developed using a stepwise-dilution method and a bimodal cation exchange (CEX)/hydrophilic interaction liquid chromatography (HILIC)-tandem mass spectrometry system equipped with an electrospray ionization source (ESI/MS/MS). This method, which was validated using quality control samples, was optimized for enhanced selectivity and sensitivity. Dithiothreitol (DTT) was used as a reducing agent to prevent the oxidation of a serum sample ($50{\mu}L$), which was then subjected to stepwise dilution using 3, 30, and 90 volumes of acetonitrile containing 0.1% formic acid. Chromatographic separation was performed on an Imtakt Intrada Amino Acid column ($50mm{\times}3mm$, $3{\mu}m$) in mixed mode packed with CEX and HILIC ligands embedded in the stationary phase. Underivatized free amino acids were eluted and separated within 10 min. As a result of the validation, the precision and accuracy for the inter- and intraday assays were determined as 2.11-11.51% and 92.82-109.40%, respectively. The lowest limit of quantification (LLOQ) was $0.5-4.0{\mu}g/mL$ and the matrix effect was 80.22-115.93%. The proposed method was successfully applied to the quantitative analysis of free amino acids in human serum.

• 지식경영연구
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• 제13권5호
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• pp.43-64
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• 2012

Emerging technologies have significant implications in establishing competitive advantages and are characterized by continuous rapid development. Efficient benchmarking is more and more important in the development of emerging technologies. Similar input level and importance are two necessary criteria need to be considered for emerging technology's benchmarking. In this study, we proposed a sequential use of self-organizing map(SOM), data envelopment analysis(DEA) and analytical hierarchy process(AHP) method for the stepwise benchmarking of emerging technology. The proposed method uses two-level SOM to cluster the emerging technologies with similar required input levels together, then, in each cluster, uses DEA-BCC model to evaluate the efficiencies of the emerging technologies and do tier analysis to form tiers. On each tier, AHP rating method is used to calculate each emerging technology's importance priority. The optimal benchmarking path of each cluster is established by connecting the emerging technologies with the highest importance priority. In order to validate the proposed method, we apply it to a case of biotechnology. The result shows the proposed method can overcome difficulties in benchmarking, select suitable benchmarking targets and make the benchmarking process more efficient and reasonable.

• KIEE International Transactions on Power Engineering
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• 제2A권3호
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• pp.121-128
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• 2002

This study proposes a new method for transmission system expansion planning using fuzzy integer programming. It presents stepwise cost characteristics analysis which is a practical condition of an actual system. A branch and bound method which includes the network flow method and the maximum flow - minimum cut set theorem has been used in order to carry out the stepwise cost characteristics analysis. Uncertainties of the permissibility of the construction cost and the lenient reserve rate and load forecasting of expansion planning have been included and also processed using the fuzzy set theory in this study. In order to carry out the latter analysis, the solving procedure is illustrated in detail by the branch and bound method which includes the network flow method and maximum flow-minimum cut set theorem. Finally, case studies on the 21- bus test system show that the algorithm proposed is efficiently applicable to the practical expansion planning of transmission systems in the future.

• 한국지능시스템학회논문지
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• 제19권4호
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• pp.574-579
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• 2009

복잡한 비선형 회귀문제들에서 최적의 신경망을 구축하기 위해서는 구조의 선정 및 노이즈에 의한 과잉학습(overtraining)등에 따른 많은 문제들이 있다. 본 논문에서는 flexible incremental 알고리즘을 이용하여 단계적으로 최적의 신경망을 구축하는 방법을 제안한다. Flexible incremental 알고리즘은 예측 잔류오차를 최소화하기 위해 단계적으로 추가되어지는 은닉노드 개수를 검증데이터를 이용하여 신축성 있게 조절하고, 빠른 학습을 위하여 ELM (Extreme Learning Machine)을 이용한다. 제안된 방법은 신경망의 구축과정에서 사용자의 어떠한 관여 없이도 빠른 학습과 적은 수의 은닉노드들에 의한 범용 근사화 (universal approximation)가 가능한 신경망의 구축이 가능한 장점을 가지고 있다. 다양한 종류의 벤치마크 데이터들을 이용한 실험 결과를 통하여 제안된 방법이 실제 회귀문제들에서 우수한 성능을 가짐을 확인하였다.

• Journal of the Korean Data and Information Science Society
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• 제21권3호
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• pp.513-521
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• 2010

대부분의 대학들은 교수업적평가를 위해 강의평가제도를 실시하고 있다. 그러나 강의평가의 결과는 강좌규모, 강의형태, 개설학년, 이수구분, 평균평점 등과 같은 개설강좌의 특성에 많은 영향을 받게 된다. 따라서 이러한 각 강좌특성들이 강의평가 결과에 영향을 미치는 효과를 제거하지 않는다면, 담당교수가 강의평가 결과에 대한 공정성과 객관성을 신뢰할 수 없게 만들 정도로 심각한 편의를 갖게 된다. 따라서 강의평가의 공정성을 위해 강좌특성에 따른 편의를 제거하기 위한 사후조정된 점수가 요구된다. 따라서 본 연구에서는 단계적 변수선택법에 의한 회귀분석을 이용하여 강의평가 결과에 대한 균등화 방법을 이용하여 사후조정된 점수를 계산하는 방법을 제안한다. 그리고 제안된 방법은 기존의 방법과 비교를 하였다.

• 한국인터넷방송통신학회논문지
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• 제21권4호
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• pp.183-188
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• 2021

협력 필터링 기반의 추천 시스템은 현재 다양한 분야의 상업용 시스템의 필수불가결한 기능으로서, 사용자들이 선호할만한 상품을 맞춤형으로 제공해 주는 유용한 서비스이다. 그러나, 사용자들의 평가 데이타가 불충분할 경우 선호상품의 예측이 부정확할 우려가 크다. 본 연구에서는 이러한 단점을 해결하기 위하여 단계적으로 상품의 평가치를 예측하는 방안을 제시한다. 각 단계에 해당하는 예측 방법의 적용 조건을 만족하지 못할 경우 다음 단계의 방법을 적용한다. 제안 방법의 성능 평가를 위해, 공개 데이터셋을 활용한 실험을 진행하였으며, 제안 방법은 여러 전통적 유사도 척도를 도입한 협력 필터링 시스템의 예측 성능과 정밀도 성능을 크게 향상시켰고, 평가데이터 희소성 해결을 위한 기존 방식들의 성능을 능가하는 결과를 보였다.

• 한국CDE학회논문집
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• 제4권2호
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• pp.100-109
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• 1999

The bearing design includes the steps of selection bering type, selection bearing subtype, and determining the peripheral equipments. In this paper decision making methodologies are compared to propose a stepwise decision methodology to the bearing selection problem. An artificial neural network trained with design cases is used for selecting a bearing type in the first step. Then the subtype of the bearing is selected using the weighting method, high is a kind of multi-criteria decision making method. Finally, the types of peripheral equipments such as lubrication devices, seals and bearing housings are determined using a rule-based expert system.