• Journal of the Korean Statistical Society
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• 제6권2호
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• pp.103-115
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• 1977

A strategy for selecting subsets of variables from a given linear model in a mixture system is discussed. The purpose is to achieve better fitting surfaces for estimation of the response in an experimental region of interest. A criterion is proposed for screening variables and illustrated with an example.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권1호
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• pp.38-59
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• 2022

Web services instances can be classified into two categories, namely trusted and untrusted from users. A web service with high throughput (TP) and low response time (RT) instance values is a trusted web service. Web services are not trustworthy due to the mismatch in the guaranteed instance values and the actual values achieved by users. To perform web services selection from users' attained TP and RT values, we need to verify the correct prediction of trusted and untrusted instances from invoked web services. This accurate prediction of web services instances is used to perform the selection of web services. We propose to construct fuzzy rules to label web services instances correctly. This paper presents web services selection using a well-known machine learning algorithm, namely REPTree, for the correct prediction of trusted and untrusted instances. Performance comparison of REPTree with five machine learning models is conducted on web services datasets. We have performed experiments on web services datasets using a ten k-fold cross-validation method. To evaluate the performance of the REPTree classifier, we used accuracy metrics (Sensitivity and Specificity). Experimental results showed that web service (WS1) gained top selection score with the (47.0588%) trusted instances, and web service (WS2) was selected the least with (25.00%) trusted instances. Evaluation results of the proposed web services selection approach were found as (asymptotic sig. = 0.019), demonstrating the relationship between final selection and recommended trust score of web services.

• 응용통계연구
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• 제33권1호
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• pp.1-10
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• 2020

본 연구에서는 선형회귀모형에서 이상치와 변수변환을 고려한 변수선택 알고리즘을 다룬다. 제안된 방법은 잠재적 이상치를 탐지하여 제거한 후 변수변환 추정을 위해 최소 절사 제곱 추정법을 적용하며 가능한 모든 회귀모형을 비교하여 최종적으로 변수를 선택한다. 정확한 변수 선택과 추정된 모델의 적합도의 맥락에서 방법의 효율성을 보여주기 위해 실제 데이터 분석 및 시뮬레이션 결과가 제시된다.

• 한국컴퓨터정보학회논문지
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• 제12권4호
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• pp.43-52
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• 2007

공개 웹 서비스의 수효가 증가하면 동일한 기능을 제공하는 웹 서비스가 여러 개 존재하게 될 것이다. 이들은 가격, 응답 시간, 가용성 등 다양한 QoS 특성들을 가지게 되는데, 주어진 QoS 제약을 만족하며 가장 적합한 서비스를 선택하는 것은 매우 중요한 작업이다. 본 논문에서는 비즈니스 프로세스의 병행 분기와 응답시간 제약을 중점적으로 고려하여 서비스의 선택 모형을 연구하였다. 다차원 다중선택 Knapsack 모형을 기본으로, 각 프로세스 실행 경로 별로 응답시간 제약조건을 갖는 방안과 전체 서비스 타입에 대하여 하나의 응답시간 제약조건을 갖는 방안, 그리고 특정 경로에 대해서만 응답시간 제약 조건을 적용하는 방안을 제시하고, 실험을 통하여 서비스 수, 병행 분기의 수 그리고 제약 조건 값의 크기 등의 변화에 따른 각 방안의 성능을 살펴보았다. 실험에 사용된 데이터를 기준으로 볼 때, 파레토 우세를 이용하여 후보 서비스 수를 줄이는 것은 매우 효과적이며, 중소규모의 복합 웹 서비스에서는 전체 서비스 타입에 대하여 하나의 응답시간 제약을 설정한 방안이 실행시간과 탐색 해의 최적 해 근접도 면에서 효율적인 것으로 분석되었다.

• Journal of Animal Science and Technology
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• 제44권6호
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• pp.669-676
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• 2002

유전표지인자를 이용한 선발(marker assisted selection; MAS)과 전통적인 표현형기록에 근거한 반응의 비교분석을 위하여 고정효과모델(deterministic model)을 이용하여 시뮬레이션을 하였다. 자신의 단일 기록을 이용한 경우와 자신의 기록과 자신의 표지인자 정보를 이용할 경우 유전력이 높을수록 MAS의 효율성이 38%정도 높게 나타났다. 그러나 유전력이 높은 경우(50%) MAS의 효율성은 약 1%정도로서 효율성이 대단히 낮은 것으로 나타났다. 자신의 기록과 부모의 표현형 정보에 표지인자 정보를 추가할 경우 MAS의 효율성은 27% 정도였으며 마찬가지로 유전력이 높은 경우에는 효율성이 0에 가깝게 나타났다. MAS의 효율성은 유전력이 낮을수록 그리고 이용한 표지인자의 유전적 변이가 클수록 효율성이 높아지는 것으로 나타났다.

• Genomics & Informatics
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• 제19권1호
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• pp.10.1-10.7
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• 2021

Although many models have been proposed to accurately predict the response of drugs in cell lines recent years, understanding the genome related to drug response is also the key for completing oncology precision medicine. In this paper, based on the cancer cell line gene expression and the drug response data, we established a reliable and accurate drug response prediction model and found predictor genes for some drugs of interest. To this end, we first performed pre-selection of genes based on the Pearson correlation coefficient and then used ElasticNet regression model for drug response prediction and fine gene selection. To find more reliable set of predictor genes, we performed regression twice for each drug, one with IC₅₀ and the other with area under the curve (AUC) (or activity area). For the 12 drugs we tested, the predictive performance in terms of Pearson correlation coefficient exceeded 0.6 and the highest one was 17-AAG for which Pearson correlation coefficient was 0.811 for IC₅₀ and 0.81 for AUC. We identify common predictor genes for IC₅₀ and AUC, with which the performance was similar to those with genes separately found for IC₅₀ and AUC, but with much smaller number of predictor genes. By using only common predictor genes, the highest performance was AZD6244 (0.8016 for IC₅₀, 0.7945 for AUC) with 321 predictor genes.

• 음성과학
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• 제11권3호
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• pp.201-211
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• 2004

This paper introduces a development of an electrical stimulator for auditory stimulation. The electrical stimulator is useful in neurotological diagnosis, audiological evaluation, candidate selection for cochlear implantation, optimal device selection and decision making of MAP strategy for severe-to-profound hearing impaired persons. The development was based on sound parameters of auditory brainstem responses and auditory electrophysiological characteristic such as effective firing of auditory nerve and recording evoked potentials during refractory period of neuron. Besides pulse parameter could adjustable by programming for more varied electrical stimulation evoked response audiometry. Using the electrical stimulator, electrical square pulse was applied to promontory, and electrically evoked auditory brainstem response and electrically middle latency response were successfully recorded in cats.

• Asian-Australasian Journal of Animal Sciences
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• 제16권6호
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• pp.789-793
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• 2003

An investigation was conducted on 729 Hariana cows maintained at Government Livestock Farm, Hisar, from 1973 to 1999, with an objective to compare the efficiency of various selection indices for attaining desired genetic gains in the index traits. The various traits included were age at first calving (AFC), service period (SP), calving interval (CI), days to first service (DFS), number of services per conception (NSPC), lactation milk yield (LY), peak yield (PY), dry period (DP). Except for LY, PY and AFC the heritabilities of all other traits were low. Desirable associations among reproductive traits are supportive of the fact that any one of these traits incorporated in simultaneous selection is expected to cause correlated response in other traits. Production traits (LY and PY) were positively correlated, while DP had low negative genetic correlation with LY, and high genetic correlation with PY. Thus, DP can be taken as additional criteria in selection index for better over all improvement. Almost all production traits except DP had low negative correlation with AFC, SP, DFS and CI meaning that reduction in reproduction traits up to certain level may increase production performance. While, the correlation of NSPC with LY and PY was moderate positive. Among four trait indices I23: incorporating PY, AFC, SP and NSPC and among three trait indices I1: incorporating LY, AFC and SP were the best as these required least number of generations (4.87 and 1.35, respectively) to attain desired goals. Next in order of preference were PY or LY along with DP and SP as the best indices (I20 and I16) of which, index with PY may be preferred instead of LY as it produced considerably high correlated response in LY and reduction in NSPC as well.

• Earthquakes and Structures
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• 제11권3호
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• pp.445-459
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• 2016

Quantitative estimation of seismic response of various structural systems at the collapse limit state is one of the most significant objectives in Performance-Based Earthquake Engineering (PBEE). Assessing the effects of uncertainties, due to variability in ground motion characteristics and random nature of earthquakes, on nonlinear structural response is a pivotal issue regarding collapse safety prediction. Incremental Dynamic Analysis (IDA) and fragility curves are utilized to estimate demand parameters and seismic performance levels of structures. Since producing these curves based on a large number of nonlinear dynamic analyses would be time-consuming, selection of appropriate earthquake ground motion records resulting in reliable responses with sufficient accuracy seems to be quite essential. The aim of this research study is to propose a methodology to assess the seismic behavior of reinforced concrete frames at collapse limit state via accurate estimation of seismic fragility curves for different Engineering Demand Parameters (EDPs) by using a limited number of ground motion records. Research results demonstrate that accurate estimating of structural collapse capacity is feasible through applying the proposed method offering an appropriate suite of limited ground motion records.

• 한국전자통신학회논문지
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• 제2권3호
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• pp.174-179
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• 2007

본 논문에서는 유전자 알고리듬을 이용하여 전력, 면적, 속도를 고려한 저전력 모듈 선택을 제안한다. 제안한 알고리듬은 최적의 모듈 선택을 통해서 전력 소모를 최소화 할 수 있다. 비교 실험에서는 최적 모듈 선택을 고려한 알고리듬은 최대 전력 감소량은 26.9 %를 얻을 수 있었고, 반면에 최소 전력 감소량은 9.0% 얻었다. 모든 벤치마크 평균 전력 감소량은 15.525%가 되었다.