• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.235-235
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• 2022

Genome selection is a promising tool for plant and animal breeding, which uses genome-wide molecular marker data to capture large and small effect quantitative trait loci and predict the genetic value of selection candidates. Genomic selection has been shown previously to have higher prediction accuracies than conventional marker-assisted selection (MAS) for quantitative traits. In this study, the prediction accuracy of 10 agricultural traits in the wheat core group with 567 points was compared. We used a cross-validation approach to train and validate prediction accuracy to evaluate the effects of training population size and training model.As for the prediction accuracy according to the model, the prediction accuracy of 0.4 or more was evaluated except for the SVN model among the 6 models (GBLUP, LASSO, BayseA, RKHS, SVN, RF) used in most all traits. For traits such as days to heading and days to maturity, the prediction accuracy was very high, over 0.8. As for the prediction accuracy according to the training group, the prediction accuracy increased as the number of training groups increased in all traits. It was confirmed that the prediction accuracy was different in the training population according to the genetic composition regardless of the number. All training models were verified through 5-fold cross-validation. To verify the prediction ability of the training population of the wheat core collection, we compared the actual phenotype and genomic estimated breeding value using 35 breeding population. In fact, out of 10 individuals with the fastest days to heading, 5 individuals were selected through genomic selection, and 6 individuals were selected through genomic selection out of the 10 individuals with the slowest days to heading. Therefore, we confirmed the possibility of selecting individuals according to traits with only the genotype for a shorter period of time through genomic selection.

• 한국산학기술학회논문지
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• 제14권9호
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• pp.4492-4497
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• 2013

차세대 무선 네트워크 시스템에서 이동 단말은 다수의 무선 액세스 네트워크를 접속할 수 있는 능력을 갖는다. 이런 이기종 환경에서 네트워크 선택 메커니즘은 사용자에게 QoS를 보장해주기 위한 중요한 역할을 담당한다. 본 연구에서는 최적의 네트워크 선택을 위해 AHP 기법을 그룹결정방법에 적용한다. 특정 QoS를 요구하는 사용자들과 유사한 특성을 갖는 액세스 네트워크들을 각각 그룹으로 생각한다. 이 경우 비슷한 특성을 갖는 네트워크들을 그룹으로 묶어, 일차적으로 그룹간의 판별을 통해 적합한 그룹을 선택한 후, 그 그룹에서 네트워크 선택 알고리즘에 의한 네트워크 순위를 통해 최적의 네트워크를 선택해 주는 방법이다. 여기서 네트워크 선택 알고리즘은 결정요소의 가중치를 계산하는 AHP와 접근 네트워크의 등급을 결정하는 GRA 방법을 이용한다. MATLAB 시뮬레이션 결과, 제안된 시스템은 각 서비스 내 모든 사용자들이 0.9 이상의 높은 판정값으로 동일한 네트워크를 선택함을 알 수 있었다. 결과적으로 제안된 시스템은 WLAN과 UMTS의 통합망에서 기존시스템에 비해 효과적인 네트워크 선택 알고리즘임을 알 수 있다.

• Journal of Communications and Networks
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• 제17권4호
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• pp.428-439
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• 2015

In this study, we present an approach for reducing the information inaccuracy of existing star aggregation based on bypass links when there are multi-constraint QoS parameters in asymmetric networks. In our approach, bypass links with low similarity are selected. Links that are not chosen as bypass links are included in each group depending on the star's link characteristics. Moreover, each link group is aggregated differently according to the similarity of the links that make up the group. The selection of a bypass link by using link similarity reduces the existing time complexity of O($N^3$) to O(N) by virtue of the simplification of the selection process. In addition, the adaptive integration according to the characteristics of the links in each group is designed to reduce the information inaccuracy caused by static aggregation. Simulation results show that the proposed method maintains low information distortion; specifically, it is 3.8 times lower than that of the existing method, even when the number of nodes in a network increases.

• Journal of Communications and Networks
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• 제7권3호
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• pp.294-306
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• 2005

Group oriented multicast applications are becoming increasingly popular in mobile ad hoc networks (MANETs). Due to dynamic topology of MANETs, stateless multicast protocols are finding increased acceptance since they do not require maintenance of state information at intermediate nodes. Recently, several multicast schemes have been proposed which scale better' with the number of multicast sessions than traditional multicast strategies. These schemes are also known as explicit multicast (Xcast; explicit list of destinations in the packet header) or small group multicast (SGM). In this paper, we propose a new scheme for small group' multicast in MANETs named extended explicit multicast (E2M), which is implemented on top of Xcast and introduces mechanisms to make it scalable with number of group members for a given multicast session. Unlike other schemes, E2M does not make any assumptions related to network topology or node location. It is based on the novel concept of dynamic selection of Xcast forwarders (XFs) between a source and its potential destinations. The XF selection is based on group membership and the processing overhead involved in supporting the Xcast protocol at a given node. If the number of members in a given session is small, E2M behaves just like the basic Xcast scheme with no intermediate XFs. As group membership increases, nodes may dynamically decide to become an XF. This scheme, which can work with few E2M aware nodes in the network, provides transparency of stateless multicast, reduces header processing overhead, minimizes Xcast control traffic, and makes Xcast scalable with the number of group members.

• 한국지능시스템학회논문지
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• 제12권4호
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• pp.317-322
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• 2002

The major operations of Evolutionary Computation include crossover, mutation, competition and selection. Although selection does not create new individuals like crossover or mutation, a poor selection mechanism may lead to problems such as taking a long time to reach an optimal solution or even not finding it at all. In view of this, this paper proposes a hybrid Evolutionary Programming (EP) algorithm that exhibits a strong capability to move toward the global optimum even when stuck at a local minimum using a synergistic combination of the following three basic ideas. First, a "local selection" technique is used in conjunction with the normal tournament selection to help escape from a local minimum. Second, the mutation step has been improved with respect to the Fast Evolutionary Programming technique previously developed in our research group. Finally, the crossover and mutation operations of the Genetic Algorithm have been added as a parallel independent branch of the search operation of an EP to enhance search diversity.

• Asian-Australasian Journal of Animal Sciences
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• 제8권1호
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• pp.29-35
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• 1995

A selection experiment with Romney Marsh sheep was used to evaluate correlated responses to selection. The selected flock was formed in 1979 by the Romney Group Breeders where selection was for prolificacy, defined as the number of live lambs born per ewe joined per year and a randomly selected control flock was established in 1982. Selection for prolificacy resulted in (i) increased ewe fertility, (ii) increased ewe ovulation rate, (iii) increased ewe litter size, (iv) decreased ewe body weight, (v) decreased lamb birth weight and (vi) decreased lamb 8-week weight. The rates of correlated responses per year respectively for ewe fertility, ewe ovulation rate, ewe litter size, ewe body weight, lamb birth weight and lamb 8-week weight were 0.033(0.002), 0.043(0.016), 0.019(0.005), -0.017(0.066), -0.055(0.025) and -0.150(0.057).

• Industrial Engineering and Management Systems
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• 제8권1호
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• pp.47-53
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• 2009

We define product line (or mix) selection problem as selecting a subset of potential product variants that can simultaneously minimize product proliferation and maintain market coverage. Selecting the most efficient product mix is a complex problem, which requires analyses of multiple criteria. This paper proposes a method based on Data Envelopment Analysis (DEA) for product line selection. Data Envelopment Analysis (DEA) is a linear programming based technique commonly used for measuring the relative performance of a group of decision making units with multiple inputs and outputs. Although DEA has been proved to be an effective evaluation tool in many fields, it has not been applied to solve the product line selection problem. In this study, we construct a five-step method that systematically adopts DEA to solve a product line selection problem. We then apply the proposed method to an existing line of staplers to provide quantitative evidence for managers to generate desirable decisions to maximize the company profits while also fulfilling market demands.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2014년도 추계 학술논문 발표대회
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• pp.218-219
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• 2014

The selection of an appropriate contract method is vital for the successful operation of the project. However, there has been a lack of studies on objective decision making support models for use in the planning stage of a project contract. The present study had the goal of analyzing the factors that influence contract method selection, as an initial study for developing a project contract method selection model. The existing related studies were analyzed, and the factors considered in the literature were selected. Then, based on the findings, the opinions of an expert group on the important factors for contract method selection were collected through a survey. The collected opinions were analyzed using factor analysis, a statistical analysis method. The results will be utilized in the future as preliminary data for developing a decision making model for selecting a contract method.

• 한국콘텐츠학회논문지
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• 제14권7호
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• pp.242-252
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• 2014

본 연구는 리더의 나이에 따라 집단 의사 결정이 어떻게 달라지는지 알아보고자 하였다. 연구 결과, 나이 많은 리더가 나이 적은 리더에 비해 토론 중 발언 비율이 높았으며, 나이 많은 리더가 속한 집단의 결정 정확률이 더 높았다. 또한 리더의 나이가 많은 경우, 집단 구성원들은 리더의 집단 대표성과 발휘된 리더십을 더 높게 인식하고 있었다. 한편, 리더의 나이가 집단 의사 결정에 끼치는 영향은 리더 선출법에 따라 달라졌다. 리더의 나이가 적은 경우에는 체계적인 방법으로 선출된 리더 집단의 토론의 질이 높게 나타난 반면, 리더의 나이가 많은 경우에는 무작위로 선출된 리더 집단의 토론의 질이 높게 나타났다. 이와 같은 결과는 리더가 소유한 권력 기반의 차이에서 비롯된 것이라 추론할 수 있다.

• 산업공학
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• 제15권3호
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• pp.308-315
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• 2002

This study presents the web based cutting parameter selection system using Group Technology (GT). The GT is basically applied to classify and code the work material and cutting process which are main factors to affect cutting parameter selection. The proposed system has been designed to electronically select proper cutting conditions based on the stored GT database. The existing approaches used in most small and medium sized companies are basically to use manufacturing engineer's experience or to find the recommended values from the manufacturing engineers handbook. These processes are often time consuming and inconsistent, especially when a new engineer is involved. Consequently, the proposed system could automatically and consistently generate the proper cutting conditions (feed, depth of cut, and cutting speed) as soon as relatively simple data input is given thanks to the classified GT database.