• 한국항해항만학회지
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• 제33권4호
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• pp.271-275
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• 2009

A strategic decision making on location selection for product transportation includes many tangible and untangible factors. To choose the best locations is a difficult job in the sense that objectives usually conflict with each other. In this paper, we consider a multi stage multi criteria transshipment problem with different types of items to be transported from the sources to the destination points. For the optimization of the problem, a goal programming formulation will be presented in which the location selection for each product type will be determined under the multi objective criteria. In the study, we generalize the transshipment model with a variety of product types and finite number of different intermediate nodes between origins and destinations. For the selection of the criteria we selected the costs(fixed cost and transportation cost), location numbers, and unsatisfied demand for each type of products in multi stage transportation, which are the main goals in transshipment modelling problems. The related conditions are also modelled through linear formats.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권2호
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• pp.231-235
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• 2004

According to revealing the DNA sequence of human and living things, it increases that a demand on a new computational processing method which utilizes DNA sequence information. In this paper we propose a classification algorithm based on negative selection of the immune system to classify DNA patterns. Negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes n group of antigenic receptor for n different patterns, they can classify into n patterns. In this paper we propose a pattern classification algorithm based on negative selection in nucleotide base level and amino acid level.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권3호
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• pp.477-493
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• 2011

The IEEE 802.16 mobile multi-hop relay (MMR) task group 'j' (TGj) has introduced the multi-hop relaying concept in the IEEE 802.16 Wireless MAN, wherein a relay station (RS) is employed to improve network coverage and capacity. Several RSs can be deployed between a base station and mobile stations, and configured to form a tree-like multi-hop topology. In such architecture, we consider the problem of a path selection through which the mobile station in and outside the coverage can communicate with the base station. In this paper, we propose a new path selection algorithm that ensures more efficient distribution of resources such as bandwidth among the relaying nodes for improving the overall performance of the network. Performance of our proposed scheme is compared with the path selection algorithms based on loss rate and the shortest path algorithm. Based on the simulation results using ns-2, we show our proposal significantly improves the performance on throughput, latency and bandwidth consumption.

• Journal of Communications and Networks
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• 제18권3호
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• pp.320-326
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• 2016

In existing literature on multiple-input multiple-output (MIMO) relaying communication systems, antenna selection is often implemented by maximizing the channel capacity or the output single-to-noise ratio (SNR). In this paper, we propose an energy-efficient low-complexity antenna selection scheme for MIMO relaying communication systems. The proposed algorithm is based on beamforming and maximizing the Frobenius norm to jointly optimize the transmit power, number of active antennas, and antenna subsets at the source, relaying and destination. We maximize the energy efficiency between the link of source to relay and the link of relay to destination to obtain the maximum energy efficiency of the system, subject to the SNR constraint. Compared to existing antenna selection methods forMIMO relaying communication systems, simulation results demonstrate that the proposed method can save more power in term of energy efficiency, while having lower computational complexity.

• 한국컴퓨터정보학회논문지
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• 제23권9호
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• pp.7-13
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• 2018

Recent advancement in data gathering technique improves the capability of information collecting, thus allowing the learning process between gathered data patterns and application sub-tasks. A pattern can be associated with multiple labels, demanding multi-label learning capability, resulting in significant attention to multi-label feature selection since it can improve multi-label learning accuracy. However, existing evolutionary multi-label feature selection methods suffer from ineffective search process. In this study, we propose a evolutionary search process for the task of multi-label feature selection problem. The proposed method creates large set of offspring or new feature subsets and then retains the most promising feature subset. Experimental results demonstrate that the proposed method can identify feature subsets giving good multi-label classification accuracy much faster than conventional methods.

• 한국컴퓨터정보학회논문지
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• 제24권2호
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• pp.171-177
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• 2019

This paper aims to find the most effective feature selection method for the sake of opinion mining tasks. Basically, opinion mining tasks belong to sentiment analysis, which is to categorize opinions of the online texts into positive and negative from a text mining point of view. By using the five product groups dataset such as apparel, books, DVDs, electronics, and kitchen, TF-IDF and Bag-of-Words(BOW) fare calculated to form the product review feature sets. Next, we applied the feature selection methods to see which method reveals most robust results. The results show that the stacking classifier based on those features out of applying Information Gain feature selection method yields best result.

• 한국식생활문화학회지
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• 제27권1호
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• pp.49-56
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• 2012

The purpose of this study was to understand the influence of instant noodle's selection attribution on satisfaction and to empirically analyze whether or not grade (elementary schoolchildren, middle school students, high school students) plays a moderating role in the relationship between selection attribution and satisfaction. Further, this study examined the differences in demographic characteristics among two groups of subjects divided by instant noodle's selection attribution. Based on a total of 1021 samples, this study verified a total of 3 hypotheses using the SPSS program. Data were analyzed by frequency analysis, chi-square, t-test, factor analysis, reliability analysis, cluster analysis, discriminant analysis, and hierarchical regression analysis. Results of the study were as follows. There were three different instant noodle's selection attributions among the children and adolescents investigated: internal element, external element, and company reliability. The multiple regression results show that internal element (=.391), external element (=.239), and company reliability (=.063) among customers' selection attributions had significant positive effects on satisfaction. In addition, the effect of selection attribution upon satisfaction was partially moderated according to grade. Further, cluster analysis divided subjects into two groups according to instant noodle's selection attribution: high-selection group vs. low-selection group. The wo groups of subjects classified by instant noodle's selection attribution were also different from each other in demographic characteristics. Limitations and future research directions are also discussed.

• 대한치과보철학회지
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• 제42권5호
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• pp.544-555
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• 2004

Statement of problem: Shade selection has traditionally been accomplished by visual examination, which is particularly relevant to the shade selection of anterior teeth, but the subjective nature of visual analysis can lead to errors in shade matching. Recently shade selection systems have been developed to provide a more objective and scientific approach to understanding and clarifying shade selection. Purpose : The purpose of this study was analysis of various shade analyzing equipment with the goal of providing a more objective shade selection. Materials and method: Visual shade matching system selection(Vita Lumin Vacuum shade guide, Vitapan 3D Master shade guide) and mechanical shade matching method($ShadeEye^{(R)}$-EX Chroma Meter, $Shadescan^{TM}$ System) used for this study. The shade guide tap specimens for 10 extracted maxillary anterior teeth were produced by selecting shades using each shade matching system. The accuracy of the selection of shades for the teeth and fabricated specimens were evaluated by analyzing the calculated shade difference(${\Delta}E^*$), using a spectrophotometer and calculating the output of value $L^*,\;a^*,\;b^*$. Results and conclusion: The results show that the average ${\{Delta}E^*$ value (difference of shade) of the shade tap specimens to the actual specimen decreased in the following order: Vita Lumin Vacuum Shade Guide(VL), $ShadeEye^{(R)}$-EX Chroma Meter(SE) Vitapan 3D Master Shade guide(V3), and $Shadescan^{TM}$ System(55) : and that there are significant statistical differences between the VL and SS (p<0.05). In the analysis of the ${\Delta}E^*$ (difference of shade) value,40% of the VL group was found to be less than 3.3 (limit value of shade tap specimens clinically acceptable), 60% in the V3 group, 50% in the SE group, and 80% in the SS group.

• Journal of the Korean Data and Information Science Society
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• 제27권5호
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• pp.1317-1325
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• 2016

본 연구에서는 한국고용정보원에서 실시한 "2013 고졸자 취업진로조사" 자료를 활용하여 특성화고 졸업자의 임금결정요인을 분석하였다. 일반적으로 임금은 개인의 취업여부와 임금의 크기에 대한 두 가지의 복합적인 정보를 담고 있다. 그러나 임금 결정요인분석의 많은 선행연구에서는 후자의 정보만을 대상으로 최소제곱법에 기초한 선형 회귀분석을 수행함으로써 표본선택에 의한 편의 (sample selection bias) 문제가 발생하게 된다. 본 연구에서는 임금결정요인분석에서 표본선택에 의한 편의 문제를 극복하기 위해 Tobit 모형과 Heckman의 표본선택 모형을 분석에 활용하였다. 주요 분석 결과를 요약하면 다음과 같다. 먼저 Tobit 모형과 Heckman의 표본선택 모형에 대한 타당성은 통계적으로 유의함을 알 수 있었다. 성별은 취업확률과 임금의 크기에서 모두 통계적으로 유의한 것으로 나타났다. 마이스터고 졸업생은 취업확률과 임금의 크기 모두 기타고 졸업생에 비해서 높은 것을 알 수 있었으며, 부모소득이 높을수록 취업확률과 임금의 크기가 모두 통계적으로 유의하게 증가하였다. 부모학력이 고졸이하에 비해서 대졸이상이 취업확률은 통계적으로 유의하게 낮지만, 임금의 크기는 높게 나타났다. 고교성적은 높을수록, 고교 만족도가 높을수록, 그리고 자격증 수가 많을수록 취업확률과 임금의 크기 모두 통계적으로 유의하게 높은 것을 알 수 있다.

• 한국학교수학회논문집
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• 제18권4호
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• pp.431-448
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• 2015

초등교사 임용후보자 선정 경쟁시험은 초등교사의 수학을 가르치기 위한 지식(MKT)을 의미 있게 측정하고, 나아가 MKT를 신장시킬 수 있는 방향으로 시행되어야 한다. 이를 위해서는 먼저 현재까지 임용시험에서 출제된 문항들에 대한 분석이 면밀한 이루어져야 할 것이다. 이에 본 연구에서는 2000년 이후 출제된 초등교사 임용시험에서 수학 교과 문항 84개의 출제 동향을 문항 유형, 대상 학년, 내용 영역, 주제별로 기준을 설정하여 임용시험의 전체적인 경향을 구체적으로 분석하고, 초등 교사의 MKT와 관련하여 분석의 결과를 도출하였다. 분석 결과, 임용시험은 문항 유형에서 서답형(71.4%)이 주로 출제되었고, 대상 학년에서는 통합 학년(41.7%)의 문제 출제 비중이 높은 것으로 나타났다. 또한, 내용 영역의 측면에서는 수와 연산(31.0%), 측정(23.8%), 도형(15.5%) 영역의 순으로 출제 비중이 높았다. 주제별 동향에서는 교과서/지도서(34.5%), 문제해결(26.2%), 학습심리(13.1%)의 순으로 비중이 높았지만, 평가와 관련된 문항은 없는 것으로 나타났다. 본 연구는 임용시험의 초등수학 출제 문항으로 2000년 이후의 모든 문항을 선행 연구의 기준을 구체화하여 분석하였으며, 초등교사의 MKT와 관련하여 분석의 결과를 도출하였다는 점에서 의미를 갖는다.