• 대한인간공학회지
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• 제31권4호
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• pp.601-607
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• 2012

Objective: The aim of this study is to classify between intentional and natural blinks in vision based eye tracking system. Through implementing the classification method, we expect that the great eye tracking method will be designed which will perform well both navigation and selection interactions. Background: Currently, eye tracking is widely used in order to increase immersion and interest of user by supporting natural user interface. Even though conventional eye tracking system is well focused on navigation interaction by tracking pupil movement, there is no breakthrough selection interaction method. Method: To determine classification threshold between intentional and natural blinks, we performed experiment by capturing eye images including intentional and natural blinks from 12 subjects. By analyzing successive eye images, two features such as eye closed duration and pupil size variation after eye open were collected. Then, the classification threshold was determined by performing SVM(Support Vector Machine) training. Results: Experimental results showed that the average detection accuracy of intentional blinks was 97.4% in wearable eye tracking system environments. Also, the detecting accuracy in non-wearable camera environment was 92.9% on the basis of the above used SVM classifier. Conclusion: By combining two features using SVM, we could implement the accurate selection interaction method in vision based eye tracking system. Application: The results of this research might help to improve efficiency and usability of vision based eye tracking method by supporting reliable selection interaction scheme.

• 한국조사연구학회지:조사연구
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• 제11권3호
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• pp.103-114
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• 2010

계속조사를 위한 표본설계를 중간에 변경하려고 할 때 부딪히게 되는 문제 중 하나는 기존의 조사에서 중요하게 고려해야 할 주요 관심변수들에 대한 모집단 정보를 얻기 어렵다는 사실이다. 본 연구의 목적은 국민여행실태조사를 위한 표본설계에서 기존의 표본조사 자료와 새로운 추출틀 자료를 통합하여 효과적인 층화변수를 선정하는 방법을 제시하는 데 있다. 먼저 기존의 표본자료의 단위와 추출틀 단위 사이의 식별번호가 일치하지 않을 경우 번호 외에 일치시킬 수 있는 방안을 찾고, 이어 회귀분석과 같은 통계적 방법에 의해 변수 간의 연관성을 검토함으로써 적절한 층화변수를 선정하는 방법을 제시한다.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 1999년도 가을 학술발표회 논문집
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• pp.415-422
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• 1999

This paper describes a new optimum design approach for piled raft foundations using the genetic algorithm. The objective function considered is the cost-based total weight of raft and piles. The genetic algorithm is a search or optimization technique based on nature selection. Successive generation evolves more fit individuals on the basis of the Darwinism survival of the fittest. In formulating the genetic algorithm-based optimum design procedure, the analysis of piled raft foundations is peformed based on the 'hybrid'approach developed by Clancy(1993), and also the simple genetic algorithm proposed by the Goldberg(1989) is used. To evaluate a validity of the optimum design procedure proposed based on the genetic algorithm, comparisons regarding optimal pile placement for minimizing differential settlements by Kim et at.(1999) are made. In addition using proposed design procedure, design examples are presented.

• 한국정밀공학회지
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• 제16권1호통권94호
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• pp.116-124
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• 1999

In most conventional design optimization of dynamic system, design sensitivities are utilized. However, design sensitivities based optimization method has numbers of drawback. First, computing design sensitivities for dynamic system is mathematically difficult, and almost impossible for many complex problems as well. Second, local optimum is obtained. On the other hand, Genetic Algorithm is the search technique based on the performance of system, not on the design sensitivities. It is the search algorithm based on the mechanics of natural selection and natural genetics. GA search, differing from conventional search techniques, starts with an initial set of random solutions called a population. Each individual in the population is called a chromosome, representing a solution to the problem at hand. The chromosomes evolve through successive iterations, called generations. As the generation is repeated, the fitness values of chromosomes were maximized, and design parameters converge to the optimal. In this study, Genetic Algorithm is applied to the actual dynamic optimization problems, to determine the optimal design parameters of the dynamic system.

• 산업공학
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• 제17권2호
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• pp.242-248
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• 2004

Lot-streaming is the process of splitting a job (lot) into a number of smaller sublots to allow the overlapping of operations between successive machines in a multi-stage production system. A new genetic algorithm (NGA) is proposed for minimizing the mean weighted absolute deviation of job completion times from due dates when jobs are scheduled in a no-wait lot-streaming flow shop. In a no-wait flow shop, each sublot must be processed continuously from its start in the first machine to its completion in the last machine without any interruption on machines and without any waiting in between the machines. NGA replaces selection and mating operators of genetic algorithms (GAs), which often lead to premature convergence, by new operators (marriage and pregnancy operators) and adopts the idea of inter-chromosomal dominance. The performance of NGA is compared with that of GA and the results of computational experiments show that NGA works well for this type of problem.

• 아동학회지
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• 제22권1호
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• pp.191-211
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• 2001

This in-depth study of portfolio method centered on efficient methods of application, including teacher education. The study was carried out in 2 public kindergartens in Taegu. The efficient portfolio assessment method was developed by revisions after successive applications, observations, and discussions with the teachers of both kindergartens. The resulting efficient portfolio method is composed of step 1: portfolio conference and planning; step 2: development of the portfolio in the process of teaching and learning; step 3: selection of the materials for the portfolio; step 4: analysis of the portfolio; and step 5: use of the portfolio method. The practical application of the portfolio assessment is included in the forms used for teachers' observations of children's play and educational interventions. Teachers' interventions include verbal interaction, presentation of materials, and participating as partners. This teaching-learning method consists of teaching and assessment by sensitive and instant responses to children's needs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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• pp.3156-3167
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• 2020

One drawback of polar codes is that they are not universal, that is, to achieve optimal performance, different polar codes are required for different kinds of channel. This paper proposes a polar code construction scheme for Nakagami-m fading channel. The scheme fully considers the characteristics of Nakagami-m fading channel, and uses the optimized Bhattacharyya parameter bounds. The constructed code is applied to an orthogonal frequency division multiplexing (OFDM) system over Nakagami-m fading channel to prove the performance of polar code. Simulation result shows the proposed codes can get excellent bit error rate (BER) performance with successive cancellation list (SCL) decoding. For example, the designed polar code with cyclic redundancy check (CRC) aided SCL (L = 8) decoding achieves 1.1dB of gain over LDPC at average BER about 10^-5 under 4-quadrature amplitude modulation (4QAM) while the code length is 1024, rate is 0.5.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2002년도 정기총회 및 학술대회
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• pp.105-109
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• 2002

The main ideas of hybrid video coding methods are to reduce the spatial and temporal redundancy for efficient data compression. If compressed video stream is transmitted through the error-prone channel, bitstream can be critically damaged and the spatio-temporal error propagates through successive frames at the decoder because of drift noise in the references between encoder and decoder. In this paper, I propose the lagrangian multiplier selection method in the error-prone environment. Finally, it is shown that the performance comparisons of the R-D optimized mode decision are made against the conventional method and simulation results are given in the following.

• 산업경영시스템학회지
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• 제37권4호
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• pp.187-192
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• 2014

Lot-streaming is the process of splitting a job (lot) into sublots to allow the overlapping of operations between successive machines in a multi-stage production system. A new genetic algorithm (NGA) is proposed for an n-job, m-machine, lot-streaming flow shop scheduling problem with equal-size sublots in which the objective is to minimize the total stretch. The stretch of a job is the ratio of the amount of time the job spent before its completion to its processing time. NGA replaces the selection and mating operators of genetic algorithms (GAs) by marriage and pregnancy operators and incorporates the idea of inter-chromosomal dominance and individuals' similarities. Extensive computational experiments for medium to large-scale lot-streaming flow-shop scheduling problems have been conducted to compare the performance of NGA with that of GA.

• 한국CDE학회논문집
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• 제6권3호
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• pp.174-183
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• 2001

This study proposes an improved genetic algorithm (GA) to derive solutions for facility layout problems having inner walls and passages. The proposed algorithm models the layout of facilities on a flour-segmented chromosome. Improved solutions are produced by employing genetic operations known as selection, crossover, inversion, mutation, and refinement of these genes for successive generations. All relationships between the facilities and passages are represented as an adjacency graph. The shortest path and distance between two facilities are calculated using Dijkstra's algorithm of graph theory. Comparative testing shows that the proposed algorithm performs better than other existing algorithm for the optimal facility layout design. Finally, the proposed algorithm is applied to ship compartment layout problems with the computational results compared to an actual ship compartment layout.