• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.2
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• pp.118-125
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• 1990

An optimal file allocation algorithm which seeks optimal solution of file allocation problem for efficient management and operation of information files in distributed computer system is proposed. Since file allocation time in practical applications that have many computer sites is tool long, the problem size has to be reduced and computation time is improved by using preassignment conditio. A new method which calculate appriasal value for accurrate value for accurrate representation of assigned state is proposed and the selection criteria to candidate nodes for rapid determination of allocation are given. By using selection criteria, file allocation is determined and final appraisal value represent total cost of assigned state.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.161-166
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• 2006

In this paper, CPLD low power technology mapping using reuse module selection under the time constraint is proposed. Traditional high-level synthesis do not allow reuse of complex, realistic datapath component during the task of scheduling. On the other hand, the proposed algorithm is able to approach a productivity of the design the low power to reuse which given a library of user-defined datapath component and to share of resource sharing on the switching activity in a shared resource Also, we are obtainable the optimal the scheduling result in experimental results of our using chaining and multi-cycling in the scheduling techniques. Low power circuit make using CPLD technology mapping algorithm for selection reuse module by scheduling.

• Genomics & Informatics
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• v.19 no.2
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• pp.15.1-15.7
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• 2021

The direction of evolution can estimate based on the variation among nonsynonymous to synonymous substitution. The simulative study investigated the nucleotide sequence of closely related strains of respiratory syndrome viruses, codon-by-codon with maximum likelihood analysis, z selection, and the divergence time. The simulated results, dN/dS > 1 signify that an entire substitution model tends towards the hypothesis's positive evolution. The effect of transition/transversion proportion, Z-test of selection, and the evolution associated with these respiratory syndromes, are also analyzed. Z-test of selection for neutral and positive evolution indicates lower to positive values of dN-dS (0.012, 0.019) due to multiple substitutions in a short span. Modified Nei-Gojobori (P) statistical technique results also favor multiple substitutions with the transition/transversion rate from 1 to 7. The divergence time analysis also supports the result of dN/dS and imparts substantiating proof of evolution. Results conclude that a positive evolution model, higher dN-dS, and transition/transversion ratio significantly analyzes the evolution trend of severe acute respiratory syndrome coronavirus 2, severe acute respiratory syndrome coronavirus, and Middle East respiratory syndrome coronavirus.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.430-438
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• 2021

The spatial distribution of neutron flux or reaction rate was calculated by cell or mesh tally in traditional Monte Carlo simulation. However, either cell or mesh tally leads to the increase of memory consumption and simulation time. In this paper, the function expansion tally (FET) method was developed in Reactor Monte Carlo code RMC to solve this problem. The FET method was applied to the tallies of neutron flux distributions of uranium block and PWR fuel rod models. Legendre polynomials were used in the axial direction, while Zernike polynomials were used in the radial direction. The results of flux, calculation time and memory consumption of different expansion orders were investigated, and compared with the mesh tally. Results showed that the continuous distribution of flux can be obtained by FET method. The flux distributions were consistent with that of mesh tally, while the memory consumption and simulation time can be effectively reduced. Finally, the convergence analysis of coefficients of polynomials were performed, and the selection strategy of FET order was proposed based on the statistics uncertainty of the coefficients. The proposed method can help to determine the order of FET, which was meaningful for the efficiency and accuracy of FET method.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.167-174
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• 2022

In metaheuristic algorithms such as Genetic Algorithm (GA), initial population has a significant impact as it affects the time such algorithm takes to obtain an optimal solution to the given problem. In addition, it may influence the quality of the solution obtained. In the machine learning field, feature selection is an important process to attaining a good performance model; Genetic algorithm has been utilized for this purpose by scientists. However, the characteristics of Genetic algorithm, namely random initial population generation from a vector of feature elements, may influence solution and execution time. In this paper, the use of a statistical algorithm has been introduced (Chi2) for feature relevant checks where p-values of conditional independence were considered. Features with low p-values were discarded and subject relevant subset of features to Genetic Algorithm. This is to gain a level of certainty of the fitness of features randomly selected. An ensembled-based learning model for Hepatitis has been developed for Hepatitis C stage classification. 1385 samples were used using Egyptian-dataset obtained from UCI repository. The comparative evaluation confirms decreased in execution time and an increase in model performance accuracy from 56% to 63%.

• Korean Journal of Cognitive Science
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• v.11 no.2
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• pp.37-51
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• 2000

The present study compared computer users target-selection response patterns when the targets were varied in terms of their relative location and distance from the current position of the cursor. In Experiment 1, where the mouse was used as an input device, the effects of different directions and distances of simple target(small rectangle) on target-selection response were investigated. The results of Experiment 1 can be summarized as follows: (1) Overshooting was more frequent than either undershooting or correct movement and (2) this tendency was more prominent when the targets were presented in the oblique direction or in farther location from the current cursor position. (3) Although the overshooting and undershooting were more frequent in the oblique direction, the degree of deviation was larger in horizontal and vertical direction. (4) Time spent in moving the mouse rather than that spent in planning, calibrating or clicking was found to be the most critical factor in determining total response time. In Experiment 2, effects of the font size and line-height of the target on target-selection response were compared with regard to two types of input devices(keyboard vs. mouse). The results are as follows: (1) Mouse generally yielded shorter target-selection time than keyboard. but this tendency was reversed when the targets were presented in horizontal and vertical directions. (2) In general, target-selection time was the longest in the condition of font size of 10 and line-height of 100%, and the shortest in the condition of font size of 12 and line-height of 150%. (3) When keyboard was used as the input device, target-selection time was shortest in the 150% line-height condition, whereas in the mouse condition, target-selection time tended to be increased as the line-height increased. which resulted in the significant interaction effect between input device and line-height. Finally, several issues relating to human-computer interaction were discussed based on the results of the present study.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.1-10
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• 2008

In order to high-performance data Processing, effective resource selection is needed since grid resources are composed of heterogeneous networks and OS systems in the grid environment. In this paper. we classify grid resources with data properties and user requirements for resource selection using a decision tree method. Our resource selection method can provide suitable resource selection methodology using classification with a decision tree to grid users. This paper evaluates our grid system performance with throughput. utilization, job loss, and average of turn-around time and shows experiment results of our resource selection model in comparison with those of existing resource selection models such as Condor-G and Nimrod-G. These experiment results showed that our resource selection model provides a vision of efficient grid resource selection methodology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1773-1793
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• 2023

Automated machine learning, often referred to as "AutoML," is the process of automating the time-consuming and iterative procedures that are associated with the building of machine learning models. There have been significant contributions in this area across a number of different stages of accomplishing a data-mining task, including model selection, hyper-parameter optimization, and preprocessing method selection. Among them, preprocessing method selection is a relatively new and fast growing research area. The current work is focused on the recommendation of preprocessing methods, i.e., feature subset selection (FSS) algorithms. One limitation in the existing studies regarding FSS algorithm recommendation is the use of a single learner for meta-modeling, which restricts its capabilities in the metamodeling. Moreover, the meta-modeling in the existing studies is typically based on a single group of data characterization measures (DCMs). Nonetheless, there are a number of complementary DCM groups, and their combination will allow them to leverage their diversity, resulting in improved meta-modeling. This study aims to address these limitations by proposing an architecture for preprocess method selection that uses ensemble learning for meta-modeling, namely AutoFE-Sel. To evaluate the proposed method, we performed an extensive experimental evaluation involving 8 FSS algorithms, 3 groups of DCMs, and 125 datasets. Results show that the proposed method achieves better performance compared to three baseline methods. The proposed architecture can also be easily extended to other preprocessing method selections, e.g., noise-filter selection and imbalance handling method selection.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.3
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• pp.87-95
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• 2008

The purpose of this study is to provide a decision support to select an appropriate rapid prototyping(RP) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model for molding, material property, build time and part cost that greatly affect the performance of RP machines. However, the selection of a RP is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate RP machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify RP machines that the users consider. After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of RP machines.

• Journal of the Ergonomics Society of Korea
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• v.24 no.3
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• pp.1-10
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• 2005

The primary objective of this study is to design input methods for assisting button selection tasks on a PDA screen. Familiar methods in the existing computing environments were investigated to develop aiding methods. Factors manipulated in the experiment included aiding method, button size, and users' prior experience with PDAs. A total of sixteen participants examined the usability of button selection tasks. Two types of button selection tasks were used as experimental tasks; one was selecting a target button, and the other was selecting multiple target buttons consecutively. The results showed that the aiding method and the button size had significant effects on the subjective satisfaction as well as the performance. In addition, users' prior experience with PDAs affected the performance significantly. The interaction between the aiding method and the button size was found to have significant effects on the performance. However, the interaction effect between the button size and the PDA experience was significant on the task performance time only for the multiple button selection tasks. Design considerations were proposed based on the experimental results. These can be applied to the PDA interaction design to make the PDAs more usable.