• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.679-688
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• 2006

Protein-protein interaction data obtained from high-throughput experiments includes high false positives. In this paper, we introduce a new protein-protein interaction reliability verification system. The proposed system integrates various biological features related with protein-protein interactions, and then selects the most relevant and informative features among them using a feature selection method. To assess the reliability of each protein-protein interaction data, the system construct a classifier that can distinguish true interacting protein pairs from noisy protein-protein interaction data based on the selected biological evidences using a classification technique. Since the performance of feature selection methods and classification techniques depends heavily upon characteristics of data, we performed rigorous comparative analysis of various feature selection methods and classification techniques to obtain optimal performance of our system. Experimental results show that the combination of feature selection method and classification algorithms provide very powerful tools in distinguishing true interacting protein pairs from noisy protein-protein interaction dataset. Also, we investigated the effects on performances of feature selection methods and classification techniques in the proposed protein interaction verification system.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.135-140
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• 2007

Feature selection is a preprocessing technique commonly used on high dimensional data. Feature selection studies how to select a subset or list of attributes that are used to construct models describing data. Feature selection methods attempt to explore data's intrinsic properties by employing statistics or information theory. The recent developments have involved approaches like correlation method, dimensionality reduction and mutual information technique. This feature selection have become the focus of much research in areas of applications with massive and complex data sets. In this paper, we provide a feature selection method considering data characteristics and generalization capability. It provides a computational approach for feature selection based on fuzzy cluster analysis of its attribute values and its performance measures. And we apply it to the system for classifying computer virus and compared with heuristic method using the contrast concept. Experimental result shows the proposed approach can give a feature ranking, select the features, and improve the system performance.

• Journal of Construction Engineering and Project Management
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• v.7 no.2
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• pp.1-10
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• 2017

The Clonal Selection Algorithm (CSA) is an algorithm inspired by the human immune system mechanism. In CSA, several parameters needs to be optimized by large amount of sensitivity analysis for the optimal results. They limit the accuracy of the results due to the uncertainty and subjectivity. Adaptive Clonal Selection (ACS), a modified version of CSA, is developed as an algorithm without controls by pre-defined parameters in terms of selection process and mutation strength. In this paper, we discuss the ACS in detail and present its implementation in construction site utilization planning (CSUP). When applied to a developed model published in research literature, it proves that the ACS are capable of searching the optimal layout of temporary facilities on construction site based on the result of objective function, especially when the parameterization process is considered. Although the ACS still needs some improvements, obtaining a promising result when working on a same case study computed by Genetic Algorithm and Electimze algorithm prove its potential in solving more complex construction optimization problems in the future.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.51-58
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• 2017

This paper deals with the improvement of cluster head selection method in L-SEP for heterogeneous nodes among hierarchical routing protocols of wireless sensor network. Wireless sensor networks are classified into homogeneous and heterogeneous network. In heterogeneous network, SEP, L-SEP are mainly used because cluster head selection probability is different depending on node type. But, since protocol based on SEP has different cluster head selection probabilities depending on the node type, clusters that transmit data inefficiently can be formed. to improve this, it is necessary to select the cluster head that minimizes the transmission distance of member node and the cluster head. Therefore, we propose a protocol that improve the cluster head selection method.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.7
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• pp.666-670
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• 2006

This paper presents the novel feature selection method for Emotion Recognition, which may include a lot of original features. Specially, the emotion recognition in this paper treated speech signal with emotion. The feature selection has some benefits on the pattern recognition performance and 'the curse of dimension'. Thus, We implemented a simulator called 'IFS' and those result was applied to a emotion recognition system(ERS), which was also implemented for this research. Our novel feature selection method was basically affected by Reinforcement Learning and since it needs responses from human user, it is called 'Interactive feature Selection'. From performing the IFS, we could get 3 best features and applied to ERS. Comparing those results with randomly selected feature set, The 3 best features were better than the randomly selected feature set.

• 유체기계공업학회:학술대회논문집
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• 2004.12a
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• pp.189-192
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• 2004

Utilizing pump selection softwares is becoming a new general trend in pump industries, substituting the old fashioned pump catalogs. One of the most powerful pump selection softwares is developed, which features pump performance viscosity correction function as well as pump selection based on the exact pump performance curves, NPSH warning, automatic determination of impeller diameter cutting to meet the customer's performance specification, performance simulation for the rpm and diameter variation, standard motor recommendation according to the motor standards and enclosure types and automatic pump datasheet generation for sales submission, automatic pump drawings and dimension generation for installation check and part preparation. This software provides pump distributors and customers with a quick, easy and exact pump selection, various performance curves review (system curves, performance curve of series or parallel operation) of the selected pumps.

• Animal cells and systems
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• v.1 no.4
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• pp.619-627
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• 1997

Maintenance of polymorphism in a two-locus system with two alleles under stabilizing selection has been tested by Monte-Carlo simulation. The effect of each allele was additive. Only gene x environment interactions and degree of genetic linkage between loci were considered. There were no other evolutionary forces acting except stabilizing selection. Fixation rates were influenced by the extent of environmental change and the degree of genetic linkage. In most cases, stabilizing selection depleted genetic variability when two loci have a lower degree of linkage (10 cM). When two loci are closely linked (0.1 cM), however, stabilizing selection promoted balanced heterozygotes in changing environments. Thus, environment-dependent selection and recombination rate are important parameters which should be incorporated into mechanisms of maintenance of genetic variability.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.11a
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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.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.209-212
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• 2011

Selection of finishing materials in the design stage is an important management factor in terms of use safety and satisfaction, and work cost and process. However, selection of materials in the design stage is usually conducted without related guidelines or a set process, but depends on the experience of the architect or advice of materials company employees. Therefore, the aim of this study was to develop a finishing materials selection process that can be used by a architect. Materials selection related rules collected through interview with experts and five office building cases were used as knowledge. In addition, another aim of the study was to propose a prototype system interface for use in the field.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.2
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• pp.19-25
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• 2008

When there are numerous wireless communication systems co-existing in the limited available frequency resource, an unexpected time delay can be caused during the system switching. So, in order to reduce this time delay, a mode selection method is required. In this paper, we propose a mode selection method to minimize the time delay for multi-system wireless communication systems. For the sake of efficiency, the mode selection method is designed by analyzing the preamble characteristics of different standards. Instead of performing a full search, we propose the preamble partial search to reduce the time delay to a minimum. Simulated with Matlab in an additive white Gaussian noise(AWGN) environment with a signal to noise ratio(SNR) of 10dB and bit error rate(BER) of $10^{-6}$, we evaluated and showed the performance improvement gained by using our proposed mode selection method.