• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.19 no.1
• /
• pp.94-100
• /
• 2010

Nowadays, several nontraditional machining(NTM) processes are widely used to machine a complex and accurate shape part of hard materials, such as titanium, ceramics, high strength temperature resistant and refractory materials which are difficult to machine and having high strength, hardness, toughness. Machining of these complex shapes in such materials by traditional machining processes are very difficult. The NTM processes is important in the areas of micro- and nano scale machining, where high accuracy and superior surface characteristics are required, which can only be achieved using these NTM processes. So, for effective selection of different NTM processes, careful decision making for a given NTM application is often necessary. An appropriate NTM process for a given material and shape condition is very difficult for the novice engineers. In this paper, an expert system based on an analytic network process(ANP) is suggested for a best selection of NTM process in a NTM application considering an prior interdependency effect among various factors.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.2 no.2
• /
• pp.3-33
• /
• 1992

The successful application of fuzzy reasoning models to fuzzy control systems depends on a number of parameters, such as fuzzy membership functions, that are usually decided upon subjectively. It is shown ill this paper that the performance of fuzzy control systems call be improved if the fuzzy reasoning model is supplemented by a genetic-based learning mechanism. The genetic algorithm enables us to generate all optimal set of parameters for the fuzzy reasoning model based either on their initial subjective selection or on a random selection. It is shown that if knowledge of the domain is available, it is exploited by the genetic algorithm leading to an even better performance of the fuzzy controller.

• Journal of Technology Innovation
• /
• v.12 no.1
• /
• pp.271-285
• /
• 2004

The purpose of this paper is an application of AHP in the problem of exportable nuclear technology selection based on data gathered from nuclear experts. In this paper, the decision criteria for evaluating export competitiveness of nuclear technologies are identified and the hierarchical structure of decision making process is developed systematically. Subsequently the values of weights for relative importance among decision criteria are derived using AHP methodology, and the score of importance of nuclear technologies with respect to each criterion is evaluated. Finally the score indicating exportability of each nuclear technology is quantified in order to prioritize then. We discuss implications of our results with a viewpoint of national nuclear technology policy.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2000.04a
• /
• pp.231-234
• /
• 2000

This paper was studied to present a model for the application of AHP to the selection of airliners. For this study, a questionnaire was developed in respect to the criteria of airliner and given to 80 airline pilots and 30 maintenances in airlines to ask their opinions about the candidates for the middle-range airliners. The AHP software developed by Korean Advanced Institute of Science Technology (KAIST) was used to process the data. The result was analyzed by the criteria of selecting airliners and the several alternatives for the middle-range airliners.

• Proceedings of the Korea Contents Association Conference
• /
• 2007.11a
• /
• pp.265-269
• /
• 2007

We should select suitable application research project to carry out e-Science research in successfuly and make the reseach implement plan such as developing component technology and preparing infrastructure. On this study, the e-Science projects pool will be composed from technology forecasting and national R&D projects and evaluated the project by making evaluation models.

• International Journal of Industrial Entomology and Biomaterials
• /
• v.15 no.2
• /
• pp.145-155
• /
• 2007

Mulberry (Morus spp.) is an economically important tree crop being cultivated in India, China and other sericulturally important countries for its foliage to feed the silk producing insect Bombyx mori L. Genetic improvements of mulberry lag behind to the same in many other economically less important crops due to the complexity of its genetics, the breeding behavior, and the lack of basic information on factors governing important agronomic traits. In this review, the general usage and advantages of different molecular markers including isoenzymes, RFLPs, RAPDs, ISSRs, SSRs, AFLPs and SNPs are described to enlighten their applicability in mulberry genetic improvement programs. Application of DNA markers in germplasm characterization, construction of genetic linkage maps, QTL identification and in marker-assisted selection was also described along with its present status and future prospects.

• Journal of Korean Society of Forest Science
• /
• v.94 no.2 s.159
• /
• pp.82-89
• /
• 2005

The purpose of this paper is to investigate index numbers by conducting various comparisons among the widely used index formulas. The comparison is considered in three ways; 1) divergences in the magnitudes of index numbers due to the use of different formulas (Laspeyres, Paasche, Fisher, and Tornqvist); 2) the effect of selection of base year (fixed-year base vs. chain-type); 3) the degree of approximation of indirect to direct quantity index. The empirical application is to sawmills and planing mills industry of U.S. using a national time series data covering years of 1948-2000. The results show that the differences between Laspeyres and Paasche index can be substantial in some cases while the difference between Fisher and Tornqvist index is minimal. We also confirm that the selection of base year can cause significant divergences, especially when the variables undergo rapid price or quantity changes over time. We find that indirect quantity index approximates direct quantity index reasonably well in U.S. sawmill industry.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.23 no.58
• /
• pp.119-128
• /
• 2000

The purpose of this study was to verify the determinants of person-organization(P-O) fit and its effects on job satisfaction and turnover intention. As a result of empirical survey, value congruence, job choice decision and similar occupation are confirmed as factors that affect on P-O Fit. And the effect of P-O fit on job satisfaction and turnover intention was significant. This findings indicated that P-O fit model can be used for organization to improve employee performance. Some limitations of this study and strategic application of P-O fit model for employee selection and retention were also discussed.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2017.06a
• /
• pp.58-58
• /
• 2017

The advent of next generation sequencing technology has elicited plenty of sequencing data available in agriculturally relevant plant species. For most crop species, it is too expensive to obtain the whole genome sequence data with sufficient coverage. Thus, many approaches have been developed to bring down the cost of NGS. Genotyping-by-sequencing (GBS) is a cost-effective genotyping method for complex genetic populations. GBS can be used for the analysis of genomic selection (GS), genome-wide association study (GWAS) and constructing haplotype and genetic linkage maps in a variety of plant species. For efficiently dealing with plant GBS data, the TASSEL-GBS pipeline is one of the most popular choices for many researchers. TASSEL-GBS is JAVA based a software package to obtain genotyping data from raw GBS sequences. Here, we describe application of GBS and bioinformatics pipeline of TASSEL-GBS for analyzing plant genetics data.

• Journal of Communications and Networks
• /
• v.9 no.1
• /
• pp.67-74
• /
• 2007

The performance of dual diversity receivers operating over correlated Ricean fading channels is analyzed. Using a previously derived rapidly converging infinite series representation for the bivariate Ricean probability density function, analytical expressions for the statistics of dual-branch selection combining, maximal-ratio combining, and equal-gain combining output signal-to-noise ratio (SNR) are derived. These expressions are employed to obtain novel analytical formulae for the average output SNR, amount of fading, average bit error probability, and outage probability. The proposed mathematical analysis is used to study various novel performance evaluation results with parameters of interest the fading severity, average input SNRs, and the correlation coefficient. The series convergence rate is also examined verifying the fast convergence of the analytical expressions. The accuracy of most of the theoretical performance evaluation results are validated by means of computer simulations.