• Journal of Information Technology Application
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• v.1
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• pp.173-211
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• 1999

The task of classification permeates all walks of life, from business and economics to science and public policy. In this context, nonlinear techniques from artificial intelligence have often proven to be more effective than the methods of classical statistics. The objective of knowledge discovery and data mining is to support decision making through the effective use of information. The automated approach to knowledge discovery is especially useful when dealing with large data sets or complex relationships. For many applications, automated software may find subtle patterns which escape the notice of manual analysis, or whose complexity exceeds the cognitive capabilities of humans. This paper explores the utility of a collaborative learning approach involving integrated models in the preprocessing and postprocessing stages. For instance, a genetic algorithm effects feature-weight optimization in a preprocessing module. Moreover, an inductive tree, artificial neural network (ANN), and k-nearest neighbor (kNN) techniques serve as postprocessing modules. More specifically, the postprocessors act as second0order classifiers which determine the best first-order classifier on a case-by-case basis. In addition to the second-order models, a voting scheme is investigated as a simple, but efficient, postprocessing model. The first-order models consist of statistical and machine learning models such as logistic regression (logit), multivariate discriminant analysis (MDA), ANN, and kNN. The genetic algorithm, inductive decision tree, and voting scheme act as kernel modules for collaborative learning. These ideas are explored against the background of a practical application relating to financial fraud management which exemplifies a binary classification problem.

• Journal of Korean Institute of Industrial Engineers
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• v.2 no.1
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• pp.37-44
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• 1976

It is necessary for developing countries to increase their consolidation of domestic technology in order to improve their economy. In order to raise their techniques, they have to try to induce the advanced know-how from other countries in spite of heavy cost. The object of this study is to establish the model on which we base our choice of the proper techniques or plants and give priority to them by using quantified selection criteria. The method in this study has two stages, and the writer has selected 12 factors affecting the decision making for the importation of technology from the industrially advanced countries. First, the lists of valuable know-how for the better development of national industry should be determined, and for the formulation and arrangement of the lists, a council of specialists which uses questionnaires in terms of the Semantic Differential Method, should be organized. Second, for the assignments of priority to the prospective items for importation, the writer has imployed both the Leontief Model and the Disman Model as objective methods and Mottley-Newton method, one of the R&D Project Selection Methods, as a general model. The writer has applied the methods described above to the fields of petrochemical industry in Korea.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.139-142
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• 2009

The worldwide energy market is enlarging rapidly according to current issues like globalization, deregulation, global warming and strengthening for environmental regulation as well as the energy technology is developing speedily by the add of information and communication techniques. In spite of these advanced techniques in the field of the renewable energy, solar power depends on the governmental aid largely in comparison with other renewable energy sources because of the high initial investment cost. Therefore it is important to investigate scrupulously for the expected erection site of solar power plant from the planning stage. This paper shows actual measurement data of solar radiation of scheduled solar power locations in the waterworks site with consideration of waterworks facilities and regional specialties and presents the data which was analyzed comparably with the radiation data of adjacent locations served by national authorities. In addition, these data were analyzed using RETScreen and used for making decision on the business validity.

• Asian Journal of Business Environment
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• v.8 no.4
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• pp.5-15
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• 2018

Purpose - The research aimed to reveal real decisional behavioral of management institutes in India for social media marketing usage, and analyses of empirical elements of social media consumption pattern. Research design, data, and methodology - The investigation was based around a research methodology using quantitative analysis with appropriate statistical techniques on random surveys of consumers, detailed exploratory and confirmatory factor analyses are applied to assess the empirical validity of the model and multiple regression employed using R studio edition to validate the reliability of the developed models. Results - A new conceptual framework is proposed - the management institutions decision model, providing a tool for effective and more focused decision-making strategies for developing better utilization techniques for social media. Management institutions have different requirements based upon objectives and resources available. The evidence suggests that the administrators need to be more aware of consumer indicators when targeting and designing social media marketing strategy. Conclusions - The research was based on samples and not the entire population of target consumers, providing limitations. As an inferential statistical method was chosen, the results might be susceptible to inaccuracy. The model developed from different age users, thereby providing rich perspectives into social media usage pattern.

• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1250-1260
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• 2013

The contrast enhancement techniques based on Laplacian pyramid image fusion have a benefit that they can faithfully describe the image information because they combine the multiple resource images by selecting the desired pixel in each image. However, they also have some problem that the output image may contain noise, because the methods evaluate the visual information on the basis of each pixel. In this paper, an improved contrast enhancement method, which effectively suppresses the noise, using image fusion is proposed. The proposed method combines the resource images by making Laplacian pyramids generated from weight maps, which are produced by measuring the difference between the block-based local well exposedness and local homogeneity for each resource image. We showed the proposed method could produce less noisy images compared to the conventional techniques in the test for various images.

• Journal of Nutrition and Health
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• v.36 no.3
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• pp.319-326
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• 2003

The purposes of this study were to : (a) analyze the menus of food service operations using the menu analysis techniques of Kasavana & Smith, Miller, Merricks & Jones, Pavesic and Uman, (b) closely examine the characteristics of the five analysis techniques. Calculations for the menu analysis were done by computer using the MS 2000 Excel spreadsheet program. Menu mix% and unit contribution margin were used as variables by Kasavana & Smith, sales volume and food cost% by Miller, sales volume and cash contribution by Merrick & Jones, weighted contribution margin and food cost% by Pavesic, and total cash contribution and unit contribution margin by Uman. In each case, a four-cell matrix was created, and menu items were located in each according they achieved high or low scores with respect to two variables. Items that scored favorably on both variables were rated in the top category (e.g., star, prime, signature, group A, winner) and those that scored below average on both were rated in the lowest category (e.g., dog, problem, loser, group D, loser). While the 3 methods of Kasavana & Smith, Miller, Merrick & Jones focus on customers' viewpoints, the others consider the managers' viewpoints. Therefore, it is more likely to be desirable for decision-making on menus if the menu analysis technique chosen is suited to its purpose.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.328-332
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• 2000

As DNA sequences have been known through the Genome project the techniques for dealing with molecule-level gene information are being made researches briskly. It is also urgent to develop new computer algorithms for making databases and analyzing it efficiently considering the vastness of the information for known sequences. In this respect, this paper studies the association rule search algorithms for finding out the characteristics shown by means of the association between promoter sequences and genes, which is one of the important research areas in molecular biology. This paper treat biological data, while previous search algorithms used transaction data. So, we design a transformed association nile algorithm that covers data types and biological properties. These research results will contribute to reducing the time and the cost for biological experiments by minimizing their candidates.

• Plant Resources
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• v.5 no.2
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• pp.95-103
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• 2002

Microscopic techniques were used to observe the microstructure of rice husk. Microscopic examination showed that two main components of husk, lemma and palea consisted of outer epidermis, layers of fibers, vascular bundles, parenchyma cells, and inner epidermis, in sequence from the outer to the inner surface. The outer epidermal walls were extremely thick, highly convoluted and lignified. The underlying fibers were also thick-walled and lignified. Parenchyma cells were thin-walled and unlignified. Inner epidermal cells were also unlignified. The outer surface of both lemma and palea were conspicuously ridged, but the lower surface had a flat appearance. As part of a detailed study to characterize rice husk using microscopic and micro-analytical techniques, distribution of silica was also examined, and is presented elsewhere. Rice husk can potentially be used as a raw material for making composite products and the observations presented here form valuable background information for our future work related to product development.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.229-241
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• 2015

Nowadays, an open-market which provides sellers and consumers a cyber place for making a transaction over the Internet has emerged as a prevalent sales channel because of convenience and relatively low price it provides. However, there are few studies about CRM strategies based on VIP consumers for an open-market even though understanding VIP consumers' behaviors in open-markets is important to increase its revenue. Therefore, we propose CRM strategies targeted on VIP customers, obtained by analyzing the transaction data of VIP customers from an open-market using data mining techniques. To that end, we first defined the VIP customers in terms of recency, frequency and monetary (RFM) values. Then, we used data mining techniques to develop a model which best classifies and identifies infiluential factors customers into VIPs or non-VIPs. We also validate each of promotion types in the aspect of effectiveness and identify association rules among the types. Then, based on the findings from these experiments, we propose strategies from the perspectives of CRM dimensions for the open-market to thrive.

• The Journal of Korean Association of Computer Education
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• v.18 no.4
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• pp.63-70
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• 2015

Program source code is a set of complex syntactic information which are expressed in text forms, and contains complex logical structures. Structural and logical complexity inside source code become barriers in applying visualization techniques shown in traditional big-data approaches when the volume of source code become over ten-thousand lines of code. This paper suggests a procedure for making visualization of structural characteristics in source code. For this purpose, this paper defines internal data structures as well as inter-procedural relationships among functions. The paper also suggests a means of outlining the structural characteristics of source code by visualizing the source codes with network forms The result of the research work can be used as a means of controling and understanding the massive volume of source code.