• Journal of Service Research and Studies
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• v.3 no.1
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• pp.1-7
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• 2013

We have to select business Item at various alternatives through BMO Evaluation Method. This study suggested selection method best business item using Visual Basic Program. Selection item of business item is technically power, capital strength, business administration capability, Maketings, Possible total sales, Goods of future growth, Expectations of competition goods, Creation of goods, and Management. Evaluation of each item value, add total values. It is important that business item selected well for adapted business. It should be able to decide business item using this study's program.

• Transactions on Electrical and Electronic Materials
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• v.13 no.3
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• pp.139-143
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• 2012

Optical emission spectroscopy (OES) is often used for real-time analysis of the plasma processes. OES has been suggested as a primary plasma process monitoring tool. It has the advantage of non-invasive in-situ monitoring capability but selecting the proper wavelengths for the analysis of OES data generally relies on empirically established methods. In this paper, we propose a practical method for the selection of OES wavelength peaks for the analysis of plasma etch process and this is done by investigating reactants and by-product gas species that reside in the plasma etch chamber. Wavelength selection criteria are based on the standard deviation and correlation coefficients. Moreover, chemical actinometry is employed for the normalization of the selected wavelengths. We also present the importance of chemical actinometry of OES data for quantitative analysis of plasma. Then, the suggested OES peak selection method is employed.. This method is used to find out the reason behind abnormal etching of PR erosion during a series of $SiO_2$ etch processes using the same recipe. From the experimental verification, we convinced that OES is not only capable for real-time detection of abnormal plasma process but it is also useful for the analysis of suspicious plasma behavior.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1168-1182
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• 2017

In the past decades, various image regularization methods have been introduced. Among them, total variation model has drawn much attention for the reason of its low computational complexity and well-understood mathematical behavior. However, regularization parameter estimation of total variation model is still an open problem. To deal with this problem, a novel adaptive regularization parameter selection scheme is proposed in this paper, by means of using the local spectral response, which has the capability of locally selecting the regularization parameters in a content-aware way and therefore adaptively adjusting the weights between the two terms of the total variation model. Experiment results on simulated and real noisy image show the good performance of our proposed method, in visual improvement and peak signal to noise ratio value.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.534-541
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• 2011

Risk evaluation approaches for bidding on international construction projects are typically partitioned into three stages: country selection, project classification, and bid-cost evaluation. However, previous studies are frequently under attack in that they have several crucial limitations: 1) a dearth of studies about country selection risk tailored for the overseas construction market at a corporate level; 2) no consideration of uncertainties for input variable per se; 3) less probabilistic approaches in estimating a range of cost variance; and 4) less inclusion of covariance impacts. This study thus suggests a three-staged risk evaluation model to resolve these inherent problems. In the first stage, a country portfolio model that maximizes the expected construction market growth rate and profit rate while decreasing market uncertainty is formulated using multi-objective genetic analysis. Following this, probabilistic approaches for screening bad projects are suggested through applying various data mining methods such as discriminant logistic regression, neural network, C5.0, and support vector machine. For the last stage, the cost overrun prediction model is simulated for determining a reasonable bid cost, while considering non-parametric distribution, effects of systematic risks, and the firm's specific capability accrued in a given country. Through the three consecutive models, this study verifies that international construction risk can be allocated, reduced, and projected to some degree, thereby contributing to sustaining stable profits and revenues in both the short-term and the long-term perspective.

• Journal of Technology Innovation
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• v.15 no.2
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• pp.123-152
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• 2007

The striking characteristic of the contemporary global security environment is that the nature of threats has become diverse and complex. For example, transnational and non-military threats including terrorism and proliferation of weapon of mass destruction has increased. In this security environment, Advanced countries funnel their investments for defense budgets into the assurance of key force capability and R&D of cutting-edge core technologies, in consideration of future battlefield environments so as to get an edge on not only defense science and technology but also intelligence capabilities. As shown by past practices of the korea's defense acquisition, the ministry of national defense has tried to enhance its force capabilities in the short-term by purchasing foreign weapon systems rather than by investing in domestic R&D. Accordingly, the technological gaps between the korea and advanced countries were widened due to both insufficient investment in development of domestic technologies and avoidance of technological transfer by advanced countries. Thus, for the effective execution of the R&D budget and the successful performance of the projects, the importance of selection, management and evaluation of the R&D projects is emphasized. So, The objective of this study is that the analysis of the proposal-selection evaluation system for the realization of the successful defense core technology R&D projects. This study focused on the improvement of the proposal-selection evaluation model which can be applicable to the national defense core R&D projects. Using the improved proposal-selection evaluation system, we propose a model to enhance the reliability of the national defense core technology R&D project evaluation system.

• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.401-411
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• 2013

Selection of profitable research and development (R&D) projects is one of the major factors affecting sustained growth of firms and countries. This paper analyze what influences the knowledge on the business model exerted on selection of a R&D project. A business model converts the technology value to the customer value, and comprehensively describes the target customers for commercializing a new technology, core values, behaviors within organizations, resources, and external partners. Thus, understanding a business model would make R&D project evaluators place the feasibility and profitability of the business above the merits of the proposed technology in evaluating the technology development. To verify this hypothesis, we had 78 R&D project evaluators acquire the knowledge on the business model and measured how their criteria for R&D project selection have changed using the AHP method. The results shows that feasibility and profitability are more important than the merit of proposed technology, especially capability of company and business development are more important than the levels of technology innovation.

• Journal of KIISE:Software and Applications
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• v.34 no.9
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• pp.857-868
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• 2007

The good classifier ensemble should have a high complementarity among classifiers in order to produce a high recognition rate and its size is small in order to be efficient. This paper proposes a classifier ensemble selection algorithm with coarse-to-fine stages. for the algorithm to be successful, the original classifier pool should be sufficiently diverse. This paper produces a large classifier pool by combining several different classification algorithms and lots of feature subsets. The aim of the coarse selection is to reduce the size of classifier pool with little sacrifice of recognition performance. The fine selection finds near-optimal ensemble using genetic algorithms. A hybrid genetic algorithm with improved searching capability is also proposed. The experimentation uses the worldwide handwritten numeral databases. The results showed that the proposed algorithm is superior to the conventional ones.

• Asia pacific journal of information systems
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• v.12 no.4
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• pp.193-213
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• 2002

The sales activity of most of small manufacturing companies is based on orders of buyers. The process of promotion, negotiation, receipt and selection of orders of the manufacturers is closely coupled with the load status of the production lines. The decision on whether to accept an order or not, or the selection of optimal order set among excessive orders is entirely dependent on the schedule of production lines. However, in the real world, since the production scheduling activity is mainly performed by human experts, most of small manufacturers are suffer from being unable to meet due dates, lack of rapid decision on the acceptance of new order. Recently, Internet based Electronic Commerce is recognized as one of the alternatives for strengthening sales power of small and medium companies. However, small and medium manufacturers can't adjust properly to the new environment because they are in short of money, personnel, and technology. To cope with this problem, this paper deals with development of part sales agent coupled with virtual manufacturing in Internet environment that consist of selection agent, advertisement agent, selection agent, negotiation agent, and virtual manufacturing system. This paper develops a time-bounded negotiation mechanism for small and medium manufacturers in agent-based automated negotiation between customers and negotiation agents. Furthermore, to select optimal order set maximized profit, we first formulate the order selection problem with mixed integer programming, but the computation time of IP is not acceptable for real world scale problem. To overcome this problem and dynamic nature of virtual manufacturing, we suggest a genetic algorithm approach, which shows a reasonable computation time for real world case and good incremental problem solving capability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10B
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• pp.639-647
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• 2005

When a DEV associates with an existing WPAN, the PNC checks the capabilities of the new DEV to see if it is more capable to be the PNC of the piconet based on the criteria defined in the IEEE Std 802.15. If the new DEV is more capable and the current security policies allow it, then the PNC has the option of handing over control of the piconet to the DEV that has just joined. And, If the PNC is shutting down or wants to leave the WPAN, it also uses the handover process to give control to another DEV in the piconet. However, IEEE 802.15.3 checks only DEV capability information for more PNC capable. For PNC selection, it should consider the radio coverage of new PNC capable DEVs. So, we propose the method of PNC selection with accessibility check. This method manages PNC candidate list in the current piconet. In this paper, we analyze accessibility problems for PNC selection in section 2. In section 3, we explain CI(Configuration Inquiry) process which is proposed by Sony Corporation and propose PCI(PNC Candidate Inquiry) process. Also, we perform numerical analysis to compare PCI process with CI process in section 4. Finally, we conclude in section 5.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.4
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• pp.13-22
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• 2018

In this study, we examined the accuracy of the assessment items for selecting start-ups used in the project to support start-ups and verified their validity in determining whether they are appropriate assessment items based on selection criteria. The results of 973 start-ups that applied for the project fostering startup leading universities were collected and logistic regression was performed using SPSS 18.0. The study results are summarized as follows. First, the differences in characteristics of start-ups were identified in terms of selection. Second, the impact of selection by assessment items was gender in 2015, capability of the founder, business establishment in 2016, performance and potential in the global market, and business startup in 2017. Third, the overall selection accuracy analysis for the last three years confirmed that the accuracy of the selection is lower each year and that the accuracy of the selection is lower than the accuracy of the non-selection. This means that the current assessment items for selecting start-ups are inaccurate for selection, and that changes in the items due to changes in the start-up environment each year have led to lower accuracy of selection. It is meaningful that this study raised the importance of assessment items and the need for improvement of assessment items for the screening functions of good start-ups to enhance efficiency of the policies for startup support.