• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.108-119
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• 2015

This study intends to propose a non-oriented DEA based game cross-efficiency approach for supplier selection. With a discussion on the choice of DEA models and approaches that are most appropriate for supplier selection, we propose a game cross efficiency model based upon the non-oriented variable returns-to-scale RAM DEA by adapting the existing game cross efficiency model based upon the oriented constant returns-to-scale CCR DEA. We develop the RAM game cross efficiency model and a convergent iterative solution procedure to find the best game cross efficiency scores that constitute a Nash equilibrium. We illustrate the proposed model with two data sets of supplier selection, and demonstrate that significantly different results are obtained when compared with the existing approaches.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.212-216
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• 2024

Feature Selection have turned into the main point of investigations particularly in bioinformatics where there are numerous applications. Deep learning technique is a useful asset to choose features, anyway not all calculations are on an equivalent balance with regards to selection of relevant features. To be sure, numerous techniques have been proposed to select multiple features using deep learning techniques. Because of the deep learning, neural systems have profited a gigantic top recovery in the previous couple of years. Anyway neural systems are blackbox models and not many endeavors have been made so as to examine the fundamental procedure. In this proposed work a new calculations so as to do feature selection with deep learning systems is introduced. To evaluate our outcomes, we create relapse and grouping issues which enable us to think about every calculation on various fronts: exhibitions, calculation time and limitations. The outcomes acquired are truly encouraging since we figure out how to accomplish our objective by outperforming irregular backwoods exhibitions for each situation. The results prove that the proposed method exhibits better performance than the traditional methods.

• The Journal of the Acoustical Society of Korea
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• v.23 no.3
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• pp.248-252
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• 2004

Cultural, social, economic and other various environmental factors affect our language and different words and terminology are used and coined for different contexts, resulting in quantitative change of vocabulary. This paper presents an automatic pronunciation generator using selection procedure for exceptional pronunciation words from added text corpus, which reflects this dynamic nature of language. For our experiment, we used the text corpus released by ETRI for speech recognition. consisting or 53,750 sentences (740.497 Eojols), and obtained a 100% performance level of the proposed automatic pronunciation generator.

• The KSFM Journal of Fluid Machinery
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• v.10 no.5
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• pp.20-26
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• 2007

Some gate valves are susceptible to pressure locking and thermal binding which prevent the safety function. The safety related gate valves susceptible to pressure locking and thermal binding shall be identified and taken preventive actions to ensure the safety function. The identification of the gate valves susceptible to pressure locking and thermal binding needs the evaluation of system design, valve and piping arrangement, test requirements, and operating conditions. Application of preventive methods should consider the system safety function, applicability, effectiveness, interface with system design, and cost. The selection procedure of valves susceptible to pressure locking and thermal binding can be effectively used in industry including nuclear power plants. In order to prevent the pressure locking, the hole can be drilled through the one disc of upstream side or down stream and the external equalizing line can be installed from bonnet to downstream or upstream. The double disc parallel seat valve type can be used instead of flexible wedge gate valve to prevent the thermal binding. The identification of gate valves susceptible to pressure locking and thermal binding, and preventive actions will meet the regulatory requirements and enhance the availability and safety of plants.

• Journal of the Korean Solar Energy Society
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• v.25 no.2
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• pp.63-69
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• 2005

This study is the survey of a transition procedure of building services systems(heat source, HVAC, water supply) through the survey of existing office buildings, building design documents. The preference & major consideration of system selection is the engineer's opinions. The results of this survey can be used in selection of building services system design. In this survey, "Hot & cold water generator system" and "single duct CAV+FCU system", "Elevated water tank system" are selected. The most important consideration in system selection is the energy saving in heat source system, and comfort in HVAC system, and water pressure in water supply system. They prefer "steam boiler+absorption chiller system" for heat source system, "steam boiler+ice thermal storage system", "hot & cold water generator system", "district heating+absorption chiller system" : "single duct CAV+FCU system" and "single duct VAV+convector system" for HVAC system: and "booster pump system" for water supply system.

• Quantitative Bio-Science
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• v.37 no.2
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• pp.133-141
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• 2018

Graphical lasso is one of the most popular methods to estimate a sparse precision matrix, which is an inverse of a covariance matrix. The objective function of graphical lasso imposes an ${\ell}_1$-penalty on the (vectorized) precision matrix, where a tuning parameter controls the strength of the penalization. The selection of the tuning parameter is practically and theoretically important since the performance of the estimation depends on an appropriate choice of tuning parameter. While information criteria (e.g. AIC, BIC, or extended BIC) have been widely used, they require an asymptotically unbiased estimator to select optimal tuning parameter. Thus, the biasedness of the ${\ell}_1$-regularized estimate in the graphical lasso may lead to a suboptimal tuning. In this paper, we propose a two-staged bias-correction procedure for the graphical lasso, where the first stage runs the usual graphical lasso and the second stage reruns the procedure with an additional constraint that zero estimates at the first stage remain zero. Our simulation and real data example show that the proposed bias correction improved on both edge recovery and estimation error compared to the single-staged graphical lasso.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.347-353
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• 2022

Using the Heckman two-step procedure, this study investigates the relationship between management accounting implementation and firm effectiveness. The research data for this study was acquired from 450 publicly traded companies in Vietnam; however, the final sample only includes 304 responses containing useful information. The reliability analysis was used to evaluate the acquired data to examine the qualities of constructs and the dimensions that make them up. Then, the Heckman two-step technique was performed to analyze the causal connection from the acceptance of management accounting to firm effectiveness allowing for the effect of environmental uncertainty and organizational characteristics on the likelihood of adopting management accounting. The empirical findings show that management accounting acceptance determines firm effectiveness; however, the research model on the relationship between management accounting adoption and firm effectiveness has a sample selection bias. The main conclusions of this study are that there is a difference in the effects of management accounting adoption on business effectiveness when sample selection bias is not taken into consideration. When potential sample selection bias is taken into account by integrating environmental uncertainty and organizational characteristics in the research model, the effect of adopting management accounting on company effectiveness becomes minor.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1057-1060
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• 2004

We propose new rotation moment invariants based on multiresolution filter bank techniques. The multiresolution pyramid motivates our simple but efficient feature selection procedure based on the fuzzy C-mean clustering, combined with the Mahalanobis distance. The procedure verifies an impact of random noise as well as an interesting and less known impact of noise due to spatial transformations. The recognition accuracy of the proposed techniques has been tested with the preceding moment invariants as well as with some wavelet based schemes. The numerical experiments, with more than 30,000 images, demonstrate a tangible accuracy increase of about 3% for low noise, 8% for the average noise and 15% for high level noise.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.607-615
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• 2005

In this study ship collision risk analysis is performed to determine the design vessel for collision impact analysis of the bridge. Method I in AASHTO LRFD bridge design specifications is a semi-deterministic analysis procedure for determining the design vessel. Method ll which is a more complicated probability based analysis procedure is used to select the design vessel for collision impact. The AF allocation by weights seems to be more reasonable than the pylon concentration allocation method because AF allocation by weights takes the design parameter characteristics quantitatively into consideration although the pylon concentration allocation method brings more economical results when the overestimated design collision strength of piers compared to the strength of pylon is moderately modified. Therefore more researches on the allocation model of AF and the selection of design vessel are required.

• Korean Journal of Computational Design and Engineering
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• v.1 no.3
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• pp.234-241
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• 1996

Recently, Genetic Algorithms(GAs), which consist of genetic operators named selection crossover and mutation, are widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GAs are very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GAs. So, they can be easily applicable to wide territory of design optimization problems. Also, virtue to multi-point search procedure, they have higher probability of convergence to global optimum compared with traditional techniques which take one-point search method. The introduction of basic theory on GAs, and the application examples in combination optimization of ten-member truss structure are presented in this paper.