• The Journal of the Acoustical Society of Korea
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• v.32 no.3
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• pp.279-285
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• 2013

In this paper, we propose a novel speech enhancement method to improve the performance of the conventional global soft decision which is based on the spectral gradient method applied to the ratio of a priori speech absence and presence probability value (q). Conventional global soft decision scheme used a fixed value of q in accordance with the hypothesis assumed, but the proposed algorithm is a technique for improving the speech absence probability which is applied adaptively variable value of q according to the speech presence or absence in the previous two frames and the conditions of the spectral gradient value. Experimental results show that the proposed improved global soft decision method based on the spectral gradient method yields better results compared to the conventional global soft decision technique based on the performance criteria of the ITU-T P. 862 PESQ (Perceptual Evaluation of Speech Quality).

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.6
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• pp.79-92
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• 2016

The objective of this study is to classify the types of rural areas (138 $si{\cdot}gun$) considering settlement environment by Decision Tree Method (CHAID). The CHAID method was used for decision tree algorithm and the seven dependant variables and 5 explanatory variables were selected, respectively. By decision tree method, rural areas were finally classified into six groups through three separate processes. City area, lower area in aging rate and higher area in farmland area ratio was analyzed to be relatively rich rather than other area in the case of settlement environment index. In the future, this study will be able to utilize as a reference to the planning of rural development projects.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.55-65
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• 2020

With the development of display hardware, image interpolation techniques have been used in various fields such as image zooming and medical imaging. Traditional image interpolation methods, such as bi-linear interpolation, bi-cubic interpolation and edge direction-based interpolation, perform interpolation in the spatial domain. Recently, interpolation techniques in the discrete cosine transform or wavelet domain are also proposed. Using these various existing interpolation methods and machine learning, we propose decision tree classification-based image interpolation methods. In other words, this paper is about the method of adaptively applying various existing interpolation methods, not the interpolation method itself. To obtain the decision model, we used Weka's J48 library with the C4.5 decision tree algorithm. The proposed method first constructs attribute set and select classes that means interpolation methods for classification model. And after training, interpolation is performed using different interpolation methods according to attributes characteristics. Simulation results show that the proposed method yields reasonable performance.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.493-493
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• 2000

Multi-valued decision making for transitional stochastic events was newly derived based on conditional probability of database. The two values (on-off) decision making method without transition had been proposed by one of the author in a previous work for a purpose of realizing human on-off decision making. The current method is an extension of the previous on-off decision making. By combining the conditional probability and the transitional probability, the closed form of the algorithm for the multi-valued transitional decision making was derived. The proposed multi-valued decision making was successfully applied to the determination of the five levels of the vigilance of a subject during the EEG recording; awake stage, drowsy stage and sleeping stages (stage 1, stage 2/3, REM (rapid eye movement)). The method for determining the vigilance level can be directly usable for the two purposes; selection of awake EEG segments for automatic EEG interpretation, and determination of sleep stages through sleep EEG. The proposed multi-valued decision making with a mathematical background of the probability can be applicable widely, in industries and in medical fields for purposes of the multi-valued decision making.

• Journal of the Korean Institute of Educational Facilities
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• v.28 no.2
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• pp.3-10
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• 2021

Community-based design is also becoming important in Korea recently. However, the existing design methods of the "conformity" method had the problem of excluding the participation of residents. Therefore, the "decision-making" method, in which residents participate in the design themselves, is drawing attention. Development of specific methods is important for residents to actively participate in "decision making." The theory of "Design Games" has long been studied as a method of community-based design in many countries. The old downtown areas of Jeju Special Self-Governing Province are increasing in number of buildings abandoned due to aging and declining. Abandoned buildings are causing many social problems. A decision-making method has been developed in Jeju for the regeneration design of abandoned buildings. This study conducted a design workshop involving residents on abandoned buildings in the old city center of Jeju City. The possibility and task of decision-making method were analyzed. As a result, participating residents were actively involved in decision-making. It also helped residents understand and learn about the attractions of the neighborhood. Meanwhile, there were also difficulties in communicating among some participants. This is a structural problem with this method. Studies have also shown that it is important for residents themselves to try to understand the neighborhood.

• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2584-2590
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• 1998

In the existing fuzzy aggregation method, the operators such as t-norm, t conorm, mean operator, Yafer's operator and $\gamma$ operator are used to aggregate the values of membership functions. However, these methods have problems in that they do not reflect the decision situation properlyin the decision process. In order to solve these problems we suggest a situation assessment model(SAM) to reflect the decision situation in the decision proess. In the fuzzy decision environment, we propose a new aggregation method to reflect the decision situation using the result of SAM. We call it the aggregation based on situation assessment (ASA) method. It makes the stepwise aggregation with derection according to the decision situation. Moreover, we compare ASA method with the existing aggregation methods.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1090-1097
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• 2008

This study conducted the decision method of lateral flow in abutment structures founded on the soft soils and the reliability analysis on the foundation pile for abutment. On the basis of the results, this study proposed the reliability design model. Reliability analysis was conducted by applying second moment method, point estimation method, and expected total cost minimization to lateral movement index, lateral movement decision index, modified lateral movement decision index, and circular failure safety factor for the decision criteria of lateral flow. The reliability index by analysis method had a similar tendency each other. Point estimation method was found as a practical method in the aspect of convenience because it could conduct the analysis only by mean and standard deviation as well as the partial derivative on random variables was not necessary. Optimum reliability index and optimum safety according to increasing in failure factors and load ratio were analyzed and loads and resistance factors of the design criteria of optimum reliability were estimated. It presented rational design model which can consider construction level and stability and economical efficiency overall.

• IE interfaces
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• v.13 no.1
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• pp.17-28
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• 2000

As knowledge has been recognized as a new resource in gaining organizational competitiveness, Knowledge Management (KM) is suggested as a method to manage and apply knowledge for business management. KM research, however, has focused on identifying, storing, and distributing the transaction-related knowledge in an organization. There has been little research on applying the knowledge to decision-making or strategy development that is the main task of business management. The application of knowledge to decision making has higher impact on organizational performance rather than just the knowledge management for process transaction. In this research, we suggest System Dynamics (SD) for the knowledge-based decision-making. Based on the modeling method of SD, we can translate partial and implicit knowledge resident in individual's mental model into organized explicit knowledge. The simulation test of the organized knowledge model enables decision-makers to understand the structure of the target problem and its behavior mechanism, which facilitates effective decision-making. We will compare the proposed method and other KM methods and discuss this research based on the application case to a real telecommunication company.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.787-790
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• 2017

Data quality is the main issue in the classification problems; generally, the presence of noisy instances in the training dataset will not lead to robust classification performance. Such instances may cause the generated decision tree to suffer from over-fitting and its accuracy may decrease. Decision trees are useful, efficient, and commonly used for solving various real world classification problems in data mining. In this paper, we introduce a preprocessing technique to improve the classification accuracy rates of the C4.5 decision tree algorithm. In the proposed preprocessing method, we applied the naive Bayes classifier to remove the noisy instances from the training dataset. We applied our proposed method to a real e-commerce sales dataset to test the performance of the proposed algorithm against the existing C4.5 decision tree classifier. As the experimental results, the proposed method improved the classification accuracy by 8.5% and 14.32% using training dataset and 10-fold crossvalidation, respectively.

• The KIPS Transactions:PartC
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• v.10C no.1
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• pp.27-32
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• 2003

An efficient soft-decision decoding algorithm for binary block codes it proposed. The proposed soft-decision decoding algorithm is implemented by a series of hard-decision decoding process. By the hard-decision decoding result, the candidate codewords are efficiently searched for A new decoding method, which prevents the missing of the candidate codeword, is proposed. Also, the method fir reducing complexity is developed. This method removes the practical complexity increase caused by the improved algorithm. There facts are confirmed by the simulation results for binary (63, 36) BCH code.