• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2003년도 추계 학술대회논문집
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• pp.82-87
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• 2003

Post-processing programs play an important role in the CFD data visualization and analysis. A variety of post-processing softwares have been developed and are being used in the CFD community. Developing a good quality of post-processing program requires dedication and efforts. In this paper an experience obtained through previous studies and developing post-processing programs are introduced which includes data structure and visualization algorithms.

• 조명전기설비학회논문지
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• 제26권2호
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• pp.61-70
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• 2012

Recently due to the increasing of the importance on the green energy is getting higher by implementing EERS(Energy Efficiency Resource Standards) and NA(Negotiated Agreement) such as lacks of natural resources and The United Nations Framework Convention on Climate Change. And the most practical solution is CHP(Combined Heat and Power) which performs the best energy efficiency. This paper developed optimal operation mechanism of CES(Community Energy System) for enhancement of energy efficiency using CHP(Combined Heat and Power), PLB(Peak Load Boiler) and ACC(ACCumulator) capacities. This method optimally operated these capacities calculated the maximum profits by Dynamic Programing. Through the case studies, it is verified that the proposed algorithm of can evaluate availability.

• 한국공간정보시스템학회:학술대회논문집
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• 한국공간정보시스템학회 2005년도 추계학술대회
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• pp.61-66
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• 2005

Spatiotemporal data mining represents the confluence of several fields including spatiotemporal databases, machine loaming, statistics, geographic visualization, and information theory. Exploration of spatial data mining and temporal data mining has received much attention independently in knowledge discovery in databases and data mining research community. In this paper, we introduce an algorithm Max_MOP for discovering moving sequences in mobile environment. Max_MOP mines only maximal frequent moving patterns. We exploit the characteristic of the problem domain, which is the spatiotemporal proximity between activities, to partition the spatiotemporal space. The task of finding moving sequences is to consider all temporally ordered combination of associations, which requires an intensive computation. However, exploiting the spatiotemporal proximity characteristic makes this task more cornputationally feasible. Our proposed technique is applicable to location-based services such as traffic service, tourist service, and location-aware advertising service.

• Journal of Mechanical Science and Technology
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• 제15권5호
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• pp.569-579
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• 2001

This study investigates the effects of operating conditions on the chattering of an automotive disk brake by experimental and computational methods. Design factors, which cause chattering in automobiles, have attracted great attentions for long time; but they are not well understood yet. For this study, we construct a brake dynamometer for measuring the disk surface temperature during chattering, and propose an efficient hybrid algorithm (combining FFT-FEA and traditional FEA program) for analyzing the thermo-elastic behavior of three-dimensional brake system. We successfully measure the judder in a brake system via the dynamometer and efficiently simulate the contact pressure variation by the hybrid algorithm. The three-dimensional simulation of thermo-mechanical interactions on the automotive brake, showing the transient thermo-elastic instability phenomenon, is presented for the first time in this academic community. We also find from the experimental study that the disk bulk temperature strongly influences the brake chattering in the automotive disk brakes.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.621-628
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• 2005

Scalability of clustering algorithms is critical issues facing the data mining community. This is particularly true for computationally intense tasks such as data clustering. Random sampling of instances is one possible means of achieving scalability but a pervasive problem with this approach is how to deal with the noise that this introduces in the evaluation of the learning algorithm. This paper develops a new optimization based clustering approach using an algorithms specifically designed for noisy performance. Numerical results illustrate that with this algorithm substantial benefits can be achieved in terms of computational time without sacrificing solution quality.

• Journal of information and communication convergence engineering
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• 제7권1호
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• pp.35-40
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• 2009

Many researchers strive to research on ways on how to improve the performance of RFID system and many papers were written to solve one of the major drawbacks of potent technology related with data management. As RFID system captures billions of data, problems arising from dirty data and large volume of data causes uproar in the RFID community those researchers are finding ways on how to address this issue. Especially, effective data management is important to manage large volume of data. Data reduction techniques in attempts to address the issues on data are also presented in this paper. This paper introduces readers to a new data reduction algorithm that might be an alternative to reduce data in RFID Systems. A process on how to extract data from the reduced database is also presented. Performance study is conducted to analyze the new data reduction algorithm. Our performance analysis shows the utility and feasibility of our categorization reduction algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.1.2-6
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• 1994

A state or the arts in Japanese chemical process control is reviewed based on experience in applying advanced process control schemes to several industrial chemical processes. The applications validate model predictive control (MPC), the most popular advanced control scheme in the process control community, as, indeed, a powerful and practical control algorithm. However, at the same time, it is elucidated that MPC can solve only the control algorithm part of the problem and one needs chemical and systems engineering aspects to solve the entire problem. By illustrating several industrial process control problems, the need for chemical engineering aspects as well as the future direction for process control are addressed, especially in light or current attitudes toward product quality.

• 한국IT서비스학회지
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• 제14권4호
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• pp.121-135
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• 2015

Ensemble classification is to utilize multiple classifiers instead of using a single classifier. Recently ensemble classifiers have attracted much attention in data mining community. Ensemble learning techniques has been proved to be very useful for improving the prediction accuracy. Bagging, boosting and random subspace are the most popular ensemble methods. In random subspace, each base classifier is trained on a randomly chosen feature subspace of the original feature space. The outputs of different base classifiers are aggregated together usually by a simple majority vote. In this study, we applied the random subspace method to the bankruptcy problem. Moreover, we proposed a method for optimizing the random subspace ensemble. The genetic algorithm was used to optimize classifier subset of random subspace ensemble for bankruptcy prediction. This paper applied the proposed genetic algorithm based random subspace ensemble model to the bankruptcy prediction problem using a real data set and compared it with other models. Experimental results showed the proposed model outperformed the other models.

• International Journal of Computer Science & Network Security
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• 제23권1호
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• pp.164-168
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• 2023

As our community has become increasingly dependent on technology, security has become a bigger concern, which makes it more important and challenging than ever. security can be enhanced with encryption as described in this paper by combining RC6 symmetric cryptographic algorithms with RSA asymmetric algorithms, as well as the Vigenère cipher, to help manage weaknesses of RC6 algorithms by utilizing the speed, security, and effectiveness of asymmetric algorithms with the effectiveness of symmetric algorithm items as well as introducing classical algorithms, which add additional confusion to the decryption process. An analysis of the proposed encryption speed and throughput has been conducted in comparison to a variety of well-known algorithms to demonstrate the effectiveness of each algorithm.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 추계학술발표대회
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• pp.322-326
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• 2023

We propose a method of movie recommendation that involves an algorithm known as spectral bipartition. The Social Network is constructed manually by considering the similar movies viewed by users in MovieLens dataset. This kind of similarity establishes implicit ties between viewers. Because we assume that there is a possibility that there might be a connection between users who share the same set of viewed movies. We cluster users by applying a community detection algorithm based on the spectral bipartition. This study helps to uncover the hidden relationships between users and recommend movies by considering that feature.