• 한국산업융합학회 논문집
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• 제3권2호
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• pp.167-178
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• 2000

Software RAID(Redundant Arrays of Inexpensive Disks) is defined as a storage system that provides capabilities of hardware RAID, and guarantees high reliability as well as high performance. In this paper, we propose an enhanced disk scheduling algorithm and a scheme to guarantee reliability of data. We also design and implement software RAID by utilizing these mechanism to develop a storage system for multimedia applications. Because the proposed algorithm improves a defect of traditional GSS algorithm that disk I/O requests arc served in a fixed order, it minimizes buffer consumption and reduces the number of deadline miss through service group exchange. Software RAID also alleviates data copy overhead during disk services by sharing kernel memory. Even though the implemented software RAID uses the parity approach to guarantee reliability of data, it adopts different data allocation scheme. Therefore, we reduce disk accesses in logical XOR operations to compute the new parity data on all write operations. In the performance evaluation experiments, we found that if we apply the proposed schemes to implement the Software RAID, it can be used as a storage system for small-sized video-on-demand servers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권11호
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• pp.2191-2203
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• 2011

In this paper, we propose a fast and robust algorithm for fighting behavior detection based on Motion Vectors (MV), in order to solve the problem of low speed and weak robustness in traditional fighting behavior detection. Firstly, we analyze the characteristics of fighting scenes and activities, and then use motion estimation algorithm based on block-matching to calculate MV of motion regions. Secondly, we extract features from magnitudes and directions of MV, and normalize these features by using Joint Gaussian Membership Function, and then fuse these features by using weighted arithmetic average method. Finally, we present the conception of Average Maximum Violence Index (AMVI) to judge the fighting behavior in surveillance scenes. Experiments show that the new algorithm achieves high speed and strong robustness for fighting behavior detection in surveillance scenes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권1호
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• pp.136-151
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• 2016

Flexible large-scale WLANs are now widely deployed in crowded and highly mobile places such as campus, airport, shopping mall and company etc. But network management is hard for large-scale WLANs due to highly uneven interference and throughput among links. So the traffic is difficult to predict accurately. In the paper, through analysis of traffic in two real large-scale WLANs, Granger Causality is found in both scenarios. In combination with information entropy, it shows that the traffic prediction of target AP considering Granger Causality can be more predictable than that utilizing target AP alone, or that of considering irrelevant APs. So We develops new method -Granger Causality and Vector Auto-Regression (GCVAR), which takes APs series sharing Granger Causality based on Vector Auto-regression (VAR) into account, to predict the traffic flow in two real scenarios, thus redundant and noise introduced by multivariate time series could be removed. Experiments show that GCVAR is much more effective compared to that of traditional univariate time series (e.g. ARIMA, WARIMA). In particular, GCVAR consumes two orders of magnitude less than that caused by ARIMA/WARIMA.

• Journal of Microbiology and Biotechnology
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• 제25권11호
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• pp.1928-1935
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• 2015

Microbial growth kinetics is often used to optimize environmental processes owing to its relation to the breakdown of substrate (contaminants). However, the quantification of bacterial populations in the environment is difficult owing to the challenges of monitoring a specific bacterial population within a diverse microbial community. Conventional methods are unable to detect and quantify the growth of individual strains separately in the mixed culture reactor. This work describes a novel quantitative PCR (qPCR)-based genomic approach to quantify each species in mixed culture and interpret its growth kinetics in the mixed system. Batch experiments were performed for both single and dual cultures of Pseudomonas putida and Escherichia coli K12 to obtain Monod kinetic parameters (μ_max and K_s). The growth curves and kinetics obtained by conventional methods (i.e., dry weight measurement and absorbance reading) were compared with that obtained by qPCR assay. We anticipate that the adoption of this qPCR-based genomic assay can contribute significantly to traditional microbial kinetics, modeling practice, and the operation of bioreactors, where handling of complex mixed cultures is required.

• 한국콘텐츠학회논문지
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• 제9권1호
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• pp.147-158
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• 2009

최근 스트림데이터 환경의 데이터 모델은 데이터의 양이 아주 크고 연속적이며 무한하다. 이에 반해 제한된 용량의 디스크나 메모리 등을 이용해서 질의 처리나 데이터 분석을 처리한다. 이러한 환경에서 트랜잭션 데이터베이스에 대한 전통적인 빈발패턴탐사는 불가능하다고 할 수 있다. 왜냐하면, 연속적으로 들어오는 스트림 데이터에 대해 어떤 항목집합이 빈발항목인지 아닌지에 대한 정보를 계속적으로 유지 관리하기가 어렵기 때문이다. 본 논문에서는 연속적으로 들어오는 스트림 데이터에 회귀모델을 적용하여 빈발 항목들을 예측할 수 있는 방법을 제안한다. 스트림 데이터로부터 회귀모델을 생성함으로써 불확실한 항목들에 대한 예측 모델로 사용할 수 있다. 다양한 실험을 통하여 제안하는 방법이 스트림 데이터 환경의 데이터에 효율적으로 사용될 수 있음을 보인다.

• 한국멀티미디어학회논문지
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• 제1권2호
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• pp.183-193
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• 1998

칼라 역 해프토닝(Color inverse half toning)은 해프토닝된 칼라 영상을 시각적으로 보다 자연스러운 연속 계조 칼라영상으로 변환해 주는 방법이다. 본 논문에서는, 칼라 채널 영상에서 나타나는 해프톤 셀 패턴을 효과적으로 제거할 수 있는 새로운 평활화 마스크를 제안하고, 이를 칼라 역 해프토닝에 활용하였다 제안한 평활화 마스크는 기존의 평활화 마스크가 잘 제거하지 못했던 해프톤 셀 패턴올 시각적으로 보다 자연스럽게 평활화할 수 있으며, 마스크의 특성이 다양한 해프톤 영상에 적합하게 자동 조정될 수 있도록 설계하였다 실험을통해, 기폰의 방법과본논문에서 제안한방법에 의한결과 영상을다양한측면에서 비교분석함으로써 제안한 평활화 마스크의 유용성올 확인하였다. 제안한 방법은 전자 출판, 칼라 팩스, 디지힐 도서관 구축 퉁과 같은 멀티미디어 분야에서 활용될 수 있다.

• 지능정보연구
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• 제15권4호
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• pp.37-51
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• 2009

서비스 인적자원 운용의 효율성 제고와 부품 또는 시설 할당의 적정성 향상을 위해 서비스센터를 통해 접수되는 서비스 요청 건수를 보다 정확하게 예측하고자 하는 필요성이 제조업을 중심으로 증가하고 있다. 본 연구에서는 제품의 특성을 반영하여 제품수명주기 별로 제품들을 군집화하고 군집 별로 적절한 예측모형을 구축한 후 예측 값을 통합하는 개별예측방식을 LCD 모니터 제조사의 사례를 통해 제시한다. 또한 예측 결과를 총량방식 및 기존에 기업이 사용하고 있는 방식과 비교. 평가하여 우수성을 증명함으로써 제품이나 산업의 특성을 반영한 맞춤형 수요예측 기법 도입의 필요성을 부각하고, 그에 따른 이론적, 실무적 가이드라인을 제공한다.

• Journal of Multimedia Information System
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• 제6권4호
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• pp.265-270
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• 2019

The technology to locate an individual has enabled various services, its utilization has increased. There were constraints such as the use of separate expensive equipment or the installation of specific devices on a facility, with most of the location technology studies focusing on the accuracy of location verification. These constraints can result in accuracy within a few tens of centimeters, but they are not technology that can be applied to a user's location in real-time in daily life. Therefore, this paper aims to track the locations of smartphones only using the basic components of smartphones. Based on smartphone sensor data, localization accuracy that can be used for verification of the users' locations is aimed at. Accelerometers, Wifi radio maps, and GPS sensor information are utilized to implement it. In forging the radio map, signal maps were built at each vertex based on the graph data structure This approach reduces traditional map-building efforts at the offline phase. Accelerometer data were made to determine the user's moving status, and the collected sensor data were fused using particle filters. Experiments have shown that the average user's location error is about 3.7 meters, which makes it reasonable for providing location-based services in everyday life.

• 한국정보처리학회논문지
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• 제4권12호
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• pp.3175-3184
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• 1997

대규모 저장 공간과 실시간 특성이 요구되는 연속 매체 저장 시스템에서 입출력 장치는 성능 개선이 필요하다. 본 논문에서는 입출력 성능을 개선하기 위해 디스크 입출력 회수를 감소시키는 버퍼 공유 기법을 활용하였다. 또한, 연속 매체 데이터에 대한 요구를 예측하기 위해 연속 매체 스트림들의 참조 계획을 이용하여 데이터 공유를 증진시켰다. 본 논문에서는 동일 데이터를 요청하는 후속 사용자들이 버퍼를 효율적으로 공유케 하는 버퍼 공유 기법을 제안하였다. 제안된 알고리즘은 데이터 블록들에 대한 참조 시간 간격 정보를 활용하여 버퍼 들을 관리한다. 제안된 알고리즘의 유효성을 검증하기 위해 시뮬레이션을 수행하였으며, 기존 버퍼 교체 알고리즘들에 비해 성능 개선 효과가 확인되었다.

• Journal of Information Processing Systems
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• 제5권2호
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• pp.105-116
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• 2009

To solve the general problems surrounding the application of genetic algorithms in stereo matching, two measures are proposed. Firstly, the strategy of simplified population-based incremental learning (PBIL) is adopted to reduce the problems with memory consumption and search inefficiency, and a scheme for controlling the distance of neighbors for disparity smoothness is inserted to obtain a wide-area consistency of disparities. In addition, an alternative version of the proposed algorithm, without the use of a probability vector, is also presented for simpler set-ups. Secondly, programmable graphics-hardware (GPU) consists of multiple multi-processors and has a powerful parallelism which can perform operations in parallel at low cost. Therefore, in order to decrease the running time further, a model of the proposed algorithm, which can be run on programmable graphics-hardware (GPU), is presented for the first time. The algorithms are implemented on the CPU as well as on the GPU and are evaluated by experiments. The experimental results show that the proposed algorithm offers better performance than traditional BMA methods with a deliberate relaxation and its modified version in terms of both running speed and stability. The comparison of computation times for the algorithm both on the GPU and the CPU shows that the former has more speed-up than the latter, the bigger the image size is.