• 조명전기설비학회논문지
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• 제20권9호
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• pp.32-39
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• 2006

In this paper, an iterative subspace-based calibration algorithm for a CDMA-based antenna array in the presence of unknown gain and phase error is presented. The algorithm does not depend on the array geometry and does not require a prior knowledge of the Directions Of Arrival (DOA) of the signals. The method requires the code sequence of a reference user only. The proposed algorithm is based on the subspace method and root finding approach, and it provides estimates of the calibration vector, the DOA and the channel impulse response, by using the code sequence of a reference user. The performance of the proposed algorithm was investigated by means of computer simulations and was verified using field data measured through a custom-built W-CDMA test-bed. The data show that experimental results match well with the theoretical calibration algorithm. Also, teh study propose an efficient algorithm using the simulated annealing technique. This algorithm overcomes the requirement of initial guessing in the subspace-based approach.

• 컴퓨터교육학회논문지
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• 제17권4호
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• pp.45-57
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• 2014

학습자가 주어진 문제를 해결하는 알고리즘을 작성한 후 그것이 정확한지, 그리고 시간 효율적인지를 확인할 수 있는 알고리즘 자동평가 시스템에 대한 연구가 최근 들어 활발히 진행 중이다. 그러나 기존에 연구되었던 시스템은 대부분 프로그래밍 콘테스트를 위한 Online Judge 방식으로 본 연구에서는 교수 학습 기능을 강화한 클라이언트-서버 기반의 시스템을 개발하였다. 특히, 문제해결력 증진을 위한 교수 학습 설계 모델 CRESST을 토대로 학습자의 메타인지와 동기가 활성화되도록 설계하였으며, 알고리즘 자동평가 시스템의 구성요소인 문제, 채점데이터 세트, 자동평가 프로그램, 사용자서비스 환경 등의 전체 시스템을 구현하였다. 본 시스템의 프로그래밍 학습 효과를 분석하기 위해 초 중 고 학생 39명에 대해서 비동질 통제집단 사전사후측정 실험을 실시하였고, 사후검사에 대한 독립표본 T-검정 결과, 실험집단(18명)의 평균점수가 통제집단(21명)보다 유의미하게 높은 것으로 확인되었다. 이것은 본 시스템을 사용한 교수 학습 방법이 전통적인 교수 학습 방법에 비해 프로그래밍 학습에 더 효과적임을 의미한다.

• 방송공학회논문지
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• 제13권5호
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• pp.662-676
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• 2008

본 논문은 불법복제된 DTV 방송프로그램의 온라인 불법전송을 차단하기 위한 비디오 복사본 검출 알고리즘을 제안한다. 제안한 알고리즘은 급격한 휘도 변화가 나타나는 방송영상의 비디오 프레임을 선별하여 키프레임(keyframe)을 구성한 후, 키프레임의 시 공간적 특징정보를 추출하여 사전에 등록된 방송영상 저작물들의 특징정보와 비교함으로써 해당 방송영상의 불법복제 여부를 판별하는 동영상 필터링(filtering) 기능을 제공한다. 특히 모든 프레임을 이용하지 않고 키프레임만을 추출함으로써 대용량 방송영상물의 저작권 침해 여부를 효율적으로 판단할 수 있으며, 온라인 전송과정에서 빈번히 적용되는 영상비 변환, 로고 삽입, 자막 삽입, 화질 열화 및 해상도 감소 등의 다양한 동영상 편집효과에도 강인함을 실험을 통하여 확인하였다. 또한 기존 알고리즘들과의 성능비교실험을 통하여 상대적 우수성을 평가하였다.

• 한국컴퓨터정보학회논문지
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• 제24권8호
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• pp.19-28
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• 2019

In this paper, an online video summarization algorithm based on multiple object detection is proposed. As crime has been on the rise due to the recent rapid urbanization, the people's appetite for safety has been growing and the installation of surveillance cameras such as a closed-circuit television(CCTV) has been increasing in many cities. However, it takes a lot of time and labor to retrieve and analyze a huge amount of video data from numerous CCTVs. As a result, there is an increasing demand for intelligent video recognition systems that can automatically detect and summarize various events occurring on CCTVs. Video summarization is a method of generating synopsis video of a long time original video so that users can watch it in a short time. The proposed video summarization method can be divided into two stages. The object extraction step detects a specific object in the video and extracts a specific object desired by the user. The video summary step creates a final synopsis video based on the objects extracted in the previous object extraction step. While the existed methods do not consider the interaction between objects from the original video when generating the synopsis video, in the proposed method, new object clustering algorithm can effectively maintain interaction between objects in original video in synopsis video. This paper also proposed an online optimization method that can efficiently summarize the large number of objects appearing in long-time videos. Finally, Experimental results show that the performance of the proposed method is superior to that of the existing video synopsis algorithm.

• 동력기계공학회지
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• 제21권3호
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• pp.60-65
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• 2017

A GA is one of the best method to find optimal value in searching area. A GA is driven by probabilistic selection that based on the survival of the fittest. So this algorithm need a huge solving time even if it can be used lots of optimizing problem such as structural design, machine learning, system's identification and so on. This GA's characteristic constrain the program to drive offline. Some studies try to use this algorithm on online or reduce the GA's running time with parallel GA or micro GA. Unfortunately these studies still didn't reduce amount of fitness solving. If the chromosome was imported to the system, it affected system's stability. And when the control system uses online GA, it also doesn't have enough learning time. In this study, try to find stability criterion to reduce the chromosome's affection and find the characteristic of the number of population and generation when GA was driven into the wide searching area.

• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2118-2126
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• 2017

The large-scale power system blackouts have indicated that conventional protection relays that based on local signals cannot fit for modern power grids with complicated setting or heavily loaded-flow transfer. In order to accurately detect various faulted lines and improve the fault-tolerance of wide-area protection, a novel multi-section weighed fault matching and detecting algorithm is proposed. The real protection vector (RPV) and expected section protection vectors (ESPVs) for five fault sections are constructed respectively. The function of multi-section weighed fault matching is established to calculate the section fault matching degrees between RPV and five ESPVs. Then the fault degree of protected line based on five section fault degrees can be obtained. Two fault detecting criterions are given to support the higher accuracy rate of detecting fault. With the enumerating method, the simulation tests illustrate the correctness and fault-tolerance of proposed algorithm. It can reach the target of 100% accuracy rate under 5 bits error of wide-area protections. The influence factors of fault-tolerance are analyzed, which include the choosing of wide-area protections, as well as the topological structures of power grid and fault threshold.

• 전기학회논문지
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• 제63권3호
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• pp.376-382
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• 2014

E-Actuator is an essential part of an eVGT, it receives the command from the main ECU and controls the vane. An e-Actuator failure can cause an abrupt change in engine output and it may induce an accident. Therefore, it is required to detect anomalies in the e-Actuator in real time to prevent accidents. In this paper, an e-Actuator fault detection method using on-line parameter identification is proposed. To implement on-line fault detection algorithm, many constraints are considered. The test input and sampling rate are selected considering the constraints. And new recursive system identification algorithm is proposed which reduces the memory and MCU power dramatically. The relationship between the identified parameters and real elements such as gears, spring and motor are derived. The fault detection method using the relationship is proposed. The experiments with the real broken gears show the effectiveness of the proposed algorithm. It is expected that the real time fault detection is possible and it can improve the safety of eVGT system.

• 산경연구논집
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• 제9권5호
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• pp.25-35
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• 2018

Purpose - The purpose of this paper is to partition a last-mile delivery network into zones and to determine locations of last mile delivery centers (LMDCs) in Bangkok, Thailand. Research design, data, and methodology - As online shopping has become popular, parcel companies need to improve their delivery services as fast as possible. A network partition has been applied to evaluate suitable service areas by using METIS algorithm to solve this scenario and a facility location problem is used to address LMDC in a partitioned area. Research design, data, and methodology - Clustering and mixed integer programming algorithms are applied to partition the network and to locate facilities in the network. Results - Network partition improves last mile delivery service. METIS algorithm divided the area into 25 partitions by minimizing the inter-network links. To serve short-haul deliveries, this paper located 96 LMDCs in compact partitioning to satisfy customer demands. Conclusions -The computational results from the case study showed that the proposed two-phase algorithm with network partitioning and facility location can efficiently design a last-mile delivery network. It improves parcel delivery services when sending parcels to customers and reduces the overall delivery time. It is expected that the proposed two-phase approach can help parcel delivery companies minimize investment while providing faster delivery services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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• pp.3057-3075
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• 2020

End-to-end network delay plays an vital role in distributed services. This delay is used to measure QoS (Quality-of-Service). It would be beneficial to know all node-pair delay information, but unfortunately it is not feasible in practice because the use of active probing will cause a quadratic growth in overhead. Alternatively, using the measured network delay to estimate the unknown network delay is an economical method. In this paper, we adopt the state-of-the-art matrix completion technology to better estimate the network delay from limited measurements. Although the number of measurements required for an exact matrix completion is theoretically bounded, it is practically less helpful. Therefore, we propose an online adaptive sampling algorithm to measure network delay in which statistical leverage scores are used to select potential matrix elements. The basic principle behind is to sample the elements with larger leverage scores to keep the traits of important rows or columns in the matrix. The amount of samples is adaptively decided by a proposed stopping condition. Simulation results based on real delay matrix show that compared with the traditional sampling algorithm, our proposed sampling algorithm can provide better performance (smaller estimation error and less convergence pressure) at a lower cost (fewer samples and shorter processing time).

• Journal of Information Processing Systems
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• 제13권4호
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• pp.987-999
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• 2017

Extraction of influential people from their respective domains has attained the attention of scholastic community during current epoch. This study introduces an innovative interaction strength metric for retrieval of the most influential users in the online social network. The interactive strength is measured by three factors, namely re-tweet strength, commencing intensity and mentioning density. In this article, we design a novel algorithm called IPRank that considers the communications from perspectives of followers and followees in order to mine and rank the most influential people based on proposed interaction strength metric. We conducted extensive experiments to evaluate the strength and rank of each user in the micro-blog network. The comparative analysis validates that IPRank discovered high ranked people in terms of interaction strength. While the prior algorithm placed some low influenced people at high rank. The proposed model uncovers influential people due to inclusion of a novel interaction strength metric that improves results significantly in contrast with prior algorithm.