• Title/Summary/Keyword: area-time complexity

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Modified SMPO for Type-II Optimal Normal Basis (Type-II 최적 정규기저에서 변형된 SMPO)

  • Yang Dong-Jin;Chang Nam-Su;Ji Sung-Yeon;Kim Chang-Han
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.16 no.2
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    • pp.105-111
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    • 2006
  • Cryptographic application and coding theory require operations in finite field $GF(2^m)$. In such a field, the area and time complexity of implementation estimate by memory and time delay. Therefore, the effort for constructing an efficient multiplier in finite field have been proceeded. Massey-Omura proposed a multiplier that uses normal bases to represent elements $CH(2^m)$ [11] and Agnew at al. suggested a sequential multiplier that is a modification of Massey-Omura's structure for reducing the path delay. Recently, Rayhani-Masoleh and Hasan and S.Kwon at al. suggested a area efficient multipliers for modifying Agnew's structure respectively[2,3]. In [2] Rayhani-Masoleh and Hasan proposed a modified multiplier that has slightly increased a critical path delay from Agnew at al's structure. But, In [3] S.Kwon at al. proposed a modified multiplier that has no loss of a time efficiency from Agnew's structure. In this paper we will propose a multiplier by modifying Rayhani-Masoleh and Hassan's structure and the area-time complexity of the proposed multiplier is exactly same as that of S.Kwon at al's structure for type-II optimal normal basis.

VARIOGRAM-BASED URBAN CHARACTERIZATION USING HIGH RESOLUTION SATELLITE IMAGERY

  • Yoo, Hee-Young;Lee, Ki-Won;Kwon, Byung-Doo
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.413-416
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    • 2006
  • As even small features can be classified as high resolution imagery, urban remote sensing is regarded as one of the important application fields in time of wide use of the commercialized high resolution satellite imageries. In this study, we have analyzed the variogram properties of high resolution imagery, which was obtained in urban area through the simple modeling and applied to the real image. Based on the grasped variogram characteristics, we have tried to decomposed two high-resolution imagery such as IKONOS and QuickBird reducing window size until the unique variogram that urban feature has come out and then been indexed. Modeling results will be used as the fundamental data for variographic analysis in urban area using high resolution imagery later on. Index map also can be used for determining urban complexity or land-use classification, because the index is influenced by the feature size.

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Required Video Analytics and Event Processing Scenario at Large Scale Urban Transit Surveillance System (도시철도 종합감시시스템에서 요구되는 객체인식 기능 및 시나리오)

  • Park, Kwang-Young;Park, Goo-Man
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.11 no.3
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    • pp.63-69
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    • 2012
  • In this paper, we introduced design of intelligent surveillance camera system and typical event processing scenario for urban transit. To analyze video, we studied events that frequently occur in surveillance camera system. Event processing scenario is designed for seven representative situations(designated area intrusion, object abandon, object removal in designated area, object tracking, loitering and congestion measurement) in urban transit. Our system is optimized for low hardware complexity, real time processing and scenario dependent solution.

On Power System Frequency Control in Emergency Conditions

  • Bevrani, H.;Ledwich, G.;Ford, J. J.;Dong, Z.Y.
    • Journal of Electrical Engineering and Technology
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    • v.3 no.4
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    • pp.499-508
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    • 2008
  • Frequency regulation in off-normal conditions has been an important problem in electric power system design/operation and is becoming much more significant today due to the increasing size, changing structure and complexity of interconnected power systems. Increasing economic pressures for power system efficiency and reliability have led to a requirement for maintaining power system frequency closer to nominal value. This paper presents a decentralized frequency control framework using a modified low-order frequency response model containing a proportional-integral(PI) controller. The proposed framework is suitable for near-normal and emergency operating conditions. An $H_{\infty}$ control technique is applied to achieve optimal PI parameters, and an analytic approach is used to analyse the system frequency response for wide area operating conditions. Time-domain simulations with a multi-area power system example show that the simulated results agree with those predicted analytically.

Prediction of sphere surface by the theoretical area error at FDM (FDM에서 이론적 면적오차법에 의한 구형제품의 표면예측)

  • 전재억;권혁준;김수광;김준안;정진서;하만경
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.10a
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    • pp.262-265
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    • 2002
  • Fused deposition modelling(FDM) is a rapid prototyping(RP) process that fabricates part layer by layer by deposition of molten thermoplastic material extrude from a nozzle. RP system has many benefit. One of the benefit would be the ability to experiment wiか physical objects of my complexity in a relatively short period of time. But it has a matter of surface roughness and geometric accuracy. We study on Influence of angle of tangent line and area error on sphere surface roughness at fused deposition.

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A Study of Scenario in Intelligent Surveillance Camera for Urban Transit (도시철도 환경에 적합한 지능형 감시카메라 시나리오의 연구)

  • Chang, Il-Sik;Jeong, Cheol-Jun;Kim, Hyung-Min;An, Tae-Ki;Park, Goo-Man
    • Proceedings of the KSR Conference
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    • 2009.05a
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    • pp.866-871
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    • 2009
  • In this paper, we introduced design of intelligent surveillance camera system and typical event processing scenario for urban transit. To analyze video, we studied events that frequently occur in surveillance camera system. Scenario is designed for estimation in the case of seven representative situations(designated area invasion, an object left alone, removed object in designated area, object tracking, loitering and congestion measurement) in urban transit. Our system is optimized for low hardware complexity, real time processing and scenario dependent solution.

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Improvement of Learning Capabilities in Multilayer Perceptron by Progressively Enlarging the Learning Domain (점진적 학습영역 확장에 의한 다층인식자의 학습능력 향상)

  • 최종호;신성식;최진영
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.1
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    • pp.94-101
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    • 1992
  • The multilayer perceptron, trained by the error back-propagation learning rule, has been known as a mapping network which can represent arbitrary functions. However depending on the complexity of a function and the initial weights of the multilayer perceptron, the error back-propagation learning may fall into a local minimum or a flat area which may require a long learning time or lead to unsuccessful learning. To solve such difficulties in training the multilayer perceptron by standard error back-propagation learning rule, the paper proposes a learning method which progressively enlarges the learning domain from a small area to the entire region. The proposed method is devised from the investigation on the roles of hidden nodes and connection weights in the multilayer perceptron which approximates a function of one variable. The validity of the proposed method was illustrated through simulations for a function of one variable and a function of two variable with many extremal points.

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Analyzing Public Transport Network Accessibility

  • Jun, Chulmin
    • Korean Journal of Geomatics
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    • v.4 no.2
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    • pp.53-57
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    • 2004
  • Due to the traffic congestion and public-oriented transportation policies of Seoul, public transportation is receiving attention and being used increasingly. However, current transport routes configuration is showing unbalanced accessibility throughout the city area creating differences in time, expenses and metal burden of users who travel the same distances. One of the reasons is that transport route planning has been partially empirical and non-quantitative tasks due to lack of relevant methods for assessing the complexity of the transport routes. This paper presents a method to compute the connectivity of public transport system based on the topological structure of the network of transport routes. The main methodological issue starts from the fact that the more transfers take place, the deeper the connectivity becomes making that area evaluated as less advantageous as for public transport accessibility. By computing the connectivity of each bus or subway station with all others in a city, we can quantify the differences in the serviceability of city areas based on the public transportation. This paper is based on the topological interpretation of the routes network and suggests an algorithm that can automate the computation process. The process is illustrated using a simple artificial network data built in a GIS.

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A precise sensor fault detection technique using statistical techniques for wireless body area networks

  • Nair, Smrithy Girijakumari Sreekantan;Balakrishnan, Ramadoss
    • ETRI Journal
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    • v.43 no.1
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    • pp.31-39
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    • 2021
  • One of the major challenges in wireless body area networks (WBANs) is sensor fault detection. This paper reports a method for the precise identification of faulty sensors, which should help users identify true medical conditions and reduce the rate of false alarms, thereby improving the quality of services offered by WBANs. The proposed sensor fault detection (SFD) algorithm is based on Pearson correlation coefficients and simple statistical methods. The proposed method identifies strongly correlated parameters using Pearson correlation coefficients, and the proposed SFD algorithm detects faulty sensors. We validated the proposed SFD algorithm using two datasets from the Multiparameter Intelligent Monitoring in Intensive Care database and compared the results to those of existing methods. The time complexity of the proposed algorithm was also compared to that of existing methods. The proposed algorithm achieved high detection rates and low false alarm rates with accuracies of 97.23% and 93.99% for Dataset 1 and Dataset 2, respectively.

Adaptive Hard Decision Aided Fast Decoding Method in Distributed Video Coding (적응적 경판정 출력을 이용한 고속 분산 비디오 복호화 기술)

  • Oh, Ryang-Geun;Shim, Hiuk-Jae;Jeon, Byeung-Woo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.6
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    • pp.66-74
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    • 2010
  • Recently distributed video coding (DVC) is spotlighted for the environment which has restriction in computing resource at encoder. Wyner-Ziv (WZ) coding is a representative scheme of DVC. The WZ encoder independently encodes key frame and WZ frame respectively by conventional intra coding and channel code. WZ decoder generates side information from reconstructed two key frames (t-1, t+1) based on temporal correlation. The side information is regarded as a noisy version of original WZ frame. Virtual channel noise can be removed by channel decoding process. So the performance of WZ coding greatly depends on the performance of channel code. Among existing channel codes, Turbo code and LDPC code have the most powerful error correction capability. These channel codes use stochastically iterative decoding process. However the iterative decoding process is quite time-consuming, so complexity of WZ decoder is considerably increased. Analysis of the complexity of LPDCA with real video data shows that the portion of complexity of LDPCA decoding is higher than 60% in total WZ decoding complexity. Using the HDA (Hard Decision Aided) method proposed in channel code area, channel decoding complexity can be much reduced. But considerable RD performance loss is possible according to different thresholds and its proper value is different for each sequence. In this paper, we propose an adaptive HDA method which sets up a proper threshold according to sequence. The proposed method shows about 62% and 32% of time saving, respectively in LDPCA and WZ decoding process, while RD performance is not that decreased.