• Title/Summary/Keyword: Component-based System

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Computational Analysis of PCA-based Face Recognition Algorithms (PCA기반의 얼굴인식 알고리즘들에 대한 연산방법 분석)

  • Hyeon Joon Moon;Sang Hoon Kim
    • Journal of Korea Multimedia Society
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    • v.6 no.2
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    • pp.247-258
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    • 2003
  • Principal component analysis (PCA) based algorithms form the basis of numerous algorithms and studies in the face recognition literature. PCA is a statistical technique and its incorporation into a face recognition system requires numerous design decisions. We explicitly take the design decisions by in-troducing a generic modular PCA-algorithm since some of these decision ate not documented in the literature We experiment with different implementations of each module, and evaluate the different im-plementations using the September 1996 FERET evaluation protocol (the do facto standard method for evaluating face recognition algorithms). We experiment with (1) changing the illumination normalization procedure; (2) studying effects on algorithm performance of compressing images using JPEG and wavelet compression algorithms; (3) varying the number of eigenvectors in the representation; and (4) changing the similarity measure in classification process. We perform two experiments. In the first experiment, we report performance results on the standard September 1996 FERET large gallery image sets. The result shows that empirical analysis of preprocessing, feature extraction, and matching performance is extremely important in order to produce optimized performance. In the second experiment, we examine variations in algorithm performance based on 100 randomly generated image sets (galleries) of the same size. The result shows that a reasonable threshold for measuring significant difference in performance for the classifiers is 0.10.

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Seismic damage mitigation of bridges with self-adaptive SMA-cable-based bearings

  • Zheng, Yue;Dong, You;Chen, Bo;Anwar, Ghazanfar Ali
    • Smart Structures and Systems
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    • v.24 no.1
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    • pp.127-139
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    • 2019
  • Residual drifts after an earthquake can incur huge repair costs and might need to replace the infrastructure because of its non-reparability. Proper functioning of bridges is also essential in the aftermath of an earthquake. In order to mitigate pounding and unseating damage of bridges subjected to earthquakes, a self-adaptive Ni-Ti shape memory alloy (SMA)-cable-based frictional sliding bearing (SMAFSB) is proposed considering self-adaptive centering, high energy dissipation, better fatigue, and corrosion resistance from SMA-cable component. The developed novel bearing is associated with the properties of modularity, replaceability, and earthquake isolation capacity, which could reduce the repair time and increase the resilience of highway bridges. To evaluate the super-elasticity of the SMA-cable, pseudo-static tests and numerical simulation on the SMA-cable specimens with a diameter of 7 mm are conducted and one dimensional (1D) constitutive hysteretic model of the SMAFSB is developed considering the effects of gap, self-centering, and high energy dissipation. Two types of the SMAFSB (i.e., movable and fixed SMAFSBs) are applied to a two-span continuous reinforced concrete (RC) bridge. The seismic vulnerabilities of the RC bridge, utilizing movable SMAFSB with the constant gap size of 60 mm and the fixed SMAFSBs with different gap sizes (e.g., 0, 30, and 60 mm), are assessed at component and system levels, respectively. It can be observed that the fixed SMAFSB with a gap of 30 mm gained the most retrofitting effect among the three cases.

A Filter Algorithm based on Partial Mask and Lagrange Interpolation for Impulse Noise Removal (임펄스 잡음 제거를 위한 부분 마스크와 라그랑지 보간법에 기반한 필터 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.5
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    • pp.675-681
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    • 2022
  • Recently, with the development of IoT technology and AI, unmanned and automated in various fields, interest in video processing, which is the basis for automation such as object recognition and object classification, is increasing. Various studies have been conducted on noise removal in the video processing process, which has a significant impact on image quality and system accuracy and reliability, but there is a problem that it is difficult to restore images for areas with high impulse noise density. In this paper proposes a filter algorithm based on partial mask and Lagrange interpolation to restore the damaged area of impulse noise in the image. In the proposed algorithm, the filtering process was switched by comparing the filtering mask with the noise estimate and the purge weight was calculated based on the low frequency component and the high frequency component of the image to restore the image.

Testing Environment based on TTCN-3 for Network-based Embedded Software (TTCN-3를 이용한 네트워크 기반 임베디드 소프트웨어 테스팅 환경 구축)

  • Chae, Hochang;Jin, Xiulin;Cho, Jeonghun;Lee, Seonghun
    • IEMEK Journal of Embedded Systems and Applications
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    • v.5 no.1
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    • pp.29-38
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    • 2010
  • It is highly requested that the more complicated embedded software is used for high performance and multiple functions of the systems. This is inevitably increasing the errors. Therefore the embedded software testing is getting important recently. There are not general testing methods which are able to be applied for any embedded systems, but via this research, we introduce a testing method which is based on TTCN-3, a testing standard, for embedded systems. A testing environment for network-based embedded software is implemented with considering the features of TTCN-3 testing which is based on message exchange. The testing environment has two additional parts with TTCN-3 test system, the network analyzer to access the network-based systems and the communication interface which is suggested for embedded systems in previous work, and we have implemented the whole testing environment with interacting these two parts. In addition to the normal testing domain, called single node testing as a unit testing of V-model, we suggest another concept to test multiple nodes in network. It could be achieved by adding keywords such as supervisor and object which are describing the feature of TTCN-3 testing component and generating the TTCN-3 Executable code which contains new keywords. The testing has done for embedded software which is based on CAN network and the demonstration of the testing environment has been shown in this paper.

Context-Awareness Technology for Location Based-Service for Ubiquitous Learning (U-Learning을 위한 위치 기반 서비스로서의 상황 인식 기술)

  • Kim, Hye-Jin
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.11
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    • pp.4869-4874
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    • 2011
  • In this paper, we defined constructivism and ontology theory and associate it in Location Based Service ubiquitous learning. And this paper aims to provide a clear vision about location based service (LBS) ubiquitous learning. The typical ubiquitous learning involving the Context Aware Intelligent system was presented. Also the Architecture for learning environment including the key idea and technical concept is being presented in this paper. Guided with these principles and with the advancement of information and communication technology the context-awareness based on Artificial intelligence for Location based Service for ubiquitous Learning was conceptualized. U-learning for Location Based Service is presented here and the concept behind this new learning paradigm. The learning environment architecture which comprises the entire component is illustrated here.

Design of Pedestrian Detection and Tracking System Using HOG-PCA and Object Tracking Algorithm (HOG-PCA와 객체 추적 알고리즘을 이용한 보행자 검출 및 추적 시스템 설계)

  • Jeon, Pil-Han;Park, Chan-Jun;Kim, Jin-Yul;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.4
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    • pp.682-691
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    • 2017
  • In this paper, we propose the fusion design methodology of both pedestrian detection and object tracking system realized with the aid of HOG-PCA based RBFNN pattern classifier. The proposed system includes detection and tracking parts. In the detection part, HOG features are extracted from input images for pedestrian detection. Dimension reduction is also dealt with in order to improve detection performance as well as processing speed by using PCA which is known as a typical dimension reduction method. The reduced features can be used as the input of the FCM-based RBFNNs pattern classifier to carry out the pedestrian detection. FCM-based RBFNNs pattern classifier consists of condition, conclusion, and inference parts. FCM clustering algorithm is used as the activation function of hidden layer. In the conclusion part of network, polynomial functions such as constant, linear, quadratic and modified quadratic are regarded as connection weights and their coefficients of polynomial function are estimated by LSE-based learning. In the tracking part, object tracking algorithms such as mean shift(MS) and cam shift(CS) leads to trace one of the pedestrian candidates nominated in the detection part. Finally, INRIA person database is used in order to evaluate the performance of the pedestrian detection of the proposed system while MIT pedestrian video as well as indoor and outdoor videos obtained from IC&CI laboratory in Suwon University are exploited to evaluate the performance of tracking.

A Study on BIM-based Facility Management System Architecture Development considering the heterogeneous solution data integration (BIM과 이기종 솔류션 데이터 통합을 고려한 시설물관리 시스템 아키텍처 개발에 관한 연구)

  • Kang, Tae Wook;Choi, Hyun Sang
    • Spatial Information Research
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    • v.21 no.4
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    • pp.25-34
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    • 2013
  • The purpose of this study is to develop an efficient BIM-based FM(Facility Management) system architecture to integrate the heterogeneous solution data related to FM. The heterogeneous solution data can be an FM system, asset management system, or facility sensor database systems, as well as files created by a modeler. In this study, we define the consideration for the external heterogeneous data integration related to BIM-based FM and propose the methodology. To implement it, trends in related studies were reviewed and general use cases of BIM-based FM were derived to develop the architecture for the integration between BIM and the heterogeneous solution data. The component architecture was designed to implement the use cases, and the schema was developed for the prototype by using the proposed architecture.

Probabilistic Risk Assessment of a Steel Composite Hybrid Cable-Stayed Bridge Based on the Optimal Reliabilities (최적신뢰성에 의한 강합성 복합사장교의 확률적 위험도평가)

  • Yoon, Jung Hyun;Cho, Hyo Nam
    • Journal of Korean Society of Steel Construction
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    • v.19 no.4
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    • pp.395-402
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    • 2007
  • Probabilistic risk assessment was conducted on a hybrid cable-stayed bridge consisting of a steel-composite plate girder and a concrete girder with a long span, designed using the working stress design and strength design methods. The component reliabilities of the bridge's cables, pylons, girders, and steel-concrete conjunction were evaluated using the AFOSM(Advanced First Order Second Moment) algorithm and the simulation technique at the critical sections, based on the maximum axial force, shear, and positive and negative moments of the selected sections. For the analysis of system reliability, the hybrid cable-stayed bridge consisting of cables, pylons, and plate girders was modeled into combined failure modes, and for system reliability, the probabilities of failure and reliability index of the structural system were evaluated. Based on the results of this study, the critical failure modes of the hybrid cable-stayed bridge based on the bridge's structural characteristics are suggested, and the efficiency of the partial ETA technique for use in the risk assessment method was confirmed.

Signal Compensation for Analog Rotor Position Errors due to Nonideal Sinusoidal Encoder Signals

  • Hwang, Seon-Hwan;Kim, Dong-Youn;Kim, Jang-Mok;Jang, Do-Hyun
    • Journal of Power Electronics
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    • v.14 no.1
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    • pp.82-91
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    • 2014
  • This paper proposes a compensation algorithm for the analog rotor position errors caused by nonideal sinusoidal encoder output signals including offset and gain errors. In order to achieve a much higher resolution, position sensors such as resolvers or incremental encoders can be replaced by sinusoidal encoders. In practice, however, the periodic ripples related to the analog rotor position are generated by the offset and gain errors between the sine and cosine output signals of sinusoidal encoders. In this paper, the effects of offset and gain errors are easily analyzed by applying the concept of a rotating coordinate system based on the dq transformation method. The synchronous d-axis signal component is used directly to detect the amplitude of the offset and gain errors for the proposed compensator. As a result, the offset and gain errors can be well corrected by three integrators located on the synchronous d-axis component. In addition, the proposed algorithm does not require any additional hardware and can be easily implemented by a simple integral operation. The effectiveness of the proposed algorithm is verified through several experimental results.

Category Variable Selection Method for Efficient Clustering

  • Heo, Jun;Kim, Chae Yun;Jung, Yong-Gyu
    • International journal of advanced smart convergence
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    • v.2 no.2
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    • pp.40-42
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    • 2013
  • Recent medical industry is an aging society and the application of national health insurance, with state-of-the-art research and development, including the pharmaceutical market is greatly increased. The nation's health care industry through new support expansion and improve the quality of life for the research and development will be needed. In addition, systemic administration of basic medical supplies, or drugs are needed, the drug at the same time managing how systematic analysis of pharmaceutical ingredients, based on data through the purchase of new medicines and pharmaceutical ingredients automatically classified by analyzing the statistics of drug purchases and the future a system that can predict a patient is needed. In this study, the drugs to the patient according to the component analysis and predictions for future research techniques, k-means clustering and k-NN (Nearest Neighbor) Comparative studies through experiments using the techniques employ a more efficient method to study how to proceed. In this study, the effects of the drugs according to the respective components in time according to the number of pieces in accordance with the patient by analyzing the statistics by predicting future patient better medical industry can be built.