• Title/Summary/Keyword: Component-based System

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Component-based AI Application Support System using Knowledge Sharing Graph for EdgeCPS Platform (EdgeCPS 플랫폼을 위한 지식 공유 그래프를 활용한 컴포넌트 기반 AI 응용 지원 시스템)

  • Kim, Young-Joo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.8
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    • pp.1103-1110
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    • 2022
  • Due to the rapid development of AI-related industries, countless edge devices are working in the real world. Since data generated within the smart space consisted of these devices is beyond imagination, it is becoming increasingly difficult for edge devices to process. To solve this issue, EdgeCPS has appeared. EdgeCPS is a technology to support harmonious execution of various application services including AI applications through interworking between edge devices and edge servers, and augmenting resources/functions. Therefore, we propose a knowledge-sharing graph-based componentized AI application support system applicable to the EdgeCPS platform. The graph is designed to effectively store information which are essential elements for creating AI applications. In order to easily change resource/function augmentation under the support of the EdgeCPS platform, AI applications are operated as components. The application support system is linked with the knowledge graph so that users can easily create and test applications, and visualizes the execution aspect of the application to users as a pipeline.

Stability evaluation model for loess deposits based on PCA-PNN

  • Li, Guangkun;Su, Maoxin;Xue, Yiguo;Song, Qian;Qiu, Daohong;Fu, Kang;Wang, Peng
    • Geomechanics and Engineering
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    • v.27 no.6
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    • pp.551-560
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    • 2021
  • Due to the low strength and high compressibility characteristics, the loess deposits tunnels are prone to large deformations and collapse. An accurate stability evaluation for loess deposits is of considerable significance in deformation control and safety work during tunnel construction. 37 groups of representative data based on real loess deposits cases were adopted to establish the stability evaluation model for the tunnel project in Yan'an, China. Physical and mechanical indices, including water content, cohesion, internal friction angle, elastic modulus, and poisson ratio are selected as index system on the stability level of loess. The data set is randomly divided into 80% as the training set and 20% as the test set. Firstly, principal component analysis (PCA) is used to convert the five index system to three linearly independent principal components X1, X2 and X3. Then, the principal components were used as input vectors for probabilistic neural network (PNN) to map the nonlinear relationship between the index system and stability level of loess. Furthermore, Leave-One-Out cross validation was applied for the training set to find the suitable smoothing factor. At last, the established model with the target smoothing factor 0.04 was applied for the test set, and a 100% prediction accuracy rate was obtained. This intelligent classification method for loess deposits can be easily conducted, which has wide potential applications in evaluating loess deposits.

On Indexing Method for Current Positions of Moving Objects (이동 객체의 현재 위치 색인 기법)

  • Park, Hyun-Kyoo;Kang, Sung-Tak;Kim, Myoung-Ho;Min, Kyoung-Wook
    • Journal of Korea Spatial Information System Society
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    • v.5 no.1 s.9
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    • pp.65-74
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    • 2003
  • Location-based service is an important spatiotemporal database application area that provides the location-aware information of wireless terminals via positioning devices such as GPS. With the rapid advances of wireless communication systems, the requirement of mobile application areas including traffic, mobile commerce and supply chaining management became the center of attention for various research issues in spatiotemporal databases. In this paper we present the A-Quadtree, an efficient indexing method for answering location-based queries where the movement vector information (e.g., speed and velocity) is not presented. We implement the A-Quadtree with an index structure for object identifiers as a.Net component to apply the component to multiplatforms. We present our approach and describe the performance evaluation through various experiments. In our experiments, we compare the performance with previous approaches and show the enhanced efficiency of our method.

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An SVM-based Face Verification System Using Multiple Feature Combination and Similarity Space (다중 특징 결합과 유사도 공간을 이용한 SVM 기반 얼굴 검증 시스템)

  • 김도형;윤호섭;이재연
    • Journal of KIISE:Software and Applications
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    • v.31 no.6
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    • pp.808-816
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    • 2004
  • This paper proposes the method of implementation of practical online face verification system based on multiple feature combination and a similarity space. The main issue in face verification is to deal with the variability in appearance. It seems difficult to solve this issue by using a single feature. Therefore, combination of mutually complementary features is necessary to cope with various changes in appearance. From this point of view, we describe the feature extraction approaches based on multiple principal component analysis and edge distribution. These features are projected on a new intra-person/extra-person similarity space that consists of several simple similarity measures, and are finally evaluated by a support vector machine. From the experiments on a realistic and large database, an equal error rate of 0.029 is achieved, which is a sufficiently practical level for many real- world applications.

Noise Cancellation and Detection of Heartbeat using A New Adaptive Noise Canceller Based on ALE(Adaptive Line Enhancer) in the CW Bio-radar (CW 바이오 레이더에서 ALE(Adaptive Line Enhancer) 기반의 새로운 적응형 잡음제거기를 이용한 잡음제거 및 심장박동 검출)

  • Seo, Myung-Hwan;Kim, Jae-Joong
    • Journal of Advanced Navigation Technology
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    • v.13 no.4
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    • pp.482-489
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    • 2009
  • This paper proposes a CW(Continuous-Wave) bio-radar applying a new adaptive noise canceller based on ALE(Adaptive Line Enhancer) which can remove the Gaussian noise and system noise. Recently the research works on this CW bio-radar which can be used to detect heartbeat and respiration are advanced by the university and research facility. Although the researches describe CW bio-radar not only is vulnerable for the Gaussian noise but also has a disadvantage of decreasing the heart-rate accuracy due to the noise, the researches do not demonstrate the effective method for removing the noise component in a baseband signal. In this paper, a CW bio-radar applying the new adaptive noise canceller based on ALE which can remove the noise component is proposed. This paper compares and analyzes the performance for increasing the heart-rate accuracy according to removing the Gaussian noise and system noise in the baseband signal through the quadrature receiver which can alleviate the demodulation sensitivity to target position.

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PRINCIPAL COMPONENTS BASED SUPPORT VECTOR REGRESSION MODEL FOR ON-LINE INSTRUMENT CALIBRATION MONITORING IN NPPS

  • Seo, In-Yong;Ha, Bok-Nam;Lee, Sung-Woo;Shin, Chang-Hoon;Kim, Seong-Jun
    • Nuclear Engineering and Technology
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    • v.42 no.2
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    • pp.219-230
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    • 2010
  • In nuclear power plants (NPPs), periodic sensor calibrations are required to assure that sensors are operating correctly. By checking the sensor's operating status at every fuel outage, faulty sensors may remain undetected for periods of up to 24 months. Moreover, typically, only a few faulty sensors are found to be calibrated. For the safe operation of NPP and the reduction of unnecessary calibration, on-line instrument calibration monitoring is needed. In this study, principal component-based auto-associative support vector regression (PCSVR) using response surface methodology (RSM) is proposed for the sensor signal validation of NPPs. This paper describes the design of a PCSVR-based sensor validation system for a power generation system. RSM is employed to determine the optimal values of SVR hyperparameters and is compared to the genetic algorithm (GA). The proposed PCSVR model is confirmed with the actual plant data of Kori Nuclear Power Plant Unit 3 and is compared with the Auto-Associative support vector regression (AASVR) and the auto-associative neural network (AANN) model. The auto-sensitivity of AASVR is improved by around six times by using a PCA, resulting in good detection of sensor drift. Compared to AANN, accuracy and cross-sensitivity are better while the auto-sensitivity is almost the same. Meanwhile, the proposed RSM for the optimization of the PCSVR algorithm performs even better in terms of accuracy, auto-sensitivity, and averaged maximum error, except in averaged RMS error, and this method is much more time efficient compared to the conventional GA method.

A Research on Cool URI based on Internationalized Resource Identifier for Web 2.0 (웹 2.0을 위한 다국어 식별자 기반의 Cool URI에 대한 연구)

  • Jung, Eui-Hyun;Kim, Weon;Song, Kwan-Ho;Park, Chan-Ki
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.5 s.43
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    • pp.223-230
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    • 2006
  • Web 2.0 and Semantic Web technology will be merged to be a next generation Web that leads presentation-oriented Web to data-centric Web. In the next generation Web, semantic processing, Web platform, and data fusion are most important technology factors. Among them, Cool URI used for data fusion can provide permanent and human readable URI and it has been already used in Blog system. However, Cool URI is not suitable to I18N environment such as Hangul and it is difficult to be adopted because several encodings are mingled in Korea Web society. In this paper, we discussed technology issues and Cool URI Web component to use Cool URI with Internationalized Resource Identifier (IRI). A proposed approach provides same function regardless of encoding type and supports both file system based and CGI based methods to be easily used from other applications. Results from several test environments show the implemented Web component satisfy the design purpose.

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Missing Value Estimation and Sensor Fault Identification using Multivariate Statistical Analysis (다변량 통계 분석을 이용한 결측 데이터의 예측과 센서이상 확인)

  • Lee, Changkyu;Lee, In-Beum
    • Korean Chemical Engineering Research
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    • v.45 no.1
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    • pp.87-92
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    • 2007
  • Recently, developments of process monitoring system in order to detect and diagnose process abnormalities has got the spotlight in process systems engineering. Normal data obtained from processes provide available information of process characteristics to be used for modeling, monitoring, and control. Since modern chemical and environmental processes have high dimensionality, strong correlation, severe dynamics and nonlinearity, it is not easy to analyze a process through model-based approach. To overcome limitations of model-based approach, lots of system engineers and academic researchers have focused on statistical approach combined with multivariable analysis such as principal component analysis (PCA), partial least squares (PLS), and so on. Several multivariate analysis methods have been modified to apply it to a chemical process with specific characteristics such as dynamics, nonlinearity, and so on.This paper discusses about missing value estimation and sensor fault identification based on process variable reconstruction using dynamic PCA and canonical variate analysis.

The Information Retrieval System for Software Reuse (소프트웨어 재사용을 위한 정보검색시스템 구축)

  • Kim, Young-Geil
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.1
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    • pp.1-8
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    • 2016
  • In this paper, several problems functioning as the obstacles against software reuse were summarized. Among them, the issues dealt with in this paper include the effective method for constructing the library, the proper structure of the library, and the efficient retrieval technique. The knowledge-based approach and the information retrieval approach were integrated to construct and manage the library. The former is on the object- oriented model. Basically the object-oriented library is based on the classes and organized by inheritance. Because inheritance hierarchy is based on syntactical information, it dose not present the relationship of functionality. Using the information retrieval approach, the index file which characterizes the component and similarity among the components can be analyzed. Especially, we focused on the reusable library for the object-oriented programming environments.

IPMSM Sensorless Control Using Square-Wave-Type Voltage Injection Method with a Simplified Signal Processing (구형파 신호 주입을 이용한 IPMSM 센서리스 제어에서 개선된 신호처리 기법)

  • Park, Nae-Chun;Kim, Sang-Hoon
    • The Transactions of the Korean Institute of Power Electronics
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    • v.18 no.3
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    • pp.225-231
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    • 2013
  • This paper presents an improved signal processing technique in the square-wave-type voltage injection method for IPMSM sensorless drives. Since the sensorless method based on the square-wave voltage injection does not use low-pass filters to get an error signal for estimating rotor position and allows the frequency of the injected voltage signal to be high, the sensorless drive system may achieve an enhanced control bandwidth and reduced acoustic noise. However, this sensorless method still requires low-pass and band-pass filters to extract the fundamental component current and the injected frequency component current from the motor current, respectively. In this paper, these filters are replaced by simple arithmetic operations so that the time delay for estimating the rotor position can be effectively reduced to only one current sampling. Hence, the proposed technique can simplify its whole signal process for the IPMSM sensorless control using the square-wave-type voltage injection. The proposed technique is verified by the experiment on the 800W IPMSM drive system.