• Title/Summary/Keyword: Vector analysis

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High-Altitude Terminal Guidance and Control Loop Design Using Thrust Vector Control (추력벡터제어를 이용한 고고도 종말 유도조종 루프 설계)

  • Jeon, Ha-Min;Park, Jongho;Ryoo, Chang-Kyung
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.50 no.6
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    • pp.393-400
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    • 2022
  • The Divert and Attitude Control System(DACS) used in high-altitude engagements is expensive and complex. In this paper, we design a high-altitude terminal guidance and control loop of guided-missile equipped with a Thrust Vector Control(TVC) that is less expensive and simpler than DACS. The proposed system utilizes a quaternion feedback control technique to track the thrust attitude command converted from the acceleration command of true proportional navigation guidance. The performance analysis of the proposed terminal guidance and control loop is conducted through engagement simulations against ballistic targets at a high altitude.

Estimation of various amounts of kaolinite on concrete alkali-silica reactions using different machine learning methods

  • Aflatoonian, Moein;Mirhosseini, Ramin Tabatabaei
    • Structural Engineering and Mechanics
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    • v.83 no.1
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    • pp.79-92
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    • 2022
  • In this paper, the impact of a vernacular pozzolanic kaolinite mine on concrete alkali-silica reaction and strength has been evaluated. For making the samples, kaolinite powder with various levels has been used in the quality specification test of aggregates based on the ASTM C1260 standard in order to investigate the effect of kaolinite particles on reducing the reaction of the mortar bars. The compressive strength, X-Ray Diffraction (XRD) and Scanning Electron Microscope (SEM) experiments have been performed on concrete specimens. The obtained results show that addition of kaolinite powder to concrete will cause a pozzolanic reaction and decrease the permeability of concrete samples comparing to the reference concrete specimen. Further, various machine learning methods have been used to predict ASR-induced expansion per different amounts of kaolinite. In the process of modeling methods, optimal method is considered to have the lowest mean square error (MSE) simultaneous to having the highest correlation coefficient (R). Therefore, to evaluate the efficiency of the proposed model, the results of the support vector machine (SVM) method were compared with the decision tree method, regression analysis and neural network algorithm. The results of comparison of forecasting tools showed that support vector machines have outperformed the results of other methods. Therefore, the support vector machine method can be mentioned as an effective approach to predict ASR-induced expansion.

Unsupervised Change Detection Based on Sequential Spectral Change Vector Analysis for Updating Land Cover Map (토지피복지도 갱신을 위한 S2CVA 기반 무감독 변화탐지)

  • Park, Nyunghee;Kim, Donghak;Ahn, Jaeyoon;Choi, Jaewan;Park, Wanyong;Park, Hyunchun
    • Korean Journal of Remote Sensing
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    • v.33 no.6_2
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    • pp.1075-1087
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    • 2017
  • In this study, we tried to utilize results of the change detection analysis for satellite images as the basis for updating the land cover map. The Sequential Spectral Change Vector Analysis ($S^2CVA$) was applied to multi-temporal multispectral satellite imagery in order to extract changed areas, efficiently. Especially, we minimized the false alarm rate of unsupervised change detection due to the seasonal variation using the direction information in $S^2CVA$. The binary image, which is the result of unsupervised change detection, was integrated with the existing land cover map using the zonal statistics. And then, object-based analysis was performed to determine the changed area. In the experiment using PlanetScope data and the land cover map of the Ministry of Environment, the change areas within the existing land cover map could be detected efficiently.

A Study on Searching Stabled EMI Shielding Effectiveness Measurement Point for Military Communication Shelter Using Support Vector Machine and Process Capability Analysis (서포트 벡터 머신과 공정능력분석을 이용한 군 통신 쉘터의 EMI 차폐효과 안정 포인트 탐색 연구)

  • Ku, Ki-Beom;Kwon, Jae-Wook;Jin, Hong-Sik
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.2
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    • pp.321-328
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    • 2019
  • A military shelter for communication and information is necessary to optimize the integrated combat ability of weapon systems in the network centric warfare. Therefore, the military shelter is required for EMI shielding performance. This study examines the stable measurement points for EMI shielding effectiveness of a military shelter for communication and information. The measurement points were found by analyzing the EMI shielding effectiveness measurement data with data mining technique and process capability analysis. First, a support vector machine was used to separate the measurement point that has stable EMI shielding effectiveness according to set condition. Second, this process was conducted with process capability analysis. Finally, the results of data mining technique were compared with those of process capability analysis. As a result, 24 measurement points with stable EMI shielding effectiveness were found.

Study on Correlation-based Feature Selection in an Automatic Quality Inspection System using Support Vector Machine (SVM) (SVM 기반 자동 품질검사 시스템에서 상관분석 기반 데이터 선정 연구)

  • Song, Donghwan;Oh, Yeong Gwang;Kim, Namhun
    • Journal of Korean Institute of Industrial Engineers
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    • v.42 no.6
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    • pp.370-376
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    • 2016
  • Manufacturing data analysis and its applications are getting a huge popularity in various industries. In spite of the fast advancement in the big data analysis technology, however, the manufacturing quality data monitored from the automated inspection system sometimes is not reliable enough due to the complex patterns of product quality. In this study, thus, we aim to define the level of trusty of an automated quality inspection system and improve the reliability of the quality inspection data. By correlation analysis and feature selection, this paper presents a method of improving the inspection accuracy and efficiency in an SVM-based automatic product quality inspection system using thermal image data in an auto part manufacturing case. The proposed method is implemented in the sealer dispensing process of the automobile manufacturing and verified by the analysis of the optimal feature selection from the quality analysis results.

An Application of Canonical Analysis on the Distribution of Lichens in Mt. Duckyuoo (덕유산 지의식물 분포에 대한 정준분석법의 적용연구)

  • Park, Seung Tai
    • The Korean Journal of Ecology
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    • v.9 no.3
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    • pp.135-147
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    • 1986
  • The simplification and the searching trends of complex data which assumed relationship between predictor variables and object variables are one of primary objective of ecological research. This study was aimed to apply cononical analysis consisting of canonical correlation analysis and canonical variate analysis related to lichen vegetation and several environmental variables which are elevation, height on grond, exposure side and cover values. Data collected from the Duckyoo National Park in August 1985. Lichen species was ranked by eqivocation information theory with cover values. Canonical correlation analysis was applied to one data set both set both environmental variables and lichem family. In order to make two sets of data matrix the scale of position vector ordination was calculated from the vector scalar product for lichen species. Canonical variate analysis was applied to rearranged data which was made by interval class code for environmental variables. The sharpness values was calculated in frequency of cotingency tables and the dispersion profiles of each species in classes of environmental variables was designed to extract component values based on the decomposition of expected frequencies in contingency table. The results of canonical correlation analysis revealed canonical first correlation value 0.815(89%), and second correlation value 0.083(11%). Significance test showed that the hypothesis of joint mutuallity of canonical correlation is accepted (P>0.05). The relation between canonical score of vegetation variables and that of environmental variable indicated linear tendency.

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A Study on Security Authentication Vector Generation of Virtualized Internal Environment using Machine Learning Algorithm (머신러닝 알고리즘이 적용된 가상화 내부 환경의 보안 인증벡터 생성에 대한 연구)

  • Choi, Do-Hyeon;Park, Jung Oh
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.16 no.6
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    • pp.33-42
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    • 2016
  • Recently, the investment and study competition regarding machine running is accelerating mainly with Google, Amazon, Microsoft and other leading companies in the field of artificial intelligence. The security weakness of virtualization technology security structure have been a serious issue continuously. Also, in most cases, the internal data security depend on the virtualization security technology of platform provider. This is because the existing software, hardware security technology is hard to access to the field of virtualization and the efficiency of data analysis and processing in security function is relatively low. This thesis have applied user significant information to machine learning algorithm, created security authentication vector able to learn to provide with a method which the security authentication can be conducted in the field of virtualization. As the result of performance analysis, the interior transmission efficiency of authentication vector in virtualization environment, high efficiency of operation method, and safety regarding the major formation parameter were demonstrated.

Insect Cell Surface Expression of Hemagglutinin (HA) of Egyptian H5N1 Avian Influenza Virus Under Transcriptional Control of Whispovirus Immediate Early-1 Promoter

  • Gadalla, M.R.;El-Deeb, A.H.;Emara, M.M.;Hussein, H.A.
    • Journal of Microbiology and Biotechnology
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    • v.24 no.12
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    • pp.1719-1727
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    • 2014
  • In the present study, whispovirus immediate early 1 promoter (ie-1) was used to initiate surface expression of the hemagglutinin (HA) protein of Egyptian H5N1 avian influenza virus (AIV) by using the baculovirus expression vector system. The HA gene and whispovirus ie-1 promoter sequence were synthesized as a fused expression cassette (ie1-HA) and successfully cloned into the pFastBac-1 transfer vector. The recombinant vector was transformed into DH10Bac competent cells, and the recombinant bacmid was generated via site-specific transposition. The recombinant bacmid was used for transfection of Spodoptera frugiperda (Sf-9) insect cells to construct the recombinant baculovirus and to induce expression of the HA protein of H5N1 AIV. The recombinant glycoprotein expressed in Sf-9 cells showed hemadsorption activity. Hemagglutination activity was also detected in both extra- and intracellular recombinant HAs. Both the HA and hemadsorption activities were inhibited by reference polyclonal anti-H5 sera. Significant expression of the recombinant protein was observed on the surface of infected insect cells by using immunofluorescence. SDS-PAGE analysis of the expressed protein revealed the presence of a visually distinguishable band of ~63 kDa in size, which was absent in the non-infected cell control. Western blot analysis confirmed that the distinct 63 kDa band corresponded to the recombinant HA glycoprotein of H5N1 AIV. This study reports the successful expression of the HA protein of H5N1 AIV. The expressed protein was displayed on the plasma membrane of infected insect cells under the control of whispovirus ie-1 promoter by using the baculovirus expression vector system.

Genetic Clustering with Semantic Vector Expansion (의미 벡터 확장을 통한 유전자 클러스터링)

  • Song, Wei;Park, Soon-Cheol
    • The Journal of the Korea Contents Association
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    • v.9 no.3
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    • pp.1-8
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    • 2009
  • This paper proposes a new document clustering system using fuzzy logic-based genetic algorithm (GA) and semantic vector expansion technology. It has been known in many GA papers that the success depends on two factors, the diversity of the population and the capability to convergence. We use the fuzzy logic-based operators to adaptively adjust the influence between these two factors. In traditional document clustering, the most popular and straightforward approach to represent the document is vector space model (VSM). However, this approach not only leads to a high dimensional feature space, but also ignores the semantic relationships between some important words, which would affect the accuracy of clustering. In this paper we use latent semantic analysis (LSA)to expand the documents to corresponding semantic vectors conceptually, rather than the individual terms. Meanwhile, the sizes of the vectors can be reduced drastically. We test our clustering algorithm on 20 news groups and Reuter collection data sets. The results show that our method outperforms the conventional GA in various document representation environments.

A Technique for Mixed Pixel Extraction by Canonical Vector Analysis (정준벡터분석에 의한 혼합화소 해석기법에 관한 연구)

  • 박민호
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.16 no.1
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    • pp.75-84
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    • 1998
  • To achieve more accurate information from satellite image data, a research on a technique for mixed pixel ex-traction has been produced. The mixed pixels with only two land covers have been experimented. By analyzing canonical vector in canonical correlation classification, the mixed pixels have been classified. The ratio of the two canonical weighted values-the elements of canonical vector have been used as a threshold to discriminate mixed pixels. In case of the classification for the mixed pixels of bridge and water class in TM data before or after the 1st of September, the threshold for the optimal classification of the mixed pixels is 4.0. That is, if the ratio of the two canonical weighted values is less than 4.0, the pixel is a mixed pixel. Also, using the distribution of canonical weighted values, the constitution percentages of land covers within one mixed pixel can be approximately deducted. The accuracy of mixed pixel extraction for experimental area is 90% and quite acceptable. Conclusively, a technique for mixed pixel extraction by canonical vector analysis is effective.

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