• 제목/요약/키워드: Component mining

검색결과 142건 처리시간 0.027초

The Heavy Metal Tolerant Soil Bacterium Achromobacter sp. AO22 Contains a Unique Copper Homeostasis Locus and Two mer Operons

  • Ng, Shee Ping;Palombo, Enzo A.;Bhave, Mrinal
    • Journal of Microbiology and Biotechnology
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    • 제22권6호
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    • pp.742-753
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    • 2012
  • Copper-containing compounds are introduced into the environment through agricultural chemicals, mining, and metal industries and cause severe detrimental effects on ecosystems. Certain microorganisms exposed to these stressors exhibit molecular mechanisms to maintain intracellular copper homeostasis and avoid toxicity. We have previously reported that the soil bacterial isolate Achromobacter sp. AO22 is multi-heavy metal tolerant and exhibits a mer operon associated with a Tn21 type transposon. The present study reports that AO22 also hosts a unique cop locus encoding copper homeostasis determinants. The putative cop genes were amplified from the strain AO22 using degenerate primers based on reported cop and pco sequences, and a constructed 10,552 base pair contig (GenBank Accession No. GU929214). BLAST analyses of the sequence revealed a unique cop locus of 10 complete open reading frames, designated copSRABGOFCDK, with unusual separation of copCD from copAB. The promoter areas exhibit two putative cop boxes, and copRS appear to be transcribed divergently from other genes. The putative protein CopA may be a copper oxidase involved in export to the periplasm, CopB is likely extracytoplasmic, CopC may be periplasmic, CopD is cytoplasmic/inner membrane, CopF is a P-type ATPase, and CopG, CopO, and CopK are likely copper chaperones. CopA, B, C, and D exhibit several potential copper ligands and CopS and CopR exhibit features of two-component regulatory systems. Sequences flanking indicate the AO22 cop locus may be present within a genomic island. Achromobacter sp. strain AO22 is thus an ideal candidate for understanding copper homeostasis mechanisms and exploiting them for copper biosensor or biosorption systems.

Development of triangular flat-shell element using a new thin-thick plate bending element based on semiLoof constrains

  • Chen, Yong-Liang;Cen, Song;Yao, Zhen-Han;Long, Yu-Qiu;Long, Zhi-Fei
    • Structural Engineering and Mechanics
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    • 제15권1호
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    • pp.83-114
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    • 2003
  • A new simple 3-node triangular flat-shell element with standard nodal DOF (6 DOF per node) is proposed for the linear and geometrically nonlinear analysis of very thin to thick plate and shell structures. The formulation of element GT9 (Long and Xu 1994), a generalized conforming membrane element with rigid rotational freedoms, is employed as the membrane component of the new shell element. Both one-point reduced integration scheme and a corresponding stabilization matrix are adopted for avoiding membrane locking and hourglass phenomenon. The bending component of the new element comes from a new generalized conforming Kirchhoff-Mindlin plate element TSL-T9, which is derived in this paper based on semiLoof constrains and rational shear interpolation. Thus the convergence can be guaranteed and no shear locking will happen. Furthermore, a simple hybrid procedure is suggested to improve the stress solutions, and the Updated Lagrangian formulae are also established for the geometrically nonlinear problems. Numerical results with solutions, which are solved by some other recent element models and the models in the commercial finite element software ABAQUS, are presented. They show that the proposed element, denoted as GMST18, exhibits excellent and better performance for the analysis of thin-think plates and shells in both linear and geometrically nonlinear problems.

스마트 환경에서 행위 인식을 위한 센서 선정 기법 (Sensor Selection Strategies for Activity Recognition in a Smart Environment)

  • 구성도;손경아
    • 정보과학회 논문지
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    • 제42권8호
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    • pp.1031-1038
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    • 2015
  • 스마트 폰의 출현에 이어 최근 웨어러블 기기와 IoT 개념의 등장으로 언제 어디서든 여러 다양한 객체들 간의 상호작용이 가능하게 되었다. 그 중 홈 네트워크를 이용한 스마트 홈 서비스를 위해서는 수많은 센서들이 필요하다. 이러한 스마트 환경에서의 센서 데이터를 이용하여 거주자의 행위를 인식하는 연구가 활발히 진행되고 있다. 각종 센서 데이터 마이닝 기법을 통한 행위 인식 및 패턴 분석을 위해 많은 센서가 사용되지만, IoT 스마트 홈 서비스를 위해 수많은 센서들이 설치되어야 한다면 비용의 문제와 에너지 소모의 문제를 야기할 것이다. 본 논문에서는 스마트 환경에서 주성분 분석과 클러스터링 기법을 활용하여 적은 수의 센서를 선정하는 방식을 제안하며, 이에 따른 거주자 행위 인식률의 개선 효과를 보인다.

Moment-rotation relationship of hollow-section beam-to-column steel joints with extended end-plates

  • Wang, Jia;Zhu, Haiming;Uy, Brian;Patel, Vipulkumar;Aslani, Farhad;Li, Dongxu
    • Steel and Composite Structures
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    • 제29권6호
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    • pp.717-734
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    • 2018
  • This paper presents the flexural performance of steel beam-to-column joints composed of hollow structural section beams and columns. A finite element (FE) model was developed incorporating geometrical and material nonlinearities to evaluate the behaviour of joints subjected to bending moments. The numerical outcomes were validated with experimental results and compared with EN1993-1-8. The demountability of the structure was discussed based on the tested specimen. A parametric analysis was carried out to investigate the effects of steel yield strength, end-plate thickness, beam thickness, column wall thickness, bolt diameter, number of bolts and location. Consequently, an analytical model was derived based on the component method to predict the moment-rotation relationships for the sub-assemblies with extended end-plates. The accuracy of the proposed model was calibrated by the experimental and numerical results. It is found that the FE model is fairly reliable to predict the initial stiffness and moment capacity of the joints, while EN1993-1-8 overestimates the initial stiffness extensively. The beam-to-column joints are shown to be demountable and reusable with a moment up to 53% of the ultimate moment capacity. The end-plate thickness and column wall thickness have a significant influence on the joint behaviour, and the layout of double bolt-rows in tension is recommended for joints with extended end-plates. The derived analytical model is capable of predicting the moment-rotation relationship of the structure.

데이터 마이닝 기법을 이용한 차량용 반도체의 불량률 예측 연구 (Prediction of field failure rate using data mining in the Automotive semiconductor)

  • 윤경식;정희운;박승범
    • 기술혁신연구
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    • 제26권3호
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    • pp.37-68
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    • 2018
  • 본 논문에서는 차량용 반도체가 제품 출하 후 사용 환경에 따라 발생되는 불량률을 데이터 마이닝 기법을 이용하여 분석하였다. 20세기 이후 가장 보편적인 이동수단인 자동차는 전자 컨트롤 장치와 자동차용 반도체의 사용량이 급격히 증가하면서 매우 빠른 속도로 진화하고 있다. 자동차용 반도체는 차량용 전자 컨트롤 장치 중 핵심 부품으로 소비자들에게 안정성, 연료 사용의 효율성, 운전의 안정감을 제공하기 위해 사용되고 있다. 자동차용 반도체는 가솔린엔진, 디젤 엔진, 전기 모터를 컨트롤하는 기술, 헤드업 디스플레이, 차선 유지 시스템 등 많은 부분에 적용되고 있다. 이와 같이 반도체는 자동차를 구성하는 거의 모든 전자 컨트롤 장치에 적용되고 있으며 기계적인 장치를 단순히 조합한 이상의 효과를 만들어 내고 있다. 자동차용 반도체는 10년 이상의 자동차 사용 기간을 고려하여 높은 신뢰성, 내구성, 장기공급 등의 특성을 요구하고 있다. 자동차용 반도체의 신뢰성은 자동차의 안전성과 직접적으로 연결되기 때문이다. 반도체업계에서는 JEDEC과 AEC 등의 산업 표준 규격을 이용하여 자동차용 반도체의 신뢰성을 평가하고 있다. 또한 자동차 산업에서 표준으로 제시한 신뢰성 실험 방법과 그 결과를 이용하여 개발 초기 단계 및 제품 양산 초기단계에서 제품의 수명을 예측 하고 있다. 하지만 고객의 다양한 사용 조건 및 사용 시간 등 여러 변수들에 의해 발생되는 불량률을 예측하는 데는 한계가 있다. 이러한 한계점을 극복하기 위하여 학계와 산업계에서 많은 연구가 있어왔다. 그 중 데이터 마이닝 기법을 이용한 연구가 다수의 반도체 분야에서 진행되고 있지만, 아직 자동차용 반도체에 대한 적용 및 연구는 미비한 상태이다. 이러한 관점에서 본 연구는 데이터 마이닝 기법을 이용하여 반도체 조립(Assembly)과 패키지 테스트(Package test) 공정 중 발생 된 데이터들간의 연관성을 규명하고, 고객 불량 데이터를 이용하여 잠재 불량률 예측에 적합한 데이터 마이닝 기법을 검증하였다.

국내 인프라사운드 전파특성 연구 (Infrasound Wave Propagation Characteristics in Korea)

  • 제일영
    • 한국지진공학회:학술대회논문집
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    • 한국지진공학회 2000년도 춘계 학술발표회 논문집 Proceedings of EESK Conference-Spring
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    • pp.63-69
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    • 2000
  • Korea Institute of Geology Mining and Materials(KIGAM) cooperating with Southern Methodist University(SMU) has been operating seismo-acoustic array in Chul-Won area to discriminate man-made explosions from natural earthquakes since at the end of July 1999. In order to characterize propagation parameters of detected seismo-acoustic signal and to associate these signals as a blast event accompanying seismic and acoustic signals simultaneously it is necessary to understand infrasound wave propagation in the atmosphere. Two comparable Effective Sound Velocity Structures(ESVS) in atmosphere were constructed by using empirical model (MSISE90 and HWM93) and by aerological observation data of Korea Meteorological Administration (KMA) at O-San area. Infrasound propagation path computed by empirical model resulted in rare arival of refracted waves on ground less than 200km from source region. On the other hand Propagation paths by KMA more realistic data had various arrivals at near source region and well agreement with analyzed seismo-acoustic signals from Chul-Won data. And infrasound propagation in specific direction was very influenced by horizontal wind component in that direction. Linear travel time curve drawn up by 9 days data of the KMA in autumn season showed 335.6m/s apparent sound velocity in near source region. The propagation characteristics will be used to associate seismo-acoustic signals and to calculate propagation parameters of infrasound wave front.

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데이터 정보를 이용한 흑색 플라스틱 분류기 설계 (Design of Black Plastics Classifier Using Data Information)

  • 박상범;오성권
    • 전기학회논문지
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    • 제67권4호
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    • pp.569-577
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    • 2018
  • In this paper, with the aid of information which is included within data, preprocessing algorithm-based black plastic classifier is designed. The slope and area of spectrum obtained by using laser induced breakdown spectroscopy(LIBS) are analyzed for each material and its ensuing information is applied as the input data of the proposed classifier. The slope is represented by the rate of change of wavelength and intensity. Also, the area is calculated by the wavelength of the spectrum peak where the material property of chemical elements such as carbon and hydrogen appears. Using informations such as slope and area, input data of the proposed classifier is constructed. In the preprocessing part of the classifier, Principal Component Analysis(PCA) and fuzzy transform are used for dimensional reduction from high dimensional input variables to low dimensional input variables. Characteristic analysis of the materials as well as the processing speed of the classifier is improved. In the condition part, FCM clustering is applied and linear function is used as connection weight in the conclusion part. By means of Particle Swarm Optimization(PSO), parameters such as the number of clusters, fuzzification coefficient and the number of input variables are optimized. To demonstrate the superiority of classification performance, classification rate is compared by using WEKA 3.8 data mining software which contains various classifiers such as Naivebayes, SVM and Multilayer perceptron.

설명기반 유전자알고리즘을 활용한 경영성과 데이터베이스이 데이터마이닝 (Data-Mining in Business Performance Database Using Explanation-Based Genetic Algorithms)

  • 조성훈;정민용
    • 경영과학
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    • 제18권1호
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    • pp.135-145
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    • 2001
  • In recent environment of dynamic management, there is growing recognition that information and knowledge management systems are essential for efficient/effective decision making by CEO. To cope with this situation, we suggest the Data-Miming scheme as a key component of integrated information and knowledge management system. The proposed system measures business performance by considering both VA(Value-Added), which represents stakeholder’s point of view and EVA (Economic Value-Added), which represents shareholder’s point of view. To mine the new information & Knowledge discovery, we applied the improved genetic algorithms that consider predictability, understandability (lucidity) and reasonability factors simultaneously, we use a linear combination model for GAs learning structure. Although this model’s predictability will be more decreased than non-linear model, this model can increase the knowledge’s understandability that is meaning of induced values. Moreover, we introduce a random variable scheme based on normal distribution for initial chromosomes in GAs, so we can expect to increase the knowledge’s reasonability that is degree of expert’s acceptability. the random variable scheme based on normal distribution uses statistical correlation/determination coefficient that is calculated with training data. To demonstrate the performance of the system, we conducted a case study using financial data of Korean automobile industry over 16 years from 1981 to 1996, which is taken from database of KISFAS (Korea Investors Services Financial Analysis System).

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크로스 층에서의 MANET을 이용한 IDS (An IDS in MANET with Cross Layer Concept)

  • 김상언;한승조
    • 한국항행학회논문지
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    • 제14권1호
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    • pp.41-48
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    • 2010
  • 침입 탐지는 인터넷 보안에 반드시 필요한 구성 요소이다. 발전하고 있는 추세에 뒤지지 않고 따라가기 위해 싱글 레이어 탐지 기술을 멀티 레이어 탐지 기술에 적용 할 수 있는 방법이 필요하다. 다른 타입의 서비스 거부 공격(DoS)은 인가된 사용자의 네트워크 접근을 방해하므로 서비스 거부 공격의 취약한 점을 찾아 피해를 최소화 하기위해 노력했다. 우리는 악의적인 노드를 발견하기 위한 새로운 크로스 레이어 침입 탐지 아키텍처를 제안한다. 프로토콜 스텍에서 서로 다른 레이어를 가로지를 수 있는 정보는 탐색의 정확성을 향상시키기 위하여 제안하였다. 제안한 프로토콜의 아키텍처를 강화하기 위해 데어터 마이닝을 사용하여 조합과 분배의 변칙적인 침입탐지 시스템을 사용했다. 제안하고 있는 구조의 시뮬레이션은 OPNET 시뮬레이터를 사용하여 결과 분석을 하였다.

Quantitative parameters of primary roughness for describing the morphology of surface discontinuities at various scales

  • Belem, Tikou
    • Geomechanics and Engineering
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    • 제11권4호
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    • pp.515-530
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    • 2016
  • In this paper, five different quantitative parameters were proposed for the characterization of the primary roughness which is the component of surface morphology that prevails during large strike-slip faults of more than 50 m. These parameters are mostly the anisotropic properties of rock surface morphology at various scales: (i) coefficient ($k_a$) and degree (${\delta}_a$) of apparent structural anisotropy of surface; (ii) coefficient ($k_r$) and degree (${\delta}_r$) of real structural anisotropy of surface; (iii) surface anisotropy function P(${\varphi}$); and (iv) degree of surface waviness ($W_s$). The coefficient and degree of apparent structural anisotropy allow qualifying the anisotropy/isotropy of a discontinuity according to a classification into four classes: anisotropic, moderately anisotropic/isotropic and isotropic. The coefficient and degree of real structural anisotropy of surface captures directly the actual surface anisotropy using geostatistical method. The anisotropy function predicts directional geometric properties of a surface of discontinuity from measurements in two orthogonal directions. These predicted data may subsequently be used to highlight the anisotropy/isotropy of the surface (radar plot). The degree of surface waviness allows qualifying the undulation of anisotropic surfaces. The proposed quantitative parameters allows their application at both lab and field scales.