• Title/Summary/Keyword: Composition Algorithm

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The Application of the Spectral Similarity Scale Algorithm and Expectation-Maximization for Unsupervised Change Detection using Hyperspectral Image (하이퍼스펙트럴 영상의 무감독 변화탐지를 위한 SSS 알고리즘과 기대최대화 기법의 적용)

  • Kim, Yong-Hyun;Kim, Dae-Sung;Kim, Yong-Il;Yu, Ki-Yun
    • 한국공간정보시스템학회:학술대회논문집
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    • 2007.06a
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    • pp.139-144
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    • 2007
  • Recording data in hundreds of narrow contiguous spectral intervals, hyperspectral images have provided the opportunity to detect small differences in material composition. But a limitation of a hyperspectral image is the signal to noise ratio (SNR) lower than that of a multispectral image. This paper presents the efficiency of Spectral Similarity Scale (SSS) in change detection of hyperspectral image and the experiment was performed with Hyperion data. SSS is an algorithm that objectively quantifies differences between reflectance spectra in both magnitude and direction dimensions. The thresholds for detecting the change area were determined through Expectation-Maximization (EM) algorithm. The experimental result shows that the SSS algorithm and EM algorithm are efficient enough to be applied to the unsupervised change detection of hyperspectral images.

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A Local Path Planning Algorithm considering the Mobility of UGV based on the Binary Map (무인차량의 주행성능을 고려한 장애물 격자지도 기반의 지역경로계획)

  • Lee, Young-Il;Lee, Ho-Joo;Ko, Jung-Ho
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.2
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    • pp.171-179
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    • 2010
  • A fundamental technology of UGV(Unmanned Ground Vehicle) to perform a given mission with success in various environment is a path planning method which generates a safe and optimal path to the goal. In this paper, we suggest a local path-planning method of UGV based on the binary map using world model data which is gathered from terrain perception sensors. In specially, we present three core algorithms such as shortest path computation algorithm, path optimization algorithm and path smoothing algorithm those are used in the each composition module of LPP component. A simulation is conducted with M&S(Modeling & Simulation) system in order to verify the performance of each core algorithm and the performance of LPP component with scenarios.

The Effect of Representative Dataset Selection on Prediction of Chemical Composition for Corn kernel by Near-Infrared Reflectance Spectroscopy (예측알고리즘 적용을 위한 데이터세트 구성이 근적외선 분광광도계를 이용한 옥수수 품질평가에 미치는 영향)

  • Choi, Sung-Won;Lee, Chang-Sug;Park, Chang-Hee;Kim, Dong-Hee;Park, Sung-Kwon;Kim, Beob-Gyun;Moon, Sang-Ho
    • Journal of Animal Environmental Science
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    • v.20 no.3
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    • pp.117-124
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    • 2014
  • The objectives were to assess the use of near-infrared reflectance spectroscopy (NIRS) as a tool for estimating nutrient compositions of corn kernel, and to apply an NIRS-based indium gallium arsenide array detector to the system for collecting spectra and analyzing calibration equations using equipments designed for field application. Partial Least Squares Regression (PLSR) was employed to develop calibration equations based on representative data sets. The kennard-stone algorithm was applied to induce a calibration set and a validation set. As a result, the method for structuring a calibration set significantly affected prediction accuracy. The prediction of chemical composition of corn kernel resulted in the following (kennard-stone algorithm: relative) moisture ($R^2=0.82$, RMSEP=0.183), crude protein ($R^2=0.80$, RMSEP=0.142), crude fat ($R^2=0.84$, RMSEP=0.098), crude fiber ($R^2=0.74$, RMSEP=0.098), and crude ash ($R^2=0.81$, RMSEP=0.048). Result of this experiment showed the potential of NIRS to predict the chemical composition of corn kernel.

A Study on Service Composition Using Case-Based Reasoning (사례 기반 추론을 이용한 서비스 컴포지션 연구)

  • Kim, Kun-Su;Lee, Dong-Hoon;Park, Doo-Kyung;Lee, Jee-Hyong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.2
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    • pp.175-182
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    • 2008
  • Context-aware service environment should provide many kinds of services according to users' requests. Users want a great variety of services. In response to their demands the service provider should make a new service every time. But making a new service every time may be inefficient even for a small number of users' requests. So, there are studies on how to efficiently support various and complex requests fFom users. In many researches, service compositions have lately attracted considerable attention. However, existing researches have mainly focused on Web services. So they are not proper to rapidly providing services in response to users' requests, especially In context-aware service environment. This paper proposes a rapid service composition using case-based reasoning. For evaluating the proposed algorithm we implement 'purchasing seTvice agent'. With this system, we compare our algorithm and the existing service composition algorithms.

Neural Network Modeling of PECVD SiN Films and Its Optimization Using Genetic Algorithms

  • Han, Seung-Soo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.1 no.1
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    • pp.87-94
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    • 2001
  • Silicon nitride films grown by plasma-enhanced chemical vapor deposition (PECVD) are useful for a variety of applications, including anti-reflecting coatings in solar cells, passivation layers, dielectric layers in metal/insulator structures, and diffusion masks. PECVD systems are controlled by many operating variables, including RF power, pressure, gas flow rate, reactant composition, and substrate temperature. The wide variety of processing conditions, as well as the complex nature of particle dynamics within a plasma, makes tailoring SiN film properties very challenging, since it is difficult to determine the exact relationship between desired film properties and controllable deposition conditions. In this study, SiN PECVD modeling using optimized neural networks has been investigated. The deposition of SiN was characterized via a central composite experimental design, and data from this experiment was used to train and optimize feed-forward neural networks using the back-propagation algorithm. From these neural process models, the effect of deposition conditions on film properties has been studied. A recipe synthesis (optimization) procedure was then performed using the optimized neural network models to generate the necessary deposition conditions to obtain several novel film qualities including high charge density and long lifetime. This optimization procedure utilized genetic algorithms, hybrid combinations of genetic algorithm and Powells algorithm, and hybrid combinations of genetic algorithm and simplex algorithm. Recipes predicted by these techniques were verified by experiment, and the performance of each optimization method are compared. It was found that the hybrid combinations of genetic algorithm and simplex algorithm generated recipes produced films of superior quality.

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Effective Design of Inference Rule for Shape Classification

  • Kim, Yoon-Ho;Lee, Sang-Sock;Lee, Joo-Shin
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.417-422
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    • 1998
  • This paper presents a method of object classification from dynamic image based on fuzzy inference algorithm which is suitable for low speed such as, conveyor, uninhabited transportation. At first, by using feature parameters of moving object, fuzzy if - then rule that can be able to adapt the wide variety of surroundings is developed. Secondly, implication function for fuzzy inference are compared with respect the proposed algorithm. Simulation results are presented to testify the performance and applicability of the proposed system.

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Estimation Method of Variable Composition Rate and Error Compensation Method of Aggregative Model for Reactive Power by Variable Composition Rate (가변구성비 추정기법과 이를 이용한 무효전력 축약모델의 오차보정기법 개발)

  • Lee, Dae-Jong;Lee, Jong-Pil;Lim, Jae-Yoon;Ji, Pyeong-Shik
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.60 no.4
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    • pp.186-192
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    • 2011
  • Recently, due to the expansion of electric power demands, nonlinear load such as converters and inverters connected to the electric power distribution system, and extensive application of harmonic generation sources with power electric devices, disturbance of the electric power system and its influences on industries have been continuously increasing. In this research, we develop a novel aggregation algorithm by considering the harmonics characteristics for residential loads. Using data sets acquired from various experiments, we analyzed load characteristics according to harmonics and presented the results obtained the proposed method.

Bottom-up Composition and Verification of Embedded Software (내장형 소프트웨어 컴포넌트의 상향식 합성과 검증)

  • Choi, Yun-Ja
    • The KIPS Transactions:PartD
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    • v.17D no.6
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    • pp.415-422
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    • 2010
  • This paper proposes service-oriented composition and verification techniques for incrementally extracting high-level abstract behavior of unit components in a systematic manner. Proposed techniques include the definition for abstract component, which is a basic building-block of the abstraction process, an algorithm for port-based synchronized abstraction, and projection abstraction. A verification framework is developed using the proposed techniques and its efficiency is demonstrated through a case example.

Identification and Determination of Oil Pollutants Based on 3-D Fluorescence Spectrum Combined with Self-weighted Alternating Trilinear Decomposition Algorithm

  • Cheng, Pengfei;Wang, Yutian;Chen, Zhikun;Yang, Zhe
    • Journal of the Optical Society of Korea
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    • v.20 no.1
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    • pp.204-211
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    • 2016
  • Oil pollution seriously endangers the biological environment and human health. Due to the diversity of oils and the complexity of oil composition, it is of great significance to identify the oil contaminants. The 3-D fluorescence spectrum combined with a second order correction algorithm was adopted to measure an oil mixture with overlapped fluorescence spectra. The self-weighted alternating trilinear decomposition (SWATLD) is a kind of second order correction, which has developed rapidly in recent years. Micellar solutions of #0 diesel, #93 gasoline and ordinary kerosene in different concentrations were made up. The 3-D fluorescence spectra of the mixed oil solutions were measured by a FLS920 fluorescence spectrometer. The SWATLD algorithm was applied to decompose the spectrum data. The predict concentration and recovery rate obtained by the experiment show that the SWATLD algorithm has advantages of insensitivity to component number and high resolution for mixed oils.

A Study On Runlength Distance Mixing Algorithm For Document Image (문서화상에 대한 차분부호장 혼합 합성 알고리즘)

  • 박일남
    • The Journal of Information Technology
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    • v.5 no.1
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    • pp.1-12
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    • 2002
  • This paper presents a composition method for document image using RDM algorithm. It is possible to compose about double quantity of document image in same document space compared with RL or DM algorithm, if it used. RDM algorithm is available to compose secret document as well as digital signatures onto non-secure document. In this case, secure transmissin of document will be realize because the third party do not recognize secure transmission.

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