• 제목/요약/키워드: 결합모델

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이중 주파수 고주파 용량성 결합 플라즈마 장치의 전극 전압 전류 신호의 위상차 및 고조파 발생 특성 연구

  • Choe, Myeong-Seon;Kim, Gon-Ho
    • Proceedings of the Korean Vacuum Society Conference
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    • 2010.08a
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    • pp.138-138
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    • 2010
  • 이중 주파수를 이용한 고주파 용량성 결합 플라즈마 장치는 반도체 및 디스플레이 생산 공정에서 널리 사용되는 장치 형태이며 일반적으로 이온 플라즈마 주파수보다 높은 주파수의 고주파 전력과 이온 플라즈마 주파수보다 낮은 주파수의 저주파 전력을 인가하여 플라즈마 발생 밀도 및 입사 이온 에너지를 독립적으로 조절할 수 있다. 용량성 결합 플라즈마 장치에서는 전극의 쉬스 임피던스가 비선형적으로 변화함에 따라 전극의 전압, 전류 및 플라즈마 전위는 수많은 고조파를 포함하게 되며, 이중 주파수가 인가된 경우 이러한 고주파와 저주파 신호의 고조파가 상호 변조된 형태로 나타나게 된다. 본 연구에서는 주파수에 따른 이온의 거동 특성 차이를 이용하여 변조된 형태의 Lieberman의 비균일 RF쉬스 모델을 가정한 고주파 쉬스를 단순한 저주파 쉬스로 모사하였다. 단순화된 저주파 쉬스 임피던스를 이용한 회로 모델을 구성하여 100MHz와 2MHz RF전력을 사용하는 용량성 결합 플라즈마 장치에서 측정된 전극 전압, 전류 및 플라즈마 전위 신호의 위상차 및 고조파 발생 특성을 분석하였다.

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Quantum Chemical Calculations of Silica Hydroxyls as Acid Site (실리카 수산기의 산성에 관한 양자화학적 해석)

  • Kim, Myung Chul
    • Applied Chemistry for Engineering
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    • v.8 no.2
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    • pp.262-266
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    • 1997
  • The CNDO/2 calculations have been applied on cluster models for the representative hydroxyls on silica surface to get Wiberg bond orders, total energies, LUMO energies, dipole moments, and formal charge densities. The Br${\ddot{o}}$nsted acidities of suggested models for the hydroxyls were explained in terms of Wiberg bond orders. The calculated bond orders of cluster models have been changed remarkably according to the hydrogen bond. However the Lewis acidities of terminal hydroxyls on silica surface were not related to the structure of hydroxyls.

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Modeling and Error Compensation of WNS with Neural Network (Neural Network를 이용한 WNS(Walking Navigation System) 모델링 및 오차 보정)

  • Cho, Seong-Yun;Park, Chan-Gook;Jee, Gyu-In;Lee, Young-Jea
    • Proceedings of the KIEE Conference
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    • 2001.07d
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    • pp.1946-1948
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    • 2001
  • 본 논문에서는 저급 관성 센서를 이용한 개인 항법 장치의 모델 및 오차 보정 기법을 제시하고 성능 평가를 위하여 시뮬레이션을 수행하였다. 걸음 검출에 의한 보행 항법에서 중요한 변수인 보폭은 신경 회로망(Neural Network)을 이용하여 결정하였고, 자이로 바이어스 등에 의하여 누적되는 오차는 GPS와의 결합에 의하여 추정, 보상하였다. 이때 GPS와의 결합은 칼만필터를 이용하였으며 칼말필터를 구성하는데 필요한 오차 모델 및 결합 방법을 제시하였다. WNS/GPS 결합에 의하여 오차의 발산을 막을 수 있으며 GPS신호가 중간에 단절되는 경우에도 오차가 발산하지 않고 좋은 결과를 유지함을 보인다.

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The Search of Pig Pheromonal Odorants for Biostimulation Control System Technologies: A 2D-QSAR Model for Binding Affinity between 2-Cyclohexyloxytetrahydrofurane Analogues and Porcine Odorant Binding Protein (생물학적 자극 통제 수단으로 활용하기 위한 돼지 페로몬성 냄새 물질의 탐색: 2-Cyclohexyloxytetrahydrofurane 유도체와 Porcine Odorant Binding Protein 사이의 결합 친화력에 관한 2D-QSAR 모델)

  • Park, Chang-Sik;Choi, Yang-Seok;Sung, Nack-Do
    • Reproductive and Developmental Biology
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    • v.31 no.1
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    • pp.15-20
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    • 2007
  • To search of a new porcine pheromonal odorant for biostimulation control system technologies to offer a potentially useful and practical way to improve reproductive efficiency in livestock species, the two dimensional quantitative structure-activity relationship (QSAR) models between physicochemical parameters as descriptors of 2-cyclohexyloxytetrahydrofurane (A), 2-phenoxytetrahydrofurane (B) analogues and binding affinity constant ($p[Od.]_{50}$) for porcine odorant-binding protein (pOBP) as receptor of pig pheromones were derived and disscused. The statistical quality of the optimized 2D-QSAR model is good ($r^{2}=0.964$) and accounts for 96.4% of the variance in the binding affinity constants. It was found that the binding affinity constants were dependent upon the optimal value, $(SL)_{opt.}=1.418$ of substituent lipole (SL) in molecules. Therefore, the SL constant was very important factor for binding affinity.

Multiple-Classifier Combination based on Image Degradation Model for Low-Quality Image Recognition (저화질 영상 인식을 위한 화질 저하 모델 기반 다중 인식기 결합)

  • Ryu, Sang-Jin;Kim, In-Jung
    • The KIPS Transactions:PartB
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    • v.17B no.3
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    • pp.233-238
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    • 2010
  • In this paper, we propose a multiple classifier combination method based on image degradation modeling to improve recognition performance on low-quality images. Using an image degradation model, it generates a set of classifiers each of which is specialized for a specific image quality. In recognition, it combines the results of the recognizers by weighted averaging to decide the final result. At this time, the weight of each recognizer is dynamically decided from the estimated quality of the input image. It assigns large weight to the recognizer specialized to the estimated quality of the input image, but small weight to other recognizers. As the result, it can effectively adapt to image quality variation. Moreover, being a multiple-classifier system, it shows more reliable performance then the single-classifier system on low-quality images. In the experiment, the proposed multiple-classifier combination method achieved higher recognition rate than multiple-classifier combination systems not considering the image quality or single classifier systems considering the image quality.

Design of customized product recommendation model on correlation analysis when using electronic commerce (전자상거래 이용시 연관성 분석을 통한 맞춤형 상품추천 모델 설계)

  • Yang, MingFei;Park, Kiyong;Choi, Sang-Hyun
    • Journal of the Korea Convergence Society
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    • v.13 no.3
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    • pp.203-216
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    • 2022
  • In the recent business environment, purchase patterns are changing around the influence of COVID-19 and the online market. This study analyzed cluster and correlation analysis based on purchase and product information. The cluster analysis of new methods was attempted by creating customer, product, and cross-bonding clusters. The cross-bonding cluster analysis was performed based on the results of each cluster analysis. As a result of the correlation analysis, it was analyzed that more association rules were derived from a cross-bonding cluster, and the overlap rate was less. The cross-bonding cluster was found to be highly efficient. The cross-bonding cluster is the most suitable model for recommending products according to customer needs. The cross-bonding cluster model can save time and provide useful information to consumers. It is expected to bring positive effects such as increasing sales for the company.

A Segmentation-Based HMM and MLP Hybrid Classifier for English Legal Word Recognition (분할기반 은닉 마르코프 모델과 다층 퍼셉트론 결합 영문수표필기단어 인식시스템)

  • 김계경;김진호;박희주
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.3
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    • pp.200-207
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    • 2001
  • In this paper, we propose an HMM(Hidden Markov modeJ)-MLP(Multi-layer perceptron) hybrid model for recognizing legal words on the English bank check. We adopt an explicit segmentation-based word level architecture to implement an HMM engine with nonscaled and non-normalized symbol vectors. We also introduce an MLP for implicit segmentation-based word recognition. The final recognition model consists of a hybrid combination of the HMM and MLP with a new hybrid probability measure. The main contributions of this model are a novel design of the segmentation-based variable length HMMs and an efficient method of combining two heterogeneous recognition engines. ExperimenLs have been conducted using the legal word database of CENPARMI with encouraging results.

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Dynamic Fracture Analysis of High-speed Impact on Granite with Peridynamic Plasticity (페리다이나믹 소성 모델을 통한 화강암의 고속 충돌 파괴 해석)

  • Ha, Youn Doh
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.32 no.1
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    • pp.37-44
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    • 2019
  • A bond-based peridynamic model has been reported dynamic fracture characteristic of brittle materials through a simple constitutive model. In the model, each bond is assumed to be a simple spring operating independently. As a result, this simple bond interaction modeling restricts the material behavior having a fixed Poisson's ratio of 1/4 and not being capable of expressing shear deformation. We consider a state-based peridynamics as a generalized peridynamic model. Constitutive models in the state-based peridynamics are corresponding to those in continuum theory. In state-based peridynamics, thus, the response of a material particle depends collectively on deformation of all bonds connected to other particles. So, a state-based peridynamic theory can represent the volume and shear changes of the material. In this paper, the perfect plasticity is considered to express plastic deformation of material by the state-based peridynamic constitutive model with perfect plastic flow rule. The elastic-plastic behavior of the material is verified through the stress-strain curves of the flat plate example. Furthermore, we simulate the high-speed impact on 3D granite model with a nonlocal contact modeling. It is observed that the damage patterns obtained by peridynamics are similar to experimental observations.

Context-sensitive Spelling Error Correction using Eojeol N-gram (어절 N-gram을 이용한 문맥의존 철자오류 교정)

  • Kim, Minho;Kwon, Hyuk-Chul;Choi, Sungki
    • Journal of KIISE
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    • v.41 no.12
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    • pp.1081-1089
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    • 2014
  • Context-sensitive spelling-error correction methods are largely classified into rule-based methods and statistical data-based methods, the latter of which is often preferred in research. Statistical error correction methods consider context-sensitive spelling error problems as word-sense disambiguation problems. The method divides a vocabulary pair, for correction, which consists of a correction target vocabulary and a replacement candidate vocabulary, according to the context. The present paper proposes a method that integrates a word-phrase n-gram model into a conventional model in order to improve the performance of the probability model by using a correction vocabulary pair, which was a result of a previous study performed by this research team. The integrated model suggested in this paper includes a method used to interpolate the probability of a sentence calculated through each model and a method used to apply the models, when both methods are sequentially applied. Both aforementioned types of integrated models exhibit relatively high accuracy and reproducibility when compared to conventional models or to a model that uses only an n-gram.