• Title/Summary/Keyword: adaptive expectation

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An Econometric Analysis of Imported Softwood Log Markets in South Korea - on the Basis of the Lagged Dependent Variable -

  • Park, Yong Bae;Youn, Yeo-Chang
    • Journal of Korean Society of Forest Science
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    • v.98 no.2
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    • pp.148-155
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    • 2009
  • The objective of this study is to know market structures of softwood logs being imported to South Korea from log producing countries. Import demand of softwood logs imported to South Korea from America, New Zealand and Chile is fixed as a function of log prices, the lagged dependent variable and output. On the basis of the adaptive expectations model, linear regression models that the explanatory variables included and the lagged dependent variable were estimated by Seemingly Unrelated Regression Equations (SURE). The short-run and long-run own price elasticity of America's softwood log import demand is -1.738 and -4.250 respectively. Then long-run elasticity is much higher than short-run elasticity. Short-run and long-run crosselasticity of New Zealand's softwood log import demand with respect to American's softwood log import price are inelastic at 0.505 and 0.883 respectively. Short-run and long-run cross-elasticity of Chile's softwood log import demands with respect to American's softwood log import prices were highly elastic at 2.442 and 4.462 respectively. Long-run elasticity was almost twice as high as short-run elasticity.

A Localized Adaptive QoS Routing Scheme Using POMDP and Exploration Bonus Techniques (POMDP와 Exploration Bonus를 이용한 지역적이고 적응적인 QoS 라우팅 기법)

  • Han Jeong-Soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.3B
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    • pp.175-182
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    • 2006
  • In this paper, we propose a Localized Adaptive QoS Routing Scheme using POMDP and Exploration Bonus Techniques. Also, this paper shows that CEA technique using expectation values can be simply POMDP problem, because performing dynamic programming to solve a POMDP is highly computationally expensive. And we use Exploration Bonus to search detour path better than current path. For this, we proposed the algorithm(SEMA) to search multiple path. Expecially, we evaluate performances of service success rate and average hop count with $\phi$ and k performance parameters, which is defined as exploration count and intervals. As result, we knew that the larger $\phi$, the better detour path search. And increasing n increased the amount of exploration.

A Neuro-Fuzzy Modeling using the Hierarchical Clustering and Gaussian Mixture Model (계층적 클러스터링과 Gaussian Mixture Model을 이용한 뉴로-퍼지 모델링)

  • Kim, Sung-Suk;Kwak, Keun-Chang;Ryu, Jeong-Woong;Chun, Myung-Geun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.5
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    • pp.512-519
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    • 2003
  • In this paper, we propose a neuro-fuzzy modeling to improve the performance using the hierarchical clustering and Gaussian Mixture Model(GMM). The hierarchical clustering algorithm has a property of producing unique parameters for the given data because it does not use the object function to perform the clustering. After optimizing the obtained parameters using the GMM, we apply them as initial parameters for Adaptive Network-based Fuzzy Inference System. Here, the number of fuzzy rules becomes to the cluster numbers. From this, we can improve the performance index and reduce the number of rules simultaneously. The proposed method is verified by applying to a neuro-fuzzy modeling for Box-Jenkins s gas furnace data and Sugeno's nonlinear system, which yields better results than previous oiles.

An Improved Weighted Filter for AWGN Removal (AWGN 제거를 위한 개선된 가중치 필터)

  • Long, Xu;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.5
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    • pp.1227-1232
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    • 2013
  • Recently, the expectation of quality about images over the increasing demand of digital devices is increasing with the development of the technology of the digital. But the images are degraded by a variety of causes, and the main reason is the noises. Therefore, the necessity of denoising comes to the fore, and the research for denoising is progressing dynamically. The images are mainly degraded by AWGN(additive white Gaussian noise), and the characteristics of denoising of existing methods such as mean filter are insufficient. In this paper, an algorithm combined by the spatial weighted filter and the modified adaptive weighted filter is proposed in order to effectively remove the AWGN. In the simulation result, the proposed algorithm showed excellent denoising capabilities.

Newly-designed adaptive non-blind deconvolution with structural similarity index in single-photon emission computed tomography

  • Kyuseok Kim;Youngjin Lee
    • Nuclear Engineering and Technology
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    • v.55 no.12
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    • pp.4591-4596
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    • 2023
  • Single-photon emission computed tomography SPECT image reconstruction methods have a significant influence on image quality, with filtered back projection (FBP) and ordered subset expectation maximization (OSEM) being the most commonly used methods. In this study, we proposed newly-designed adaptive non-blind deconvolution with a structural similarity (SSIM) index that can take advantage of the FBP and OSEM image reconstruction methods. After acquiring brain SPECT images, the proposed image was obtained using an algorithm that applied the SSIM metric, defined by predicting the distribution and amount of blurring. As a result of the contrast to noise ratio (CNR) and coefficient of variation evaluation (COV), the resulting image of the proposed algorithm showed a similar trend in spatial resolution to that of FBP, while obtaining values similar to those of OSEM. In addition, we confirmed that the CNR and COV values of the proposed algorithm improved by approximately 1.69 and 1.59 times, respectively, compared with those of the algorithm involving an inappropriate deblurring process. To summarize, we proposed a new type of algorithm that combines the advantages of SPECT image reconstruction techniques and is expected to be applicable in various fields.

Daily adaptive proton therapy: Feasibility study of detection of tumor variations based on tomographic imaging of prompt gamma emission from proton-boron fusion reaction

  • Choi, Min-Geon;Law, Martin;Djeng, Shin-Kien;Kim, Moo-Sub;Shin, Han-Back;Choe, Bo-Young;Yoon, Do-Kun;Suh, Tae Suk
    • Nuclear Engineering and Technology
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    • v.54 no.8
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    • pp.3006-3016
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    • 2022
  • In this study, the images of specific prompt gamma (PG)-rays of 719 keV emitted from proton-boron reactions were analyzed using single-photon emission computed tomography (SPECT). Quantitative evaluation of the images verified the detection of anatomical changes in tumors, one of the important factors in daily adaptive proton therapy (DAPT) and verified the possibility of application of the PG-ray images to DAPT. Six scenarios were considered based on various sizes and locations compared to the reference virtual tumor to observe the anatomical alterations in the virtual tumor. Subsequently, PG-rays SPECT images were acquired using the modified ordered subset expectation-maximization algorithm, and these were evaluated using quantitative analysis methods. The results confirmed that the pixel range and location of the highest value of the normalized pixel in the PG-rays SPECT image profile changed according to the size and location of the virtual tumor. Moreover, the alterations in the virtual tumor size and location in the PG-rays SPECT images were similar to the true size and location alterations set in the phantom. Based on the above results, the tumor anatomical alterations in DAPT could be adequately detected and verified through SPECT imaging using the 719 keV PG-rays acquired during treatment.

Adaptive and Recursive Tracking of Unpaved Roads (무인주행차량을 위한 비포장 도로추적)

  • Chung, Hong;Koo, Bon-Seok
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10b
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    • pp.548-550
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    • 1999
  • 무인 주행 차량에 있어서, 포장 또는 비포장 도로의 시각적 추적은 매우 중요한 문제중의 하나이다. 따라서, 비디오 이미지로부터 비포장 도로를 추적할 수 있는 신속한 비젼 알고리즘의 개발이 필요하다. 이 논문에서는 칼만 필터와 EM(Expectation Maximization) 이론을 이용해 도로를 예측하고 시스템 파라미터를 갱신하는 방법을 제시한다. 시스템 파라미터, 도로 state, 도로 경계선, 그리고 모든 과거 데이터들을 각각 EM 파라미터, hidden data, incomplete data와 complete data로 정의함으로서 도로 state를 예측하고 시스템 파라미터를 추정할 수 있는 시간 회귀적 수식을 유도해 낼 수 있다. 이러한 방법을 이용하여 도로 state는 칼만 필터에 의해 매 프레임마다 예측되며, 시스템 파라미터들은 주기적으로 갱신되는 것이다. 결과적으로 이 방법은 주변환경과 날씨에 많은 영향을 받는 도로의 모양과 특징을 잘 찾아낼 수 있다. 또한 도로의 다음 state를 예측할 수 있는 점을 이용하면 계산량을 줄일 수 있으므로 실시간 구현에 용이하다. 이와 같은 방법으로 우리는 0.1 sec/frame 처리속도를 보장하는 도로추적 시스템을 구현하였다.

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Consumer Satisfaction and Dissatisfaction in Return Process (반품과정에서의 소비자만족.불만경험)

  • Park Kyung-Ae
    • Journal of the Korean Society of Clothing and Textiles
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    • v.30 no.7 s.155
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    • pp.1116-1125
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    • 2006
  • This study investigated consumer satisfaction and dissatisfaction experiences in post-purchase product return process. As an exploratory research the study collected qualitative data of subjective consumer experiences using an open-ended questionnaire and identified and classified themes and patterns of satisfaction and dissatisfaction experiences. A total of 113 cases were categorized into satisfied experiences, unsatisfied experiences, and neutral experiences. Further, satisfied experiences were sub-categorized into kind sales associates, quick and easy return process, and services higher than expected based on sources of satisfaction in the return process while unsatisfied experiences were sub-classified into rejection of return, attitude of sales associates, and hassle of return process. In-store adaptive behaviors and intentions on future behaviors were also observed. The results indicated that service quality in the post-purchase service encounter and consumer expectation were important in determining satisfaction and dissatisfaction in the return process. Insights for research questions were proposed.

Biological smart sensing strategies in weakly electric fish

  • Nelson, Mark E.
    • Smart Structures and Systems
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    • v.8 no.1
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    • pp.107-117
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    • 2011
  • Biological sensory systems continuously monitor and analyze changes in real-world environments that are relevant to an animal's specific behavioral needs and goals. Understanding the sensory mechanisms and information processing principles that biological systems utilize for efficient sensory data acquisition may provide useful guidance for the design of smart-sensing systems in engineering applications. Weakly electric fish, which use self-generated electrical energy to actively sense their environment, provide an excellent model system for studying biological principles of sensory data acquisition. The electrosensory system enables these fish to hunt and navigate at night without the use of visual cues. To achieve reliable, real-time task performance, the electrosensory system implements a number of smart sensing strategies, including efficient stimulus encoding, multi-scale virtual sensor arrays, task-dependent filtering and online subtraction of sensory expectation.

PDC Intelligent control-based theory for structure system dynamics

  • Chen, Tim;Lohnash, Megan;Owens, Emmanuel;Chen, C.Y.J.
    • Smart Structures and Systems
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    • v.25 no.4
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    • pp.401-408
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    • 2020
  • This paper deals with the problem of global stabilization for a class of nonlinear control systems. An effective approach is proposed for controlling the system interaction of structures through a combination of parallel distributed compensation (PDC) intelligent controllers and fuzzy observers. An efficient approximate inference algorithm using expectation propagation and a Bayesian additive model is developed which allows us to predict the total number of control systems, thereby contributing to a more adaptive trajectory for the closed-loop system and that of its corresponding model. The closed-loop fuzzy system can be made as close as desired, so that the behavior of the closed-loop system can be rigorously predicted by establishing that of the closed-loop fuzzy system.