• Title/Summary/Keyword: Boundary Decision

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Improved Detecting Schemes for Micro-Electronic Devices Based on Adaptive Hybrid Classification Algorithms (적응형 복합 분류 알고리즘을 이용한 초소형 전자소자 탐지 향상 기법)

  • Kim, Kwangyul;Lim, Jeonghwan;Kim, Songkang;Cho, Junkyung;Shin, Yoan
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38A no.6
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    • pp.504-511
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    • 2013
  • This paper proposes improved detection schemes for concealed micro-electronic devices using clustering and classification of radio frequency harmonics in order to protect intellectual property rights. In general, if a radio wave with a specific fundamental frequency is propagated from the transmitter of a classifier to a concealed object, the second and the third harmonics will be returned as the radio wave is reflected. Using this principle, we exploit the fuzzy c-means clustering and the ${\kappa}$-nearest neighbor classification for detecting diverse concealed objects. Simulation results indicate that the proposed scheme can detect electronic devices and metal devices in various learning environments by efficient classification. Thus, the proposed schemes can be utilized as an effective detection method for concealed micro-electronic device to protect intellectual property rights.

An Analysis on Electric Power Policy through ACMS Model : Focused on the Power Generation Subsidiary Company of the Korea Electric Power Corporation (ACMS 모형을 적용한 전력정책의 변동 분석 : 한국전력공사의 발전자회사를 중심으로)

  • Ji, Byoung-Seog;Kang, Seung-Jin
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.65 no.1
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    • pp.31-40
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    • 2016
  • The purpose of this study is to dimensionally examine the factors of policy changes by applying the ACMS model to KEPCO's structural reorganization privatization policies and study its implications. As a result of the analysis, among the external variables that affect as a financial source or restriction to advocates, all areas except for the difference in opinion of the people as well as policy decision and effects of other subordinate systems were shown to be in an advantageous condition acting as a financial source to advocates of structural reorganization privatization. On the other hand, advocates affected by the external variables share a certain belief system in which the advocates of privatization share the justification of profitability while the advocates of collectivization share the justification of publicness. In these flows, the announcement of the privatization plan of public enterprises of the committee of planning and budgeting acts as a matter of contact which opens the windows for policy changes, and this window goes through ignition, explosion, and fixation which causes fierce interactions among advocates of both sides. Eventually, in accordance with the contents of excluding electricity(KEPCO) from the list for privatization the window for policy changes has closed and things have changed to a transitional KEPCO privatization policy. Based on this, the first implication is that non-official participants such as the people, social organizations, labor unions, etc. influence policy changes more than they did before. Secondly, in the process of policy changes, there is an order of boundary even in the fierce interactions between each advocate. Thirdly, specific variables can play various roles in complex policy phenomenon. Fourthly, a logical analysis using the ACMS model is possible in Korea as well. Fifthly, as a result of analyzing the change process of the KEPCO structural reorganization privatization policy through the ACMS model, not all matched with the main research results implied by the ACMS model.

Analysis of Sucess Factors on Crop Switching Management: Applying the HERO Model (작목전환의 단계별 성공요인 분석 -HERO 모델 적용-)

  • Ahn, Kyeong Ah;Park, Sung Hee;Jo, Hea Bin;Choe, Young Chan
    • Journal of Agricultural Extension & Community Development
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    • v.19 no.3
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    • pp.699-727
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    • 2012
  • Conditions of farm crop switching are affected by several important external factors such as agricultural products import opening, policy support, and climate change. Farming environment is always changing; barriers to imports are becoming lower and lower because of FTA and others, and climate change affects a boundary line of cultivation. Those situations give farmers motivation to change crops in order to cope with them. In addition, crop switching has been done in response to the local government measures about purchase of local agricultural products according to the local food and the expansion of organic agricultural products in school meal. Even though the favorable environment toward crop switching has been created, there are not many researches or outcomes regarding crop switching. Only few studies focus on the list of decision-making in crop switching, and locally suitable crop selection is not treated. In order to utilize crop switching as a farm management strategy, the proper frame should be studied and practical researches on application possibility also need. Therefore, study on crop switching is in a timely, proactive manner because farms catch the chance of expansion of school meal by changing crops. This paper applies HERO model used for venture foundation process to crop switching process. Success factors of HERO model are comprised of Habitate, Entrepreneurship, Resource, and Opportunity, and these phased application factors are applied to crop switching process. By doing so, each phase success factor of crop switching can be uncovered. Three farm organizations supplying organic agricultural products to schools are studied in Gyeonggi province. As a result, the stabilization stage cannot be achieved because of the habitate conditions and social conditions with low risk bearing of crop switching and current school meal systems are the main problems to block the diversification of risks. In order to succeed in crop switching, constructing the habitate in local districts or in systems of school meal is more effective than supporting each farm.

Improving Correctness in the Satellite Remote Sensing Data Analysis -Laying Stress on the Application of Bayesian MLC in the Classification Stage- (인공위성 원격탐사 데이타의 분석 정확도 향상에 관한 연구 -분류과정에서의 Bayesian MIC 적용을 중심으로-)

  • 안철호;김용일
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.9 no.2
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    • pp.81-91
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    • 1991
  • This thesis aims to improve the analysis accuracy of remotely sensed digital imagery, and the improvement is achieved by considering the weight factors(a priori probabilities) of Bayesian MLC in the classification stage. To be concrete, Bayesian decision theory is studied from remote sensing field of view, and the equations in the n-dimensional form are derived from normal probability density functions. The amount of the misclassified pixels is extracted from probability function data using the thres-holding, and this is a basis of evaluating the classification accuracy. The results indicate that 5.21% of accuracy improvement was carried out. The data used in this study is LANDSAT TM(1985.10.21 ; 116-34), and the study area is within the administrative boundary of Seoul.

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Emergy-Simulation Based Building Retrofit

  • Hwang, Yi
    • KIEAE Journal
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    • v.14 no.3
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    • pp.5-13
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    • 2014
  • This paper introduces emergy(spelled with "m") that is a new environmental indicator in architecture, aiming to clarify conflicting claims of building design components in the process of energy-retrofit. Much of design practitioners' attention on low energy use in operational phases, may simply shift the lowered environmental impact within the building boundary to large consumption of energy in another area. Specifically, building energy reduction strategies without a holistic view starting from natural formation, may lead to the depletion of non-renewable geobiological sources (e.g. minerals, fossil fuels, etc.), which leaves a building with an isolated energy-efficient object. Therefore, to overcome the narrow outlook, this research discusses the total ecological impact of a building which embraces all process energy as well as environmental cost represented by emergy. A case study has been conducted to explore emergy-driven design work. In comparison with operational energy-driven scenarios, the results elucidate how energy and emergy-oriented decision-making bring about different design results, and quantify building components' emergy contribution in the end. An average-size ($101.9m^2$) single family house located in South Korea was sampled as a benchmark case, and the analysis of energy and material use was conducted for establishment of the baseline. Adoption of the small building is effective for the goal of study since this research intends to measure environmental impact according to variation of passive design elements (windows size, building orientation, wall materials) with new metric (emergy) regardless of mechanical systems. Performance simulations of operational energy were developed and analyzed separately from the calculation of emergy magnitudes in building construction, and then the total emergy demand of each proposed design was evaluated. Emergy synthesis results verify that the least operational energy scenario requires greater investment in indirect energy in construction, which clearly reveals that efficiency gains are likely to be overwhelmed by increment of material flows. This result places importance on consideration of indirect energy use underscoring necessity of emergy evaluation towards the environment-friendly building in broader sense.

Detection of Onset and Offset Time of Muscle Activity in Surface EMG using the Kalman Smoother

  • Lee Jung-Hoon;Lee Hyun-Sook;Lee Young-Hee;Yoon Young-Ro
    • Journal of Biomedical Engineering Research
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    • v.27 no.3
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    • pp.131-141
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    • 2006
  • A visual decision by clinical experts like physical therapists is a best way to detect onset and offset time of muscle activation. The current computer-based algorithms are being researched toward similar results of clinical experts. The new algorithm in this paper has an ability to extract a trend from noisy input data. Kalman smoother is used to recognize the trend to be revealed from disorderly signals. Histogram of smoothed signals by Kalman smoother has a clear boundary to separate muscle contractions from relaxations. To verify that the Kalman smoother algorithm is reliable way to detect onset and offset time of muscle contractions, the algorithm of Robert P. Di Fabio (published in 1987) is compared with Kalman smoother. For 31 templates of subjects, an average and a standard deviation are compared. The average of errors between Di Fabio's algorithm and experts is 109 milliseconds in onset detection and 142 milliseconds in offset detection. But the average between Kalman smoother and experts is 90 and 137 milliseconds in each case. Moreover, the standard deviations of errors are 133 (onset) and 210 (offset) milliseconds in Di Fabio's one, but 48 (onset) and 55 (offset) milliseconds in Kalman smoother. As a result, the Kalman smoother is much closer to determinations of clinical experts and more reliable than Di Fabio's one.

Application of the BMORE Plot to Analyze Simulation Output Data with Bivariate Performance Measures (이변량 성과척도를 가지는 시뮬레이션 결과 분석을 위한 BMORE 도표의 활용)

  • Lee, Mi Lim;Lee, Jinpyo;Park, Minjae
    • Journal of the Korea Society for Simulation
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    • v.29 no.2
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    • pp.83-93
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    • 2020
  • Bivariate measure of risk and error(BMORE) plot is originally designed to depict bivariate output data and related statistics obtained from a stochastic simulation such as sample mean, median, outliers, and a boundary of a certain percentile of simulation data. When compared to the static numbers, the plot has a big advantage in visualization that enables scholars and practitioners to understand the potential variability and risk in the simulation data. In this study, beyond just the construction of the plot to depict the variability of a certain system, we add a chance constraint to the plot and apply it for decision making such as checking the feasibility of systems, comparing performances of the systems on statistical background, and also analyzing the sensitivity of the problem parameters. In order to demonstrate an application of the plot, we employ an inventory management problem as an example. However, the techniques and algorithms suggested in this paper can be applied to any other problems comparing systems on bivariate performance measures with simulation/experiment results.

Self Organizing RBF Neural Network Equalizer (자력(自力) RBF 신경망 등화기)

  • Kim, Jeong-Su;Jeong, Jeong-Hwa
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.39 no.1
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    • pp.35-47
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    • 2002
  • This paper proposes a self organizing RBF neural network equalizer for the equalization of digital communications. It is the most important for the equalizer using the RBF neural network to estimate the RBF centers correctly and quickly, which are the desired channel states. However, the previous RBF equalizers are not used in the actual communication system because of some drawbacks that the number of channel states has to be known in advance and many centers are necessary. Self organizing neural network equalizer proposed in this paper can implement the equalization without prior information regarding the number of channel states because it selects RBF centers among the signals that are transmitted to the equalizer by the new addition and removal criteria. Furthermore, the proposed equalizer has a merit that is able to make a equalization with fewer centers than those of prior one by the course of the training using LMS and clustering algorithm. In the linear, nonlinear and standard telephone channel, the proposed equalizer is compared with the optimal Bayesian equalizer for the BER performance, the symbol decision boundary and the number of centers. As a result of the comparison, we can confirm that the proposed equalizer has almost similar performance with the Bavesian enualizer.

Vegetational Changes of Mt. Nam Park, Seoul (서울 남산공원의 식생변화)

  • 임양재;양금철
    • The Korean Journal of Ecology
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    • v.21 no.5_3
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    • pp.589-602
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    • 1998
  • Mt. Nam (265m), a city park of Seoul, was originally covered with a typical deciduous broad-leaved forests in Central Korea. However, the park forests have been changed the development for various purpose such as the construction of castle wall, road way, broadcasting station, theater, hotel and apartments, in addition, to thoughtless plantation or alien plant introduction. Human population growth from ca. 100 thousands persons less in that time established Seoul as the capital of choseon dynasty in 1394 to ten millions over persons at present, accelerated the vegetational changes of the park. mt. Nam boundary in those days of sunjong (1908) also was much shrinked as much the range of 300 m distance in the northern most to 700 or 800m distance in some places. The actual vegetation of Mt. Nam largely can be classified by floristic composition into two plant communities of Quercus mongolica community and Pinus densiflora community, four plantations of Pinus rigida, Robinia pseudo-acacia, Populus tomentiglandulosa and other tree species, and on mixed forest with native and alien tree species in secondary succession stage (Yim et al. 1987). The restoration movement of Mt. Nam toward to the natural condition of forest or biodiversity is moving now. However, in the movement there are some problems such as the lack of ecological consideration and the undesirable decision of priority in the practice. A warning should be given, especially, on the undesirable plantation of non-native tree species restricting the forest succession, as in the case of southern slope of Mt. Nam. First of all, the most importance in Mt. Nam management is that the restoration for natural forest and biodiversity should be carried on the basis of integrated ecological principles based on the site evaluation.

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A Substitute Model Learning Method Using Data Augmentation with a Decay Factor and Adversarial Data Generation Using Substitute Model (감쇠 요소가 적용된 데이터 어그멘테이션을 이용한 대체 모델 학습과 적대적 데이터 생성 방법)

  • Min, Jungki;Moon, Jong-sub
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.29 no.6
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    • pp.1383-1392
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    • 2019
  • Adversarial attack, which geneartes adversarial data to make target model misclassify the input data, is able to confuse real life applications of classification models and cause severe damage to the classification system. An Black-box adversarial attack learns a substitute model, which have similar decision boundary to the target model, and then generates adversarial data with the substitute model. Jacobian-based data augmentation is used to synthesize the training data to learn substitutes, but has a drawback that the data synthesized by the augmentation get distorted more and more as the training loop proceeds. We suggest data augmentation with 'decay factor' to alleviate this problem. The result shows that attack success rate of our method is higher(around 8.5%) than the existing method.