• Title/Summary/Keyword: Random selection

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Ensemble Learning for Underwater Target Classification (수중 표적 식별을 위한 앙상블 학습)

  • Seok, Jongwon
    • Journal of Korea Multimedia Society
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    • v.18 no.11
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    • pp.1261-1267
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    • 2015
  • The problem of underwater target detection and classification has been attracted a substantial amount of attention and studied from many researchers for both military and non-military purposes. The difficulty is complicate due to various environmental conditions. In this paper, we study classifier ensemble methods for active sonar target classification to improve the classification performance. In general, classifier ensemble method is useful for classifiers whose variances relatively large such as decision trees and neural networks. Bagging, Random selection samples, Random subspace and Rotation forest are selected as classifier ensemble methods. Using the four ensemble methods based on 31 neural network classifiers, the classification tests were carried out and performances were compared.

A study on low power and design-for-testability technique of digital IC (저전력 소모와 테스트 용이성을 고려한 회로 설계)

  • 이종원;손윤식;정정화;임인칠
    • Proceedings of the IEEK Conference
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    • 1998.06a
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    • pp.875-878
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    • 1998
  • In this thesis, we present efficient techniques to reduce the switching activity in a CMOS combinational logic network based on local logic transforms. But this techniques is not appropriate in the view of testability because of deteriorating the random pattern testability of a circuit. This thesis proposes a circuit design method having two operation modes. For the sake of power dissipation(normal operation mode), a gate output switches as rarely as possible, implying highly skewed signal probabilities for 1 or 0. On the other hand, at test mode, signals have probabilities of being 1 or 0 approaching 0.5, so it is possible to exact both stuck-at faults on the wire. Therefore, the goals of synthesis for low power and random pattern testability are achieved. The hardware overhead sof proposed design method are only one primary input for mode selection and AND/OR gate for each redundant connection.

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Structural Response Analysis on Inner Barrel Assembly Top Plate of APR1400 Reactor Vessel (APR1400 원자로 내부배럴집합체 상부판 구조응답해석)

  • Kim, Kyu-Hyung;Ko, Do-Young;Kim, Sung-Hwan
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2012.04a
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    • pp.907-910
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    • 2012
  • Since the inner barrel assembly of the Advanced Power Reactor 1400 reactor vessel is a new design feature introduced instead of CEA(control element assembly) shroud assembly, the inner barrel assembly can be a significant object of structural integrity assessment. This paper covers the structural responses of top plate, which is a component of the inner barrel assembly, against the deterministic hydraulic load induced by pump pulsation and the random hydraulic load induced by turbulence of coolant. The top plate responds to the deterministic hydraulic load more than to the random hydraulic load and shows enough structural integrity. The results of this paper will be important basis for the selection of instruments and measurement location.

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Predicting Gross Box Office Revenue for Domestic Films

  • Song, Jongwoo;Han, Suji
    • Communications for Statistical Applications and Methods
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    • v.20 no.4
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    • pp.301-309
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    • 2013
  • This paper predicts gross box office revenue for domestic films using the Korean film data from 2008-2011. We use three regression methods, Linear Regression, Random Forest and Gradient Boosting to predict the gross box office revenue. We only consider domestic films with a revenue size of at least KRW 500 million; relevant explanatory variables are chosen by data visualization and variable selection techniques. The key idea of analyzing this data is to construct the meaningful explanatory variables from the data sources available to the public. Some variables must be categorized to conduct more effective analysis and clustering methods are applied to achieve this task. We choose the best model based on performance in the test set and important explanatory variables are discussed.

Predicting stock price direction by using data mining methods : Emphasis on comparing single classifiers and ensemble classifiers

  • Eo, Kyun Sun;Lee, Kun Chang
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.11
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    • pp.111-116
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    • 2017
  • This paper proposes a data mining approach to predicting stock price direction. Stock market fluctuates due to many factors. Therefore, predicting stock price direction has become an important issue in the field of stock market analysis. However, in literature, there are few studies applying data mining approaches to predicting the stock price direction. To contribute to literature, this paper proposes comparing single classifiers and ensemble classifiers. Single classifiers include logistic regression, decision tree, neural network, and support vector machine. Ensemble classifiers we consider are adaboost, random forest, bagging, stacking, and vote. For the sake of experiments, we garnered dataset from Korea Stock Exchange (KRX) ranging from 2008 to 2015. Data mining experiments using WEKA revealed that random forest, one of ensemble classifiers, shows best results in terms of metrics such as AUC (area under the ROC curve) and accuracy.

Parameter Design for COBF Based on Kappa-factor Channel Model (Kappa-factor 채널모델에 기반을 둔 최적의 코드북 기반 Opportunistic Beamformer 파라미터 디자인)

  • Kang, Ji-Won;Kwon, Dong-Seung;Lee, Chung-Yong;Hwang, Young-Soo
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.45 no.12
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    • pp.20-25
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    • 2008
  • Codebook-based opportunistic beamforming (COBF) technique provides a beam selection diversity to the conventional opportunistic beamforming. In this paper, we design the random matrix and codebook for the COBF technique based on a kappa-factor channel model. Applying the proposed design to the COBF, nearly optimal beams are generated. Therefore, the COBF shows an outstanding performance without regard to the channel correlation related to the kappa-factor.

A New Traffic Load Shedding Scheme in Microcellular CDMA with Uniform and Non-uniform Traffic Load

  • Park, Woo-Goo;Rhee, Ja-Gan;Lee, Hu;Lee, Sang-Ho
    • Journal of Electrical Engineering and information Science
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    • v.2 no.5
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    • pp.33-39
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    • 1997
  • In this paper we proposed a new traffic load shedding scheme which maximizes the throughput of traffic control by decreasing the load of the hot-spot cell using minimum load cell selection (MLCS) algorithm and deployed control flow of calls to define characteristic for hadoff region. we compared the performance of the random shedding approach with that of the proposed algorithm. The results of simulation show that MLCS algorithm minimizes the cal blocking rate under a high-density traffic compared to the random shedding scheme.

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Conducted Noise Reduction in Random Pulse Width Modulation (Random PWM 기법에 의한 전도노이즈)

  • Jung, Dong-Hyo;Kim, Sang-Nam
    • Proceedings of the KIEE Conference
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    • 2002.06a
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    • pp.98-101
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    • 2002
  • The switching-mode power converter has been widely used because of its features of high efficiency and small weight and size. These features are brought by the ON-OFF operation of semiconductor switching devices. However, this switching operation causes the surge and EMI(Electromagnetic Interference) which deteriorate the reliability of the converter themselves and entire electronic systems. This problem on the surge and noise is one of the most serious difficulties in AC-to-DC converter. In the case of carrier frequency selection, output-voltage of steady state and transient state is fully regulated. A RPWM control method was proposed in order to smooth the switching noise spectrum and reduce it's level. Experimental results are verified by converter operating at 300V/1kW with 5%${\sim}$30% white noise input. Spectrum analysis is performed on the Phase current and the CM noise voltage. The former is measured with Current Probe and the latter is achieved with USN. which are connected to the spectrum analyzer respectively.

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A Study On User Skin Color-Based Foundation Color Recommendation Method Using Deep Learning (딥러닝을 이용한 사용자 피부색 기반 파운데이션 색상 추천 기법 연구)

  • Jeong, Minuk;Kim, Hyeonji;Gwak, Chaewon;Oh, Yoosoo
    • Journal of Korea Multimedia Society
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    • v.25 no.9
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    • pp.1367-1374
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    • 2022
  • In this paper, we propose an automatic cosmetic foundation recommendation system that suggests a good foundation product based on the user's skin color. The proposed system receives and preprocesses user images and detects skin color with OpenCV and machine learning algorithms. The system then compares the performance of the training model using XGBoost, Gradient Boost, Random Forest, and Adaptive Boost (AdaBoost), based on 550 datasets collected as essential bestsellers in the United States. Based on the comparison results, this paper implements a recommendation system using the highest performing machine learning model. As a result of the experiment, our system can effectively recommend a suitable skin color foundation. Thus, our system model is 98% accurate. Furthermore, our system can reduce the selection trials of foundations against the user's skin color. It can also save time in selecting foundations.

Application of Common Random Numbers in Simulation Experiments Using Central Composite Design (중심합성계획 시뮬레이션 실험에서 공통난수의 활용)

  • Kwon, Chi-Myung
    • Journal of the Korea Society for Simulation
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    • v.23 no.3
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    • pp.11-17
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    • 2014
  • The central composite design (CCD) is often used to estimate the second-order linear model. This paper uses a correlation induction strategy of common random numbers (CRN) in simulation experiment and utilizes the induced correlations to obtain better estimates for the second-order linear model. This strategy assigns the CRN to all design points in the CCD. An appropriate selection of the axial points in CCD makes the weighted least squares (WLS) estimator be equivalent to ordinary least squares (OLS) estimator in estimating the linear model parameters of CCD. We analytically investigate the efficiency of this strategy in estimation of model parameters. Under certain conditions, this correlation induction strategy yields better results than independent random number strategy in estimating model parameters except intercept. The simulation experiment on a selected model supports such results. We expect a suggested random number assignment is useful in application of CCD in simulation experiments.