• Title/Summary/Keyword: Weight Vector Analysis

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Weight Vector Analysis to Portfolio Performance with Diversification Constraints (비중 상한 제약조건에 따른 포트폴리오 성과에 대한 투자 비중 분석)

  • Park, Kyungchan;Kim, Hongseon;Kim, Seongmoon
    • Korean Management Science Review
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    • v.33 no.4
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    • pp.51-64
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    • 2016
  • The maximum weight of single stock in mutual fund is limited by regulations to enforce diversification. Under incomplete information with added constraints on portfolio weights, enhanced performance had been reported in previous researches. We analyze a weight vector to examine the effects of additional constraints on the portfolio's performance by computing the Euclidean distance from the in-sample tangency portfolio, as opposed to previous researches which analyzed ex-post return only. Empirical experiment was performed on Mean-variance and Minimum-variance model with Fama French's 30 industry portfolio and 10 industry portfolio for the last 1,000 months from August 1932 to November 2015. We find that diversification-constrained portfolios have 7% to 26% smaller Euclidean distances with the benchmark portfolio compared to those of unconstrained portfolios and 3% to 11% greater Sharpe Ratio.

Analysis and Implementation of Speech/Music Classification for 3GPP2 SMV Codec Employing SVM Based on Discriminative Weight Training (SMV코덱의 음성/음악 분류 성능 향상을 위한 최적화된 가중치를 적용한 입력벡터 기반의 SVM 구현)

  • Kim, Sang-Kyun;Chang, Joon-Hyuk;Cho, Ki-Ho;Kim, Nam-Soo
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.5
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    • pp.471-476
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    • 2009
  • In this paper, we apply a discriminative weight training to a support vector machine (SVM) based speech/music classification for the selectable mode vocoder (SMV) of 3GPP2. In our approach, the speech/music decision rule is expressed as the SVM discriminant function by incorporating optimally weighted features of the SMV based on a minimum classification error (MCE) method which is different from the previous work in that different weights are assigned to each the feature of SMV. The performance of the proposed approach is evaluated under various conditions and yields better results compared with the conventional scheme in the SVM.

Direction Vector for Efficient Structural Optimization with Genetic Algorithm (효율적 구조최적화를 위한 유전자 알고리즘의 방향벡터)

  • Lee, Hong-Woo
    • Journal of Korean Association for Spatial Structures
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    • v.8 no.3
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    • pp.75-82
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    • 2008
  • In this study, the modified genetic algorithm, D-GA, is proposed. D-GA is a hybrid genetic algorithm combined a simple genetic algorithm and the local search algorithm using direction vectors. Also, two types of direction vectors, learning direction vector and random direction vector, are defined without the sensitivity analysis. The accuracy of D-GA is compared with that of simple genetic algorithm. It is demonstrated that the proposed approach can be an effective optimization technique through a minimum weight structural optimization of ten bar truss.

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Study on the Development of Auto-classification Algorithm for Ginseng Seedling using SVM (Support Vector Machine) (SVM(Support Vector Machine)을 이용한 묘삼 자동등급 판정 알고리즘 개발에 관한 연구)

  • Oh, Hyun-Keun;Lee, Hoon-Soo;Chung, Sun-Ok;Cho, Byoung-Kwan
    • Journal of Biosystems Engineering
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    • v.36 no.1
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    • pp.40-47
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    • 2011
  • Image analysis algorithm for the quality evaluation of ginseng seedling was investigated. The images of ginseng seedling were acquired with a color CCD camera and processed with the image analysis methods, such as binary conversion, labeling, and thinning. The processed images were used to calculate the length and weight of ginseng seedlings. The length and weight of the samples could be predicted with standard errors of 0.343 mm, and 0.0214 g respectively, $R^2$ values of 0.8738 and 0.9835 respectively. For the evaluation of the three quality grades of Gab, Eul, and abnormal ginseng seedlings, features from the processed images were extracted. The features combined with the ratio of the lengths and areas of the ginseng seedlings efficiently differentiate the abnormal shapes from the normal ones of the samples. The grade levels were evaluated with an efficient pattern recognition method of support vector machine analysis. The quality grade of ginseng seedling could be evaluated with an accuracy of 95% and 97% for training and validation, respectively. The result indicates that color image analysis with support vector machine algorithm has good potential to be used for the development of an automatic sorting system for ginseng seedling.

Static Structural Analysis of 75 tonf-class Engine with TVC actuation force (TVC 구동력을 고려한 75톤급 엔진 정적 구조 해석)

  • Yoo, Jaehan;Gwak, Junyoung;Kim, Okgu;Jeon, Seongmin;Jeong, Eunhwan
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2017.05a
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    • pp.913-914
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    • 2017
  • Structural analyses of a engine system is required in development stage for increasing structural reliability and reducing weight. Attitude of a launch vehicle during flight is controlled by combustion chamber rotation varying with TVC (thrust vector control) actuator displacements. In this study nonlinear static analysis is performed for a 75 tonf-class liquid rocket engine using before and after the TVC actuation.

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A Leading Price Estimation of Jeju Flounder Producer Prices by Fish Weight and a Dynamic Influence Analysis of Market Price Impulse (중량별 제주 넙치 산지가격의 선도가격 추정 및 시장가격 충격에 대한 동태적 영향 분석)

  • SON, Jingon;NAM, Jongoh
    • Journal of Fisheries and Marine Sciences Education
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    • v.28 no.1
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    • pp.198-210
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    • 2016
  • This study firstly aims to estimate a leading-price of Jeju flounders with various price-classes by fish weight and secondly plans to provide policy implications of flounder purchase projects by understanding dynamic changes and interactions among flounder producer price-classes caused by price impulses in the market. This study applies an unit root test for stability of data, uses a Granger causality test to estimate the leading-price among producer prices by fish weight, employs the vector autoregressive model to analyze statistical impacts among t-1 variables used in models, and finally utilizes impulse response analyses and forecast error variance decomposition analyses to understand dynamic changes and interactions among change rates of the producer prices caused by price impulses in the market. The results of the study are as follows. Firstly, KPSS, PP, and ADF tests show that the change rate of Jeju flounder monthly producer prices by fish weight differentiated by logarithm is stable. Secondly, the Granger causality test presents that the change rate of the 1kg flounder producer price strongly leads it of 500g, 700g, and 2kg flounder producer prices respectively. Thirdly, the vector autoregressive model indicates that the change rate of the 1kg producer price in t-1 period statistically, significantly influences it of own weight in t period and also slightly affects price change rates of other weights in t period. Fourthly, the impulse response analysis indicates that impulse responses of structural shocks for the change rate of the 1kg producer price are relatively more powerful in its own weight and in other weights than shocks emanating from price change rates of other weights. Fifthly, the variance decomposition analysis points out that the change rate of the 1kg producer price is relatively more influential than it of 500g, 700g, and 2kg producer prices respectively. In conclusion, the change rate of the 1kg Jeju flounder producer price leads the change rates of other ones and Jeju purchase projects need to be targeted to the 1kg Jeju flounder producer price as the purchase project implemented in 2014.

Prediction of Weight of Spiral Molding Using Injection Molding Analysis and Machine Learning (사출성형 CAE와 머신러닝을 이용한 스파이럴 성형품의 중량 예측)

  • Bum-Soo Kim;Seong-Yeol Han
    • Design & Manufacturing
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    • v.17 no.1
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    • pp.27-32
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    • 2023
  • In this paper, we intend to predict the mass of the spiral using CAE and machine learning. First, We generated 125 data for the experiment through a complete factor design of 3 factors and 5 levels. Next, the data were derived by performing a molding analysis through CAE, and the machine learning process was performed using a machine learning tool. To select the optimal model among the models learned using the learning data, accuracy was evaluated using RMSE. The evaluation results confirmed that the Support Vector Machine had a good predictive performance. To evaluate the predictive performance of the predictive model, We randomly generated 10 non-overlapping data within the existing injection molding condition level. We compared the CAE and support vector machine results by applying random data. As a result, good performance was confirmed with a MAPE value of 0.48%.

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A Study on Performance Improvement of Adaptive SLC System Using Eigenanalysis Method and Comparing with RLS Method (Eigenanalysis 방식의 적응 SLC(sidelobe canceller) 시스템의 적용에 따른 성능향상 및 RLS 방식과외 비교에 관한 연구)

  • Jung, Sin-Chul;Kim, Se-Yon;Lee, Byung-Seub
    • Journal of Advanced Navigation Technology
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    • v.5 no.2
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    • pp.111-122
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    • 2001
  • In this paper, we study the performance of eigencanceller which use a eigenvector and eigenvalue in order to update a weighter vector. Eigencanceller can suppress directional interferences and noise effectively while maintaining specified beam pattern constraints. The constraints and optimal weight vector of eigencanceller vary by using interference and noise or desired signal, interference signal and noise as array input signal. From the analysis results in the steady state, We show that weight vectors in each case are simplified the form of projection equation that belongs to desired subspace orthogonal to interference subspace and eigencanceller has the better performance than RLS method through mathematical analysis and simulation.

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Numerical Analysis of Secondary Injection for Thrust Vector Control on 2-Dimensional Supersonic Nozzle (2차원 초음속 노즐에서의 2차 유동분사에 의한 추력 방향 제어 특성의 수치적 해석)

  • 오대환;손창현;이충원
    • Journal of the Korean Society of Propulsion Engineers
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    • v.4 no.1
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    • pp.13-21
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    • 2000
  • The advantages of the SITVC (Secondary Injection for Thrust Vector Control) technique over mechanical thrust vectoring systems include a reduction in both the nozzle weight and complexity due to the elimination of the mechanical actuators that are used in conventional vectoring. The optimal operating conditions of SITVC were investigated using in-house developed compressible flow analysis codes. Numerical experiments were used to examine the impact of the thrust vector direction with a variety of injection positions, mass flow rates, and injection angles on the two-dimensional expansion cone of a supersonic nozzle. The computational results showed that the optimal position of the secondary injection, with the maximum deviation angle and side thrust, was where the oblique shock generated by the secondary injection reached the end of the nozzle exit.

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Effect of Exercise and Physical Stresses on the Electrocardiogram (운동부하 및 각종 신체조건이 혈압 및 ECG에 미치는 영향 -제2보- (각종 Stress에 의한 심전도 변화))

  • Park, Won-Kyun;Chae, E-Up
    • The Korean Journal of Physiology
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    • v.16 no.2
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    • pp.129-136
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    • 1982
  • We studied this experiment to compare the effects of exercise and other body conditions: i.e., Flack test, cold pressor test and bicycle ergometry on the electrocardiogram. We had sixty healthy college students who were thirty nine men and twenty one women. Their $mean{\pm}SD$ values of physical characteristics were as follows: age; $22.0{\pm}1.4$, weight; men $61.7{\pm}5.6\;kg$, women $46.2{\pm}7.47\;kg$. We observed the changes of P-Q and Q-T interval, R and T amplitude, mean QRS vector, S-T segment deviation, and P and T vector. The result obtained were summarized as follows: P vector was shifted rightward regardless of the type of stress. T vector was shifted var-in each stress but in the bicycle ergometry T vector was shifted leftward. Mean QRS vector was shifted rightward immediately after the bicycle ergometry. Percentage of the occurrence of the depression of S-T segment was 21.7% at the immediately after the submaximal bicycle ergometry in lead II. The elevation of S-T segment was often observed after the mild stresses. Increased amplitude of T wave in the cold pressor test and decreased amplitude of T wave in the bicycle ergometry were observed. In the bicycle ergometry and other stresses, the precise mechanism of S-T segment changes was unexplained but insufficient repolarization in base or apex of the left ventricle due to heart strain was indicated by so called S-T vector analysis.

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