• Title/Summary/Keyword: dimension reduction method

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Implementation of unsupervised clustering methods for measurement gases using artificial olfactory sensing system (인공 후각 센싱 시스템을 이용한 측정 가스의 Unsupervised clustering 방법의 구현)

  • 최지혁;함유경;최찬석;김정도;변형기
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.405-405
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    • 2000
  • We designed the artificial olfactory sensing system (Electronic Nose) using MOS type sensor array fur recognizing and analyzing odour. The response of individual sensors of sensor array, each processing a slightly different response towards the sample volatiles, can provide enough information to discriminate between sample odours. In this paper, we applied clustering algorithm for dimension reduction, such as linear projection mapping (PCA method), nonlinear mapping (Sammon mapping method) and the combination of PCA and Sammon mapping having a better discriminating ability. The odours used are VOC (Volatile chemical compound) and Toxic gases.

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A Dimension Reduction Method for High-Dimensional Image Patterns Using Relational Discriminant Analysis (Relational Discriminant Analysis를 이용한 고차원 영상패턴의 차원축소)

  • Kim, Sang-Woon;Koo, Byum-Yong
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.689-690
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    • 2006
  • Relational discriminant analysis is a way of representing an object based on the dissimilarity measures among the prototypes extracted from feature vectors instead of the vectors themselves. Thus, by appropriately selecting a few number of representatives and by defining the dissimilarity measure, in this paper we propose a method of reducing the dimensionality and getting to achieve a better classification performance in both speed and accuracy. Our experimental results demonstrate that the proposed mechanism increases the performance as compared with the conventional approaches for samples involving artificial data sets.

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Bayesian inference of the cumulative logistic principal component regression models

  • Kyung, Minjung
    • Communications for Statistical Applications and Methods
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    • v.29 no.2
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    • pp.203-223
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    • 2022
  • We propose a Bayesian approach to cumulative logistic regression model for the ordinal response based on the orthogonal principal components via singular value decomposition considering the multicollinearity among predictors. The advantage of the suggested method is considering dimension reduction and parameter estimation simultaneously. To evaluate the performance of the proposed model we conduct a simulation study with considering a high-dimensional and highly correlated explanatory matrix. Also, we fit the suggested method to a real data concerning sprout- and scab-damaged kernels of wheat and compare it to EM based proportional-odds logistic regression model. Compared to EM based methods, we argue that the proposed model works better for the highly correlated high-dimensional data with providing parameter estimates and provides good predictions.

Feature Extraction by Optimizing the Cepstral Resolution of Frequency Sub-bands (주파수 부대역의 켑스트럼 해상도 최적화에 의한 특징추출)

  • 지상문;조훈영;오영환
    • The Journal of the Acoustical Society of Korea
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    • v.22 no.1
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    • pp.35-41
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    • 2003
  • Feature vectors for conventional speech recognition are usually extracted in full frequency band. Therefore, each sub-band contributes equally to final speech recognition results. In this paper, feature Teeters are extracted indepedently in each sub-band. The cepstral resolution of each sub-band feature is controlled for the optimal speech recognition. For this purpose, different dimension of each sub-band ceptral vectors are extracted based on the multi-band approach, which extracts feature vector independently for each sub-band. Speech recognition rates and clustering quality are suggested as the criteria for finding the optimal combination of sub-band Teeter dimension. In the connected digit recognition experiments using TIDIGITS database, the proposed method gave string accuracy of 99.125%, 99.775% percent correct, and 99.705% percent accuracy, which is 38%, 32% and 37% error rate reduction relative to baseline full-band feature vector, respectively.

Efficient Image Stitching Using Fast Feature Descriptor Extraction and Matching (빠른 특징점 기술자 추출 및 정합을 이용한 효율적인 이미지 스티칭 기법)

  • Rhee, Sang-Burm
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.1
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    • pp.65-70
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    • 2013
  • Recently, the field of computer vision has been actively researched through digital image which can be easily generated as the development and expansion of digital camera technology. Especially, research that extracts and utilizes the feature in image has been actively carried out. The image stitching is a method that creates the high resolution image using features extract and match. Image stitching can be widely used in military and medical purposes as well as in variety fields of real life. In this paper, we have proposed efficient image stitching method using fast feature descriptor extraction and matching based on SURF algorithm. It can be accurately, and quickly found matching point by reduction of dimension of feature descriptor. The feature descriptor is generated by classifying of unnecessary minutiae in extracted features. To reduce the computational time and efficient match feature, we have reduced dimension of the descriptor and expanded orientation window. In our results, the processing time of feature matching and image stitching are faster than previous algorithms, and also that method can make natural-looking stitched image.

Effective Combination of Temporal Information and Linear Transformation of Feature Vector in Speaker Verification (화자확인에서 특징벡터의 순시 정보와 선형 변환의 효과적인 적용)

  • Seo, Chang-Woo;Zhao, Mei-Hua;Lim, Young-Hwan;Jeon, Sung-Chae
    • Phonetics and Speech Sciences
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    • v.1 no.4
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    • pp.127-132
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    • 2009
  • The feature vectors which are used in conventional speaker recognition (SR) systems may have many correlations between their neighbors. To improve the performance of the SR, many researchers adopted linear transformation method like principal component analysis (PCA). In general, the linear transformation of the feature vectors is based on concatenated form of the static features and their dynamic features. However, the linear transformation which based on both the static features and their dynamic features is more complex than that based on the static features alone due to the high order of the features. To overcome these problems, we propose an efficient method that applies linear transformation and temporal information of the features to reduce complexity and improve the performance in speaker verification (SV). The proposed method first performs a linear transformation by PCA coefficients. The delta parameters for temporal information are then obtained from the transformed features. The proposed method only requires 1/4 in the size of the covariance matrix compared with adding the static and their dynamic features for PCA coefficients. Also, the delta parameters are extracted from the linearly transformed features after the reduction of dimension in the static features. Compared with the PCA and conventional methods in terms of equal error rate (EER) in SV, the proposed method shows better performance while requiring less storage space and complexity.

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Development of a Design System for Multi-Stage Gear Drives (2nd Report : Development of a Generalized New Design Algortitm

  • Chong, Tae-Hyong;Inho Bae
    • International Journal of Precision Engineering and Manufacturing
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    • v.2 no.2
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    • pp.65-72
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    • 2001
  • The design of multi-stage gear drives is a time-consuming process, since on includes more complicated problems, which are not considered in the design of single-stage gear drives. The designer has th determine the number of reduction stages and the gear ratios of each reduction state. In addition, the design problems include not only the dimensional design but also the configuration design of gear drive elements. There is no definite rule and principle for these types of design problems. Thus the design practices largely depend on the sense and the experiences of the designer , and consequently result in undesirable design solution. We propose a new generalized design algorithm to support the designer at the preliminary design phase of multi-stage gear drives. The proposed design algorithm automates the design process by integrating the dimensional design and the configuration design process. The algorithm consists of four steps. In the first step, a designer determines the number of reduction stage. In the second step. gear ratios se chosen by using the random search method. In the third step, the values of basic design parameter are chosen by using the generate and test method. Then, the values of other dimension, such ad pitch diameter, outer diameter, and face width, are calculated for the configuration design in the final step. The strength and durability of a gear is guaranteed by the bending strength and the pitting resistance rating practices by using the AGMA rating formulas. In the final step, the configuration design is carried out b using the simulated annealing algorithm. The positions of gears and shafts are determined to minimize the geometrical volume(size) of a gearbox, while satisfying spatial constraints between them. These steps are carried out iteratively until a desirable solution is acquired. The propose design algorithm has been applied to the preliminary design of four-stage gear drives in order to validate the availability. The design solution have shown considerably good results in both aspects of the dimensional and the configuration design.

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The Motion Artifact Reduction from the PPG based on EWMA (지수가중 이동평균 기반의 PPG 신호 동잡음 제거)

  • Lee, Jun-Yeon
    • Journal of Digital Convergence
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    • v.11 no.8
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    • pp.183-190
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    • 2013
  • The Photoplethysmogram is a similar periodic signal that synchrinized to a heartbeat. In this paper, we propose a exponential weight moving average filter that use similarity of Photoplethysmogram. This filtering method has the average value of each samples through separating the cycle of PPG signal. If there are some motion artifacts in continuous PPG signal, disjoin the signal based on cycle. And then, we made these signals to have same cycle by coordinating the number of sample. After arrange these cycles in 2 dimension, we put the average value of each samples from starting till now. So, we can eliminate the motion artifacts without damaged PPG signal.

Enhancing the static behavior of laminated composite plates using a porous layer

  • Yuan, Yuan;Zhao, Ke;Xu, Kuo
    • Structural Engineering and Mechanics
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    • v.72 no.6
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    • pp.763-774
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    • 2019
  • The main aim of this paper is enhancing design of traditional laminated composite plates subjected to static loads. In this regard, this paper suggests embedding a lightweight porous layer in the middle of laminated composite as the core layer of the resulted sandwich plate. The static responses of the suggested structures with uniform, symmetric and non-symmetric porosity distributions are compared to optimize their design. Using the first order shear deformation theories, the static governing equations of the suggested laminated composite plates with a porous layer (LCPPL) rested on two-parameter foundation are obtained. A finite element method is also utilized to solve the governing equations of LCPPLs. Effects of laminated composite and porosity characteristics as well as geometry dimension, edges' boundary conditions and foundation coefficients on the static deflection and stress distribution of the suggested composite plates have been investigated. The results reveal that the use of core between the layers of laminated composites leads to a sharp reduction in the static deflections of LCPPLs. Furthermore, in compare with perfect cores, the use of porous core between the layers of laminated composite plates can offer a considerable reduction in structural weight without a significant difference in their static responses.

The Motion Artifact Reduction using Periodic Moving Average Filter (주기적 이동평균필터를 이용한 동잡음 제거)

  • Lee, Jun-Yeon
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.4
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    • pp.75-82
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    • 2012
  • The Photoplethysmogram is a similar periodic signal that synchronized to a heartbeat. In this paper, we propose a periodic moving average filter that use similarity of Photoplethysmogram. This filtering method has the average value of each samples through separating the cycle of PPG signal. If there are some motion artifacts in continuous PPG signal, disjoin the signal based on cycle. And then, we made these signals to have same cycle by coordinating the number of sample. After arrange these cycles in 2 dimension, we put the average value of each samples from starting till now. So, we can eliminate the motion artifacts without damaged PPG signal.