• Title/Summary/Keyword: correlation feature analysis

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Sound Quality Evaluation of Vehicle Interior Noise Using Virtual Sound Quality Analysis (가상 음질 분석을 이용한 자동차 실내소음 음질 평가)

  • Kang, Sang-wook
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.27 no.1
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    • pp.100-106
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    • 2017
  • Sound quality engineering in automobile noise applications has become more and more important under the current quiet driving condition because various noise components masked under high noise level can be audible in quieter driving situation. Many researches have been carried out for subjective and objective assessments on automobile sounds and noises. In particular, the interior sound quality has been one of research fields that can give high-quality feature to automobile products. Although many works related to the interior sound quality have been progressed or completed in foreign countries, limited research results are presented in the country. In the study, subjective assessments are first performed with 20 subjects to select perceptual adjectives suitable to the assessment of car interior noises during acceleration. The selected perceptual adjectives are employed as the assessment scales to evaluate the acceleration noises in questionnaire procedures using 35 subjects, for which several noises are created through digital filtering of the acceleration noises measured. Mean values and standard deviations for subjective assessment scores obtained by the questionnaire procedures are calculated and their reliability are also verified. Finally, various statistical analyses such as the correlation analysis and the factor analysis are carried out to reveal the interrelationship between the assessment scales and the spectrum components of the acceleration noises.

Exploratory Study of Distribution and Logistics Industry: Do Global Competitive Capabilities Affect Business Performance?

  • KIM, Boine;KIM, Byoung-Goo
    • Journal of Distribution Science
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    • v.20 no.2
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    • pp.101-108
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    • 2022
  • Purpose: In this logistics disturbance period, this study conducts research of distribution and logistics firms in Korea. The purpose of this exploratory research is to analyze global competitive capability influence on business performance. And give managerial implications and contribute to academics. Research design, data, and methodology: This research empirically analyzes the relationship between global competitive capability and business performance. As for business performance this research considered non-financial performance and measured with business performance fulfillment. As for antecedent variables, this research measured three global competitive capability constructs; preparation, utilization, intensive capability. And each construct includes two capability concepts. This study used 2,316 executing direct export distribution and logistics industry firmsfrom KOTRA's GCL data. This research used frequency analysis, reliability analysis, correlation analysis, and step-wise regression analysis by SPSS26. Results: The result shows that all the variables except export infra showed statistically significant. As results show, mid/long strategy & global mind of preparation capability, both communication and marketing of utilization capability and market strategy and product/goods/service of intensive capability give a positive influence on business performance fulfillment. Conclusions: Based on the results, this research provide implication for practical management, contribution to academic, and suggestion for feature research.

Prediction model of osteoporosis using nutritional components based on association (연관성 규칙 기반 영양소를 이용한 골다공증 예측 모델)

  • Yoo, JungHun;Lee, Bum Ju
    • The Journal of the Convergence on Culture Technology
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    • v.6 no.3
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    • pp.457-462
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    • 2020
  • Osteoporosis is a disease that occurs mainly in the elderly and increases the risk of fractures due to structural deterioration of bone mass and tissues. The purpose of this study are to assess the relationship between nutritional components and osteoporosis and to evaluate models for predicting osteoporosis based on nutrient components. In experimental method, association was performed using binary logistic regression, and predictive models were generated using the naive Bayes algorithm and variable subset selection methods. The analysis results for single variables indicated that food intake and vitamin B2 showed the highest value of the area under the receiver operating characteristic curve (AUC) for predicting osteoporosis in men. In women, monounsaturated fatty acids showed the highest AUC value. In prediction model of female osteoporosis, the models generated by the correlation based feature subset and wrapper based variable subset methods showed an AUC value of 0.662. In men, the model by the full variable obtained an AUC of 0.626, and in other male models, the predictive performance was very low in sensitivity and 1-specificity. The results of these studies are expected to be used as the basic information for the treatment and prevention of osteoporosis.

Stock Price Direction Prediction Using Convolutional Neural Network: Emphasis on Correlation Feature Selection (합성곱 신경망을 이용한 주가방향 예측: 상관관계 속성선택 방법을 중심으로)

  • Kyun Sun Eo;Kun Chang Lee
    • Information Systems Review
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    • v.22 no.4
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    • pp.21-39
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    • 2020
  • Recently, deep learning has shown high performance in various applications such as pattern analysis and image classification. Especially known as a difficult task in the field of machine learning research, stock market forecasting is an area where the effectiveness of deep learning techniques is being verified by many researchers. This study proposed a deep learning Convolutional Neural Network (CNN) model to predict the direction of stock prices. We then used the feature selection method to improve the performance of the model. We compared the performance of machine learning classifiers against CNN. The classifiers used in this study are as follows: Logistic Regression, Decision Tree, Neural Network, Support Vector Machine, Adaboost, Bagging, and Random Forest. The results of this study confirmed that the CNN showed higher performancecompared with other classifiers in the case of feature selection. The results show that the CNN model effectively predicted the stock price direction by analyzing the embedded values of the financial data

Temporal and Spatial Evaluation of Water Pollution Loads of the Tributaries in Gohyeon Stream Watershed (고현천 유입지류에 대한 오염부하량의 시.공간적 평가)

  • Kim, Sung Jae
    • Journal of Wetlands Research
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    • v.14 no.4
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    • pp.607-628
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    • 2012
  • The watershed of Gohyeon Stream was divided into the 10 sub-basins, and 19 sampling points were selected in their tributaries, which the characteristics of the water quality and pollution loads variance were investigated for during the rainy and dry seasons. The results of water quality analysis revealed that the upper watershed(T1~T8) of Gohyeon Stream had a feature of rural area, and its lower watershed(T9~T19) had a feature of the municipal area. The non-point pollution loads of the tributaries were estimated with 2,063, 601, 365, and 45 ton/yr of SS, COD, DIN, and DIP, respectively. The pollution loads of the parameters except DIP were generated about 60% during the rainy season, which suggested that a precipitation significantly influenced on the discharge of non-point source pollution. Meanwhile, the non-point pollution load of DIP was generated about 60% during the ordinary and dry seasons, which suggested that control of a phosphorus pollution source was significantly required during these seasons. Pearson's correlation analysis revealed that SS pollution source of the upper watershed was definitely different from that of the lower watershed, that is, the pollution load from the upper watershed was mainly caused by the discharge of SS due to soil erosion in the farmland and forest land during the rainy season, and that of the lower watershed by the discharge of sewage and municipal run-off.

Character Recognition Algorithm using Accumulation Mask

  • Yoo, Suk Won
    • International Journal of Advanced Culture Technology
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    • v.6 no.2
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    • pp.123-128
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    • 2018
  • Learning data is composed of 100 characters with 10 different fonts, and test data is composed of 10 characters with a new font that is not used for the learning data. In order to consider the variety of learning data with several different fonts, 10 learning masks are constructed by accumulating pixel values of same characters with 10 different fonts. This process eliminates minute difference of characters with different fonts. After finding maximum values of learning masks, test data is expanded by multiplying these maximum values to the test data. The algorithm calculates sum of differences of two corresponding pixel values of the expanded test data and the learning masks. The learning mask with the smallest value among these 10 calculated sums is selected as the result of the recognition process for the test data. The proposed algorithm can recognize various types of fonts, and the learning data can be modified easily by adding a new font. Also, the recognition process is easy to understand, and the algorithm makes satisfactory results for character recognition.

The Cytologic Analysis of Microinvasive Squamous Cell Carcinoma of the Uterine Cervix on Cervical Smear (자궁경부 세포도말 검사에시 미세침윤성 편평세포암종의 세포학적 분석)

  • Choi, Hyun-Joo;Park, In-Ae
    • The Korean Journal of Cytopathology
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    • v.12 no.1
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    • pp.31-37
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    • 2001
  • Whlie cytologic characteristics of squamous dysplasia, carcinoma in situ, and invasive squamous cell carcinoma of the uterine cervix are well documented, relatively few studios have dealt with the cellular features of microinvasive carcinoma. In order to describe the cellular characteristics of microinvasive squamous cell carcinoma, we retrospectively reviewed 45 cervovaginal smears(15 carcinoma in situ, 15 microinvasive cancer, 15 invasive cancer) which were confirmed by histologic examination of specimens obtained by hysterectomy at the Seoul National University Hospital during S years from 1995 to 1999. The cytologic features about tumor diathesis, inflammatory background, ceil arrangement, anisonucleosis, nuclear membrane irregularity, nuclear chromatin pattern, and nucleoli were observed. The cytologlc characteristics of microinvasive squamous cell carcinoma of the uterine cervix are syncytial pattern, mild tumor diathesis, the irregularity of nuclear membrane, irregularly distributed nuclear chromatin, and occurrence of micronucleoli. But, correlation between the depth of Invasion and the cytologic feature had limited value.

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Optical Detection of Red Blood Cell Aggregation under vibration (진동장에서의 적혈구 응집성을 측정하는 광학적 방법)

  • Jang, Ju-Hee;Park, Myung-Su;Ku, Yun-Hee;Shin, Se-Hyun
    • Proceedings of the KSME Conference
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    • 2004.11a
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    • pp.1510-1515
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    • 2004
  • Aggregability of red blood cells (RBCs) was determined by a laser backscattering light analysis in a microfluidic channel. Available techniques for RBC aggregation often adopt a rotational Couette-flow using bob-and-cup system for disaggregating RBCs, which causes the system to be complex and expensive. A disposable microfluidic channel and vibration generating mechanism were used in the proposed new detection system for RBC aggregation. Prior to measurement, RBC aggregates in a blood sample were completely disaggregated by applying vibration-induced shear. With the present apparatus, the aggregation indexes of RBCs can be easily measured with small quantities of blood sample. The measurements with the present aggregometer were compared with those of LORCA and showed a strong correlation between them. The aggregability of the defibrinogenated blood RBCs is markedly lower than that of the normal RBCs. The noble feature of this design is the vibration-induced disaggregation mechanism, which enables to incorporate disposable element that holds the blood sample.

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Fuzzy Neural Network-Based Noisiness Decision of Road Scene for Lane Detection (퍼지신경망을 이용한 도로 씬의 차선정보의 잡음도 판별)

  • Yi, Un-Kun;Baek, Kwang-Ryul;Kwon, Seok-Geon;Lee, Joon-Woong
    • Proceedings of the KIEE Conference
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    • 2000.11d
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    • pp.761-764
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    • 2000
  • This paper presents a Fuzzy Neural Network (FNN) system to decide whether or not the right information of lanes can be extracted from gray-level images of road scene. The decision of noisy level of input images has been required because much noises usually deteriorates the performance of feature detection based on image processing and lead to erroneous results. As input parameters to FNN, eight noisiness indexes are constructed from a cumulative distribution function (CDF) and proved the indexes being classifiers of images as the good and the bad corrupted by sources of noise by correlation analysis between input images and the indexes. Considering real-time processing and discrimination efficiency, the proposed FNN is structured by eight input parameters, three fuzzy variables and single output. We conduct much experiments and show that our system has comparable performance in terms of false-positive rates.

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Performance Analysis of Spatial Adaptive Null Pattern Control Algorithm for 5 Elements Array Antenna (5소자 배열안테나의 공간 적응 널패턴 제어 알고리즘 성능분석)

  • Ahn, Seung-Gwan;Lee, Sang-Jeong
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.2
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    • pp.313-319
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    • 2010
  • GNSS receiver which uses the weak satellite signal is very vulnerable to the intentional jamming or non-intentional electromagnetic interference. One of the best method to overcome this disadvantage is to use an adaptive array antenna which has the capability of beamforming or nulling to the certain direction. In this paper, the performance of spatial adaptive null pattern control algorithm of 5 element array antenna is analyzed. A control algorithm which is designed in the 5 element array antenna is OPM(Output Power Minimization) which is eliminating the correlation characteristics between a reference antenna and the others. This algorithm can be applied effectively to the satellite navigation's CRPA because the satellite direction is not considered and GNSS signal power is below the thermal noise. The feature of the OPM algorithm is analyzed and the performance is compared with other null pattern control algorithm.