• Title/Summary/Keyword: Data Mining Technique

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Effects of Work Motivation and Leadership toward Work Satisfaction and Employee Performance: Evidence from Indonesia

  • PANCASILA, Irwan;HARYONO, Siswoyo;SULISTYO, Beni Agus
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.6
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    • pp.387-397
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    • 2020
  • The purpose of this study is to determine the effect of work motivation and leadership on job satisfaction and its implications on employee performance. A total of 355 samples of Bukit Asam Coal Mining Company Ltd. in Indonesia were selected proportionally with random sampling. Data were obtained through questionnaires. Data analysis technique employed structural equation modeling (SEM) with AMOS 22. The results of the study show that leadership and work motivation have a positive and significant effect on job satisfaction. Leadership has a more considerable influence (0.263) than work motivation (0.171) toward employee job satisfaction. The influence of leadership towards job performance is 0.175. The influence of work motivation towards job performance is 0.166. Job satisfaction has the most dominant influence (0.363) towards employee performance. The direct effect of leadership on employee performance is 0.175 greater than the indirect influence of leadership on employee performance through employee job satisfaction, which is only 0.096. Likewise, the direct effect of work motivation towards employee performance is 0.166 greater than the indirect effect of work motivation towards employee performance through employee job satisfaction, which is only 0.062. Thus, job satisfaction does not mediate the effects of leadership and work motivation toward employee performance.

A Diagnostic Feature Subset Selection of Breast Tumor Based on Neighborhood Rough Set Model (Neighborhood 러프집합 모델을 활용한 유방 종양의 진단적 특징 선택)

  • Son, Chang-Sik;Choi, Rock-Hyun;Kang, Won-Seok;Lee, Jong-Ha
    • Journal of Korea Society of Industrial Information Systems
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    • v.21 no.6
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    • pp.13-21
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    • 2016
  • Feature selection is the one of important issue in the field of data mining and machine learning. It is the technique to find a subset of features which provides the best classification performance, from the source data. We propose a feature subset selection method using the neighborhood rough set model based on information granularity. To demonstrate the effectiveness of proposed method, it was applied to select the useful features associated with breast tumor diagnosis of 298 shape features extracted from 5,252 breast ultrasound images, which include 2,745 benign and 2,507 malignant cases. Experimental results showed that 19 diagnostic features were strong predictors of breast cancer diagnosis and then average classification accuracy was 97.6%.

Electricity Price Prediction Based on Semi-Supervised Learning and Neural Network Algorithms (준지도 학습 및 신경망 알고리즘을 이용한 전기가격 예측)

  • Kim, Hang Seok;Shin, Hyun Jung
    • Journal of Korean Institute of Industrial Engineers
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    • v.39 no.1
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    • pp.30-45
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    • 2013
  • Predicting monthly electricity price has been a significant factor of decision-making for plant resource management, fuel purchase plan, plans to plant, operating plan budget, and so on. In this paper, we propose a sophisticated prediction model in terms of the technique of modeling and the variety of the collected variables. The proposed model hybridizes the semi-supervised learning and the artificial neural network algorithms. The former is the most recent and a spotlighted algorithm in data mining and machine learning fields, and the latter is known as one of the well-established algorithms in the fields. Diverse economic/financial indexes such as the crude oil prices, LNG prices, exchange rates, composite indexes of representative global stock markets, etc. are collected and used for the semi-supervised learning which predicts the up-down movement of the price. Whereas various climatic indexes such as temperature, rainfall, sunlight, air pressure, etc, are used for the artificial neural network which predicts the real-values of the price. The resulting values are hybridized in the proposed model. The excellency of the model was empirically verified with the monthly data of electricity price provided by the Korea Energy Economics Institute.

Nonlinear damage detection using linear ARMA models with classification algorithms

  • Chen, Liujie;Yu, Ling;Fu, Jiyang;Ng, Ching-Tai
    • Smart Structures and Systems
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    • v.26 no.1
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    • pp.23-33
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    • 2020
  • Majority of the damage in engineering structures is nonlinear. Damage sensitive features (DSFs) extracted by traditional methods from linear time series models cannot effectively handle nonlinearity induced by structural damage. A new DSF is proposed based on vector space cosine similarity (VSCS), which combines K-means cluster analysis and Bayesian discrimination to detect nonlinear structural damage. A reference autoregressive moving average (ARMA) model is built based on measured acceleration data. This study first considers an existing DSF, residual standard deviation (RSD). The DSF is further advanced using the VSCS, and then the advanced VSCS is classified using K-means cluster analysis and Bayes discriminant analysis, respectively. The performance of the proposed approach is then verified using experimental data from a three-story shear building structure, and compared with the results of existing RSD. It is demonstrated that combining the linear ARMA model and the advanced VSCS, with cluster analysis and Bayes discriminant analysis, respectively, is an effective approach for detection of nonlinear damage. This approach improves the reliability and accuracy of the nonlinear damage detection using the linear model and significantly reduces the computational cost. The results indicate that the proposed approach is potential to be a promising damage detection technique.

Ubiquitous Recognition Survey and Analysis for Gyeongnam Inhabitants (유비쿼터스에 대한 경남도민 인식 조사 및 결과 분석)

  • Cho, Kwang-Hyun;Park, Hee-Chang
    • 한국데이터정보과학회:학술대회논문집
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    • 2006.04a
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    • pp.87-98
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    • 2006
  • The reform of the information technique is very decisive in reforming effort of the government, and ubiquitous government is a representative example. But a problem in ubiquitous government service is that the efficiency is low. The reason is that the service of ubiquitous government could not be provided with a corresponding service to the inhabitants which is real and actual user. from now on, Gyeongnam province must have the ubiquitous service plan which can be the corresponding to the need of the inhabitants. In this paper we survey a ubiquitous recognition of Gyenongnam inhabitants and analyze the present situation by association rule mining. We can offer a basic data of policy about a ubiquitous service construction of Gyeongnam from the results of this paper.

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Similarity Measure based on XML Document's Structure and Contents (XML 문서의 구조와 내용을 고려한 유사도 측정)

  • Kim, Woo-Saeng
    • Journal of Korea Multimedia Society
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    • v.11 no.8
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    • pp.1043-1050
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    • 2008
  • XML has become a standard for data representation and exchange on the Internet. With a large number of XML documents on the Web, there is an increasing need to automatically process those structurally rich documents for information retrieval, document management, and data mining applications. In this paper, we propose a new method to measure the similarity between XML documents by considering their structures and contents. The similarity of document's structure is found by a simple string matching technique and that of document's contents is found by weights taking into account of the names and positions of elements. The overall algorithm runs in time that is linear in the combined size of the two documents involved in comparison evaluation.

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A Study on the Possible New Fusion between Mobile and Healthcare Service (모바일과 의료서비스 간의 새로운 융합 가능성에 관한 연구)

  • Shin, Yong Jae;Kim, Jin Hwa;Lee, Jea Beom
    • Journal of Information Technology Services
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    • v.11 no.sup
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    • pp.27-39
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    • 2012
  • As many applications are possible now in mobile environment with the trend of mobile convergence, diverse applications in healthcare industry are also possible in mobile devices. Though lots of researches on mobile and health services are introduced, they are limited to specific area or techniques. This study shows possible directions of fusion between mobile technologies and health services in the future using a data mining technique called association rule analysis. The data used in this study is collected from web pages containing key words related to mobile technologies and health services. The analysis shows that current cases of fusion between monitoring based telemedicine and patients. It also shows another case of fusion between mobile hospital and medical screen charts. These show that fusion between mobile technologies and health services already began in industry. Association rules are found between well-being, city, diet, and sleep. The association rules containing security and privacy, though their associations are not so strong, also show that security and privacy of patient information should be protected in the future. The results show that the fusion of mobile technologies and health services is expected to provide health services to more users and larger areas. It is also expected to create new diverse business models in the future.

Research on User's Query Processing in Search Engine for Ocean using the Association Rules (연관 규칙 탐사 기법을 이용한 해양 전문 검색 엔진에서의 질의어 처리에 관한 연구)

  • 하창승;윤병수;류길수
    • Journal of the Korea Society of Computer and Information
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    • v.8 no.2
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    • pp.8-15
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    • 2003
  • Recently various of information suppliers provide information via WWW so the necessary of search engine grows larger. However the efficiency of most search engines is low comparatively because of using simple pattern match technique between user's query and web document. A specialized search engine returns the specialized information depend on each user's search goal. It is trend to develop specialized search engines in many countries. However, most such engines don't satisfy the user's needs. This paper proposes the specialized search engine for ocean information that uses user's query related with ocean and the association rules in web data mining can prove relation between web documents. So this search engine improved the recall of data and the precision in existent search method.

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2D Image Construction from Low Resolution Response of a New Non-invasive Measurement for Medical Application

  • Hieda, Ichiro;Nam, Ki-Chang
    • ETRI Journal
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    • v.27 no.4
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    • pp.385-393
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    • 2005
  • This paper presents an application of digital signal processing to data acquired by the radio imaging method (RIM) that was adopted to measure moisture distribution inside the human body. RIM was originally developed for the mining industry; we are applying the method to a biomedical measurement because of its simplicity, economy, and safety. When a two-dimensional image was constructed from the measured data, the method provided insufficient resolution because the wavelength of the measurement medium, a weak electromagnetic wave in a VHF band, was longer than human tissues. We built and measured a phantom, a model simulating the human body, consisting of two water tanks representing large internal organs. A digital equalizer was applied to the measured values as a weight function, and images were reconstructed that corresponded to the original shape of the two water tanks. As a result, a two-dimensional image containing two individual peaks corresponding to the original two small water tanks was constructed. The result suggests the method was applicable to biomedical measurement by the assistance of digital signal processing. This technique may be applicable to home-based medical care and other situations in which safety, simplicity, and economy are important.

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Determination of Shallow Velocity-Interface Model by Pseudo Full Waveform Inversion (유사파형역산에 의한 천부의 속도-경계면 모델 결정)

  • Jeong, Sang Yong;Shin, Chang Soo;Yang, Seung Jin
    • Economic and Environmental Geology
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    • v.28 no.5
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    • pp.481-485
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    • 1995
  • This paper presents a new approaching method to determine the velocity and geometry of shallow subsurface from seismic refraction events. After picking the first breaks from seismic refraction data, we assume that field refraction seismogram can be replaced by the unit delta function having time shift of first break. Time curves are generated by shooting ray tracing. The partial derivatives seismogram for a damped least squares method is computed analytically at each step of the forward ray tracing. The technique is successfully tested on synthetic and real data. It has the advantage of real full waveform inversion, which is robust at low frequency band even if the initial guess is far from the true model.

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