• 제목/요약/키워드: Empirical Data Training

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Empirical modeling of flexural and splitting tensile strengths of concrete containing fly ash by GEP

  • Saridemir, Mustafa
    • Computers and Concrete
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    • 제17권4호
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    • pp.489-498
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    • 2016
  • In this paper, the flexural strength ($f_{fs}$) and splitting tensile strength ($f_{sts}$) of concrete containing different proportions of fly ash have been modeled by using gene expression programming (GEP). Two GEP models called GEP-I and GEP-II are constituted to predict the $f_{fs}$ and $f_{sts}$ values, respectively. In these models, the age of specimen, cement, water, sand, aggregate, superplasticizer and fly ash are used as independent input parameters. GEP-I model is constructed by 292 experimental data and trisected into 170, 86 and 36 data for training, testing and validating sets, respectively. Similarly, GEP-II model is constructed by 278 experimental data and trisected into 142, 70 and 66 data for training, testing and validating sets, respectively. The experimental data used in the validating set of these models are independent from the training and testing sets. The results of the statistical parameters obtained from the models indicate that the proposed empirical models have good prediction and generalization capability.

Issues and Empirical Results for Improving Text Classification

  • Ko, Young-Joong;Seo, Jung-Yun
    • Journal of Computing Science and Engineering
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    • 제5권2호
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    • pp.150-160
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    • 2011
  • Automatic text classification has a long history and many studies have been conducted in this field. In particular, many machine learning algorithms and information retrieval techniques have been applied to text classification tasks. Even though much technical progress has been made in text classification, there is still room for improvement in text classification. In this paper, we will discuss remaining issues in improving text classification. In this paper, three improvement issues are presented including automatic training data generation, noisy data treatment and term weighting and indexing, and four actual studies and their empirical results for those issues are introduced. First, the semi-supervised learning technique is applied to text classification to efficiently create training data. For effective noisy data treatment, a noisy data reduction method and a robust text classifier from noisy data are developed as a solution. Finally, the term weighting and indexing technique is revised by reflecting the importance of sentences into term weight calculation using summarization techniques.

An Application of E-learning on Training and Education: An Empirical Study in Vietnam

  • HUYNH, Quang Linh
    • The Journal of Asian Finance, Economics and Business
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    • 제9권9호
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    • pp.241-248
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    • 2022
  • The current article examines the interactions among students' attitudes to e-learning, their implementation of e-learning in their studies, and learning effectiveness. Significantly, it emphasizes the mediating role of accepting e-learning in training. It applied reliability analyses to test the measurement of items and construct validity, using the research data collected from students at Vietnam National University of Ho Chi Minh. Then, the current article used multiple regressions to inspect the causal relations; and applied procedures to investigate the mediating influence. The empirical results indicate students' attitude to e-learning positively influences their implementation of e-learning in their studies. When students apply e-learning in their studies, they likely achieve the best possible training effectiveness. Statistical evidence on the mediating role of accepting e-learning in training by students on the linkage between their attitude to e-learning and training effectiveness is revealed in this article. The findings of this article make some contributions. For educational administrators, it offers insight into the links among students' attitudes to e-learning, their implementation of e-learning in their studies, and training effectiveness, which likely allows them to establish suitable online training programs. This will be beneficial to both learners and educational institutes.

종합병원 직원의 교육훈련 만족에 관한 연구 (A Study on the Education Training Satisfaction of Employees in General Hospitals)

  • 안상윤
    • 한국병원경영학회지
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    • 제17권2호
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    • pp.34-51
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    • 2012
  • This study is an empirical research to identify difference of education training satisfaction by demographic variables, and to investigate the influence of education training satisfaction on the member's organizational commitment in general hospitals. As a result of ANOVA, t-test based on the data of 325 employees in 7 general hospitals in Korea, education training satisfaction has a significant difference by a construct and demographic variables. Education training satisfaction has a significant difference by a construct such as education training system, education training administration and education training practice. Education training satisfaction has a significant difference by occupation, career, scholarship. Education training satisfaction has a partly significant difference by status, age. But it has not a significant difference by sex distinction. Satisfaction of education training system and education training practice has a significantly positive relationship with organizational commitment. But Satisfaction of education training administration has a partly positive relationship with organizational commitment. By these results, the advanced education training structure needs to equipped in order to elevate management performance in general hospitals.

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CNN기반 상품분류 딥러닝모델을 위한 학습데이터 영향 실증 분석 (Empirical Study on Analyzing Training Data for CNN-based Product Classification Deep Learning Model)

  • 이나경;김주연;심준호
    • 한국전자거래학회지
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    • 제26권1호
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    • pp.107-126
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    • 2021
  • 전자상거래에서 상품 정보에 따른 신속하고 정확한 자동 상품 분류는 중요하다. 최근의 딥러닝 기술 발전은 자동 상품 분류에도 적용이 시도되고 있다. 성능이 우수한 딥러닝 모델개발에 있어, 학습 데이터의 품질과 모델에 적합한 데이터 전처리는 중요하다. 본 연구에서는, 텍스트 상품 데이터를 기반으로 카테고리를 자동 유추할 때, 데이터의 전처리 정도에 따른 영향력과 학습 데이터 선택 범위 영향력을 CNN모델을 사례 모델로 이용하여 비교 분석한다. 실험 분석에 사용한 데이터는 실제 데이터를 사용하여 연구 결과의 실증을 담보하였다. 본 연구가 도출한 실증 분석 및 결과는 딥러닝 상품 분류 모델 개발 시 성능 향상을 위한 레퍼런스로서 의의가 있다.

효과적인 종합적 품질경영(TQM)교육 실행의 성공요인에 관한 연구 (An Empirical Study on Factors for Effective Total Quality Management Education)

  • 서창적;김재환
    • 품질경영학회지
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    • 제28권3호
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    • pp.68-81
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    • 2000
  • In this paper, we studied the four stages of quality related education and training and identified alignment factors that have influence on successful TQM education and training. Based on extensive literature reviews the four stages are extracted such as quality concepts training, quality tools training, special topics training, and leadership training. Also we determine the alignment factors. A framewok of research model including above factors is developed and tested statistically. The perceived data are collected from managers of quality departments of 140 Korean firms through survey. The results show that alignment factors which achieve success in Quality related education training are using relevant examples and implementing training at the top in quality concepts training, providing time and opportunity to master skills in quality tools training, organizing courses into a logical curriculum in special topics training, and providing ongoing feedback in leadership training. We also offered numerous suggestions that can help organizations develop effective training programs to meet their objectives.

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Prediction of concrete spall damage under blast: Neural approach with synthetic data

  • Dauji, Saha
    • Computers and Concrete
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    • 제26권6호
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    • pp.533-546
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    • 2020
  • The prediction of spall response of reinforced concrete members like columns and slabs have been attempted by earlier researchers with analytical solutions, as well as with empirical models developed from data generated from physical or numerical experiments, with different degrees of success. In this article, compared to the empirical models, more versatile and accurate models are developed based on model-free approach of artificial neural network (ANN). Synthetic data extracted from the results of numerical experiments from literature have been utilized for the purpose of training and testing of the ANN models. For two concrete members, namely, slabs and columns, different sets of ANN models were developed, each of which proved to have definite advantages over the corresponding empirical model reported in literature. In case of slabs, for all three categories of spall, the ANN model results were superior to the empirical models as evaluated by the various performance metrics, such as correlation, root mean square error, mean absolute error, maximum overestimation and maximum underestimation. The ANN models for each category of column spall could handle three variables together: namely, depth, spacing of longitudinal and transverse reinforcement, as contrasted to the empirical models that handled one variable at a time, and at the same time yielded comparable performance. The application of the ANN models for spall prediction of concrete slabs and columns developed in this study has been discussed along with their limitations.

The Impact of Self-Efficacy on Training, Leadership Attitudes, and Entrepreneurial Performance: An Empirical Study in Indonesia

  • SETIAWAN, Iyan;DISMAN, Disman;SAPRIYA, Sapriya;MALIHAH, Elly
    • The Journal of Asian Finance, Economics and Business
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    • 제8권10호
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    • pp.37-45
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    • 2021
  • The purpose of this study was to explore and investigate: the direct impact of training on entrepreneurial performance and self-efficacy, the direct impact of leadership attitudes on entrepreneurial performance, and self-efficacy, the direct impact of self-efficacy on entrepreneurial performance, self-efficacy as a mediator of the effect of training on entrepreneurial performance, and self-efficacy as a mediator of the effect of leadership attitudes on entrepreneurial performance. This study purposively involved 131 entrepreneurs in Village-Owned Enterprises, Kuningan, Indonesia. The data was collected using a questionnaire. The data obtained was analyzed using Path Analysis with SPSS statistical software. This study has several findings. First, training has a significant effect on entrepreneurial performance and self-efficacy. Second, leadership attitudes have a significant effect on entrepreneurial performance and self-efficacy. Third, self-efficacy has a significant effect on entrepreneurial performance. Fourth, self-efficacy mediates the effect of training on entrepreneurial performance. Fifth, self-efficacy mediates the effect of leadership attitudes on entrepreneurial performance. The findings demonstrated that using self-efficacy-based training and leadership attitudes can enhance entrepreneurial self-confidence and assist them to improve their performance.

Entrepreneurship and Training Programs for Young Entrepreneurs in the New Era: An Empirical Study from Indonesia

  • MUSLIM, Abdul;NADIROH, Nadiroh;ARINI, Dewi Eka
    • The Journal of Asian Finance, Economics and Business
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    • 제10권1호
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    • pp.169-179
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    • 2023
  • This study aims to determine the factors that influence training programs in increasing entrepreneurial success as a new model for developing entrepreneurship training in a new era. It intended to provide a suggestion for building an entrepreneurship training model for Beginner Young Entrepreneurs (BYE) organized by the Ministry of Youth and Sports of Indonesia. The study used a quantitative method by collecting data through a Google form questionnaire distributed via the WhatsApp group. This study employs samples from 358 BYE training participants for 2017-2020, and data was processed using Amos SEM software to analyze factors that influence the success of entrepreneurship. The results showed that entrepreneurial motivation is a partial mediator in increasing the effect of training on its success by BYE participants. Furthermore, the key factor for increasing entrepreneurial motivation is challenging young people to start businesses. This study recommends that BYE program policymakers build a training model by considering many practical case studies to increase motivation as an important mediator in influencing entrepreneurial success. Meanwhile, to boost the morale of training participants, it is necessary to add significant real challenges for participants to start entrepreneurship. Moreover, future studies should add other independent variables, such as personality.

The Effect of Security Awareness Training on the Use of Biometric Authentication: Focusing on the Protection Motivational Behaviors

  • Jung, Seungmin;Park, Joo Yeon
    • Journal of Information Technology Applications and Management
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    • 제27권2호
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    • pp.1-21
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    • 2020
  • The purpose of this study is to investigate the behavioral factors affecting the security attitude and intention to use biometrics password based on the protection motivation theory. This study also investigates security awareness training to understand trust, privacy, and security vulnerability regarding biometric authentication password. This empirical analysis reveals security awareness training boosts the protection motivational factors that affect on the behavior and intention of using biometric authentication passwords. This study also indicates that biometric authentication passwords can be used when the overall belief in a biometric system is present. After all, security awareness training enhances the belief of biometric passwords and increase the motivation to protect security threats. The study will provide insights into protecting security vulnerability with security awareness training.