• Title/Summary/Keyword: 성공예측

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Comparison of Korean Classification Models' Korean Essay Score Range Prediction Performance (한국어 학습 모델별 한국어 쓰기 답안지 점수 구간 예측 성능 비교)

  • Cho, Heeryon;Im, Hyeonyeol;Yi, Yumi;Cha, Junwoo
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.3
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    • pp.133-140
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    • 2022
  • We investigate the performance of deep learning-based Korean language models on a task of predicting the score range of Korean essays written by foreign students. We construct a data set containing a total of 304 essays, which include essays discussing the criteria for choosing a job ('job'), conditions of a happy life ('happ'), relationship between money and happiness ('econ'), and definition of success ('succ'). These essays were labeled according to four letter grades (A, B, C, and D), and a total of eleven essay score range prediction experiments were conducted (i.e., five for predicting the score range of 'job' essays, five for predicting the score range of 'happiness' essays, and one for predicting the score range of mixed topic essays). Three deep learning-based Korean language models, KoBERT, KcBERT, and KR-BERT, were fine-tuned using various training data. Moreover, two traditional probabilistic machine learning classifiers, naive Bayes and logistic regression, were also evaluated. Experiment results show that deep learning-based Korean language models performed better than the two traditional classifiers, with KR-BERT performing the best with 55.83% overall average prediction accuracy. A close second was KcBERT (55.77%) followed by KoBERT (54.91%). The performances of naive Bayes and logistic regression classifiers were 52.52% and 50.28% respectively. Due to the scarcity of training data and the imbalance in class distribution, the overall prediction performance was not high for all classifiers. Moreover, the classifiers' vocabulary did not explicitly capture the error features that were helpful in correctly grading the Korean essay. By overcoming these two limitations, we expect the score range prediction performance to improve.

A Study on the Factors to Affecting Career Success among Workers with Disabilities (지체장애근로자의 직업성공 요인에 관한 연구)

  • Lee, Dal-Yob
    • Korean Journal of Social Welfare
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    • v.55
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    • pp.131-153
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    • 2003
  • This study was aimed at investigating important factors influencing career success among disabled workers. The current researcher scrutinized the degree to which variables and factors affect the career success and occupational turnover rates of the research participants. The participants in this study (n=837) were 374 workers with disabilities and 463 workers without disabilities. The results of this study can be summarized as follows: First, the results of factor analysis showed important categories of conceptual themes of career success. The initial conceptual factor model did not accord with the empirical one. Second, both research participant groups seemed to be influenced by their occupational types. However, all predictive variables excluding the wage rate and the average length of work years had significant impact on job success for the disabled work group, while all the variables excluding the frequency of advice and length of working years had significant impact on job success for the non-disabled worker group. Third, the turnover rate was significantly influenced by the age and the experience of turnover of the research participants. However, the number of co-workers was the strongest predictive variable for the worker group with disabilities, but the occupation choice variable for the worker group without disabilities. Fifth, as a result of verifying the hypothetical path model, it showed that the first model was somewhat proper and could predict the career success on both research participant groups. In conclusion, the following research implications can be suggested. The occupational type of research participants was one of the most important variables to predict the career success for both research participant groups.

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Performance Analysis of a Sampling Cyclone (샘플링 싸이클론의 성능해석)

  • 김철한;이진원
    • Proceedings of the Korea Air Pollution Research Association Conference
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    • 1999.10a
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    • pp.246-247
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    • 1999
  • 싸이클론에 관한 연구는 그 내부의 복잡한 유동특성으로 인하여 실험에 의존하는 부분적인 모델이 있을 뿐, 완전한 예측모델이 정립되어 있지 않은 상태이며, 최근 들어 컴퓨터의 눈부신 발달과 함께 상용패키지를 이용한 전산유체역학(CFD)이 값싸고 효율적인 방법으로 대두되고 있으나, 이 또한 부분적으로만 성공을 거두었다(Griffiths and Boysan, 1996).(중략)

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향후 30년간의 항공우주기술 예측

  • 한국항공우주산업진흥협회
    • Aerospace Industry
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    • v.56
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    • pp.48-51
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    • 1997
  • 과학기술은 잠시도 쉬지 않고 연구발전하고 있다. 그리고 지금 아무꺼리낌없이 우리가 이용하고 있는 많은 기술이 모두 과학자들의 끊임없는 연구 개발의 결과로 나타난 것이다. 그러나 실험실에서의 연구 성공이 곧 실용기술로 모두 이용되는 것은 아니다. 여러 연구 가운데는 상당히 쓸모있는 연구인데도 불구하고 끝내 실용화되지 못하고 만 예도 없지 않다.

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베스트셀러의 유형학으로 본 1991년 책의 사회사

  • Jeong, Hye-Ok
    • The Korean Publising Journal, Monthly
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    • s.96
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    • pp.12-13
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    • 1991
  • 국제정세의 급변과 국내경제의 위기설이 대두되면서 외국 기업의 성공비결을 파헤친 책이나 미래예측서 등에 독자들의 관심이 쏠리고 있다. 또한 잠깐씩 들춰볼 수 있는 짧은 글의 모음이 큰 인기를끌었고 지난해 기승을 부렸던 대중시집들의 열기는 다소 떨어졌는데, 전반적으로 눈에 띄는 책이 적었다는 게 중론이다.

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A Study on a Strategic Product Development for a success. (성공적 제품 개발을 위한 전략적 디자인에 관한 연구)

  • 이효열;신지형;최민영
    • Proceedings of the Korea Society of Design Studies Conference
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    • 1999.10a
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    • pp.74-75
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    • 1999
  • 세계적인 규모의 인수 합병이 진행되고 있는 요즘의 자동차 시장은 이제 세계 6대 메이커 주도의 시장으로 재편될 것이라는 예측이 나타나고 있다. 또한 공급 과잉에 의한 경쟁의 심화는 이제 피할 수 없는 자동차 산업의 과제로 인식되고 있다. (중략)

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A study on the factors to affect the career success among workers with disabilities (지체장애근로자의 직업성공 요인에 관한 연구)

  • Lee, Dal-Yob
    • 한국사회복지학회:학술대회논문집
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    • 2003.10a
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    • pp.185-216
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    • 2003
  • This study was aimed at investigating important factors influencing career success among regular workers. The current researcher scrutinized the degree to which variables and factors affect the career success and occupational turnover rates of the research participants. At the same tune, two hypothetical path models established by the researcher were examined using linear multiple regression methods and the LISREL. After examining the differences among the factors of career success, a comparison was made between the disabled worker group and the non-disabled worker group. A questionnaire using the 5-point Likert scale was distributed to a group of 374 workers with disabilities and 463 workers without disabilities. For the data analysis purpose, the structural equation model, factor analysis, correlation analysis, and multiple regression analysis were carried out. The results of this study ran be summarized as follows. First, the results of factor analysis showed important categories of conceptual themes of career success. The initial conceptual factor model did not accord with the empirical one. A three-factorial model revealed categories of personal, family, and organizational factor respectively. The personal factor was composed of the self-esteem and self-efficiency. The family factor was consisted of the multi-roles stress and the number of children. Finally, the organizational factor was composed of the capacity for utilizing resources, networking, and the frequency of mentoring. In addition, the total 10 sub areas of career success were divided by two important aspects; the subjective career success and the objective career success. Second, both research participant groups seemed to be influenced by their occupational types. However, all predictive variables excluding the wage rate and the average length of work years had significant impact on job success for the disabled work group, while all the variables excluding the frequency of advice and length of working years had significant impact on job success for the non-disabled worker group. Third, the turnover rate was significantly influenced by the age and the experience of turnover of the research participants. However, the number of co-workers was the strongest predictive variable for the worker group with disabilities, but the occupation choice variable for the worker group without disabilities. For the disabled worker group, the turnover rate was differently influenced by the type of occupation, the length of working years, while multi-role stress and the average working years at the time of turnover for the worker group without disabilities. Fifth, as a result of verifying the hypothetical path model, it showed that the first model was somewhat proper and could predict the career success on both research participant groups. In the second model, the Chi-square, the degree of freedom (($x^2=64.950$, df=61, P=0.341), and the adjusted Goodness of Fit Index (AGFI) were .964, and the Comparative Fit Index (CFI) were .997, and the Root Mean Squared Residual (RMR) was respectively. .038. The model was best fitted and could predict the career success more highly because the goodness of fit index in the whole models was within the allowed range. In conclusion, the following research implications can be suggested. First, the occupational type of research participants was one of the most important variables to predict the career success for both research participant groups. It means that people with disabilities require human development services including education. They need to improve themselves in this knowledge-based society. Furthermore, for maintaining the career success, people with disabilities should be approached by considering the subjective career success aspects including wages and the promotion opportunities than the objective career success aspects.

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Development of Extra-large Hydraulic Breaker (초대형 유압브레이커 개발)

  • Ahn, Kyubok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.5
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    • pp.3081-3086
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    • 2015
  • Development of a extra-large hydraulic breaker, which could be used for a 100 ton-class excavator were carried out Hot-firing tests were carried out. Before designing a hydraulic breaker, the analysis method to predict the performance such as impact energy and impact rate were studied. Based on the analysis result, the design and manufacture of a extra-large hydraulic breaker were performed, and the breaker were confirmed to operate successfully. The data of impact energy and impact rate were measured during the operation of the breaker, and were compared with the analysis result. The analysis result of impact rate anticipated well the test data, but that of impact energy showed a large difference with the test data. The extra-large hydraulic breaker were successfully developed and the analysis method of impact energy will be updated taking into account friction, hydraulic circuit, etc.

Prediction of Employability by Job Seeker Data Through Deep Learning (딥러닝을 활용한 취업준비생 데이터에 의한 취업 가능성 예측)

  • Song, Min-Jung;Song, Won-Mi;Son, Juri;Moon, Yoo-Jin
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.01a
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    • pp.9-10
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    • 2022
  • 본 논문에서는 딥러닝을 활용하여 취업준비생들의 데이터에 의하여 취업 가능 여부와 그에 따른 유용한 정보들을 얻기 위한 시스템을 제안한다. 취업 가능성이 성공적으로 평가된다면 예비 사회인, 취업준비생, 대학생들이 미리 취업 준비가 어느 정도 이루어졌는지 본인의 위치를 평가할 수 있으며 강점과 약점을 파악할 수 있을 것이다. 본 연구를 위해 취업생 및 취업준비생 데이터를 포함하는 CSV파일을 생성하였고, 딥러닝을 활용하여 유용한 정보들을 추출해내는데 성공했다. 이를 통해 취업 가능성 예측 프로그램은 취업준비생들과 기업의 인사관리자들에게 커다란 이점을 제공할 수 있을 것으로 보인다. 더 나아가 이 프로그램은 기업 구성원들의 업무능력을 평가할 수 있는 프로그램으로도 활용할 수 있을 것으로 사료된다.

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