• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.127-134
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• 2009

Universities or job training institutes need to develop training courses that match up with requirements of enterprises. Therefore, job analysis system that analyzes skills which are needed for job performing and makes it possible to be reflected in the curriculums is requested for deriving generalized curriculum system. In this paper, to develop a curriculum that fulfills the requirements of enterprises, we implemented a series of DACUM(Developing A CurriculUM) based process that performs verification of tasks for workers and roadmap for curriculum, etc. And, we analyzed a instance of this application system. The proposed system is implemented by Java and MS Access database. The system is possible to work with central database realized by MS SQL Server through the Internet.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.173-180
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• 2014

Life competencies most required for university students, who receive a higher education and prepare to go into society, are job competencies. People with a variety of competencies are needed in the job market in a globally-oriented 21st-Century knowledge-based society. Now that raising competent people who have a high level of job competency is regarded as one of university functions, a way to improve job competencies through university education needs to be investigated. This study proposes a convergence education system to improve job competencies. The convergence education system includes five type of convergence: convergence in major fields of study, convergence in education courses, convergence in education space, convergence in education methods, and convergence in education period. This education system is expected to improve a variety of job competencies including cognitive competencies, non-cognitive competencies, and global competencies.

• Journal of the Korean Society of Costume
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• v.61 no.8
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• pp.127-140
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• 2011

The purpose of this study is to offer the basic data regarding the career development supporting system of senior fashion students. This study investigated contents of required vocational information and vocational information seeking behavior of senior fashion students. And this study also intended to analyse vocational choice anxiety factors and its relationship with level of vocational information requirement. The subjects of this study consisted 261 senior fashion students at eleven universities in the nation. The results of the study are as follows. First, five dimensions of required vocational information of fashion students were identified by factor analysis; information related to judgement of eligibility to apply for the job & company, information of work environment, information of fashion company that has the potential to hire them, information of level of compensation, stability of employment and promotion, and information of kind of job & job roles in the fashion field. Second, the senior fashion students faced few obstacles obtaining vocational information such as insufficient online vocational information, difficulties in discovering the sources of vocational information and time restriction for job search & career indecision. Third, the fashion students perceived diverse anxieties about making vocational choices. The survey identified five categories of the anxieties; anxiety about adapting to new job environment & recruiting process of the fashion company, anxiety about too heavy workload, anxiety about stability of employment & level of compensation, anxiety about lack confidence of their ability to do the job and anxiety about ability in English & the qualification for application. And there was significant relationship between vocational choice anxiety and requirement level of vocational information. This result proved providing vocational information relieves anxiety about getting a job.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.177-184
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• 2015

This study aims to identify the effects of job factors related to children's teachers on job satisfaction and present suggestions through an analysis of the modulating effects according to the type of institute. In order to achieve this purpose, this study set up a cause and effect model on teacher's efficacy, emotional intelligence, friendship, and a reward system as factors of job satisfaction and analysed them based on interviews using a questionnaire. To look into the results of the analysis, it was discovered that a reward system had the greatest effect on job satisfaction for the subjects, followed by emotional intelligence, friendship, and teacher's efficacy. In an analysis of modulating effects according to the type of institute, the effect of emotional intelligence differed significantly depending on kindergartens and day care centers. Teacher's efficacy, friendship and a reward system were not significantly different. Based on the results above, this study provides basic data for the development of strategies for children's teachers to effectively achieve job satisfaction.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.1
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• pp.14-22
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• 2002

We propose the fuzzy BCMP queueing network model for the performance evaluation of distributed processing system with the ambiguous arrival rates of job, service requirements, and service rates of server by the network environments. This model is classified as the open and closed type whether or not the network accepts jobs from the system outside. We derived the measures for system performances such as the job average spending time, average job number in the system and server utilizations using fuzzy mean value analysis which can process the fuzzy factors for both types. Computer simulation was performed for verifying the effectiveness of derived equations of performance evaluation. The fuzzy BCMP queueing network model was evaluated according to the fuzzy arrival rates of job, the number of clients, and the fuzzy service requirements of job for each the open and closed type. The results were agreed with the predicted performance evaluations of the system.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.317-318
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• 2010

클라우드 컴퓨팅 서비스를 제공하기 위해서는 클라우드 컴퓨팅에 적합한 데이터 분산 저장 및 병렬 처리가 가능한 IT 인프라 구축이 필수적이다. 이를 위해서 분산 파일 시스템 중 하나인 HDFS(Hadoop File System)와 병렬 데이터 처리를 지원하기 위한 MapReduce 프레임워크 관련 연구가 각광 받고 있다. 하지만 MapReduce 프레임워크를 구성하는 JobTracker 노드는 SPoF(Single Point of Failure)이기 때문에, 작업 도중 JobTracker 노드의 결함이 발생하게 되면 전체 작업이 실패하게 된다. 위와 같은 문제를 해결하기 위해서 본 논문에서는 MapReduce 프레임워크의 JobTracker 노드 결함 발생에 대처할 수 있는 결함허용 메커니즘을 제안하였다.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.11a
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• pp.279-280
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• 2012

The Construction Standard Production Unit(CSPU) has been used for the standard cost estimate in public and private construction projects. However, It is questionable if the reliability and/or authenticity of the system is acceptable due to the lack of consistent enactment and/or revision procedures. This study identifies informational conditions and issues relative to using daily work report as a data collection method for enacting and/or revising CSPU system, and establishes the measures for improving the daily work report. This study aims on the information constitution of daily job-site report, daily manpower report, wages register for specialty contractors. According to the research results, most of necessary data were included in a daily job-site report. In conclusion, it is investigated that data of daily manpower report and wage register need to be included in a daily job-site report for understanding the current state of worker in the future.

• Journal of Distribution Science
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• v.13 no.5
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• pp.113-120
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• 2015

Purpose - As the rapid development of ICT has been made recently, many domestic companies are trying to introduce smart work infrastructure. The purpose of institution of smart work is to enhance their performance. To this end, it is necessary to advance the way of working. Developing employees' collective intelligence should be regarded as a prerequisite for advancing the way of working. Job satisfaction of the employees is another important factor to enhance organizational performance. So this study aims to provide the theoretical background of systematic approach to smart work quality by empirically analyzing the effect of smart work quality on collective intelligence and job satisfaction. Research design, data, and methodology - A structural equation model was designed to examine cause-and-effect relationships among three latent variables(smart work quality, collective intelligence, job satisfaction). Three hypotheses were formulated. The first hypothesis is that the effect of smart work quality on collective intelligence will be positively and statistically significant. Likewise, the second hypothesis is that the effect of smart work quality on job satisfaction will be positively and statistically significant. Finally, the third hypothesis is that the effect of collective intelligence on job satisfaction will be positively and statistically significant. Based on the previous researches, 34 questionnaire items were developed to measure the effect of the three variables. The survey was conducted on 162 employees who are working under smart work environment. The number of the effective questionnaires for the analysis was 154. PASW Statistics 18 and AMOS 18 were used for the statistical analysis. Results - The validity and reliability test for questionnaire items have been carried out. From the factor analysis, 1 out of 34 items was eliminated. As a result, 33 out of 34 items were used for analyzing. The values of Cronbach's α ranged from 0.701 to 0.910, indicating the acceptable reliability of the questionnaire items. The values of χ2, df, CFI, TLI, RMSEA of the model are 102.838, 51, 0.949, 0.935, 0.082, respectively. So the structural equation model was statistically significant. The first and third hypotheses were supported. But the second hypothesis was rejected. Conclusions - An analysis using structural equation model showed meaningful implications about the effect of smart work quality on collective intelligence and job satisfaction. First, as the five quality elements of the smart work improved, the level of collective intelligence increased. Second, the statistical analysis showed smart work didn't have a direct effect on job satisfaction, which is inconsistent with the prior findings. The main purpose of smart work is to help achieve greater performance. The companies also need to make efforts to improve job satisfaction of their employees along with achieving greater performance. Third, an organization with higher level of collective intelligence showed greater job satisfaction. The companies under smart work environment need to develop functions to encourage participation, sharing, openness, and collaboration. This research will provide useful information for the companies which want to introduce smart work, distribution information system, management information system, etc.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.43-50
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• 2020

In this paper, we propose an efficient dynamic workload balancing strategy which improves the performance of high-performance computing system. The key idea of this dynamic workload balancing strategy is to minimize execution time of each job and to maximize the system throughput by effectively using system resource such as CPU, memory. Also, this strategy dynamically allocates job by considering demanded memory size of executing job and workload status of each node. If an overload node occurs due to allocated job, the proposed scheme migrates job, executing in overload nodes, to another free nodes and reduces the waiting time and execution time of job by balancing workload of each node. Through simulation, we show that the proposed dynamic workload balancing strategy based on CPU, memory improves the performance of high-performance computing system compared to previous strategies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2993-3010
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• 2021

The job shop scheduling problem (JSSP) plays a critical role in smart manufacturing, an effective JSSP scheduler could save time cost and increase productivity. Conventional methods are very time-consumption and cannot deal with complicated JSSP instances as it uses one optimal algorithm to solve JSSP. This paper proposes an effective scheduler based on deep learning technology named self-supervised long-short term memory (SS-LSTM) to handle complex JSSP accurately. First, using the optimal method to generate sufficient training samples in small-scale JSSP. SS-LSTM is then applied to extract rich feature representations from generated training samples and decide the next action. In the proposed SS-LSTM, two channels are employed to reflect the full production statues. Specifically, the detailed-level channel records 18 detailed product information while the system-level channel reflects the type of whole system states identified by the k-means algorithm. Moreover, adopting a self-supervised mechanism with LSTM autoencoder to keep high feature extraction capacity simultaneously ensuring the reliable feature representative ability. The authors implemented, trained, and compared the proposed method with the other leading learning-based methods on some complicated JSSP instances. The experimental results have confirmed the effectiveness and priority of the proposed method for solving complex JSSP instances in terms of make-span.