• Journal of Information Processing Systems
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• v.18 no.3
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• pp.374-388
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• 2022

Database systems usually have many parameters that must be configured by database administrators and users. RocksDB achieves fast data writing performance using a log-structured merged tree. This database has many parameters associated with write and space amplifications. Write amplification degrades the database performance, and space amplification leads to an increased storage space owing to the storage of unwanted data. Previously, it was proven that significant performance improvements can be achieved by tuning the database parameters. However, tuning the multiple parameters of a database is a laborious task owing to the large number of potential configuration combinations. To address this problem, we selected the important parameters that affect the performance of RocksDB using random forest. We then analyzed the effects of the selected parameters on write and space amplifications using analysis of variance. We used a genetic algorithm to obtain optimized values of the major parameters. The experimental results indicate an insignificant reduction (-5.64%) in the execution time when using these optimized values; however, write amplification, space amplification, and data processing rates improved considerably by 20.65%, 54.50%, and 89.68%, respectively, as compared to the performance when using the default settings.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3507-3522
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• 2022

Model pruning methods have attracted huge attention owing to the increasing demand of deploying models on low-resource devices recently. Most existing methods use the weight norm of filters to represent their importance, and discard the ones with small value directly to achieve the pruning target, which ignores the contribution of the small norm filters. This is not only results in filter contribution waste, but also gives comparable performance to training with the random initialized weights [1]. In this paper, we point out that the small norm filters can harm the performance of the pruned model greatly, if they are discarded directly. Therefore, we propose a novel filter contribution recycle (FCR) method for structured model pruning to resolve the fore-mentioned problem. FCR collects and reassembles contribution from the small norm filters to obtain a mixed contribution collector, and then assigns the reassembled contribution to other filters with higher probability to be preserved. To achieve the target FLOPs, FCR also adopts a weight decay strategy for the small norm filters. To explore the effectiveness of our approach, extensive experiments are conducted on ImageNet2012 and CIFAR-10 datasets, and superior results are reported when comparing with other methods under the same or even more FLOPs reduction. In addition, our method is flexible to be combined with other different pruning criterions.

• Journal of Information Technology Services
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• v.22 no.4
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• pp.123-140
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• 2023

In recent times, the global economy has been subject to increasing volatility, which has made it considerably more difficult to accurately predict economic indicators compared to previous periods. In response to this challenge, the present study conducts an exploratory investigation that aims to predict the Business Survey Index (BSI) by leveraging data mining techniques on both structured and unstructured data sources. For the structured data, we have collected information regarding foreign, domestic, and industrial conditions, while the unstructured data consists of content extracted from newspaper articles. By employing an extensive set of 44 distinct data mining techniques, our research strives to enhance the BSI prediction accuracy and provide valuable insights. The results of our analysis demonstrate that the highest predictive power was attained when using data exclusively from the t-1 period. Interestingly, this suggests that previous timeframes play a vital role in forecasting the BSI effectively. The findings of this study hold significant implications for economic decision-makers, as they will not only facilitate better-informed decisions but also serve as a robust foundation for predicting a wide range of other economic indicators. By improving the prediction of crucial economic metrics, this study ultimately aims to contribute to the overall efficacy of economic policy-making and decision processes.

• Journal of Distribution Science
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• v.22 no.1
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• pp.25-36
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• 2024

Purpose: The study attempts to explore the operational performance of the existing Malaysian logistics companies and the extent of their adoption of digitalization. The role of digitalization in enhancing the performance of companies in the logistics industry in Malaysia, for value creation, is the topic of study. Research design, data and methodology: A qualitative research method with a semi-structured interview approach was applied and judgmental sampling was used as the sampling technique to collect data. The research has chosen nine companies in the logistics industry in Peninsular Malaysia, with the interviews aimed at eleven members of top and middle-level management. Data analysis was performed using logical system techniques to examine and evaluate data, reorganizing feedback, comparing it with literature, and transforming it into structured, valuable information after interviews. Results: The study revealed mixed opinions on digitalization in logistics, despite its potential benefits such as improved operational efficiency, real-time information, and customer service. However, high costs may hinder financial performance and require revisions due to stakeholder involvement. Conclusions: The Malaysian logistics industry's adoption of digitalization is gaining traction, with most companies satisfied with their status. However, challenges like cost and inefficiency persist, prompting calls for government support to improve efficiency and reduce costs while ensuring sustainable transportation.

• Journal of The Korean Association For Science Education
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• v.32 no.4
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• pp.570-585
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• 2012

The Korean national curriculum for secondary school emphasizes scientific problem solving. In line with the national curriculum, many educational studies have been conducted in relation to science education. The objects of these studies were well-defined and well-structured problems. The studies were criticized for overlooking ill-defined and ill-structured problems. Some research has dealt with problem finding in ill-structured problems, which is related to creativity. There is a need for a study of scientific problem finding process in an ill-structured problem situation, because this study will help teachers wanting to teach scientific problem-finding in an ill-structured problem situation. The objective of this study was to conduct an empirical study on the scientific problem finding process in an ill-structured problem situation. One task of scientific problem finding in an ill-structured problem situation was assigned to 92 university students; thereafter, 32 of them participated in the research through interviews. Results indicated that the scientific problem finding process depended on initial clues and tentative solutions. Initial clues were affected by students' experiences, such as major classes, films, and novels. Tentative solutions were influenced by background knowledge of the tasks. Students screened information browsed on the Internet. They applied some standards for selection, particularly emphasized reliability standards, which are supposed to be studied in other contexts. All the students used assumptions to make their problems appear probable, which could be a useful tool to articulate.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.682-688
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• 2006

This paper deals with the delay-dependent and rate-independent stabilization of systems with multiple unknown time-varying delays and time-varying structured uncertainties. All the linear matrix inequalities based conditions are derived by employing free-weighting matrices to express the relationships between the terms in the Leibniz-Newton formula. The criteria do not require any tuning parameters. Numerical examples demonstrate the validity of the method.

• Proceedings of the Korea Association of Information Systems Conference
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• 1997.10a
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• pp.445-449
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• 1997

구조 지향적인 개발방법론(Structured Methods)에서 객체 지향적인 개발방법론 (Object Orientation)으로 개발 방법의 변경은 시스템 개발 과정의 패러다임 쉬프트 (Paradigm Shift)라고 불린다. 본 연구는 이러한 시스템 개발 도구의 변경에서 나타나는 개 발자들의 혼동을 구조 지향적 개발방법론의 객체 지향적 개발방법론에 대한 지식간섭 (Knowledge Interference)의 현상으로 간주한다. 개인의 특성에, 예를 들면 지식간섭에 영 향을 미치는 구조 지향적 개발방법론의 사용 경험과 신기술에 대한 개방성, 맞는 훈련방법 이나 정보원이 존재하는지를 규명하는 연구모형을 제시한다.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.279-289
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• 2006

This paper concerns with the effects of the specialized projected for the local W university on education which was planned and conducted in October 2004. From the empirical study using the correlation analysis, regression analysis, and structured equation model, we found some results that educational service satisfaction was highly correlated with general instruction factor and hard ware factor less correlated. Also we investigated that university educational service satisfaction was deeply correlated with word of mouth.

• Asia pacific journal of information systems
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• v.14 no.2
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• pp.151-172
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• 2004

본 연구는 가상커뮤니티의 상업화에 관한 연구이다. 가상커뮤니티의 상업화에 미치는 영향요인을 문헌조사에 의하여 정리하고 가상커뮤니티 사이트를 실증 분석하였다. 공변량 구조방정식을 이용하여 연구모형을 제시하였으며 215개의 설문내용에 대해서 통계분석을 하였다. 본 연구결과는 현재 가상커뮤니티를 구축하거나, 운영중인 기업의 의사결정과 운영 전략 수립에 기여할 수 있을 뿐 아니라 가상커뮤니티의 비즈니스 모델을 제시하는데 유용한 자료가 될 것이다.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.174-176
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• 1998

역파일 구조(inverted file structure)는 검색 속도가 빠르기 때문에 정보검색 시스템의 색인정보 하부 저장구조로 널리 이용되지만 문서의 동적 삭제는 어려운 형태이다. 본 논문에서는 기존역파일 구조에 문서마다 색인어의 포스팅 레코드를 기록한 목록을 유지함으로써 문서의 동적 삭제가 용이하고, 위치정보를 포스팅 레코드에서 분리하여 위치 검색이 효율적인 역파일 구조를 설계한다. 설계된 역파일 구조는 STEER(Structured Entity Element Retrieval) 정보검색 시스템에서 구현되었다.