• Journal of Advanced Navigation Technology
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• v.12 no.5
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• pp.470-482
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• 2008

This paper propose role base access control model that use context information for ubiquitous environment. Concept of access control that use context information assigns permission that can approach in some information or object in part. And do so that can assigned user in part to it and acquire permission. So it can approach in information or object. Therefore, user approaches in information or object in assigned role, and the role that is allocated ro own is having. So, do so that can secure information or utilization of object safety. Proposa1 model investigated lacking restriction item in GEO-RBAC model. So, it considered that present new restriction condition and role conflict in various case. Also, to GEO-RBAC model proposed suitable model, analyzed old model's advantage, shortcoming. And it presented proposal model to GEO-RBAC because improving this.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.309-323
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• 2023

As the role of online reviews has become increasingly crucial, numerous studies have been conducted to utilize helpful reviews. Helpful reviews, perceived by customers, have been verified in various research studies to be influenced by factors such as ratings, review length, review content, and so on. The determination of a review's helpfulness is generally based on the number of 'helpful' votes from consumers, with more 'helpful' votes considered to have a more significant impact on consumers' purchasing decisions. However, recently written reviews that have not been exposed to many customers may have relatively few 'helpful' votes and may lack 'helpful' votes altogether due to a lack of participation. Therefore, rather than relying on the number of 'helpful' votes to assess the helpfulness of reviews, we aim to classify them based on review content. In addition, the text of the review emerges as the most influential factor in review helpfulness. This study employs text mining techniques, including topic modeling and sentiment analysis, to analyze the diverse impacts of content and emotions embedded in the review text. In this study, we propose a review helpfulness prediction model based on review content, utilizing movie reviews from IMDb, a global movie information site. We construct a review helpfulness prediction model by using an explainable Graph Neural Network (GNN), while addressing the interpretability limitations of the machine learning model. The explainable graph neural network is expected to provide more reliable information about helpful or non-helpful reviews as it can identify connections between reviews.

• Journal of the Korean Chemical Society
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• v.60 no.5
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• pp.327-341
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• 2016

This study explores the effective visual resources in the “regularity in chemical reactions” unit of ninth grade science textbooks (2009 revised version). The frequency and role of visual resources were initially examined, and the students’ perceptions of visual resources were investigated. The results of the analysis represented the learning material presentation (68%), motivational categories (14%), guide to inquiry procedures (9%), and inquiry results and summaries (8%). According to the investigation of the students’ perceptions of visual resources, the most effective visual resource for motivation is a photograph depicting physical and chemical changes, such as in bread baking and the most effective for learning material presentations in mass conservation, definite proportion, and stoichiometric concept units were a cartoon, graph, and formula representing stoichiometric phenomena, respectively. The most effective resource for guide to inquiry (experimental) procedures were photographs of both instruments and sequential experiment processes; and in the inquiry results and summary category, incomplete tables and graphs for students to work on themselves. The aims of this research are to increase the usefulness of visual resources in the teaching-learning activity and provide informative supplements for the development and improvement of visual resources, according to the students’ perceptions.

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.929-936
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• 2004

A major limitation of available component-based platforms Is that they do not provide suitable means for describing and reasoning on the concurrent behaviour of interacting component-based system. Indeed while these platforms provide convenient ways to describe the typed signatures of components, e.g. like CORBA's IDL, they offer a quite low-level support to describe the concurrent behaviour of component. The ability to describe and verify the concurrent behaviour of interacting components is key aspect In the development of large component-based software system. This study propose a component interface specification using process algebra and configuration's role which allows one to prove correctness of software architecture generated at design level as well as to define compatibility relations by our evolution rule and $\pi$-graph. Also, we shown on an appropriateness of a specification techniques and definitions proposed in this paper by case-study.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.719-720
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• 2006

In the mechanical system, optimization of motion control is very essential in the aspect of automation technique progress. In the servo system, the function of controller is very important but most of the controllers have played only the role of pulse generator because the controller with main function is very expensive. In this thesis, the system was composed of PC, commonly used driver AC servo motor and a produced control board. The PC transmit a gain, a locus data to a driver and controller. At the same time, it converts imformation from the controller and convert them into data and offer an output with graph. The role of a controller is to trasmit a locus data to a driver and counting the pulse on the phase of an encoder to the PC. We have performed the experiment in order to confirm with variable PID parameter capable of the optimization of gain tuning with the counting of feedback control sensor signal with regard to the external interface into the system, such as torque. Based on the experiment result, we have confirmed as follows: First, it was confirmed that we could easily input control factors P.I Gain, constant $K_P,\;K_I$ into PC. Second, not only pulse generator function was possible, but with this pulse it was also possible to count using software with PIC chip. And third, using the multi-purpose PIC micro chip, simple operation and the formation of small size AC Servo Controller was possible.

• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.141-156
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• 2010

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour, and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.67-86
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• 2020

Recommender Systems have been huge influence users and business more and more. Recently the importance of E-commerce has been reached rapid growth greatly in world-wide COVID-19 pandemic. Recommender system is the center of E-commerce lively. Top ranked E-commerce managers mentioned that recommender systems have a major influence on customer's purchase such as about 50% of Netflix, Amazon sales from their recommender systems. Most algorithms have been focused on improving accuracy of recommender system regardless of novelty, diversity, serendipity etc. Recommender systems with only high accuracy cannot satisfy business long-term profit because of generating sales polarization. In addition, customers do not experience enjoyment of shopping from only focusing accuracy recommender system because customer's preference is changed constantly. Therefore, recommender systems with various values need to be developed for user's high satisfaction. Reranking is the most useful methodology to realize diversity of recommender system. In this paper, diversity of recommender system is represented through constructing high similarity with users who have different preference using each user's purchased item's category algorithm. It is distinguished from past research approach which is changing the algorithm of recommender system without user's diversity preference level. We tried to discover user's diversity preference level and observed the results how the effect was different according to user's diversity preference level. In addition, graph-based recommender system was used to show diversity through user's network, not collaborative filtering. In this paper, Amazon Grocery and Gourmet Food data was used because the low-involvement product, such as habitual product, foods, low-priced goods etc., had high probability to show customer's diversity. First, a bipartite graph with users and items simultaneously is constructed to make graph-based recommender system. However, each users and items unipartite graph also need to be established to show diversity of recommender system. The weight of each unipartite graph has played crucial role changing Jaccard Distance of item's category. We can observe two important results from the user's unipartite network. First, the user's diversity preference level is observed from the network and second, dissimilar users can be discovered in the user's network. Through the research process, diversity of recommender system is presented highly with small accuracy loss and optimalization for higher accuracy is possible controlling diversity ratio. This paper has three important theoretical points. First, this research expands recommender system research for user's satisfaction with various values. Second, the graph-based recommender system is developed newly. Third, the evaluation indicator of diversity is made for diversity. In addition, recommender systems are useful for corporate profit practically and this paper has contribution on business closely. Above all, business long-term profit can be improved using recommender system with diversity and the recommender system can provide right service according to user's diversity level. Lastly, the corporate selling low-involvement products have great effect based on the results.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.1
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• pp.53-65
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• 1992

For improving the performance of maglev systems with a combined lift and guidance, it is suggested that the multivariable control systems and a secondary suspension should be added. The former is required to reject both track irregularities in vertical disturbances and wind gusts in lateral disturbances, and the latter to guarantee passengers against an unsatisfied criteria in ride quality. In this paper, bond graph model for the study of nonlinear dynamics of maglev systems with a combined lift and guidance is presented briefly. And, the secondary suspension is analyzed to understand the role of stiffness and damping factors in passive devices. Finally, LQG/LTR mulitivariable control systems are designed for the overall maglev systems with and without secondary suspension, and then the system performances in these two cases are evaluated.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.3
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• pp.63-74
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• 1996

Ordering plays an important role in solving an LP problem with sparse matrix by the interior point method. Since ordering is NP-complete, we try to find an efficient method. The objective of this paper is to present an efficient heuristic ordering method for implementation of the minimum deficiency method. Both the ordering method and the data structure play important roles in implementation. First we define a new heuristic pseudo-deficiency ordering method and a data structure for the method-quotient graph and cliqued storage. Next we show an experimental result in terms of time and nonzero numbers by NETLIB problems.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.10 no.2
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• pp.1-17
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• 2000

We investigated dissatisfaction of elements of local exhaust system, needs for local exhaust system, and information networks for local exhaust system from June 1998 to September 1999 using the questionnaire structured. It contained questions concerning general characteristics of factory and local exhaust system, troubles and dissatisfaction of elements of local exhaust system, and information networks for local exhaust system. The collected data were analyzed by descriptive statistics analysis. Information networks for local exhaust system were analyzed by multidimensional scaling using path distance of network analysis and by graph analysis using Krackplot. Among complaints of local exhaust system, that of duct has show the highest percentage of complaint. In the information network for local exhaust system, Seoul is positioned in the center of network with mediating role.