• Journal of Information Science Theory and Practice
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• v.11 no.3
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• pp.58-78
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• 2023

This study aimed to discover the notable experiences of Library and Information Science students in a virtual internship program. It employed qualitative descriptive research design by thematically analyzing the monthly internship journal of the interns. Using Colaizzi's method to identify themes from their experiences, the study revealed that interns expected to gain knowledge and skills on operations, services, and new information communication technologies in libraries. Orientation was found helpful in identifying the things interns needed to prepare. The interns faced issues from procrastination and technical difficulties, which they coped with employing avoidance strategies. Overall, the internship was viewed as an opportunity to learn and navigate the online digital system of the library despite the coronavirus disease 2019 pandemic. They realized their capacity and reflected on which competencies need improvement. In conclusion, students still learned the necessary knowledge and skills of a librarian; experienced the challenges faced in an actual library and were provided with various opportunities and realizations regarding the practice of librarianship. This study proposed a three-stage framework that outlines the involvement of the supervising instructors, librarians, and interns in the internship program from the preparation to the process and post-assessment.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.33-40
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• 2009

We study Interpreted Systems, ATL, and ATEL to capture the notion of time, knowledge, and strategy which are important in the analysis of multi-agent systems and propose strategic constraints based on subgame perfect Nash equilibrium of game theory as one of the solutions for the issues of ATEL which an agent can access the current state of the whole system when making up his strategy even when he should be uncertain about the state, and no explicit representation of actions in ATEL models makes some natural situations harder to model. Also, we present strategic constraints-based Interpreted Systems for model checking of multi-agent systems.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.455-456
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• 2002

Wear is one of the main factors causing breakdown and fault of machine, so ferrography technique analyzing wear particles can be an effective way for condition monitoring and fault diagnosis. On the base of the forward multilayer neural network, a nodes self-deleting neural network model is provided in this paper. This network can itself deletes the nodes to optimize its construction. On the basis of the nodes self-deleting neural network, an intelligent ferrography diagnosis expert system (IFDES) for wear particles recognition and wear diagnosis is described. This intelligent expert system can automatically slim lip knowledge by learning from samples and realize basically the entirely automatic processing from wear particles recognition to wear diagnosis.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2483-2486
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• 2013

Background: The aim of this study was to determine the epidemiology of tobacco smoking, toombak dipping and alcohol consumption as risk factors for cancer in the adult population of the northern state of Sudan. Materials and Methods: A cross-sectional survey from March to April 2010, covering 963 adults, was performed. Result: Only 207 had responded, and the male female prevalence was 20.8% and 0.73%. Out of 207 respondents, 29.5% had smoked tobacco in their lifetime, 38% were toombak dippers, while 14% were consumers of alcoholic beverages. Conclusions: The prevalence of toombak dipping was higher than tobacco smoking among the adult population in the northern state of Sudan. Female participation in tobacco and alcohol related studies was found to suffer from major obstacles since these habits are considered as social stigma. Appreciation of the full impact of smoking on population health will definitely make a major contribution to improvement of the poor public health situation in Sudan.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1905-1910
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• 2003

It is well known that parameter uncertainties and time-delays cannot be avoided in practice and result in poor performance and even instability. Nevertheless, to the authors' best knowledge, there exist few results on model predictive control (MPC) handling explicitly uncertain time-delayed systems. In this paper, we present an MPC algorithm for uncertain time-varying systems with input constraints and state-delay. An optimization problem is suggested to find a memoryless state-feedback MPC law and the closed-loop stability is established under feasibility and certain conditions.

• Journal of Korean Institute of Industrial Engineers
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• v.5 no.2
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• pp.21-36
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• 1979

Static muscle contractions when prolonged or frequently repeated result in discomfort, fatigue, and musculosketal injuries. An analytic and quantitative model has been developed in order to expand the working knowledge on muscle fatigue. In this paper, three Markov models of muscle fatigue are developed. These models are based on motor unit fatigue-recovery characteristics obtained from information on motor unit behavior as it relates to fatigue and graded exertions. Three successively more realistic models are developed that involve: (1) homogeneous motor units with intensity-dependent fatigue rates and state-independent recovery rates (the HMSI model); (2) homogeneous motor units, intensity-dependent fatigue rates and state-dependent recovery rates (the HMSD model); and (3) non-homogeneous motor units (i.e., Type S and Type F), intensity-dependent fatigue rates and state-dependent recovery rates (the HMSD model). The result indicate that a simple stochastic model provide a means to analyze the complex nature of muscle fatigue in sequential static exertions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.457-462
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• 1995

This paper describes diagnosis strategy of the Flexible Multiple Fault Diagnosis Module for forecasting faults in system and deciding current machine state form sensor information. Most studydeal with diagnosis control stategy about single fault in a system, this studies deal with multiple fault diagnosis. This strategy is consist of diagnosis control module such as backward tracking expert system shell, various neural network, numerical model to predict machine state and communication module for information exchange and cooperate between each model. This models are used to describe structure, function and behavior of subsystem, complex component and total system. Hierarchical structure is very efficient to represent structural, functional and behavioral knowledge. FT(Fault Tree). ST(Symptom Tree), FCD(Fault Consequence Diagrapy), SGM(State Graph Model) and FFM(Functional Flow Model) are used to represent hierachical structure. In this study, IA(Intelligent Agent) concept is introduced to match FT component and event symbol in diagnosed system and to transfer message between each event process. Proposed diagnosis control module is made of IPC(Inter Process Communication) method under UNIX operating system.

• Journal of Korean society of Dental Hygiene
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• v.7 no.4
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• pp.441-453
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• 2007

This study was conducted among 831 industrial workers in Gumi City in Gyung-Sang-Buk Do for the purpose of acquiring knowledge to improve quality of life though industrial workers' oral health promotion. Oral examination and questionnaire surveying were used to evaluate workers' oral health state and subjective health state and analyze their effect on quality of life. At the same time, the scales used in measuring the subjects' health state and quality of life-OHIP and WHOQOL-BREF-were validated for their constituent concepts and their relations were analyzed through structural modeling. The analysis results can be summarized as follows; The constituent concepts of OHIP and QOL factor structural models were validated since they were all in the range of appropriateness, as shown in the result of analysis using Indices of Fit-GFI, CFL, TLI and RMSEA. The result of analysis of constituent concepts to identitify the relations between OHIP and QOL confirmed that OHIP influences QOL.

• Journal of Korean Association for Spatial Structures
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• v.3 no.2 s.8
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• pp.101-107
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• 2003

There exists a structural problem for link structures in the unstable state. The primary characteristics of this problem are in the existence of rigid body displacements without strain, and in the possibility of the introduction of prestressing to change an unstable state into a stable state. When we make local linearized incremental equations in order to obtain knowledge about these unstable structures, the determinant of the coefficient matrices is zero, so that we face a numerically unstable situation. This is similar to the situation in the stability problem. To avoid such a difficult situation, in this paper a simple and straightforward method was presented by means of the generalized inverse for the numerical analysis of stability problem.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.371-374
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• 2004

The ultimate purpose of Supply Chain Management (SCM) is maximizing the profits of the overall Supply Chain (SC) through increasing customer satisfaction and decreasing operating cost. It can be successfully accomplished only when SC system balances demands with supply activities coordinated by aggregate planning, mid-term level of Supply Chain Planning(SCP). However, the existing measures to mainly estimate the specific function of SCM are not enough to evaluate the state of SC with respect to the balance between supply and demand in operating. To solve this problem, we develop a new SC performance measure, Balancing Point, using momentum concept. a fundamental knowledge of physics. Momentum concept can explain the relation among objects so that it can consider the balance between supply and demand in SC operating. The developed measure can not only consider the current state of the SC system but also take planned but not executed supply activities and upcoming demands into account. Therefore, using Balancing point, we can be aware of the unbalanced state of SC in advance.