• Journal of Radiation Protection and Research
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• v.30 no.3
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• pp.131-148
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• 2005

In a nuclear emergency, protective actions for the public should be taken in time. It is internationally proposed that generic intervention levels (GILs) and generic action levels, determined based on cost-benefit analyses, be used as the decision criteria for protective actions. Operational intervention levels (OILs) are directly or easily measurable quantities corresponding to these generic levels. To assess the necessity of protective actions in a nuclear emergency, it is important that the environmental monitoring data required for applying and revising OILs should be promptly produced. It is discussed what and how to do for this task in the course of the emergency response. For an emergency environmental monitoring to be performed effectively, a thorough preparedness has to be made including maintenance of the organization and equipments, establishment of various procedure manuals, development of a supporting computer system and periodical training and exercises. It is pointed out that Korean legal provisions concerning GILs and OILs need to be amended or newly established.

• Smart Structures and Systems
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• v.6 no.8
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• pp.939-951
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• 2010

A low-cost wireless sensor network (WSN) solution with highly expandable super and simple nodes was developed. The super node was designed as a sensing unit as well as a receiving terminal with low energy consumption. The simple node was designed to serve as a cheaper alternative for large-scale deployment. A 12-bit ADC inputs and DAC outputs were reserved for sensor boards to ease the sensing integration. Vibration and thermal field tests of the Chi-Lu Bridge were conducted to evaluate the WSN's performance. Integral acceleration, temperature and tilt sensing modules were constructed to simplify the task of long-term environmental monitoring on this bridge, while a star topology was used to avoid collisions and reduce power consumption. We showed that, given sufficient power and additional power amplifier, the WSN can successfully be active for more than 7 days and satisfy the half bridge 120-meter transmission requirement. The time and frequency responses of cables shocked by external force and temperature variations around cables in one day were recorded and analyzed. Finally, guidelines on power characterization of the WSN platform and selection of acceleration sensors for structural health monitoring applications were given.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.157-166
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• 2022

In the case of a die-casting process, defects that are difficult to confirm by visual inspection, such as shrinkage bubbles, may occur due to an error in maintaining a vacuum state. Since these casting defects are discovered during post-processing operations such as heat treatment or finishing work, they cannot be taken in advance at the casting time, which can cause a large number of defects. In this study, we propose an approach that can predict the occurrence of casting defects by defect type using machine learning technology based on casting parameter data collected from equipment in the die casting process in real time. Die-casting parameter data can basically be collected through the casting equipment controller. In order to perform classification analysis for predicting defects by defect type, labeling of casting parameters must be performed. In this study, first, the defective data set is separated by performing the primary clustering based on the total defect rate obtained during the post-processing. Second, the secondary cluster analysis is performed using the defect rate by type for the separated defect data set, and the labeling task is performed by defect type using the cluster analysis result. Finally, a classification learning model is created by collecting the entire labeled data set, and a real-time monitoring system for defect prediction using LabView and Python was implemented. When a defect is predicted, notification is performed so that the operator can cope with it, such as displaying on the monitoring screen and alarm notification.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.25 no.4
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• pp.446-464
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• 2015

Objectives: This study was conducted to evaluate the task-specific hazards of chemicals used by nail technicians in Daegu Metropolitan City. Materials: A total of 30 nail shops located in Daegu City were surveyed to investigate the major tasks and practices performed by nail technicians and the ingredients listed in nail care products used in shops. We also collected instructions for use and material safety data sheets(MSDSs) of nail care products and compared CAS Nos. of ingredients with the lists of chemicals regulated by the Industrial Safety and Health Act(ISHA) and Chemical Substances Control Act(CSCA). Results: A total of 125 chemical ingredients were found in 468 nail care products used at the 30 nail shops. The most frequently found ingredients were ethyl acetate(72%), followed by n-butyl acetate(71.8%), isopropanol(56%), benzophenone(51.1%), nitrocellulose(46.4%) and ethanol(45.3%). Comparing six tasks, the task of manicuring used the most products at 222 products containing 91 ingredients. Among the 125 ingredients, there are 31 chemicals with occupational exposure limits(OEL) designated by the Ministry of Employment and Labor(MoEL), eight categorized as carcinogens, one mutagen and two reproductive toxic chemicals. In terms of carcinogens, formaldehyde was identified as the only confirmed human carcinogen(1A). We found that there was one chemical with a permissible limit, one special management substance, 18 workplace monitoring substances and ten special health diagnosis substances regulated by ISHA. For CSCA, nine poisonous substances, six substances requiring preparation for accidents and one restricted substance were identified. Conclusions: Based on these findings, formaldehyde was identified as one of the chemicals that should most strictly be controlled for the protection of the health of nail technicians and customers. At the same time, it is necessary to distribute materials with detailed hazardous information of nail care products for nail shop technicians.

• The Mathematical Education
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• v.63 no.2
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• pp.273-294
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• 2024

Recently, interest in Edu-Tech, which applies new technologies to the educational field, is growing. Edu-Tech is now being naturally used in schools, allowing both teachers and students to adapt to these changes. Particularly, there's significant attention on using Edu-Tech to bridge the educational gap through various teaching and learning strategies. This study focuses on the importance of self-directed task management by students for supplementary learning. It developed and utilized a math learning platform that enables teachers to easily provide and manage necessary tasks for students. Initially, the study developed "Sussam-MathTeacher" a problem-based learning application for middle school students, aimed at enhancing problem-solving abilities. This platform operates as a task management system, allowing teachers to assign or recommend problems to either the entire class or individual students. It aims to improve students' problem-solving abilities through a process that includes presenting necessary tasks, monitoring their own progress in solving problems, and self-assessing growth. Through this study, students demonstrated improved problem-solving skills by tackling tasks suited to their levels using "Sussam" highlighting the critical role of teachers in the digital educational environment.

• Journal of the Korean Dietetic Association
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• v.19 no.3
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• pp.265-286
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• 2013

The present study was conducted to develop a standardized job description for clinical dietitians working in hospitals. A developing curriculum (DACUM) method was used for the job analysis of clinical dietitians. Based on DACUM analysis with 14 members, including clinical dietitians and professors majoring in clinical nutrition and job analysis, information on the duties, tasks, and task elements of clinical dietitians was determined. To verify the job descriptions derived from DACUM analysis, a total of 46 tertiary and general hospitals with over 500 beds were recruited for the survey. The final developed job description for clinical dietitians included 7 duties, 27 tasks, and 93 task elements. The duties consisted of nutritional assessment, nutrition diagnosis, nutrition intervention, nutrition monitoring evaluation, consultation cooperation, nutrition research, and self-development. The mean scores of perceived importance, performance, and difficulty on the clinical dietitian's task elements (out of a maximum score of 5.0) were 4.5, 3.7, and 3.5, respectively, with significant differences between the items (P<0.001). The perceived importance and performance grid of clinical dietitian's tasks showed that "construction and maintenance of collaboration" (E2) and "activity of quality improvement" (F1) received relatively low scores for performance despite their high importance scores; thus the performance of these tasks requires significant improvement. In conclusion, the job descriptions of clinical dietitians developed from this study are useful for the qualitative improvement of clinical nutrition services in hospitals.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.610-622
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• 2021

The DECOVALEX project is one of the representative international cooperative projects to enhance the understanding of the complex Thermo-Hydro-Mechanical-Chemical(THMC) coupled behavior in the high-level radioactive waste disposal system based on the numerical simulation. DECOVALEX-2023 is the current phase consisting of 7 tasks, and Task C aims to model the THM coupled behavior in the disposal system based on the Full-scale Emplacement (FE) experiment at the Mont-Terri underground rock laboratory. This study performs the numerical simulation based on the OGS-FLAC developed for the current study. In the numerical model, we emplaced the heater with constant power horizontally based on the FE experiment and monitored the pressure development, temperature increase, and mechanical deformation at the specific monitoring points. We monitored the capillary pressure as the primary effect inducing the flow in the buffer system, and thermal stress and pressurization were dominant in the surrounding rocks' area. The results will also be compared and validated with the other participating groups and the experimental data further.

• Asian Journal of Innovation and Policy
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• v.5 no.3
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• pp.315-329
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• 2016

Public R&D investment information has diverse implications for researching R&D trends. Also, as it is important for the establishment of R&D policy to grasp the current situation and trends of R&D to improve science and technology level, science and technology information service system, such as NTIS (National Science & Technology Information Service), is operated at a national level in most countries. However, since the data forms provided by current NTIS are raw data, it is necessary to develop the R&D performance indicator or to use additional scientometric methods by analyzing scientific papers or scientific R&D project information for grasping R&D trends or analyzing R&D task results. Thus, this study applied public R&D investment information to investigate and monitor R&D trends in the field of information & communication technology (ICT) of meteorology and climatology by using NTIS data of Korea and NSF (National Science Foundation) data of USA.

• Smart Structures and Systems
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• v.7 no.2
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• pp.133-152
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• 2011

System identification is a fundamental step towards the application of structural health monitoring and damage detection techniques. On this respect, the development of evolved identification strategies is a priority for obtaining reliable and repeatable baseline modal parameters of an undamaged structure to be adopted as references for future structural health assessments. The paper presents the identification of the modal parameters of the Guangzhou New Television Tower, China, using a data-driven stochastic subspace identification (SSI-data) approach complemented with an appropriate automatic mode selection strategy which proved to be successful in previous literature studies. This well-known approach is based on a clustering technique which is adopted to discriminate structural modes from spurious noise ones. The method is applied to the acceleration measurements made available within the task I of the ANCRiSST benchmark problem, which cover 24 hours of continuous monitoring of the structural response under ambient excitation. These records are then subdivided into a convenient number of data sets and the variability of modal parameter estimates with ambient temperature and mean wind velocity are pointed out. Both 10 minutes and 1 hour long records are considered for this purpose. A comparison with finite element model predictions is finally carried out, using the structural matrices provided within the benchmark, in order to check that all the structural modes contained in the considered frequency interval are effectively identified via SSI-data.

• Journal of Applied Reliability
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• v.10 no.1
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• pp.39-56
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• 2010

Statistical process control (SPC) is a powerful technique for monitoring, managing, analysing and improving the process performance. However, its has limitations such as lack of engineering, statistical skill and training, and lesser importance of activity. To solve the problems, this study proposes an intelligent SPC system using specified agents which are derived through analysis and evaluation of the SPC activities. The activities investigated by the relevant researches are categorized as collection, process analysis, diagnosis, detection, cause analysis and rule generation. Also, the evaluation criteria are established as feasibility of automation, frequency, level and time. The requirements of the agent functions are derived by the evaluation, and the types of customized agents are as data collection, store, analysis, diagnosis, monitoring, alarm and reporting. A prototype SPC system represents that the functions of the proposed agents are successfully validated.