• Proceedings of the KSR Conference
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• 2005.11a
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• pp.32-37
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• 2005

Many developed countries use risk based safety management system. Currently many research efforts are made for the application of risk concept in safety management within the boundary of the railway safety act 2005. But results of these efforts can be applied around 2008 due to many background data and analysis techniques. For the prompt and efficient construction of mid and long term safety plan$(2006\~2010)$ various reports on safety issues and expert opinions are analysed in this study without risk analysis. Identification of railway safety issues are summarized and effective measure are proposed in this study.

• The KIPS Transactions:PartD
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• v.17D no.5
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• pp.347-352
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• 2010

Automatic service identification and quality evaluation is one of key characteristics for a Service-Oriented Computing, being receiving a lot of attention from researchers in recent years. However, most researchers focus on identifying and evaluating application services and do not present methods for automatically identifying and evaluating business services from business processes. In general, the manual business service identification process by a human expert is a highly expensive and ambiguous task and may result in the service design with bad quality because of errors and misconception. We propose an automatic business service identification and quality evaluation method using Enterprise Architecture as a machine understandable knowledge-base. We verify the effectiveness of the proposed method through a case study on Department of Defense Enterprise Architecture.

• Safety and Health at Work
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• v.12 no.3
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• pp.317-323
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• 2021

Background: The surface mining industry has one of the highest fatality rates among private industries in the United States. Despite recent decreases in the fatality rates of comparable industries, the fatality rate in the surface mining industry has increased. Meanwhile, a lack of safety research in surface mining has hindered efforts to improve safety strategies in the surface mining workplace. Method: This study examined quarry workers' hazard identification skills by conducting a case study of a surface mining facility in the Mid-Atlantic region of the United States. Semistructured interviews were conducted with eight quarry workers who were employed at the mine facility. In addition to the interviews, data were collected through field notes, notes from an expert meeting with safety managers, and site photographs to explore quarry workers' safety behaviors in the workplace. Results: The results showed that quarry workers identified hazards and improved their safety performance by translating safety knowledge learned from training into practice, acquiring hands-on work experience, learning from coworkers, and sharing responsibilities among team members. Conclusion: This study contributes to understanding quarry workers' safe performance beyond what they have learned in safety training to include their interaction with other workers and hand-on experience in the workplace. This study informs practitioners in the surface mining industry to build a safe work environment as they design effective safety programs for employees.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.4
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• pp.381-392
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• 2003

Component-based Development(CBD) based on the software reuse has been more attractive from software companies that want to enhance software productivity. However, since component identification process is mainly dependent on domain expert´s intuition and experience, it was very difficult to develop tools for supporting the component identification process. In this paper, we propose a systematic procedure of identifying reusable component by using object dependencies and object usages and provide a design and implementation of its supporting tool. In object-oriented domain models. there exists several diagrams which are described in different viewpoints. From these diagrams, object dependency and object usages are extracted and merged into an object dependency network, which is a basis for performing a comfonent identification algorithm. Finally, through a case study of internet banking system, we evaluate the applicability of the proposed identification process and tool.

• The Journal of Pediatrics of Korean Medicine
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• v.33 no.2
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• pp.1-11
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• 2019

Objectives The objectives of this study is to investigate the characteristics of Attention-deficit/hyperactivity disorder (ADHD) pattern identification based on the survey of frequencies of symptoms and signs according to the pediatricians and psychiatrists in Korean Medicine. Methods Eleven pediatricians and fourteen psychiatrists participated in this study. 38 symptoms and signs of 4 ADHD pattern identifications (Kidney yin deficiency and liver yang ascendant hyperactivity 腎虛肝亢, Dual deficiencies in the heart and spleen 心脾兩虛, Phlegm-fire harassing the heart 痰火擾心, Spleen weakness and liver energy preponderance 脾虛肝旺) were used to evaluate the frequencies of ADHD. The differences in frequencies of symptoms and signs amongst ADHD pattern identifications, and the correlations between them were analyzed. Results There were significant differences in the frequencies of symptoms and signs between each pattern identification. Dual Deficiencies in the Heart and Spleen 心脾兩虛 is negatively related with hyperactivity and impulsivity, and positively related with inattention. Phlegm-fire Harassing the Heart 痰火擾心 is positively related with hyperactivity and impulsivity, and negatively related with inattention. Conclusions The results of the characteristics of ADHD pattern identifications from the survey analysis could be used in the clinical practices of ADHD as well as to improve the ADHD pattern identification questionnaire.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.160-163
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• 1995

An optimal EEG and artifact classifier is proposed using neural network operating characteristics. The neural network operating characteristics are two dimensional parametric representations of the right and false identification probabilities of the network classifier. Since the EEG and EP signals acquired from multi -channel electrodes placed on the head surface are often interfered by other relatively large physiological signals such as electromyogram (EMG) or electroculogram (EOG), the removal of the artifact-affected EEGs is one of the key elements in neuro-functional mapping. Conventionally this task has been carried out by human experts spending lots of examination time. Using the neural-network based classification, human expert's efforts and time can be substantially reduced. From experiments, the neural-network based classification performs as good as human experts: variation of decisions between the neural network and human expert appears even smaller than that between human experts.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.451-456
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• 2005

In this paper, we propose the navigation control method for intelligent robot using messy genetic algorithm. The fuzzy controller design for navigation of the intelligent robot was dependant on expert's knowledge. But, the parameters of the fuzzy logic controller obtained from expert's control action may not be outimal. In this paper, to solve the above problem, we propose the identification method to automatically tune the number of fuzzy rule and parameters of memberships of fuzzy controller using mGA. Finally, to show and evaluate the generality and feasibility of the proposed method, we provides some simulations for wall following navigation of intelligent robot.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.177-184
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• 2021

All over the world, people are affected by many chronic diseases and medical practitioners are working hard to find out the symptoms and remedies for the diseases. Many researchers focus on the feature detection of the disease and trying to get a better health recommendation system. It is necessary to detect the features automatically to provide the most relevant solution for the disease. This research gives the framework of Health Recommendation System (HRS) for identification of relevant and non-redundant features in the dataset for prediction and recommendation of diseases. This system consists of three phases such as Pre-processing, Feature Selection and Performance evaluation. It supports for handling of missing and noisy data using the proposed Imputation of missing data and noise detection based Pre-processing algorithm (IMDNDP). The selection of features from the pre-processed dataset is performed by proposed ensemble-based feature selection using an expert's knowledge (EFS-EK). It is very difficult to detect and monitor the diseases manually and also needs the expertise in the field so that process becomes time consuming. Finally, the prediction and recommendation can be done using Support Vector Machine (SVM) and rule-based approaches.

• Journal of Korea Technology Innovation Society
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• v.11 no.4
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• pp.476-509
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• 2008

This research investigates the determinant factors of technology licensing contracts and the relative importance of each factor. To accomplish this objective we classify various factors affecting technology licenses into two categories, technology and environment, and conduct an Analytic Hierarchy Process (AHP) with a Korean expert survey. From the AHP results, we find that the possibility of commercial success, as well as the scope and levels of exclusive rights which are transferred together with technology to the licensee, are very important among technological factors in technology transfer. Moreover, we conclude that the technology utilization capacity and the learning capabilities of the licensee are also important environmental factors. Finally, we conclude that the factors which the licensor and licensee consider in technology transfer are different from each other. Based on this result, we discuss implications with regard to reducing this factor gap between the licensor and licensee as a means of promoting and improving technology transfer in the Republic of Korea.

• Environmental Analysis Health and Toxicology
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• v.25 no.3
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• pp.187-195
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• 2010

Nanotechnology is the fastest growing area in scientific research and it has important applications in a wide variety of fields. Nevertheless, consumers encountered this new technology without any identification of risks and benefits. Also until now, there are no specific safety evaluation methods for nanotechnology. For this reason, we studied risk communication strategy for nanotechnology to prepare its application in commercialized products on public. A survey was conducted to identify the differences in perception between public (N=110) and expert (N=37) toward applied nanotechnology in food, drugs and cosmetic products. The survey results were used to draw up a risk cognitive map which was introduced by Paul Slovic, and the perception level of public and expert on nanotechnology was evaluated. As a result of the survey, public recognized nanotechnology as "unknown but low dread" risk factor, but expert recognized it as "unknown and high dread" risk factor. These results indicate that there are perception differences between two groups. Several risk communication strategies are reported including care, consensus and risk communication. In the case of nanotechnology, it contains both risks and benefits. Considering the nature of nanotechnology, the "consensus communication" which informs consumers about risks and benefits of issues is the most appropriate strategy.