• Proceedings of the KSR Conference
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• 2004.10a
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• pp.139-144
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• 2004

Since the braking system of rolling stock is directly linked to it's safety, ensuring reliability of braking system and evaluation of performance of it are very important. To develope the performance of braking system, it is required advanced technology and gradually various factors in the field test result This study is designed to analyze various factors about braking force in rolling stock, also, by comparing braking force of KTX with that of high speed train. The study suggests to establish a method of computation of braking force suitable for high speed train having a lot of trouble in calculating braking distance by diversification of patterns of braking system such as the train of speed up and introduction of electric and pneumatic braking system.

• 유공압시스템학회:학술대회논문집
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• 2010.06a
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• pp.93-97
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• 2010

Wheel skids may occur during train operations due to low adhesion at the wheel-rail contact point abnormally, and the skids, in turn, result in flats appearing on the wheels, which affect safety and ride comfort significantly. Thus, anti-skid control has a crucial role for safe braking and prevention from flats that could cause a disastrous train accident. This paper presents simulation studies on an anti-skid control unit (ASCU) with a brake system of a rolling stock including a pneumatic model for brake power supply and dump valve operation.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1988-1998
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• 2008

Performed was a survey to find the level of interest on passenger services using IT and smart sensor technology in connection with High Speed Train development in Korea. The survey respondents were sampled from the KTX passengers, KTX crews, Korail employees, IT or sensor experts, and rolling stock experts. The results of the survey were categorized as importance, urgency/necessity, importance vs urgency/necessity, improvement measure, preferable activities based on the trip length, and inconveniencies. By analyzing the results, service items that can be implemented to the High Speed Train were recognized. The results showed that a passenger tends to expect to have his/her comfort and convenience, an attendant safety and serviceability, a Korail employee information provision and serviceability, an IT/sensor expert technological implementation done, and a rolling stock expert implementation done in practical level.

• Asia Pacific Journal of Business Review
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• v.3 no.2
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• pp.1-25
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• 2019

This study aims to examine the relationship between certain dimensions of Corporate Social Responsibility (CSR) with market performance, measured by Tobin's Q, on companies within various industries in Indonesia. This study disaggregates CSR into 7 dimensions: environment, energy, occupational safety and health, employee, product, community, and general. Samples consisted of 385 companies listed on the Indonesia Stock Exchange (IDX) during 2007-2014. OLS analysis shows that CSR contributes greatly to the formation of market performance of consumer goods, agriculture, and miscellaneous industries. The dimensions of CSR contribute differently to the formation of Q ratios in different industries. We also found that there are differences in the speed of effect of several dimensions of CSR on the formation of market performance; some CSR dimensions give immediate effect while others are lagged.

• Safety and Health at Work
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• v.14 no.3
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• pp.259-266
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• 2023

Background: Recent research on occupational injuries in companies has faced difficulties in obtaining representative data, leading to studies relying on surveys or case studies. Moreover, it is difficult to find studies on how a company's industry characteristics affect occupational injuries. This study aims to address these limitations. Methods: We collected 11 years of disclosure data from 1,247 listed companies in the Korean stock market and combined it with their occupational injury histories collected by the Republic of Korea Occupational Safety and Health Agency (KOSHA) to build a dataset. We attempted to analyze a linear panel model by dividing the dataset into manufacturing, construction, and other industries. Results: The higher proportion of full-time employees and better job skills correlate with lower occupational injuries in other industries. The wage increase reduces occupational injuries in manufacturing and other industries, but the substitution effect produces the opposite outcome in construction. Also, foreign ownership and credit ratings increase effectively reduce occupational injuries mainly in the manufacturing industry. Conclusion: Our results suggest that in explaining the relationship between corporate characteristics and occupational injuries, it is necessary to consider the nature of the industry more closely, and in particular, employment and labor policies for preventing occupational injuries need to be selectively applied according to industry. In addition, to improve the limitations and increase the usability of the research results, further detailed studies are needed in the future.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.5
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• pp.50-58
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• 2014

The PRT(Personal Rapid Transit) system is highly interested to meet a need for demand-responsive transport service and increasing demands of traffic in Korea recently. And it is being spotlighted as an eco-friendly transportation system. For these reasons, researches on the PRT system are actively undergoing in Korea. In this study, we evaluated the static structural and fatigue strengths based on ASCE-APM standards and ERRI B 12/RP 17 by means of FE simulation. We also evaluate the running stability by multi-body dynamic analyses and the rollover safety by a theoretical static stability factor according to the road modeling scenarios for the PRT system. From the results of this study, we confirmed the durability and running stability of the Korean PRT under development.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.57-64
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• 2017

In order to reduce damages to major railroad components, which have the potential to cause interruptions to railroad services and safety accidents and to generate unnecessary maintenance costs, the development of rolling stock maintenance technology is switching from preventive maintenance based on the inspection period to predictive maintenance technology, led by advanced countries. Furthermore, to enhance trust in accordance with the speedup of system and reduce maintenances cost simultaneously, the demand for fault diagnosis and prognostic health management technology is increasing. The objective of this paper is to propose a highly reliable learning model using various machine learning algorithms that can be applied to critical rolling stock components. This paper presents a model for railway rolling stock component fault diagnosis and conducts a mechanical failure diagnosis of motor components by applying the machine learning technique in order to ensure efficient maintenance support along with a data preprocessing plan for component fault diagnosis. This paper first defines a failure diagnosis model for rolling stock components. Function-based algorithms ANFIS and SMO were used as machine learning techniques for generating the failure diagnosis model. Two tree-based algorithms, RadomForest and CART, were also employed. In order to evaluate the performance of the algorithms to be used for diagnosing failures in motors as a critical railroad component, an experiment was carried out on 2 data sets with different classes (includes 6 classes and 3 class levels). According to the results of the experiment, the random forest algorithm, a tree-based machine learning technique, showed the best performance.

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.82-82
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• 2017

Chum salmon, Oncorhynchus keta, has received considerable attention in recent years for population genetic studies due to its broad geographic distribution and high commercial importance in North Pacific fisheries. The Bering Sea and North Pacific Ocean provide major feeding habitats for various salmon stocks originating from Japan, Russia and North America. Chum salmon are a dominant pelagic fish in the Bering Sea during summer and their numbers fall when they moved in coastal areas to spawn. Population genetic data for chum salmon that can serve as a baseline for stock identification studies are scarce. In this review, we describe recently developed molecular markers and discuss their use in the study of genetic population structure of chum salmon in the Pacific Rim. In addition, we review previous genetic studies focused on the assessment of stock compositions in mixed chum salmon aggregations in the Bering Sea and North Pacific Ocean.

• Journal of the Korean Society for Railway
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• v.16 no.2
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• pp.79-84
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• 2013

The definition and classification of shunting, which involves the process of sorting rolling stock into complete train sets inside station yard, are not clearly specified in Korean domestic safety regulations for railway operations. As a result, collisions during shunting occur rather frequently compared with other types of accidents in railway operations. Therefore, new systematic safety principles are proposed in this paper to improve operation safety during shunting. The improvements in safety and efficiency derived from the newly proposed approach are analyzed and verified in field application.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.147-153
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• 2017

The mortality rate in industrial accidents in South Korea was 11 per 100,000 workers in 2015. It's five times higher than the OECD average. Economic losses due to industrial accidents continue to grow, reaching 19 trillion won much more than natural disaster losses equivalent to 1.1 trillion won. It requires fundamental changes according to industrial safety management. In this study, We classified the risk of accidents in industrial complex of Ulju-gun using spatial analytics and data mining. We collected 119 data on accident data, factory characteristics data, company information such as sales amount, capital stock, building information, weather information, official land price, etc. Through the pre-processing and data convergence process, the analysis dataset was constructed. Then we conducted geographically weighted regression with spatial factors affecting fire incidents and calculated the risk of fire accidents with analytical model for combining Boosting and CART (Classification and Regression Tree). We drew the main factors that affect the fire accident. The drawn main factors are deterioration of buildings, capital stock, employee number, officially assessed land price and height of building. Finally the predicted accident rates were divided into four class (risk category-alert, hazard, caution, and attention) with Jenks Natural Breaks Classification. It is divided by seeking to minimize each class's average deviation from the class mean, while maximizing each class's deviation from the means of the other groups. As the analysis results were also visualized on maps, the danger zone can be intuitively checked. It is judged to be available in different policy decisions for different types, such as those used by different types of risk ratings.