• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.17-33
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• 2005

Highway design speed is a very important design element which determines highway design level. When determining highway design speed, one would estimate it utilizing the most likelihood of design speed and vehicle operating speed relationship. Existing operating speed prediction models only include highway geometric characteristics and their impacts on speed, which usually can not consider the impact of highway design speed on surrounding roadway environment and land use pattern. If this happens, excessive highway construction cost and huge environmental impact can occur. In this research project, a new vehicle operating speed prediction model was developed which can reflect the effect of surrounding roadway environment into vehicle speed prediction. The followings are the research findings : Firstly, highway terrain types and land use pattern on national roads were classified and integrated into drivers' visual recognition pattern. This was performed using a data management software. Secondly, the developed highway terrain types and land use pattern were related to vehicle speeds and it was found that there were significant statistical differences among vehicle speed for each different terrain and land use pattern. Thirdly. the General Linear Model analysis was employed to analyze the effects of highway geometric features, terrain types, and land use patterns. For two-lane highway and four-lane highway tested in this research project, it was found that R squares were 0.67 and 0.85, respectively. Additionally an optimal highway design speed range table, based on this research project. was proposed for practical use. This table can be reliably used on South Korean national road design, but discretion is required for applying this table to other types of highways including provincial roads and municipal roads.

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.145-154
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• 2004

The growing demand for customer-responsive, made-to-order manufacturing is stimulating the need for improved dynamic decision-making processes in commercial fleet operations. Moreover, the rapid growth of electronic commerce through the internet is also requiring advanced and precise real-time operation of vehicle fleets. Accompanying these demand side developments/pressures, the growing availability of technologies such as AVL(Automatic Vehicle Location) systems and continuous two-way communication devices is driving developments on the supply side. These technologies enable the dispatcher to identify the current location of trucks and to communicate with drivers in real time affording the carrier fleet dispatcher the opportunity to dynamically respond to changes in demand, driver and vehicle availability, as well as traffic network conditions. This research investigates key aspects of real time dynamic routing and scheduling problems in fleet operation particularly in a truckload pickup-and-delivery problem under various settings, in which information of stochastic demands is revealed on a continuous basis, i.e., as the scheduled routes are executed. The most promising solution strategies for dealing with this real-time problem are analyzed and integrated. Furthermore, this research develops. analyzes, and implements hybrid algorithms for solving them, which combine fast local heuristic approach with an optimization-based approach. In addition, various partitioning algorithms being able to deal with large fleet of vehicles are developed based on 'divided & conquer' technique. Simulation experiments are developed and conducted to evaluate the performance of these algorithms.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.325-332
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• 2014

High cognitive workload decreases a driver's ability of judgement and response in traffic situation and could result in a traffic accident. Electrocardiography (ECG) has been used for evaluation of drivers' cognitive workload; however, individual differences in ECG response corresponding to cognitive workload have not been fully considered. The present study developed an evaluation method of individual driver's cognitive workload based on ECG data, and evaluated its usefulness through an experiment in a driving simulator. The evaluation method developed by the present study determined the optimal ECG evaluation condition for individual participant by analysis of area under the receiver operating characteristic curve (AUC) for various conditions (total number of conditions = 144) in terms of four aspects (ECG measure, window span, update rate, and workload level). AUC analysis on the various conditions showed that the optimal ECG evaluation condition for each participant was significantly different. In addition, the optimal ECG evaluation condition could accurately detect changes in cognitive workload for 47% of the total participants (n = 15). The evaluation method proposed in the present study can be utilized in the evaluation of individual driver's cognitive workload for an intelligent vehicle.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.11
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• pp.1651-1659
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• 2017

Objective: Lao PDR's recent accession to the World Trade Organization necessitates a greater understanding of the patterns and risk of livestock production in order to better align national policy with the Agreement on the Application of Sanitary and Phytosanitary Measures. This eco-health study was conducted to improve understanding of the interrelations between market chains and zoonotic infection risks at two strategic cross border points between Lao PDR, Thailand and Viet Nam. Methods: Information gained from smallholder farmer/trader interviews was integrated with serological surveys for pig-associated zoonoses-including hepatitis E virus (HEV), Taenia solium (T. solium) and trichinella-to identify potential linkages between disease risk and pig production and slaughter in low input systems common across the country. Results: Trichinella and HEV exposure was high in both humans and pigs in both study areas, significantly associated with pig slaughter and the subsequent consumption and handling of raw pork products. T. solium demonstrated a strong geographical and ethnic association with the northern study area bordering Vietnam. With the right knowledge and accessible, affordable inputs, the majority of smallholder farmers indicated a willingness to invest more in pig production, which could simultaneously improve livelihoods and decrease exposure to HEV, Trichinella, and T. solium through increased access to formal markets and an improved slaughter processes. Conclusion: The linkages identified when assessing disease risk in the context of potential economic and cultural drivers of transmission highlight the importance of a systems-based approach for the detection and control of zoonotic disease, and contributes to an improved understanding of the Lao PDR livestock sector.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.8
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• pp.343-352
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• 2017

IEC62541, known as OPC-UA, is a standard communication protocol for Smart Grid (SG) and Smart Factory application platform. It was accepted as an IEC standard (IEC62541) in 2011 by IEC TC57, and is extending range of application as collaborating with other standrads. The government's policies to popularize EVs ("Workplace Charging Challenge"), the number of Electric vehicle which try to be charging in the factory is expected to increase. In this situation, indiscreet and uncontrolled EV charging can lead to some problems, such as excess of the peak demand capacity. Therefore, EVs, which is charging in SFs, must be monitoring and controlling to avoid and reduce peak demand. However, the standards for EVs charging differ from the standards for SFs. In other words, to increase the ease of use for drivers, and reduce risk for enterprise, we have needs of study to develop the protocols or to provide interoperability, for EVs charging in SFs. This paper deals with a EV charging management platform installing in a smart factory. And this platform can be easily integrated as part of SF management software. The main goal of this paper is to implement EV management system based on IEC61851 and IEC62541.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.63-73
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• 2024

Autonomous vehicles at Levels 3 to 5, currently under global research and development, seek to replace the driver's perception, judgment, and control processes with various sensors integrated into the vehicle. This integration enables artificial intelligence to autonomously perform the majority of driving tasks. However, autonomous vehicles currently obtain temporary driving permits, allowing them to operate on roads if they meet minimum criteria for autonomous judgment abilities set by individual countries. When autonomous vehicles become more widespread in the future, it is anticipated that buyers may not have high confidence in the ability of these vehicles to avoid hazardous situations due to the limitations of temporary driving permits. In this study, we propose a method for grading the judgment abilities of autonomous vehicles based on a driving simulator experiment comparing and evaluating drivers' abilities to avoid hazardous situations. The goal is to derive evaluation criteria that allow for grading based on specific scenarios and to propose a framework for grading autonomous vehicles. Thirty adults (25 males and 5 females) participated in the driving simulator experiment. The analysis of the experimental results involved K-means cluster analysis and independent sample t-tests, confirming the possibility of classifying the judgment abilities of autonomous vehicles and the statistical significance of such classifications. Enhancing confidence in the risk-avoidance capabilities of autonomous vehicles in future hazardous situations could be a significant contribution of this research.

• 한국사회정책
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• v.25 no.2
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• pp.429-446
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• 2018

The $4^{th}$ Industrial Revolution, symbolizing the explosive innovation of digital technologies, is expected to have a great impact on labor relations and produce a lot of contested issues. The labor-management issues, created by the $4^{th}$ Industrial Revolution, are as follows: (1) employment restructuring, job re-allocation, and skill-reformation, driven by the technological displacement, resetting of worker-machine relationship, and negotiation on labor intensity and autonomy, (2) the legislation of institutional protection for the digital dependent self-employed, derived from the proliferation of platform-mediated labor, and the statutory recognition of their 'workerness', (3) unemployment safety net, income guarantee, and skill formation assistance for precarious workeforce, (4) the protection of worker privacy from workplace surveillance, (5) protecting labor rights of the digital dependent self-employed and prcarious workers and guaranteeing their unionization and collective bargaining. In comparing how labor unions in Western countries have responded to the $4^{th}$ Industrial Revolution, German unions have showed a strategic approach of policy formation toward digital technological innovations by effectively building and utilizing diverse channel of social dialogue and collective bargaining, while those in the US and UK have adopted the traditional approach of organizing and protesting in attempting to protect the interest of platform-mediated workers (i.e. Uber drivers). In light of the best practice demonstrated by German unions, it is necessary to build the process of productive policy consultation among three parties- the government, employers, and labor unions - at multi levels (i.e. workplace, sectoral and national levels), in order to prevent the destructive damage as well as labor-management confrotation, caused by digital technological innovations. In such policy consultation procesess, moreover, the inclusive and integrated approach is required to tackle with diverse problems, derived from the $4^{th}$ Industrial Revolution, in a holistic manner.