• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.101-108
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• 2004

The new transit fare in the Seoul Metropolitan is basically determined based on the distance-based fare system (DBFS). The total fare in DBFS consists of three parts- (1) basic fare, (2) transfer fare, and (3) extra fare. The fixed amount of basic fare for each mode is charged when a passenger gets on a mode, and it proceeds until traveling within basic travel distance. The transfer fare may be added when a passenger switches from the present mode to another. The extra fare is imposed if the total travel distance exceeds the basic travel distance, and after that, the longer distance the more extra fare based on the extra-fare-charging rule. This study proposes an algorithm for finding minimum fare route in DBFS. This study first exploits the link-label-based searching method to enable shortest path algorithms to implement without network expansion at junction nodes in inter-modal transit networks. Moreover, the link-expansion technique is adopted in order for each mode's travel to be treated like duplicated links, which have the same start and end nodes, but different link features. In this study, therefore, some notations associated with modes can be saved, thus the existing link-based shortest path algorithm is applicable without any loss of generality. For fare calculation as next steps, a mathematical formula is proposed to embrace fare-charging process using search process of two adjacent links illustrated from the origin. A shortest path algorithm for finding a minimum fare route is derived by converting the formula as a recursive form. The implementation process of the algorithm is evaluated through a simple network test.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.870-874
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• 2018

In the worst maritime accidents, people should abandon ship, but ship structures are narrow and complex and operation takes place on rough seas, so escape is not easy. In particular, passengers on cruise ships are untrained and varied, making evacuation prospects worse. In such a case, the evacuation management of the crew plays a very important role. If a rescuer enters a ship at distress and conducts rescue activities, which zones represent the most effective entry should be examined. Generally, crew and rescuers take the shortest route, but if an accident occurs along the shortest route, it is necessary to select the second-best alternative. To solve this situation, this study aims to calculate evacuation routes using Q-Learning of Reinforcement Learning, which is a machine learning technique. Reinforcement learning is one of the most important functions of artificial intelligence and is currently used in many fields. Most evacuation analysis programs developed so far use the shortest path search method. For this reason, this study explored optimal paths using reinforcement learning. In the future, machine learning techniques will be applicable to various marine-related industries for such purposes as the selection of optimal routes for autonomous vessels and risk avoidance.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.39-47
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• 2020

This paper introduces a novel system-level framework that derives energy efficient electric vehicle (EV) driving speed profile to extend EV driving range without additional cost. This paper first implements an EV power train model considering forces acting on a driving vehicle and motor efficiency. Then, it derivate the minimum-energy driving speed profile for a given driving mission defined by the route. This framework first formulates an optimization problem and uses the dynamic programming algorithm with a weighting factor to derive a speed profile minimizing both of energy consumption and driving time. This paper introduces various weighting factor tracking methods to satisfy the driving time constraint. Simulation results show that runtime of the proposed scaling algorithm is 34% and 50% smaller than those of the binary search algorithm and greedy algorithm, respectively.

• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.75-82
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• 2013

This paper proposes a $O(n^2)$ polynomial time algorithm to obtain optimal solution for Traveling Salesman problem that is a NP-complete because polynomial time algorithm has been not known yet. The biggest problem in a large-scale Traveling Salesman problem is the fact that the amount of data to be processed is $n{\times}n$, and thus as n increases, the data increases by multifold. Therefore, this paper proposes a methodology by which the data amount is first reduced to approximately n/2. Then, it seeks a bi-directional route at a random point. The proposed algorithm has proved to be successful in obtaining the optimal solutions with $O(n^2)$ time complexity when applied to TSP-1 with 26 European cities and TSP-2 with 46 cities of the USA. It could therefore be applied as a generalized algorithm for TSP.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.1-20
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• 2022

The basic way to charge vehicles for using road and public transport networks is the entry-exit toll system. This system works by reading Hi-Pass and public transportation cards of the vehicles using card readers. However, the problems of navigating a route in consideration of entry-exit toll systems include the non-additive costs of enumerating routes. This problem is known as an NP-complete task that enumerates all paths and derives the optimal path. So far, the solution to the entry-exit toll system charging has been proposed in the form of transforming the road network. However, unlike in the public transport network where the cards are generalized, this solution has not been found in situations where network expansion is required with a transfer, multi-modes and multiple card readers. Hence, this study introduced the Link Label for a public transportation network composed of card readers in which network expansion is bypassed in selecting the optimal path by enumerating the paths through a one-to-one k-path search. Since the method proposed in this study constructs a relatively small set of paths, finding the optimal path is not burdensome in terms of computing power. In addition, the ease of comparison of sensitivity between paths indicates the possibility of using this method as a generalized means of deriving an optimal path.

• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.27-34
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• 2013

Mobile robot has the exploration function in order to perform its own task. Robot exploration can be used in many applications such as surveillance, rescue and resource detection. The workspace that robots performed in was complicated or quite wide, the multi search using the several mobile robots was mainly used. In this paper, we proposed a scheme that all areas are searched for by using one robot. The method to be proposed extract a area that can be explored in the workspace then the robot investigates the area and updates the map at the same time. The explored area is saved as a hybrid map that combines the nice attributes of the grid and topological maps. The robot can produce the safe navigation route without the obstacles by using hybrid map. The proposed hybrid map uses less memory than a grid map, but it can be used for complete coverage with the same efficiency of a topological map. Experimental results show that the proposed scheme can generate a map of an environment with only 6% of the memory that a grid map requires.

• The KIPS Transactions:PartC
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• v.17C no.6
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• pp.465-470
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• 2010

In this paper we propose a method which can be used to enhance the reliability of E-ODMRP (Enhanced On-Demand Multicast Routing Protocol). E-ODMRP has low overhead compared to its predecessors since it performs periodic refresh at a rate dynamically adapted to the nodes' mobility and adopts the local recovery. Upon detecting a broken route, a node performs a local search to graft to the forwarding mesh proactively. However in E-ODMRP there is no packet recovery mechanism. A receiver may lose some packets when it is detached from the multicast tree. We propose a simple packet recovery mechanism that can be incorporated into E-ODMRP for enhanced reliability. We show via simulation that our mechanism effectively enhances the reliability of E-ODMRP.

• Korean Journal of Clinical Pharmacy
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• v.23 no.1
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• pp.57-64
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• 2013

Purpose: Drug can be hazardous for people if misused although they are useful for their indication. In urgent incidences such as overdose, proper treatment for intoxication can save patients' lives. In emergent case regarding drug overdose, pharmacists should know how to provide correct information including antidote to other healthcare providers. However, in Korea, there is neither regular class nor education material regarding detoxification. Therefore, the object of our study is to investigate the perception of pharmacists about it. Method: We surveyed hospital pharmacists by means of self-reporting questionnaire in order to investigate the pharmacists' perception of detoxification treatments from May $12^{th}$ 2012 to August $10^{th}$ 2012. The questionnaire comprised of demographic information, interest in detoxification treatment (inquiry from patients and education about antidote), knowledge of antidote, effective drug search route and perception of the need for education and stocking materials about antidotes). Results: It included total 281 hospital pharmacists from 30 hospitals in S. Korea. Of them, only 16.7% have been questioned about drug overdose from patient or representative and 35% have learned about antidotes in case of drug overdose through education program of Korean association of hospital pharmacist or university. About 98% thought that education and stocking materials about frequently overdosed drug and antidotes are helpful for patients in emergent case. Also, the percentage of correct answer of each questions about antidotes were higher in educated group ($p{\leq}0.001$). The more work years are, the percentage of correct answer of each questions are higher ($p{\leq}0.001$). Conclusion: In conclusion, it will be helpful for reducing damage by drug overdose that pharmacists take regular education about antidote for all pharmacist and pharmacy student. In addition, preparing and keeping booklet for Korean Style-antidote in pharmacy is needed currently for protecting public health.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.1
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• pp.26-36
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• 2021

The topic of this study is the field of humanitarian logistics for disaster response. Many existing studies have revealed that compliance with the golden time in response to a disaster determines the success or failure of relief activities, and logistics costs account for 80% of the disaster response cost. Besides, the agility, responsiveness, and effectiveness of the humanitarian logistics system are emphasized in consideration of the disaster situation's characteristics, such as the urgency of life-saving and rapid environmental changes. In other words, they emphasize the importance of logistics activities in disaster response, which includes the effective and efficient distribution of relief supplies. This study proposes a mathematical model for establishing a transport plan to distribute relief supplies in a disaster situation. To determine vehicles' route and the amount of relief for cities suffering a disaster, it mainly considers the urgency, effectiveness (restoration rate), and uncertainty in the logistics system. The model is initially developed as a mixed-integer nonlinear programming (MINLP) model containing some nonlinear functions and transform into a Mixed-integer linear programming (MILP) model using a logarithmic transformation and piecewise linear approximation method. Furthermore, a minimax problem is suggested to search for breakpoints and slopes to define a piecewise linear function that minimizes the linear approximation error. A numerical experiment is performed to verify the MILP model, and linear approximation error is also analyzed in the experiment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.100-111
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• 2019

The existing selected station analysis (SSA) method analyzes the link transfer mode data between origin and destination of individuals passing through stations from a microscopic standpoint. As such, existing SSA is insufficient as it uses integrated analysis using macroscopic data such as subway lines. This research builds a line chain OD based on path search of individual passenger's movement through the subway, and explores means to utilize the findings. First, a method is proposed that searches the traversed subway path from the linked passage modes that the passenger uses and applies the results to SSA line analysis. Compared to the existing SSA, this method provides for analysis of commonly conflicting features such as the line on which the station is passed, and the stations included on the line thanks to the presence of complete information of the individual passenger's traversed path. It also allows for integrated observation of the line chain OD that approaches a certain station. For enhanced understanding, Seoul Metro Line 9 is used as a case study to demonstrate the integrated formulation concept of line chain OD centered around a certain station as well as the macroscopic features of the traversed path that approaches stations included on the line.