• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.981-988
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• 2023

As the usage of unmanned aerial vehicles expands, the development and the demand of related technologies are increasing. As the frequency of operation increases and the convenience of operation is emphasized, the importance of related autonomous flight technology is also highlighted. Establishing a path plan to reach the destination in autonomous flight of an unmanned aerial vehicle is important in guidance and control, and a technology for automatically generating path plan is required in order to maximize the effect of unmanned aerial vehicle. In this study, the optimization research of path planning using rapid-exploring random tree method was performed for increasing the effectiveness of autonomous operation. The path planning optimization method considering the characteristics of the unmanned aerial vehicle is proposed. In order to achieve indexes such as optimal distance, shortest time, and passage of mission points, the path planning was optimized in consideration of the mission goals and dynamic characteristics of the unmanned aerial vehicle. The proposed methods confirmed their applicability to the generation of path planning for unmanned aerial vehicles through performance verification for obstacle situations.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.69-77
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• 2006

Geocasting is a form of communication that transmits messages to all nodes within a given geographical region(i.e., the geocasting region). Most of conventional onery aware protocols were based on shortest-hop routing that is, they minimized the cost in terms of the distance and total transmission energy not considering both the residual energy at each node and the link error ratio when selecting the routes for communication. In this paper we propose a MLRG(Maximum Lifetime Reliable Geocast) protocol for energy-efficient and reliable geocasting in Ad-hoc networks. The proposed MLRG, a position-based and routing-based geocasting algorithm, maximizes the network lifetime using newly defined cost function and selecting the energy balanced routes on the basis of each node's residual energy, and provides a reliable communication considering the link error ratio.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.81-91
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• 2005

The Traveling Salesman Problem(TSP) is one of the NP-complete (None-deterministic Polynomial time complete) route optimization problems. Its calculation time increases very rapidly as the number of nodes does. Therefore, the near optimum solution has been searched by heuristic algorithms rather than the real optimum has. This paper reviews the Ant System Algorithm(ANS), an heuristic algorithm of TSP and its applicability in the parcel delivery service in Korea. ASA, which is an heuristic algorithm of NP-complete has been studied by M. Dorigo in the early 1990. ASA finds the optimum route by the probabilistic method based on the cumulated pheromone on the links by ants. ASA has been known as one of the efficient heuristic algorithms in terms of its calculation time and result. Its applications have been expanded to vehicle routing problems, network management and highway alignment planning. The precise criteria for vehicle routing has not been set up in the parcel delivery service of Korea. Vehicle routing has been determined by the vehicle deriver himself or herself. In this paper the applicability of ASA to the parcel delivery service has been reviewed. When the driver s vehicle routing is assumed to follow the Nearest Neighbor Algorithm (NNA) with 20 nodes (pick-up and drop-off places) in $10Km{\times}10Km$ service area, his or her decision was compared with ASA's one. Also, ASA showed better results than NNA as the number of nodes increases from 10 to 200. If ASA is applied, the transport cost savings could be expected in the parcel delivery service in Korea.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.105-111
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• 2004

DNA computing has been using to solve TSP (Traveling Salesman Problems). However, when the typical DNA computing is applied to TSP, it can`t efficiently express vertices and weights of between vertices. In this paper, we proposed ACO (Algorithm for Code Optimization) that applies DNA coding method to DNA computing to efficiently express vertices and weights of between vertices for TSP. We applied ACO to TSP and as a result ACO could express DNA codes which have variable lengths and weights of between vertices more efficiently than Adleman`s DNA computing algorithm could. In addition, compared to Adleman`s DNA computing algorithm, ACO could reduce search time and biological error rate by 50% and could search for a shortest path in a short time.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.114-125
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• 2006

Since wireless Internet services and small mobile communication devices come into wide use as well as the use of GPS is rapidly growing, researches on moving object, whose location information shifts sequently in accordance with time interval, are being carried out actively. Especially, the researches on vehicle moving object are applied to Advanced traveler information system, vehicle tracking system, and distribution transport system. These systems are very useful in searching previous positions, predicted future positions, the optimum course, and the shortest course of a vehicle by managing historical data of the vehicle movement. In addition, vehicle historical data are used for distribution transport plan and vehicle allocation. Vehicle historical data are stored at regular intervals, which can have a pattern. For example, a vehicle going repeatedly around a specific section follows a route very similar to another. If historical data of the vehicle with a repeated route course are stored at regular intervals, many redundant data occur, which result in much waste of storage. Therefore this thesis suggest a vehicle historical data store scheme for vehicles with a repeated route course using similar trajectory which efficiently store vehicle historical data.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.171-182
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• 2001

Travel Time is an important characteristic of traffic conditions in a road network. Currently, there are so many road users to get a unsatisfactory traffic information that is provided by existing collection systems such as, Detector, Probe car, CCTV and Anecdotal Report. This paper presents the results achieved with Data Fusion Model, Hybrid Neuro Fuzzy System for on - line estimation of travel times using RTMS(Remote Traffic Microwave Sensor) and Probe Data in the signalized arterial road. Data Fusion is the most important process to compose the various of data which can present real value for traffic situation and is also the one of the major process part in the TIC(Traffic Information Center) for analyzing and processing data. On-line travel time estimation methods(FALEM) on the basis of detector data has been evaluated by real value under KangNam Test Area.

• Journal of Korean Society of Transportation
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• v.17 no.5
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• pp.111-122
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• 1999

A service network design model for LTL freight transportation is formulated as a mixed integer Programming Problem with two heuristic solution a1gorithms. The Proposed model derives the transportation Path for each origination-destination pair, taking into account transportation cost over the links and handling costs over the nodes. The first algorithm searches for a local minimum solution from a given initial solution by improving the quality of solution repeatedly while the second a1gorithm searches for a better solution using Simulated Annealing Method. For both solution algorithms, the initial solution is derived by a modified reverse Diikstras shortest Path a1gorithm. An illustrative example, Presented in the last part of the Paper, shows that the proposed algorithms find solutions which reduce the cost by 12% and 15% respectively, compared to the initial solution.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.91-98
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• 2004

This study focuses on the development of dynamic assignment for evaluation and application for dynamic route guidance strategy. Travelers are classified according to information contents which they received pre/on trip. The first group have no traffic information, so they travel with fixed route. The second group have real-time shortest path and travel according to it. The last group have car navigation system or individual method(cellular phone, PDA-two way communication available) for traffic information on trip. And then they are assigned in accordance with the proposed multiclass dynamic assignment model. At this time the last group is gotten under control with DFS(decentralized feedback strategy). In use of this Process we expect that various traffic information strategy can be tested and also be the key factor for success of ITS, location of VMS(variable message sign), cycle of information, area of traffic information, etc).

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.17-29
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• 2010

A container terminal productivity is maximized by a minimized time for processing containers. So, we have been elevated the container terminal productivity through an improvement of computing system, but there are a limitation because of problems for transportation management and method. A Y/T(Yard Tractor), which is a representative transportation, is able to do only one process, loading or unloading, at one time. So if the Y/T can do loading and unloading step by step at a same time, the processing time would be shortened. In this paper, we proposed an effective operating process of Y/T(Yard Tractor) Multi-Cycle System by applying RTLS(Real Time Location System) to Y/T(Yard Tractor) in order to improve the process of loading and unloading at the container terminal. For this, we described Multi-Cycle System. This system consists of a real time location of Y/T based on RTLS, an indicating of Y/T location in real time with GIS technology, and an algorithm(Dijkstra's algorithm) of the shortest distance. And we used the system in container terminal process and could improve the container terminal productivity. As the result of simulation for the proposed system in this paper, we could verify that 9% of driving distance was reduced compared with the existing rate and 19% of driving distance was reduced compared with the maximum rate. Consequently, we could find out the container performance is maximized.