• Journal of Advanced Marine Engineering and Technology
• /
• v.32 no.8
• /
• pp.1269-1277
• /
• 2008

Ships at sea cannot exchange data among them easily so far. Basically voice-oriented communication systems are the main methods, some of them utilize the HF radio systems at lower bit rates, and for higher bit rates, the Inmarsat or VSAT are adopted. None of them are used widely because of lower qualities and higher costs. There exist many technical and economical limits to have the Internet service just like on land such as the WWW service. In order to achieve the improved transmission rates of the maritime communication networks at farther sea, MANET(Mobile Ad Hoc Network) is one of the most practical models. In this paper, a new routing protocol named EZR (Expansive Search Zone Routing Protocol) is proposed, which is based on SANET (Ship Ad Hoc Network) model that has some different features from MANET and VANET (Vehicular Ad Hoc Network). The search zone for the shortest path is firstly found by EZR. If no path is searched in the zone, the zone is expanded according to the rule of EZR. The zone-expanding and path-searching procedures are repeated until the path is found out. The performance of EZR is evaluated and compared with LAR protocol which is one of the most typical routing protocols based on geographical information. The simulated results show that EZR is much better than LAR at sea environments in terms of routing success rate, route optimality, and a single index of performance combined the previous two metrics.

• Journal of Korean Institute of Industrial Engineers
• /
• v.32 no.3
• /
• pp.226-235
• /
• 2006

Telematics is expected to be one of the fastest growing businesses in information technology area. It may create a new emerging market in industry related to automotive, telecommunications, and information services. Especially vehicle navigation service is considered as a killer application among telematics service applications. The current vehicle navigation service typically recommends a single path that is based on the traveling time or distance from the origin to the destination. The system provides two options for users to choose either via highway or via any road. Since the traffics and road conditions of big cities are very complicated and dynamic, the demand of multi-path guidance system is increasing in telematics market. The multi-path guidance system should allow drivers to choose a path based on their individual preferences such as traveling time, distance, or route familiarity. Using the Lawler's algorithm, it is possible to find multiple paths; however, due to the lengthy computational time, it is not suitable for the real-time services. This study suggests a computationally feasible and efficient heuristic multiple paths finding algorithm that is reliable for the real-time vehicle navigation services.

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

• The Journal of Korea Robotics Society
• /
• v.18 no.1
• /
• pp.1-9
• /
• 2023

This paper presents an optimal path planning strategy for aerial searching and surveying of a user-designated area using multiple Unmanned Aerial Vehicles (UAVs). The method is designed to deal with a single unseparated polygonal area, regardless of polygonal convexity. By defining the search area into a set of grids, the algorithm enables UAVs to completely search without leaving unsearched space. The presented strategy consists of two main algorithmic steps: cellular decomposition and path planning stages. The cellular decomposition method divides the area to designate a conflict-free subsearch-space to an individual UAV, while accounting the assigned flight velocity, take-off and landing positions. Then, the path planning strategy forms paths based on every point located in end of each grid row. The first waypoint is chosen as the closest point from the vehicle-starting position, and it recursively updates the nearest endpoint set to generate the shortest path. The path planning policy produces four path candidates by alternating the starting point (left or right edge), and the travel direction (vertical or horizontal). The optimal-selection policy is enforced to maximize the search efficiency, which is time dependent; the policy imposes the total path-length and turning number criteria per candidate. The results demonstrate that the proposed cellular decomposition method improves the search-time efficiency. In addition, the candidate selection enhances the algorithmic efficacy toward further mission time-duration reduction. The method shows robustness against both convex and non-convex shaped search area.

• Journal of the Society of Naval Architects of Korea
• /
• v.54 no.3
• /
• pp.187-195
• /
• 2017

The operation planning of transports used to move blocks is the one of key factors. Furthermore, reducing the running time through the effective plan contributes to pulling forward the whole logistic process of the shipyard and substantially saving the fuel consumption of itself as well. The past researches of the transporter focused on finding only the shortest distances, so called, Manhattan distance. However, these searching approaches cannot help having the significant difference in the real operational time and distance with the minimum cost approach which considers the speed retardation for turns or safety at the intersection. This study suggests the noble transporter's operational model which could take account of the consuming operational time around the crossroads on the shipyard. Concretely, the proposed method guarantees the minimization of transporters' turns and passage number which are huge burdensome to the operation time and the whole planning of transports with the given period. Resultantly, this paper is willing to explain the appropriateness of our approach, compared with the previous ones.

• Journal of Advanced Navigation Technology
• /
• v.19 no.2
• /
• pp.116-122
• /
• 2015

Motivated by continuous increase in flight demand, awareness of the importance in developing ways to increase aircraft operational efficiency on the airport movement area has been raised. This paper proposes a new routing algorithm for providing the shortest path in a right time, enhancing the aircraft movement efficiency. Many researches on developing algorithms have been performed, for example, Dijkstra algorithm and $A^*$ algorithm. The Dijkstra algorithm provide optimal solution but could possibly provide it with a cost of relatively longer computation time. On the other hand, $A^*$ algorithm does not guarantee the optimality of a solution. In this paper, we suggest a Hybrid $A^*$ algorithm, incorporating both algorithms to eliminate the weaknesses. Rigorous test shows the proposed Hybrid $A^*$ algorithm may achieve shorter computing time and optimality in searching the shortest path.

• The Journal of Bigdata
• /
• v.7 no.2
• /
• pp.129-137
• /
• 2022

With the development of the 4th industry, the logistics industry is evolving into a smart logistics system. However, ship work that transports vehicles is progressing slowly due to various problems. In this paper, we propose an stowage automation algorithm that can be used for cargo loading of vehicle carriers that shortens loading and unloading work time. The stowage automation algorithm returns the shortest distance by searching for a loading space and a movable path in the ship in consideration of the structure of the ship. The algorithm identifies walls, ramps and vehicles that have already been shipped, and can work even with randomly placed. In particular, it is expected to contribute to developing a smart logistics system for vehicle carriers by referring to the ship's master plan to search for vehicle loading and unloading space in each port and predict the shortest movable path.

• Journal of KIISE:Computer Systems and Theory
• /
• v.30 no.11
• /
• pp.603-609
• /
• 2003

Adaptive routing methods are studied for effective routing in many topologies where occurrence of the faulty nodes are inevitable. Mesh topology provides simplicity in implementing these methods. Many routing methods for mesh are able to tolerate a large number of faults enclosed by a rectangular faulty block. But they consider even good nodes in the faulty block as faulty nodes. Hence, it results the degradation of node utilization. This problem is solved by a method which transmits messages to destinations within faulty blocks via multiple “intermediate nodes”. It also divides faulty block into multiple expanded meshes. With these expanded meshes, DAG(Directed Acyclic Graph) is formed and a message is able to be routed by the shortest path according to the DAG. Therefore, the additional number of hops can be resulted. We propose a method that reduces the number of hops by searching direct paths from the destination node to the border of the faulty block. This path is called SCP(Short-Cut Path). If the path and the traversing message is on the same side of outside border of the faulty block, the message will cut into the path found by our method. It also reduces the message traverse latency between the source and the destination node.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.52 no.9
• /
• pp.533-539
• /
• 2003

Reinforcement learning (RL) has been widely used as a learning mechanism of an artificial life system. However, RL usually suffers from slow convergence to the optimum state-action sequence or a sequence of stimulus-response (SR) behaviors, and may not correctly work in non-Markov processes. In this paper, first, to cope with slow-convergence problem, if some state-action pairs are considered as disturbance for optimum sequence, then they no to be eliminated in long-term memory (LTM), where such disturbances are found by a shortest path-finding algorithm. This process is shown to let the system get an enhanced learning speed. Second, to partly solve a non-Markov problem, if a stimulus is frequently met in a searching-process, then the stimulus will be classified as a sequential percept for a non-Markov hidden state. And thus, a correct behavior for a non-Markov hidden state can be learned as in a Markov environment. To show the validity of our proposed learning technologies, several simulation result j will be illustrated.

• Journal of the Korea Society for Simulation
• /
• v.14 no.2
• /
• pp.25-34
• /
• 2005

Determination of component mounting sequence on printed circuit board assembly process is a typical NP-hard problem. It is a kind of traveling salesman problems, but it has one more hard to meet constraint of matching component type per mounting position as well as searching the shortest path. An efficient method is developed by separation of crowed area and allowing up to two slots per component type. A simulation model is constructed using Visual C++ for evaluation of the suggested heuristic.