• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.8
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• pp.1270-1281
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• 1989

This paper presents two new storage schemes of 3-D objects to accelerate the finding of the first intersecting object and the shadow computation steps in ray tracing. The 3-D objects which are potentially intersected with the first reflection (refraction)ray are enrolled within a so called reflection (refraction) frustum' for a polygon object. Only those objects registered in the corres ponding frustum are immediately checked for intersection with the secondary rays emanating from the same polygon. The other is called a shadow pyramid' which contains the candidate objects possibly blocking the path from the relevant light source to any point on the relevant polgon. The shadow testing of a point is performed only against the objects contained in the associated shadow pyramid. Despite the cost needed for registration of objects within frusta or shadow pyramids, the total rendering time of ray tracing using the proposed approaches was reduced by approximately 50% (10% in color rendering time and 70% in shadoe testing time) from the conventional cell 50% (10% in color rendering time and 70% in shadow testing time) from the conventional cell traversal scheme under the 3-D uniform subdivision environment due to the fast finding of candidate objects for intersection and the reduced number of intersection calculations.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.237-242
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• 2003

Ant Colony System (ACS) Algorithm is new meta heuristic for hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem (TSP). In this paper, we introduce ACS of new method that adds reinforcement value for each edge that visit to Local/Global updating rule. and the performance results under various conditions are conducted, and the comparision between the original ACS and the proposed method is shown. It turns out that our proposed method can compete with tile original ACS in terms of solution quality and computation speed to these problem.

• 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 the Korea Society of Computer and Information
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• v.26 no.4
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• pp.63-74
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• 2021

Location-based services (LBSs) are expected to process a large number of spatial queries, such as shortest path and k-nearest neighbor queries that arrive simultaneously at peak periods. Deploying more LBS servers to process these simultaneous spatial queries is a potential solution. However, this significantly increases service operating costs. Recently, batch processing solutions have been proposed to process a set of queries using shareable computation. In this study, we investigate the problem of batch processing moving k-nearest neighbor (MkNN) queries in dynamic spatial networks, where the travel time of each road segment changes frequently based on the traffic conditions. LBS servers based on one-query-at-a-time processing often fail to process simultaneous MkNN queries because of the significant number of redundant computations. We aim to improve the efficiency algorithmically by processing MkNN queries in batches and reusing sharable computations. Extensive evaluation using real-world roadmaps shows the superiority of our solution compared with state-of-the-art methods.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.376-386
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• 2020

The aim of this study was to develop a new efficient strategy that uses the Vector form Intrinsic Finite-element (VFIFE) method to conduct the static and dynamic analyses of marine pipes. Nonlinear problems, such as large displacement, small strain, and contact and collision, can be analyzed using a unified calculation process in the VFIFE method according to the fundamental theories of point value description, path element, and reverse motion. This method enables analysis without the need to integrate the stiffness matrix of the structure, because only motion equations of particles established according to Newton's second law are required. These characteristics of the VFIFE facilitate the modeling and computation efficiencies in analyzing the nonlinear dynamic problem of flexible pipe with large deflections. In this study, a three-dimensional (3-D) dynamical model based on 3-D beam element was established according to the VFIFE method. The deep-sea flexible pipe was described by a set of spatial mass particles linked by 3-D beam element. The motion and configuration of the pipe are determined by these spatial particles. Based on this model, a simulation procedure to predict the 3-D dynamical behavior of flexible pipe was developed and verified. It was found that the spatial configuration and static internal force of the mining pipe can be obtained by calculating the stationary state of pipe motion. Using this simulation procedure, an analysis was conducted on the static and dynamic behaviors of the flexible mining pipe based on a 1000-m sea trial system. The results of the analysis proved that the VFIFE method can be efficiently applied to the static and dynamic analyses of marine pipes.

• Structural Engineering and Mechanics
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• v.62 no.5
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• pp.619-629
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• 2017

This paper focuses on the study of complete dynamic modeling and maximum dynamic load carrying capacity computation of N-flexible links and N-flexible joints mobile manipulator undergoing large deformation. Nonlinear dynamic analysis relies on the Timoshenko theory of beams. In order to model the system completely and precisely, structural and joint flexibility, nonlinear strain-displacement relationship, payload, and non-holonomic constraints will be considered to. A finite element solution method based on mixed method is applied to model the shear deformation. This procedure is considerably more involved than displacement based element and shear deformation can be readily included without inducing the shear locking in the element. Another goal of this paper is to present a computational procedure for determination of the maximum dynamic load of geometrically nonlinear manipulators with structural and joint flexibility. An effective measure named as Moment-Height Stability (MHS) measure is applied to consider the dynamic stability of a wheeled mobile manipulator. Simulations are performed for mobile base manipulator with two flexible links and joints. The results represent that dynamic stability constraint is sensitive when calculating the maximum carrying load. Furthermore, by changing the trajectory of end effector, allowable load also changes. The effect of torsional spring parameter on the joint deformation is investigated in a parametric sensitivity study. The findings show that, by the increase of torsional stiffness, the behavior of system approaches to a system with rigid joints and allowable load of robot is also enhanced. A comparison is also made between the results obtained from small and large deformation models. Fluctuation range in obtained figures for angular displacement of links and end effector path is bigger for large deformation model. Experimental results are also provided to validate the theoretical model and these have good agreement with the simulated results.

• Journal of Communications and Networks
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• v.6 no.3
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• pp.269-279
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• 2004

A new online multi-layer integrated routing (MLIR) scheme that combines IP (electrical) layer routing with WDM (optical) layer routing is investigated. It is a highly efficient and cost-effective routing scheme viable for the next generation integrated optical Internet. A new simplified weighted graph model for the integrated optical Internet consisted of optical routers with multi-granularity optical-electrical hybrid switching capability is firstly proposed. Then, based on the proposed graph model, we develop an online integrated routing scheme called differentiated weighted fair algorithm (DWFA) employing adaptive admission control (routing) strategies with the motivation of service/bandwidth differentiation, which can jointly solve multi-layer routing problem by simply applying the minimal weighted path computation algorithm. The major objective of DWFA is fourfold: 1) Quality of service (QoS) routing for traffic requests with various priorities; 2) blocking fairness for traffic requests with various bandwidth granularities; 3) adaptive routing according to the policy parameters from service provider; 4) lower computational complexity. Simulation results show that DWFA performs better than traditional overlay routing schemes such as optical-first-routing (OFR) and electrical-first-routing (EFR), in terms of traffic blocking ratio, traffic blocking fairness, average traffic logical hop counts, and global network resource utilization. It has been proved that the DWFA is a simple, comprehensive, and practical scheme of integrated routing in optical Internet for service providers.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.22-30
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• 2022

The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

• Journal of IKEEE
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• v.11 no.4
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• pp.348-357
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• 2007

Due to the improved performance and cost of personal mobile devices and rapid progress of wireless communication technology, the number of users who utilize these devices is increasing. This trend requires various types of services be available to users. So far, there have been many solutions provided for the shortest path problem. But, technologies which can offer various recommendation services to user depending on user’s current location are focused on Euclidean spaces rather than road network. Thus, in this paper, we extend the previous work to satisfy this requirement on road network database. Our proposed scheme requires pre-computation for the efficient query processing. In the preprocessing step, we first partition the input road network into a fixed number of Voronoi polygons and then pre-compute routing information for each polygon. In the meantime, we select the number of Voronoi polygons in proposition to the scale of road network. Through this selection, the required size of pre-computation is linearly increasing to the size of road network. Using this pre-computated information, we can process queries more quickly. Through experiments, we have shown that our proposed scheme can achieve excellent performance in terms of scheduling time and the number of visited nodes.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.3
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• pp.254-263
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• 2012

The survivability of warship is assessed by susceptibility, vulnerability and recoverability. Essentially, a vulnerability assessment is a measure of the effectiveness of a warship to resist hostile weapon effects. Considering the shot line and its penetration effect on the warship, present study introduces the procedural aspects of vulnerability assessments of warship. Present study also considers the prediction of penetration damage to a target caused by the impact of projectiles. It reflects the interaction between the weapon and the target from a perspective of vulnerable area method and COVART model. The shotline and tracing calculation have been directly integrated into the vulnerability assessment method based on the penetration equation empirically obtained. A simplified geometric description of the desired target and specification of a threat type is incorporated with the penetration effect. This study describes how to expand the vulnerable area assessment method to the penetration effect. Finally, an example shows that the proposed method can provide the vulnerability parameters of the warship or its component under threat being hit through tracing the shotline path thereby enabling the vulnerability calculation. In addition, the proposed procedure enabling the calculation of the component's multi-hit vulnerability introduces a propulsion system in dealing with redundant Non-overlapping components.