• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.7
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• pp.747-756
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• 2014

In this paper, we propose a path loss model with the multiple antennas using diversity effect. Currently wireless communication systems use the multiple antennas in order to improve the channel capacity or diversity gain. However, until recently, many researches on path loss model only consider geographical environment between the transmitter and the receiver. There is no study about path loss model considering diversity effect. Nowaday wireless communication use the multiple antennas and we in common find examples using diversity scheme that is method in order to enhance a channel capacity. Moreover we anticipate that it work harder in future researches. But in this communication system, path loss model isn't established that predict strength of received signal. So, in order to predict strength of received signal, we take changing SNR by diversity gain. When exceeding the number of antennas of receiver are 7 in proposed model, diversity effect is saturated. Therefore we consider the number of antenna of receiver until 10. We find RMSE between proposed model and value of calculation is 1. We calculate the diversity gain by conventional BER curve. Proposed model can predict loss of received signal in system using multiple antennas.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.2
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• pp.377-386
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• 2016

As the number of malware has been increased, it is necessary to analyze malware rapidly against cyber attack. Additionally, Dynamic malware analysis has been widely studied to overcome the limitation of static analysis such as packing and obfuscation, but still has a problem of exploring multiple execution path. Previous works for exploring multiple execution path have several problems that it requires much time to analyze and resource for preparing analysis environment. In this paper, we proposed efficient exploring approach for multiple execution path in a single analysis environment by pipelining processes and showed the improvement of speed by 29% in 2-core and 70% in 4-core through experiment.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.4
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• pp.1-8
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• 2014

In order to cope with shadow areas and to extend cell coverage, relay-assisted wireless communication systems have been widely studied. In this paper, we propose a space-frequency(SF) block coded orthogonal frequency division multiple access(OFDMA) transmission system in a relaying multi-path shadow area. The receiving performance of mobile station in a shadow area can be improved by applying SF block code to the recovered signals of multiple relays before re-transmitting them. The simulation result shows that the proposed SF block coded OFDMA transmission system considerably outperforms the conventional single-path OFDMA transmission system.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.2
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• pp.172-178
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• 2010

The multiple regression analysis and path analysis in each dominant area of noise source are conducted to analyze the relationship between dependent variables like annoyance and independent ones such as noise and non-noise factors. The multiple regression analysis shows that impact of noise factors is the highest to annoyance in dominant areas of road traffic and railway noise. Meanwhile, impact of non-noise factors such as sensitivity and satisfaction of environment on annoyance is also high in these areas. The path analysis result for multivariate analysis between various independent and dependent variables is similar to that of the multiple regression analysis. However, noise factor is the greatest factor influent on annoyance in the dominant areas of the combined noise, and relationship between annoyance and sensitivity is the highest in combined area exposed to road traffic noise and railway noise.

• Journal of Communications and Networks
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• v.11 no.6
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• pp.589-598
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• 2009

In wireless sensor networks, a node that reports information gathered from adjacent assets should relay packets appropriately so that its location context is kept private, and thereby helping ensure the security of the assets that are being monitored. Unfortunately, existing routing methods that counter the local eavesdropping-based tracing deal with a single asset, and most of them suffer from the packet-delivery latency as they prefer to take a separate path of many hops for each packet being sent. In this paper, we propose a routing method, greedy perimeter stateless routing-based source-location privacy with crew size w (GSLP-w), that enhances location privacy of the packet-originating node (i.e., active source) in the presence of multiple assets. GSLP-w is a hybrid method, in which the next-hop node is chosen in one of four modes, namely greedy, random, perimeter, and retreat modes. Random forwarding brings the path diversity, while greedy forwarding refrains from taking an excessively long path and leads to convergence to the destination. Perimeter routing makes detours that avoid the nodes near assets so that they cannot be located by an adversary tracing up the route path. We study the performance of GSLP-w with respect to crew size w (the number of packets being sent per path) and the number of sources. GSLP-w is compared with phantom routing-single path (PR-SP), which is a notable routing method for source-location privacy and our simulation results show that improvements from the point of the ratio of safety period and delivery latency become significant as the number of source nodes increases.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.181-188
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• 2019

The migration path of a multiple-generation technology that occurs during a technological substitution by a new technology is important to understanding the phenomenon of technological substitution, and can contribute to understanding the process of technological innovation. This research defines the concept of migration path and develops a model of the types of migration paths by multiple dimensions (actor, generation, and time) in a multiple-generation technology. Based on a literature review and tracking of migration paths according to multiple dimensions, the definitions and types of migration paths were provided, and the accuracy of the model was verified based on a case study of the semiconductor industry. The migration paths of suppliers are modeled with three types (switching, leapfrogging, and new entrance paths), and the migration paths of customers are modeled with four types (switching, leapfrogging, new entrance, and diffusion paths) in a multiple-generation technology. This research will be useful for understanding the migration paths in the phenomenon of technological substitution, and can be applied to other industries in addition to the semiconductor industry, including various actors. In addition, suppliers and customers can understand technological substitution and can establish a technology strategy against their competitors.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.569-571
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• 1995

This paper compares the simulated annealing and the Hopfield neural network method for an optimal routing in a multistage interconnection network(MIN). The MIN provides a multiple number of paths for ATM cells to avoid cell conflict. Exhaustive search always finds the optimal path, but with heavy computation. Although greedy method sets up a path quickly, the path found need not be optimal. The simulated annealing can find an sub optimal path in time comparable with the greedy method.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.1-9
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• 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 Korean Operations Research and Management Science Society
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• v.25 no.4
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• pp.97-109
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• 2000

This work proposes a neural network approach to solve vehicle routing problems which have diverse application areas such as vehicle routing and robot programming. In solving these problems, classical mathematical approaches have many difficulties. In particular, it is almost impossible to implement a real-time vehicle routing with multiple vehicles. Recently, many researchers proposed methods to overcome the limitation by adopting heuristic algorithms, genetic algorithms, neural network techniques and others. The most basic model for path planning is the Travelling Salesman Problem(TSP) for a minimum distance path. We extend this for a problem with dynamic upcoming of new positions with multiple vehicles. In this paper, we propose an algorithm based on SOM(Self-Organization Map) to obtain a sub-optimal solution for a real-time vehicle routing problem. We develope a model of a generalized multiple TSP and suggest and efficient solving procedure.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.49-54
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• 2017

Pathfinding for pedestrians provided by various navigation programs is based on a shortest path search algorithm. There is no big difference in their guide results, which makes the path quality more important. Multiple criteria should be included in the search cost to calculate the path quality, which is called a multi-criteria pathfinding. In this paper we propose a user adaptive pathfinding algorithm in which the cost function for a multi-criteria pathfinding is defined as a weighted sum of multiple criteria and the weights are learned automatically by Perceptron learning. Weight learning is implemented in two ways: short-term weight learning that reflects weight changes in real time as the user moves and long-term weight learning that updates the weights by the average value of the entire path after completing the movement. We use the weight update method with momentum for long-term weight learning, so that learning speed is improved and the learned weight can be stabilized. The proposed method is implemented as an app and is applied to various movement situations. The results show that customized pathfinding based on user preference can be obtained.