• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.710-715
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• 2016

Due to its simplicity and high reliability, the box-counting(BC) method is one of the most frequently used techniques to estimate the fractal dimensions of a binary image with a self-similarity property. The fractal calculation requires data sampling that determines the size of boxes to be sampled from the given image and directly affects the accuracy of the fractal dimension estimation. There are three non-overlapping regular grid methods: geometric-step method, arithmetic-step method and divisor-step method. These methods have some drawbacks when the image size M becomes large. This paper presents a BC algorithm for enhancing the accuracy of the fractal dimension estimation based on a new sampling method. Instead of using the geometric-step method, the new sampling method, called the coverage ratio-step method, selects the number of steps according to the coverage ratio. A set of experiments using well-known fractal images showed that the proposed method outperforms the existing BC method and the triangular BC method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.17-24
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• 2006

We consider the sensor location problem (SLP) on a given sensor field. We present the sensor field as grid of points. There are several types of sensors which have different detection ranges and costs. If a sensor is placed in some point, the points inside of its detection range can be covered. The coverage ratio decreases with distance. The problem we consider in this thesis is called multiple-type differential coverage sensor location problem (MDSLP). MDSLP is more realistic than SLP. The coverage quantities of points are different with their distance form sensor location in MDSLP. The objective of MDSLP is to minimize total sensor costs while covering every sensor field. This problem is known as NP-hard. We propose a new integer programming formulation of the problem. In comparison with the previous models, the new model has a smaller number of constraints and variables. This problem has symmetric structure in its solutions. This group is used for pruning in the branch-and-bound tree. We solved this problem by branch-and-cut(B&C) approach. We tested our algorithm on about 60 instances with varying sizes.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.8-19
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• 2023

This paper presents advancement in multi- unmanned aerial vehicle (UAV) cooperative area surveillance, focusing on optimizing UAV route planning through the application of genetic algorithms. Addressing the complexities of comprehensive coverage, two real-time dynamic path planning methods are introduced, leveraging genetic algorithms to enhance surveillance efficiency while accounting for flight constraints. These methodologies adapt multi-UAV routes by encoding turning angles and employing coverage-driven fitness functions, facilitating real-time monitoring optimization. The paper introduces a novel path planning model for scenarios where UAVs navigate collaboratively without predetermined destinations during regional surveillance. Empirical evaluations confirm the effectiveness of the proposed methods, showcasing improved coverage and heightened efficiency in multi-UAV path planning. Furthermore, we introduce innovative optimization strategies, (Foresightedness and Multi-step) offering distinct trade-offs between solution quality and computational time. This research contributes innovative solutions to the intricate challenges of cooperative area surveillance, showcasing the transformative potential of genetic algorithms in multi-UAV technology. By enabling smarter route planning, these methods underscore the feasibility of more efficient, adaptable, and intelligent cooperative surveillance missions.

• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.141-148
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• 2013

This paper proposes an EMS algorithm designed to determine the optimal locations for Emergency Medical Service centers that both satisfy the maximum ambulance response time T in case of emergency and cover the largest possible number of residents given a limited number of emergency medical services p in a city divided into different zones. This methodology generally applies integer programming whereby cases are categorized into 1 if the distance between two zones is within the response time and 0 if not and subsequently employs linear programming to obtain the optimal solution. In this paper, where p=1, the algorithm determines a node with maximum coverage. In cases where $p{\geq}2$, the algorithm selects top 5 nodes with maximum coverage. Based on inclusion-exclusion method, this selection entails repeatedly selecting a node with the maximum coverage when nodes with lower numbers are deleted. Among these 5 selected nodes, the algorithm selects a single node set with the greatest coverage and thereby as the optimal EMS location. The proposed algorithm has proven to accurately and expeditiously obtain the optimal solutions for 12-node network, 21-node network, and Swain's 55-node network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.12
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• pp.2311-2318
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• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. Accurate predictions of software release times, and estimation of the reliability and availability of a software product require Release times of a critical element of the software testing process : test coverage. This model called Enhanced non-homogeneous Poission process(ENHPP). In this paper, exponential coverage and S-shaped model was reviewed, proposes the Kappa coverage model, which make out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics and Kolmogorov distance, for the sake of efficient model, was employed. Numerical examples using real data set for the sake of proposing Kappa coverage model was employed. This analysis of failure data compared with the Kappaa coverage model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.137-140
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• 2000

In this paper, we have proposed an efficient test generation method for asynchronous circuits. The test generation is based on specification level, especially on Signal Transition Graph(STG)〔1〕 which is a kind of specification method for asynchronous circuits. To conduct a high-level test generation, we have defined a high-level fault model, called single State Transition Fault(STF) model on STG and proposed a test generation algorithm for STF model. The effectiveness of the proposed fault model and its test generation algorithm is shown by experimental results on a set of benchmarks given in the form of STG. Experimental results show that the generated test for the proposed fault model achieves high fault coverage over single input stuck-at fault model with low cost. We have also proposed extended STF model with additional gate-level information to achieve higher fault coverage in cost of longer execution time.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.7
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• pp.73-80
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• 2009

This paper describes a path planning algorithm, which is the minimal turning path based on the shape and size of the cell to clean up the whole area with two cleaning robots. Our method divides the whole cleaning area with each cell by cellular decomposition, and then provides some path plans among of the robots to reduce the rate of energy consumption and cleaning time of it. In addition we suggest how to plan between the robots especially when they are cleaning in the same cell. Finally simulation results demonstrate the effectiveness of the algorithm in an unknown area with multiple robots. And then we compare the performance index of two algorithms such as total of turn, total of time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.3
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• pp.477-493
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• 2011

The IEEE 802.16 mobile multi-hop relay (MMR) task group 'j' (TGj) has introduced the multi-hop relaying concept in the IEEE 802.16 Wireless MAN, wherein a relay station (RS) is employed to improve network coverage and capacity. Several RSs can be deployed between a base station and mobile stations, and configured to form a tree-like multi-hop topology. In such architecture, we consider the problem of a path selection through which the mobile station in and outside the coverage can communicate with the base station. In this paper, we propose a new path selection algorithm that ensures more efficient distribution of resources such as bandwidth among the relaying nodes for improving the overall performance of the network. Performance of our proposed scheme is compared with the path selection algorithms based on loss rate and the shortest path algorithm. Based on the simulation results using ns-2, we show our proposal significantly improves the performance on throughput, latency and bandwidth consumption.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1342-1350
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• 1999

A new design procedure for micro cellular coverage prediction is presented here on this paper, which contains a new propagation analysis algorithm based on processing of vector data representing roads and buildings which mainly affect the propagation phenomena in micro-cell environments. The propagation analysis algorithm presented here has been developed to aim at the practical application for micro-cellular systems such as PCS or CE-2. As all the vectors used here are of closed poly lines, i.e., polygons, a simplified ray path search technique can be developed not only to determine if the calculation points are on the road polygons and but also to calculate the amount of blockage by buildings. The result shows a capability of predicting path loss with an RMS error of 5dB or lower.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8A
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• pp.691-701
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• 2011

In rotatable directional sensor networks, maximizing network lifetime while covering all the targets and forwarding the sensed data to the sink is a challenge problem. In this paper, we address the Maximum Directional Cover Tree (MDCT) problem of organizing the directional sensors into a group of non-disjoint subsets to extend the network lifetime. Each subset in which the directional sensors cover all the targets and forward the sensed data to the sink is activated at one time. For the MDCT problem, we first present an energy consumption model which mainly takes into account the energy consumption for rotation work. We also develop the Directional Coverage and Connectivity (DCC)-greedy algorithm to solve the MDCT problem. To evaluate the algorithm, we conduct simulations and show that it can extend the network lifetime.