• Journal of Information Processing Systems
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• v.13 no.2
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• pp.360-369
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• 2017

In this paper, a new iterative algorithm for reconstructing block sparse signals, called block backtracking-based adaptive orthogonal matching pursuit (BBAOMP) method, is proposed. Compared with existing methods, the BBAOMP method can bring some flexibility between computational complexity and reconstruction property by using the backtracking step. Another outstanding advantage of BBAOMP algorithm is that it can be done without another information of signal sparsity. Several experiments illustrate that the BBAOMP algorithm occupies certain superiority in terms of probability of exact reconstruction and running time.

• The Journal of Engineering Research
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• v.6 no.2
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• pp.11-22
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• 2004

A distributed constraint satisfaction problem (distributed CSP) is a constraint satisfaction problem(CSP) in which variables and constraints are distributed among multiple automated agents. ACSP is a problem to find a consistent assignment of values to variables. Even though the definition of a CSP is very simple, a surprisingly wide variety of AI problems can be formalized as CSPs. Similarly, various application problems in DAI (Distributed AI) that are concerned with finding a consistent combination of agent actions can be formalized as distributed CAPs. In recent years, many new backtracking algorithms for solving distributed CSPs have been proposed. But most of all, they have common drawbacks that the algorithm assumes the priority of agents is static. In this thesis, we establish a basic algorithm for solving distributed CSPs called dynamic priority search algorithm that is more efficient than common backtracking algorithms in which the priority order is static. In this algorithm, agents act asynchronously and concurrently based on their local knowledge without any global control, and have a flexible organization, in which the hierarchical order is changed dynamically, while the completeness of the algorithm is guaranteed. And we showed that the dynamic priority search algorithm can solve various problems, such as the distributed 200-queens problem, the distributed graph-coloring problem that common backtracking algorithm fails to solve within a reasonable amount of time. The experimental results on example problems show that this algorithm is by far more efficient than the backtracking algorithm, in which the priority order is static. The priority order represents a hierarchy of agent authority, i.e., the priority of decision-making. Therefore, these results imply that a flexible agent organization, in which the hierarchical order is changed dynamically, actually performs better than an organization in which the hierarchical order is static and rigid. Furthermore, we describe that the agent can be available to hold multiple variables in the searching scheme.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.8
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• pp.1281-1286
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• 2003

A line search algorithm to increase a convergence in Newton's method is developed and applied to nonlinear finite element analysis. The algorithm is based on the slack line search theory which is an efficient algorithm to determine initial acceleration coefficient, variable backtracking algorithm proposed by some researchers, and convergence criterion based on residual norm. Also, it is capable of avoiding exceptional diverging conditions. Developed program is tested in metal forming simulation such as forging and ring rolling. Numerical result shows the validity of the algorithm for a highly nonlinear system .

• The KIPS Transactions:PartA
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• v.18A no.3
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• pp.115-122
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• 2011

It is very hard to obtain a general algorithm for solution of all the constraint satisfaction optimization problems. However, if the whole problem is separated into subproblems by characteristics of decision variables, we can assume that an algorithm to obtain solutions of these subproblems is easier. Under the assumption, we propose a problem classifying rule which subdivide the whole problem, and develop backtracking algorithms fit for these subproblems. One of the methods of finding a quick solution is efficiently arrange for any order of the search tree nodes. We choose the cluster head positioning problem in wireless sensor networks in which static characteristics is dominant and interference minimization problem of RFID readers that has hybrid mixture of static and dynamic characteristics. For these problems, we develop optimal variable ordering algorithms, and compare with the conventional methods. As a result of classifying the problem into subproblems, we can realize a backtracking framework for systematic search. We also have shown that developed backtracking algorithms have good performance in their quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.2
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• pp.629-648
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• 2012

Given a video stream delivering system deployed on a multicast tree, which is embedded in a multi-channel multi-radio wireless mesh network, our problem is concerned about how to allocate interference-free channels to tree links and maximize the number of serviced mesh clients at the same time. In this paper, we propose a channel allocation heuristic algorithm based on best-first search and backtracking techniques. The experimental results show that our BFB based CA algorithm outperforms previous methods such as DFS and BFS based CA methods. This superiority is due to the backtracking technique used in BFB approach. It allows previous channel-allocated links to have feasibility to select the other eligible channels when no conflict-free channel can be found for the current link during the CA process. In addition to that, we also propose a tree refinement method to enhance the quality of channel-allocated trees by adding uncovered destinations at the cost of deletion of some covered destinations. Our aim of this refinement is to increase the number of serviced mesh clients. According to our simulation results, it is proved to be an effective method for improving multicast trees produced by BFB, BFS and DFS CA algorithms.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.159-167
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• 2023

Objective: • To detect black hole and warm hole attacks in wireless sensor networks. • To give a solution for energy depletion and security breach in wireless sensor networks. • To address the security problem using strategic decision support system. Methods: The proposed stackelberg game is used to make the spirited relations between multi leaders and multi followers. In this game, all cluster heads are acts as leaders, whereas agent nodes are acts as followers. The game is initially modeled as Quadratic Programming and also use backtracking search optimization algorithm for getting threshold value to determine the optimal strategies of both defender and attacker. Findings: To find optimal payoffs of multi leaders and multi followers are based on their utility functions. The attacks are easily detected based on some defined rules and optimum results of the game. Finally, the simulations are executed in matlab and the impacts of detection of black hole and warm hole attacks are also presented in this paper. Novelty: The novelty of this study is to considering the stackelberg game with backtracking search optimization algorithm (BSOA). BSOA is based on iterative process which tries to minimize the objective function. Thus we obtain the better optimization results than the earlier approaches.

• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.171-179
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• 2005

This paper presents the algorithm using fuzzy inference that preestimates each link speed changed by different kinds of road situations. The elements we are considered are time zone, rainfall probability information and lane control information. This paper is consists of three parts. First of all we set up the fuzzy variables, and preestimate link speed changed by various road situations. For this process, we build the membership functions for each fuzzy variable and establish the fuzzy inference relations to find how fuzzy variables influence on link speed. Second, using backtracking method, we search the shortest route influenced by link speed changed by fuzzy inference. Third, we apply this algorithm to hypothetical network and find the shortest path. As a result, it is shown that this algorithm choose appropriate roundabout path according to the changing road situations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.155-161
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• 2017

This paper suggests polynomial time solution algorithm for Sudoku puzzle problem. This problem has been known NP (non-deterministic polynomial time)-complete. The proposed algorithm set the initial value of blank cells to value range of [$1,2,{\cdots},9$]. Then the candidate set values in blank cells deleted by preassigned clue in row, column, and block. We apply the basic rules of Stuart, and proposes two additional rules. Finally we apply binary backtracking(BBT) technique. For the experimental Sudoku puzzle with various categories of solution, the BBT algorithm can be obtain all of given Sudoku puzzle regardless of any types of solution.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.136-145
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• 1993

This paper considers a reliability problem as a special type of flow problem and presents an algorithm to evaluate the exact 2-terminal reliability of networks by using a backtracking technique. It employs a polygon-to-chain reduction in addition to series and parallel reduction techniques to reduce execution time. In comparisons, it presents a much better performance than other algorithms known to us. We also propose a methodology to apply the algorithm for approximation of the system reliability.

• Journal of the Korea Society of Computer and Information
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• v.18 no.2
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• pp.69-76
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• 2013

Reader-to-reader interference in RFID system is occurred due to the use of limited number of frequencies, and this is the main cause of read rate reduction in the passive RFID tags. Therefore, in order to maximize the read rate under the circumstances of limited frequency resources, it is necessary to minimize the frequency interference among RFID readers. This paper presents a hybrid FDM/TDM constraint satisfaction problem models for frequency interference minimization problems of the RFID readers, and assigns optimal channels to each readers using conventional backtracking search algorithms. A depth first search based on backtracking are accomplished to find solutions of constraint satisfaction problems. At this moment, a variable ordering algorithm is very important to find a solution quickly. Variable ordering algorithms applied in the experiment are known as efficient in the graph coloring. To justify the performance of the proposed constraint satisfaction problem model, optimal channels for each readers in the passive UHF RFID system are allocated by using computer simulation satisfying various interference constraints.