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Conference on Image and Signal Processing for Remote Sensing XXII

作者： Zhang, Haiying Lin, Yonggui Xiao, Fangxiong Xiamen Univ Software Sch Xiamen 361005 Peoples R China Guangxi Univ Finance & Econ Sch Informat & Stat Guangxi 530003 Peoples R China Jinling Inst Technol Sch Software Engn Nanjing 211169 Jiangsu Peoples R China

ISBN: (数字)9781510604131

ISBN: (纸本)9781510604124;9781510604131

The series problem of infrared small target detection in heavy clutter is a challenging work in active vision. During different imaging environments the size and gray intensity of target will keep changing which lead to unstable detection. Focus on mining more robust feature of small targets and following the sequential detection framework, we propose a novel research scheme based on density-based clustering and backtracking strategy in this paper. First, point of interest is extracted by the speeded up robust feature (SURF) detector for its better performance in digging features invariant to uniform scaling, orientation and illumination changes. Second, due to the local aggregation property of target trajectory in space, a new proposed density-based clustering method is introduced to segment the target trajectory, so that the target detection problem is transformed into the extract the target trajectory. Then, In order to keep the integral and independence of the trace as much as possible, two factors: percent and are exploited to help deciding the clustering granularity. Later, the backtracking strategy is adopted to search for the target trajectory with pruning function on the basis of the consistence and continuity of the short-time target trajectory in temporal-spatial. Extended experiments show the validity of our method. Compared with the data association methods executed on the huge candidate trajectory space, the time-consuming is reduced obviously. Additional, the feature detection is more stable for the use of SURF and the false alarm suppression rate is superior to most baseline and state-of-arts methods.

关键词： infrared small target SURF density-based clustering backtracking algorithm

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An Online Incremental Scheduling and backtracking Mechanism for Time-Sensitive Networking

An Online Incremental Scheduling and Backtracking Mechanism ...

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9th International Conference on Signal and Image Processing (ICSIP)

作者： Guo, Haoyi Pan, Weiqiang Chen, Zhuoxing Wang, Meng Lu, Yiqin Qin, Jiancheng South China Univ Technol Sch Elect & Informat Engn Guangzhou Peoples R China

ISBN: (纸本)9798350350920

With the growth of real-time application scenarios, the deployment of Time-Sensitive Networking (TSN) in dynamic scenarios has attracted more and more attention. However, since information such as the period, size, and arrival time of a new flow is uncertain, the previous scheduling results will seriously reduce the performance of subsequent scheduling. Most online scheduling methods will easily reach the bottleneck of flow scheduling, resulting in a decrease in schedulability. This paper analyzes the combinability of Time-Triggered (TT) flows and proposes the Possibility of Collision (PoC) as a measure of the degree of collisions on a link. In addition, we design a PoC-aware incremental scheduling and backtracking (PA/ISAB) mechanism to realize per-flow online deployment. The backtracking mechanism migrates the configured flows on the link based on the PoC, thereby alleviating the scheduling bottleneck while realizing the deployment of new flows. Meanwhile, we establish a PoC-aware pre-routing (PAPR) algorithm to improve schedulability. The evaluations verify that PA/ISAB can effectively reduce the execution time and reconfiguration overhead while ensuring high schedulability, thus realizing fast online deployment of the network.

关键词： Time-Sensitive Networking Online Incremental Scheduling backtracking algorithm

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A group-based search for solutions of the n-queens problem

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DISCRETE MATHEMATICS 2007年第21期307卷 2535-2551页

作者： Engelhardt, Matthias R. Unterreichenbacherstr 9 D-90455 Nurnberg Germany

The n-queens problem is a well-known problem in mathematics, yet a full search for n-queens solutions has been tackled until now using only simple algorithms (with the exception of the Rivin-Zabih algorithm). In this article, we discuss optimizations that mainly rely on group actions on the set of n-queens solutions. Most of our arguments deal with the case of toroidal queens;at the end, the application to the regular n-queens problem is discussed, and also the Rivin-Zabih algorithm. (C) 2007 Elsevier B.V. All rights reserved.

关键词： n-Queens problem finite group action complete enumeration backtracking algorithm

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Feature selection with test cost constraint

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INTERNATIONAL JOURNAL OF APPROXIMATE REASONING 2014年第1期55卷 167-179页

作者： Min, Fan Hu, Qinghua Zhu, William Zhangzhou Normal Univ Lab Granular Comp Zhangzhou 363000 Peoples R China Tianjin Univ Tianjin 300072 Peoples R China

Feature selection is an important preprocessing step in machine learning and data mining. In real-world applications, costs, including money, time and other resources, are required to acquire the features. In some cases, there is a test cost constraint due to limited resources. We shall deliberately select an informative and cheap feature subset for classification. This paper proposes the feature selection with test cost constraint problem for this issue. The new problem has a simple form while described as a constraint satisfaction problem (CSP). backtracking is a general algorithm for CSP, and it is efficient in solving the new problem on medium-sized data. As the backtracking algorithm is not scalable to large datasets, a heuristic algorithm is also developed. Experimental results show that the heuristic algorithm can find the optimal solution in most cases. We also redefine some existing feature selection problems in rough sets, especially in decision-theoretic rough sets, from the viewpoint of CSP. These new definitions provide insight to some new research directions. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Feature selection Cost-sensitive learning Constraint satisfaction problem backtracking algorithm Heuristic algorithm Decision-theoretic rough sets

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Process configuration based on generative constraint satisfaction problem

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JOURNAL OF INTELLIGENT MANUFACTURING 2017年第4期28卷 945-957页

作者： Wang, Lin Zhong, Shi-Sheng Zhang, Yong-Jian Harbin Inst Technol Sch Mechatron Engn 92 West Dazhi St Harbin 150001 Peoples R China Harbin Inst Technol Sch Naval Architecture & Ocean Engn 2 Wenhuaxi Rd Weihai 264209 Peoples R China

Product configuration, a widely used technology in product family design, is one of the most effective technologies of mass customization strategies which have been deployed by many companies for years. Nevertheless, the mass customization needs to cover the management of the whole customizable product cycle. In order to assist the development of mass customization, it is essential to extend the configuration technology to product family process planning, which is the technological essence of process configuration. In this article the process configuration task is confirmed based on the analysis of characteristics of process planning. Compared with the solving scheme of product configuration, the process configuration is then mapped into a generative constraint satisfaction problem (GCSP), and the variables and constraints of the process configuration GCSP model are identified respectively. An algorithm based on backtracking algorithm is introduced to complete the process configuration. Finally, an experiment on machining process configuration for satellite plate panel verifies the validity of our algorithm.

关键词： Process configuration Generative constraints satisfaction problem Variable modeling Constraint identification backtracking algorithm

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2 algorithmS FOR DETERMINING A MINIMUM INDEPENDENT DOMINATING SET

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INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 1984年第3-4期15卷 213-229页

作者： LOUKAKIS, E University of Thessaloniki School of Engineering Thessaloniki Greece

The problem of determining a minimum independent dominating set is fundamental to both the theory and applications of graphs. Computationally it belongs to the class of hard combinatorial optimization problems known as NP-hard. In this paper, we develop a backtracking algorithm and a dynamic programming algorithm to determine a minimum independent dominating set. Computational experience with the backtracking algorithm on more than 1000 randomly generated graphs ranging from 100 to 200 vertices and from 10% to 60% densities has shown that the algorithm is effective. © 1984, Taylor & Francis Group, LLC. All rights reserved.

关键词： backtracking algorithm dynamic programming algorithm Minimum independent dominating set NP-hard

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Classification of 6-(14,7,4) designs with nontrivial automorphism groups

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JOURNAL OF COMBINATORIAL DESIGNS 2002年第3期10卷 180-194页

作者： Khosrovshahi, GB Mohammad-Noori, M Rezaie, BT Inst Studies Theoret Phys & Math Tehran Iran Univ Tehran Dept Math Tehran Iran

In this paper, we introduce some intersection matrices for t-designs. Utilizing these matrices together with a modified version of a backtracking algorithm, we classify all 6-(14,7,4) and 5-(13,6,4) designs with nontr... 详细信息

关键词： t-design halving automorphism group backtracking algorithm interaction numbers

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Scale invariant SURF detector and automatic clustering segmentation for infrared small targets detection

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INFRARED PHYSICS & TECHNOLOGY 2017年 83卷 7-16页

作者： Zhang, Haiying Bai, Jiaojiao Li, Zhengjie Liu, Yan Liu, Kunhong Xiamen Univ Software Sch Xiamen 361005 Peoples R China

The detection and discrimination of infrared small dim targets is a challenge in automatic target recognition (ATR), because there is no salient information of size, shape and texture. Many researchers focus on mining more discriminative information of targets in temporal-spatial. However, such information may not be available with the change of imaging environments, and the targets size and intensity keep changing in different imaging distance. So in this paper, we propose a novel research scheme using density based clustering and backtracking strategy. In this scheme, the speeded up robust feature (SURF) detector is applied to capture candidate targets in single frame at first. And then, these points are mapped into one frame, so that target traces form a local aggregation pattern. In order to isolate the targets from noises, a newly proposed density-based clustering algorithm, fast search and find of density peak (FSFDP for short), is employed to cluster targets by the spatial intensive distribution. Two important factors of the algorithm, percent and gamma, are exploited fully to determine the clustering scale automatically, so as to extract the trace with highest clutter suppression ratio. And at the final step, a backtracking algorithm is designed to detect and discriminate target trace as well as to eliminate clutter. The consistence and continuity of the short-time target trajectory in temporal-spatial is incorporated into the bounding function to speed up the pruning. Compared with several state-of-arts methods, our algorithm is more effective for the dim targets with lower signal-to clutter ratio (SCR). Furthermore, it avoids constructing the candidate target trajectory searching space, so its time complexity is limited to a polynomial level. The extensive experimental results show that it has superior performance in probability of detection (Pd) and false alarm suppressing rate aiming at variety of complex backgrounds. (C) 2017 Elsevier B.V. All rights re

关键词： Small target Sequential detection SURF Clustering backtracking algorithm

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On E(s²)-optimal and minimax-optimal supersaturated designs with 20 rows and 76 columns

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JOURNAL OF COMBINATORIAL DESIGNS 2018年第7期26卷 344-355页

作者： Morales, Luis B. Bulutoglu, Dursun A. Univ Nacl Autonoma Mexico IIMAS Mexico City 04510 DF Mexico US Air Force Inst Technol Wright Patterson AFB OH 45433 USA

We derive a previously unknown lower bound of 41 for the frequency of s max =8 of an E(s(2))-optimal and minimax-optimal supersaturated design (SSD) with 20 rows and 76 columns. This is accomplished by an exhaustive computer search that uses the combinatorial properties of resolvable 2 - (20, 10, 36) designs and the parallel class intersection pattern method. We also classify all nonisomorphic E(s(2))-optimal 4-circulant SSDs with 20 rows and s(max) = 8.

关键词： backtracking algorithm maximum clique parallel class intersection pattern method resolvable balanced incomplete block designs

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Phase balancing algorithms

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ELECTRIC POWER SYSTEMS RESEARCH 2013年第Mar.期96卷 218-224页

作者： Wang, Kai Skiena, Steven Robertazzi, Thomas G. SUNY Stony Brook Dept Elect Engn Stony Brook NY 11790 USA SUNY Stony Brook Dept Comp Sci Stony Brook NY 11790 USA

Unbalanced loads on feeders increase power system investment and operating costs. Single-phase lateral loads phase swapping is one of the popular methods to balance such systems. In this paper, six algorithms for phase balancing are studied, including a genetic algorithm, simulated annealing, a greedy algorithm, exhaustive search, backtracking algorithm and a dynamic programming algorithm. The novel dynamic programming algorithm in particular produces optimal solutions for this NP-complete problem efficiently. (c) 2012 Elsevier B.V. All rights reserved.

关键词： Phase balancing Dynamic programming Genetic algorithm Simulated annealing Greedy algorithm backtracking algorithm

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