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Exploiting relay nodes for maximizing wireless underground sensor network lifetime

APPLIED INTELLIGENCE 2020年第12期50卷 4568-4585页

作者： Tam, Nguyen Thi Dung, Dinh Anh Hung, Tran Huy Binh, Huynh Thi Thanh Yu, Shui Hanoi Univ Sci & Technol Hanoi Vietnam VNU Univ Sci Hanoi Vietnam Univ Technol Sydney Ultimo NSW 2007 Australia

A major challenge in wireless underground sensor networks is the signal attenuation originated from multi-environment transmission between underground sensor nodes and the above-ground base station. To overcome this issue, an efficient approach is deploying a set of relay nodes aboveground, thereby reducing transmission loss by shortening transmitting distance. However, this introduces several new challenges, including load balancing and transmission loss minimization. This paper tackles the problem of deploying relay nodes to reduce transmission loss under a load balancing constraint by proposing two approximation algorithms. The first algorithm is inspired by Beam Search, combined with a new selection scheme based on Boltzmann distribution. The second algorithm aims to further improve the solutions obtained by the former by reducing the transmission loss. We observe that we can find an optimal assignment between sensor nodes and a set of the chosen relay in polynomial time by reformulating the part of the problem as a bipartite matching problem with minimum cost. Experimental results indicate that the proposed methods perform better than the other existing ones in most of our test instances while reducing the execution time.

关键词： Wireless underground sensor network Relay nodes placement Load balancing Network lifetime Beam search hopcroft-karp algorithm

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MINIMUM COVERING RUN EXPRESSION OF DOCUMENT IMAGES BASED ON MATCHING OF BIPARTITE GRAPH

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 1993年第4期E76D卷 462-469页

作者： CHINVEERAPHAN, S DOUNIWA, K SATO, M Tokyo Inst of Technology Yokohama Japan

An efficient technique for expressing document image is required as part of a unified approach to document image processing. This paper presents a new method, Minimum Covering Run (MCR), for expressing binary images. The name being adapted from horizontal or vertical run representation. The proposed technique uses some horizontal and vertical runs together to represent binary images in which the total number of representative runs is minimized. Considering the characteristic of above run types precisely, it is shown that horizontal and vertical runs of any binary image could be thought of as partite sets of a bipartite graph. Consequently, the MCR expression that corresponds to the construction of one of the most interesting problems in graphs;i.e., maximum matching, is analogously found by using an algorithm which solves this problem in a corresponding graph. The most efficient algorithm (4) takes at most O(n5/2) computations for solving the problem where n is the sum of cardinalities of both partite sets. However, some patterns in images like tables or line drawings, generally, have a large number of runs representing them which results in a long processing time. Therefore, we provide the Rectangular Segment Analysis (RSA) as a pre-processing to define runs representing such patterns beforehand. We also show that horizontal and vertical covering parts of the proposed expression are able to represent stroke components of characters in document images. As an implementation, an efficient algorithm including arrangement for run data structure of the MCR expression is presented. The experimental results show the possibility of stroke extraction of characters in document images. As an application, some patterns such as tables can be extracted from document images.

关键词： MINIMUM COVERING RUN (MCR) EXPRESSION RUN BIPARTITE GRAPH ADJACENCY MATRIX MINIMUM VERTEX-COVERING MAXIMUM MATCHING hopcroft-karp algorithm

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Measuring empirical discrepancy in image segmentation results

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IET COMPUTER VISION 2012年第3期6卷 224-230页

作者： Correa-Tome, F. E. Sanchez-Yanez, R. E. Ayala-Ramirez, V. Univ Guanajuato DICIS Salamanca Gto 36885 Mexico

A methodology for comparison of boundary and segmentation images based on Precision-Recall graphs is presented in this study. The proposed methodology compares the location of edge pixels between an image under test and an ideal reference, in order to obtain a precise normalised similarity measure. This approach also deals with the case when multiple references are available using a merging procedure. Small displacement errors in edge pixel location are handled using a tolerance radius, which introduces the problem of multiple matching between test and reference edge pixels. This problem is addressed as a bipartite graph, solved by using the hopcroft-karp algorithm to obtain the maximum number of unique matchings. Experiments have been carried out in order to determine the performance of this evaluation approach.

关键词： image segmentation graph theory edge pixels precision-recall graphs bipartite graph image matching displacement errors empirical discrepancy measurement hopcroft-karp algorithm Combinatorial mathematics Optical, image and video signal processing Computer vision and image processing techniques merging procedure

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JOURNAL OF REAL-TIME IMAGE PROCESSING 2016年第1期12卷 145-153页

作者： Correa-Tome, Fernando E. Sanchez-Yanez, Raul E. Univ Guanajuato DICIS Comunidad Palo Blanco Salamanca 36885 Guanajuato Mexico

In this study, a visual similarity metric based on precision-recall graphs is presented as an alternative to the widely used Hausdorff distance (HD). Such metric, called maximum cardinality similarity metric, is computed between a reference shape and a test template, each one represented by a set of edge points. We address this problem using a bipartite graph representation of the relationship between the sets. The matching problem is solved using the hopcroft-karp algorithm, taking advantage of its low computational complexity. We present a comparison between our results and those obtained from applying the partial Hausdorff distance (PHD) to the same test sets. Similar results were found using both approaches for standard template-matching applications. Nevertheless, the proposed methodology is more accurate at determining the completeness of partial shapes under noise conditions. Furthermore, the processing time required by our methodology is lower than that required to compute the PHD, for a large set of points.

关键词： Maximum cardinality similarity metric Template matching Hausdorff distance hopcroft-karp algorithm

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FAST algorithmS FOR MINIMUM COVERING RUN EXPRESSION

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 1994年第3期E77D卷 317-325页

作者： CHINVEERAPHAN, S ZIDOURI, ABC SATO, M Tokyo Inst of Technology Yokohama-shi Japan

The Minimum Covering Run (MCR) expression used for representing binary images has been proposed [1]-[3]. The MCR expression is an adaptation from horizontal and vertical run expression. In the expression, some horizontal and vertical runs are used together for representing binary images in which total number of them is minimized. It was shown that, sets of horizontal and vertical runs representing any binary image could be viewed as partite sets of a bipartite graph, then the MCR expression of binary images was found analogously by constructing a maximum matching as well as a minimum covering in the corresponding graph. In the original algorithm, the most efficient algorithm, proposed by hopcroft [8], solving the graph-theoretical problems mentioned above, associated with the Rectangular Segment Analysis (RSA) was used for finding the MCR expression. However, the original algorithm still suffers from a long processing time. In this paper, we propose two new efficient MCR algorithms that are beneficial to a practical implementation. The new algorithms are composed of two main procedures;i.e., Partial Segment Analysis (PSA) and construction of a maximum matching. It is shown in this paper that the first procedure which is directly an improvement to the RSA, appoints well a lot of representative runs of the MCR expression in regions of text and line drawing. Due to the PSA, the new algorithms reduce the number of runs used in the technique of solving the matching problem in corresponding graphs so that satisfactory processing time can be obtained. To clarify the validity of new algorithms proposed in this paper, the experimental results show the comparative performance of the original and new algorithms in terms of processing time.

关键词： MINIMUM COVERING RUN (MCR) EXPRESSION BIPARTITE GRAPH MINIMUM COVERING MAXIMUM MATCHING hopcroft-karp algorithm

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Comparative Study on Solving the Minimum Fleet of Shared Autonomous Vehicles 20

Comparative Study on Solving the Minimum Fleet of Shared Aut...

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20th COTA International Conference of Transportation Professionals (CICTP) - Advanced Transportation, Enhanced Connection

作者： Wang, Guan Wuhan Planning & Design Co Ltd Wuhan Hubei Peoples R China

ISBN: (数字)9780784483053

ISBN: (纸本)9780784483053

Assuming that all travel demands are met by shared autonomous vehicle (SAV), the paper compares graph theory method and the multiple travelling salesman problem (MTSP) method in solving the minimum fleet size problem. With the trajectory data of 50 new energy private cars in Shanghai for 1 year, travel demands are extracted. A specific method for calculating whether two trips can be served by one SAV is developed. Then, the minimum fleet size problem are transformed into the minimum path cover problem on directed graph (graph theory method) and MTSP shortest path problem (MTSP method). hopcroft-karp algorithm is adopted in graph theory method, while genetic algorithm (GA) is adopted in the MTSP method. Results show that graph theory method outperforms the MTSP method both in the quality of solution and the computing time. Results indicate that a SAV can replace 2.5 traditional private cars on average.

关键词： Shared autonomous vehicle Minimum fleet size Graph theory hopcroft-karp algorithm Multiple travelling salesman problem Genetic algorithm

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Research on the Fleet Size of Shared Autonomous Vehicles in the Future City: An Example in Shanghai 20

Research on the Fleet Size of Shared Autonomous Vehicles in ...

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20th COTA International Conference of Transportation Professionals (CICTP) - Advanced Transportation, Enhanced Connection

作者： Wang, Guan Wuhan Planning & Design Co Ltd 1268 Jinghan Ave Wuhan 430014 Hubei Peoples R China

ISBN: (数字)9780784482933

ISBN: (纸本)9780784482933

The development of autonomous driving technology makes it possible to replace traditional vehicles with shared autonomous vehicles (SAV) in the future. The SAV's fleet size problem is studied in the case of using SAV to meet all motorized travel demands. The cell phone signaling data of 3 million users in Shanghai is used to extract motorized travel demands. The impact of actual road conditions is considered. A graph theory model based on the vehicle-sharing network is established to convert the minimum fleet size problem into the minimum path cover problem of directed acyclic graphs, which is solved by the hopcroft-karp algorithm. To meet motorized travel demands of 3 million cell phone users, 128,000 SAVs are needed. The impact of the maximum scheduling time limit and traffic congestion are also studied. The study provides a reference for determining the fleet size of SAVs and corresponding infrastructure planning at the city level.

关键词： Intelligent transportation Autopilot Fleet size Vehicle-sharing network Minimum path cover hopcroft-karp algorithm

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Point cloud registration with quantile assignment

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MACHINE VISION AND APPLICATIONS 2024年第3期35卷 38-38页

作者： Oguz, Ecenur Dogan, Yalim Gudukbay, Ugur Karasan, Oya Pinar, Mustafa Bilkent Univ Dept Ind Engn TR-06800 Ankara Turkiye Bilkent Univ Dept Comp Engn TR-06800 Ankara Turkiye

Point cloud registration is a fundamental problem in computer vision. The problem encompasses critical tasks such as feature estimation, correspondence matching, and transformation estimation. The point cloud registration problem can be cast as a quantile matching problem. We refined the quantile assignment algorithm by integrating prevalent feature descriptors and transformation estimation methods to enhance the correspondence between the source and target point clouds. We evaluated the performances of these descriptors and methods with our approach through controlled experiments on a dataset we constructed using well-known 3D models. This systematic investigation led us to identify the most suitable methods for complementing our approach. Subsequently, we devised a new end-to-end, coarse-to-fine pairwise point cloud registration framework. Finally, we tested our framework on indoor and outdoor benchmark datasets and compared our results with state-of-the-art point cloud registration methods.

关键词： Point cloud registration Fast point feature histograms (FPFH) descriptor Quantile assignment Iterative closest point algorithm Bipartite graph matching Hungarian algorithm hopcroft-karp algorithm

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