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6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022

作者： Firgiawan, Wawan Zainuddin, Zahir Achmad, Andani Universitas Hasanuddin Dapartment of Informatics Makassar Indonesia

ISBN: (纸本)9798350399615

digital Elevation Model (dEM) is data used for modeling water flow. dEM data is in the form of a grid with X and Y points as coordinates and Z representing the surface elevation. One of the challenges in modeling the direction of water flow is the computational time of the d*algorithm to model the flow on dEM data. Based on the initial tests conducted in this study, it can be seen that the increase in computation time will always be directly proportional to the amount of data processed by the application. To overcome this problem, certain methods are needed to shorten computation time to make it more efficient. This study contributes to the existence of a computational model using a decision tree to solve the problem of finding the direction of surface water flow using the d16 d*algorithm. The d16 d*algorithm is a method for modeling the direction of surface water flow. The d*algorithm works by forming 16 flow directions in the search space. For testing in this study, we will compare the sequential computational model and the computational model with the decision tree that the author made to see the computational time efficiency of the d16 d*algorithm completion model. The test results show that modeling the direction of water flow with a decision tree produces a good computation time compared to the sequential program model, with an average computational difference of 82.66 seconds. © 2022 IEEE.

关键词： Computation time d16 d*algorithm decision tree dEM Surface water flow direction

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An Improved MOEA/d d*algorithm for the Solution of the Multi-Objective Optimal Power Flow Problem

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PROCESSES 2023年第2期11卷 337页

作者： Wu, Zhitao Liu, Hao Zhao, Jian Li, Zhiwu Univ Sci & Technol Liaoning Sch Elect & Informat Engn Anshan 114051 Peoples R China Univ Sci & Technol Liaoning Sch Sci Anshan 114051 Peoples R China Macau Univ Sci & Technol Inst Syst Engn Taipa 999087 Macau Peoples R China

The optimal power flow (OPF) is an important tool for the secure and economic operation of the power system. It attracts many researchers to pay close attention. Many d*algorithms are used to solve the OPF problem. The decomposition-based multi-objective d*algorithm (MOEA/d) is one of them. However, the effectiveness of the d*algorithm decreases as the size of the power system increases. Therefore, an improved MOEA/d (IMOEA/d) is proposed in this paper to solve the OPF problem. The main goal of IMOEA/d is to speed up the convergence of the d*algorithm and increase species diversity. To achieve this goal, three improvement strategies are introduced. Firstly, the competition strategy between the barnacle optimization d*algorithm and differential evolution d*algorithm is adopted to overcome the reduced species diversity. Secondly, an adaptive mutation strategy is employed to enhance species diversity at the latter stage of iteration. Finally, the selective candidate with similarity selection is used to balance the exploration and exploitation capabilities of the proposed d*algorithm. Simulation experiments are performed on IEEE 30-bus and IEEE 57-bus test systems. The obtained results show that the above three measures can effectively improve the diversity of the population, and also demonstrate the competitiveness and effectiveness of the proposed d*algorithm for the OPF problem.

关键词： multi-objective optimal power flow MOEA d d*algorithm competition strategy adaptive mutation strategy selective candidate with similarity selection

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A multithreaded real-time solution for 2d EIT reconstruction with the d-bar d*algorithm

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JOURNAL OF COMPUTATIONAL SCIENCE 2023年 67卷

作者： Alsaker, Melody Mueller, Jennifer L. Stahel, Andreas Gonzaga Univ Dept Math Spokane WA 99258 USA Colorado State Univ Dept Math Ft Collins CO 80523 USA Bern Univ Appl Sci Sch Engn & Comp Sci CH-2501 Biel Switzerland

Electrical impedance tomography (EIT) is a non-ionizing real-time imaging tool for bedside pulmonary imaging. dynamic cross-sectional images of ventilation and perfusion can be produced in real time with fast d*algorithms from measured voltage data arising from current applied on electrodes placed around the circumference of the patient's chest. The d-bar method is a direct (non-iterative) reconstruction d*algorithm for EIT that uses equations of inverse scattering to independently reconstruct the conductivity at each point in the region of interest. However, this nonlinear reconstruction method has a computational complexity that makes real-time imaging a challenge. At the same time, it has the attributes that it does not require successive solutions of the forward problem, as is the case with iterative methods, and it is trivially parallelizable in the spatial variable. Here, we present a novel multithreaded implementation of the d-bar method with a front-end MATLAB/Octave program interfaced with C code that uses the pthreads library. The implementation is analyzed on several different platforms with concurrent threads ranging from 2 to 32 for spatial grids of several sizes. We demonstrate that on a CPU with many cores, very high frame rates (50 frames/s) with high resolution (6000 grid points) are achievable, and on a single AMd CPU real-time reconstructions (faster than 30 frames/s) are achieved with this implementation using 10 or more threads on a grid of 1969 points.

关键词： Electrical impedance tomography Multithreading d-bar d*algorithm Real-time imaging

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Wi-Fi Received Signal Strength-based Indoor Localization System Using K-Nearest Neighbors fingerprint integrated d*d*algorithm 23

Wi-Fi Received Signal Strength-based Indoor Localization Sys...

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23rd International Conference on Advanced Communications Technology (ICACT) - On-Line security in Pandemic Era

作者： Jarawan, Tanatthep Kamsing, Patcharin Tortceka, Peerapong Manuthasna, Shariff Hematulin, Warunyu Chooraks, Tachodom Phisannupawong, Thaweerath Sanzkarak, Sitthirak Munakhud, Sookaseam Somjit, Thananorn Int Acad Aviat Ind King Mongkuts Inst Technol Ladkrabang Air Space Control Optimizat & Management Lab Dept Aeronaut Engn Bangkok 10520 Thailand Natl Astron Res Inst Thailand Chiangmai 50180 Thailand

ISBN: (纸本)9791188428069

The indoor localization system is essential since the Global Positioning System cannot give an accurate position indoors, especially when several floor plans are considered. Wi-Fi received signal strength becomes an alternative indicator for indoor localization systems. The experiment proposed a localization system created by integrating and working between the K-Nearest Neighbors d*algorithm and the d*d*algorithm. The result illustrates the optimal path from the start point to the target point by avoiding the obstacle performing exceptionally well. The K -Nearest Neighbors d*algorithm provide the result for localization with Root Mean Square Errors of displacement at 1.190 meters, 2.491 meters, and 1.363 meters of X-Axis Y-Axis, respectively. The proposed indoor localization system can have various applications considering different environmental factors in different applications, such as the size of unmanned aerial vehicles when applying indoor unmanned aerial vehicles.

关键词： Indoor localization Wi-Fi Received Signal Strength Indicator K -Nearest Neighbor d*d*algorithm Indoor positioning

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Path planning of unmanned surface vessel in an unknown environment based on improved d*Lite d*algorithm

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OCEAN ENGINEERING 2022年 266卷

作者： Yu, Jiabin Yang, Meng Zhao, Zhiyao Wang, Xiaoyi Bai, Yuting Wu, Jiguang Xu, Jiping Beijing Technol & Business Univ Sch Artificial Intelligence 11-33 FuCheng Rd Beijing 100048 Peoples R China Beijing Technol & Business Univ China & Beijing Lab Intelligent Environm Protect Beijing 100048 Peoples R China Beijing Technol & Business Univ Key Lab Ind Internet & Big Data China Natl Light Ind Beijing 100048 Peoples R China

To solve the problem of path planning for an unmanned surface vessel in an unknown environment, this paper proposes a path planning d*algorithm based on the improved d*Lite d*algorithm. First, to improve the computational efficiency of the traditional d*Lite d*algorithm, the path cost function is improved to reduce the expansion range of nodes, and the node expansion direction is limited to avoid double node computation. Second, the path planned by the traditional d*Lite d*algorithm on the grid map is suboptimal;so, the inverse distance weighted (IdW) interpolation method is applied to shorten the path length. To improve the smoothness of the planned path by the traditional d*Lite d*algorithm, the dubins d*algorithm is introduced for local path smoothing, and a smooth collision-free path that conforms to the motion dynamics of the unmanned surface vessel is obtained. The proposed d*algorithm was verified by experiments in known and unknown environments. The performance of the proposed d*algorithm was compared with the traditional d*Lite d*algorithm in terms of planning time, path length, and path smoothness. The results revealed that the proposed d*algorithm has the shortest path length, a shorter planning time, and the best smooth path.

关键词： Smooth path planning d*Lite d*algorithm dubins curve Unknown obstacle environment Unmanned surface vessel

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Improved d*Lite d*algorithm path planning in complex environment

Improved D*Lite algorithm path planning in complex environme...

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Chinese Automation Congress (CAC)

作者： Yu, Jabin Liu, Guandong Zhao, Zhiyao Wang, Xiaoyi Xu, Jiping Bai, Yuting Beijing Technol & Business Univ Sch Artificial Intelligence Beijing Peoples R China

ISBN: (纸本)9781728176871

Aiming at the problem of slow planning speed of d*Lite d*algorithm in unmanned cruise ship path planning, an improved d*Lite d*algorithm is proposed and applied to complex environments with dynamic obstacles. This method reduces the unnecessary search area by improving the heuristic function, so as to shorten the path search time, and smooth the obtained path to reduce the path planning distance. Experiments show that the improved d*Lite d*algorithm effectively improves the performance of path planning in many aspects.

关键词： d*Lite d*algorithm dynamic obstacles heuristic function path smoothing

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Route Optimization for Multiple Forklifts Using d* Lite d*algorithm 12

Route Optimization for Multiple Forklifts Using D* Lite Algo...

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IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)

作者： Yumang, Analyn Magwili, Glenn Ruben, Paul Carlos Sy, Mark Lewis M. Siapoc, dan Robert P. Mapua Univ Sch EECE Manila Philippines

ISBN: (纸本)9781665419710

Route optimization is used to determine which path is the most efficient among all the available paths. The study provided forklift operators with a graphical model of the warehouse. The goal of this study is to determine the shortest path from the initial point to the destination point with d* Lite d*algorithm. To execute d* Lite d*algorithm Bluetooth Low Energy Triangulation was used. BLE Triangulation helped d* Lite d*algorithm by mapping the warehouse and locating the real-time location of the forklift/s. The system is an effective path finding for forklift/s inside a warehouse. Through the implementation of the system the group was able to reduce the time needed for the operator to navigate the warehouse. The T-statistic value for tables IV,V and V is 13.0380, 14.0324, and 7.2088 respectively which is greater than the one-tailed critical value of 1.8331 that rejects the null ***, the implementation of the system is successful in reducing the time needed by forklift operators to navigate around the warehouse and that the system can be implemented with multiple forklifts.

关键词： shortest path path finding d* Lite d*algorithm mapping forklift

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Fast Tongue Image Extraction Fusing Multi-dimensional Information and Concurrent d-search d*algorithm 20

Fast Tongue Image Extraction Fusing Multi-dimensional Inform...

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Proceedings of the 2020 4th International Conference on Electronic Information Technology and Computer Engineering

作者： Mingfeng Zhu Jianqiang du Chenghua ding Yangming He Kang Zhang Yimin Zhu School of Computer Jiangxi University of Traditional Chinese Medicine Nanchang China School of Fundamental Medical Science Jiangxi University of Traditional Chinese Medicine Nanchang China

ISBN: (纸本)9781450387811

Tongue image extraction is a primary and fundamental step in the objectification of the tongue diagnoses of traditional Chinese medicine. Aiming at the problems that some methods need to adjust parameters by manual and their accuracy and efficiency are not high, in this paper, a kind of novel concurrent d-search d*algorithm fusing multi-dimensional information is proposed for the application of tongue image extraction in order to realize automatic, fast and accurate tongue image extraction. In our method, original tongue image is considered as a pixel network. Starting from the seed pixel of central region, according to the intensity, hue and relative position information of the pixels of tongue image, a novel d-search d*algorithm is utilized to search tongue body region in original tongue image. Because tongue coating is surrounded by tongue substance in most cases, we propose a novel position operator to decide whether current pixel is surrounded by tongue substance in our d-search d*algorithm so as to extract tongue image with coating accurately. In the same time, to improve the efficiency of our d*algorithm, the original tongue image is divided into several regions (i.e. sub-images), concurrent techniques are utilized to search different tongue regions separately, so as to get the tongue image templates of different regions quickly, and then they are combined into one template. In addition, morphological operators including closing and opening are applied to the template after combination, so that small holes in the template image can be filled. In the end, an and operation is applied to the ultimate template and original tongue image, in order to get extracted tongue image. In our study, we conduct the comparison experiments of 4 methods including the method of manual extraction, our method, tongue image extraction based on greedy rules and tongue image extraction based on random walk. The comparison experiments are conducted from the aspects of accuracy and efficiency

关键词： Tongue image extraction HSI color space Multi-dimensional information d-search d*algorithm Concurrent computing

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dynamic Path Planning for Collision Avoidance of USV based on d* d*algorithm

International Core Journal of Engineering

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International Core Journal of Engineering 2020年第5期6卷 73-83页

作者： Lin Xu

This paper proposes a dynamic path search method for collision avoidance of the unmanned surface vehicle (USV) based on d* d*algorithm to solve the problems of slow search speed, long route and low obstacle avoidance efficiency faced by the USV in path planning with dynamic obstacles. The method uses the information of voyage environment based on the electronic sea chart. Firstly, it carries on the reverse calculation from the target point to the starting point and stores the information of each possible position on the path. Then, the USV is allowed to move from the starting point to the target point. When dynamic obstacles appear on the next path, it only needs to change the local path behind to avoid obstacles so that it is more efficient than other methods because of less computation. The part of model simulation is using MATLAB programming to realize the running program of dynamic collision avoidance path planning of USV based on d* d*algorithm, and comparing with the simulation results of path planning based on the traditional dijstra d*algorithm and A* d*algorithm. The test results show that the d* d*algorithm can significantly reduce the search time and the path length when USV meet dynamic obstacles.

关键词： USV Collision avoidance dynamic path planning d* d*algorithm

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A New Method for Software Test data Generation Inspired by d-d*algorithm 37

A New Method for Software Test Data Generation Inspired by D...

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37th IEEE VLSI Test Symposium (VTS)

作者： Zhang, Jianwei Gupta, Sandeep K. Halfond, William G. J. Univ Southern Calif Los Angeles CA 90007 USA

ISBN: (纸本)9781728111704

Test generation for digital hardware is highly automated, scalable (in practice), and provides high test quality. In contrast, current software automatic test data generation approaches suffer from low test quality or high complexity. While mutation-oriented constraint-based test data generation for software was proposed to generate high quality test data for real program bugs, all existing approaches require symbolic analysis for the whole program, and hence are not scalable even for unit testing, i.e., testing the lowest-level software modules. We propose a new method inspired by hardware d-d*algorithm and divide and conquer for software test data generation. To reduce runtime complexity and improve scalability, we combine global structural analysis and a sequence of small reusable symbolic analyses of parts of the program, instead of symbolically executing each mutated version of the entire program. We also propose a multi-pass test generation system to further reduce runtime complexity and compact test data. We compare our tools with one of the best software test generation tools (EvoSuite[20], which won the SBST 2017 tool competition) and demonstrate that our approach generates higher quality unit tests in a scalable manner and provides a compact set of tests.

关键词： test data generation for software d-d*algorithm ATPG mutation testing software testing

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