Multipath-Assisted Ultra-Wideband Vehicle Localization in Underground Parking Environment Using Ray-Tracing by Shuo Hu, Lixin Guo, Zhongyu Liu, Shuaishuai Gao

“…To combat significant NLOS noise interference, a robust iterative reweighted least squares (W-IRLS) method synergizes initial weights with optimal position estimation. Integrating ultra-wideband (UWB) delay and angular measurements, four distinct localization modes based on W-IRLS are developed: angle-of-arrival (AOA), time-of-arrival (TOA), AOA/TOA hybrid, and AOA/time-difference-of-arrival (TDOA) hybrid. …”
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A review on the charging strategy of wireless sensor networks utilizing mobile charging devices by Chen Yaqian, Jiao Wanguo, Zhou Lei

“…In this paper, we first introduce the research actuality of the charging strategy of the wireless sensor network by using mobile charging devices from different aspects. Then, the paper summarizes research results obtained by charging strategies using mobile charging vehicle or unmanned aerial vehicle, which include charging manner selection, travelling path optimization, the number of charging device minimization, and etc. …”
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Predicting potentially suitable Bletilla striata habitats in China under future climate change scenarios using the optimized MaxEnt model by Ming Luo, Pingfei Yang, Lili Yang, Zhihong Zheng, Yaya Chen, Huan Li, Mingkai Wu

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A Global Path Planning Algorithm Based on Bidirectional SVGA by Taizhi Lv, Chunxia Zhao, Jiancheng Bao

“…This algorithm does not construct a visibility graph before the path optimization. However it constructs a visibility graph and searches for an optimal path at the same time. …”
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PATH PLANNING AND OBSTACLE AVOIDANCE METHODS FOR AUTONOMOUS MOBILE ROBOTS by Ihor Berizka

“…A promising approach is to use several types of sensors and algorithms, combining the results of different algorithms to achieve a more optimal final result, so called sensor fusion. …”
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Path Choice of Emergency Logistics Based on Cumulative Prospect Theory by Chang-feng Zhu, Zheng-kun Zhang, Qing-rong Wang

“…In addition, perturbation analyses of related parameter are carried out to further reveal the influence mechanism between the prospect value of each path and related parameters. The result shows that the decision-making model can make emergency logistics path choice with higher efficiency and reliability under different complex interference conditions.…”
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Toward more realistic career path prediction: evaluation and methods by Elena Senger, Elena Senger, Yuri Campbell, Rob van der Goot, Barbara Plank

“…Predicting career trajectories is a complex yet impactful task, offering significant benefits for personalized career counseling, recruitment optimization, and workforce planning. However, effective career path prediction (CPP) modeling faces challenges including highly variable career trajectories, free-text resume data, and limited publicly available benchmark datasets. …”
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Development and Evaluation of a Multi-Robot Path Planning Graph Algorithm by Fatma A. S. Alwafi, Xu Xu, Reza Saatchi, Lyuba Alboul

“…The devised MRPP algorithm significantly improved path length efficiency across different configurations. …”
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Fast loop-free path migration strategy in software defined network by Binghao YAN, Qinrang LIU, Jianliang SHEN, Xiantuo TANG, Dong LIANG

“…Aiming at the problems of slow and faulty path migration caused by distributed deployment and asynchronous operation of data plane forwarding devices in software defined network, a fast loop-free path migration strategy was proposed.First, a fast loop detection algorithm based on node ranking was proposed.By comparing the position differences of adjacent nodes on the old and new paths of the flow, whether there was a forwarding loop in the path migration process and the location detection where the loop occurs could be quickly determined.Then, a greedy update mechanism based on node relaxation dependency was proposed.The fast loop detection algorithm was used to uncover the relaxation dependency between the common switches on the old and new paths, and the number of switches updated in each round of the migration process was ensured to be maximized.Simulation results show that the proposed strategy can effectively avoid migration loops and obtain the optimal update time overhead under different network states compared with existing migration schemes.…”
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Seepage Grouting Mechanism for Foundations in Goaf Sites considering Diffusion Paths by Hui Wang, You Li, Zhiyuan Dun, Jianhua Cheng, Zhilin Dun, Chenxi Wu

“…Under the influences of the overburden of the mining, the distribution of grouting in goaf foundation is quite different from that of conventional grouting mechanism in porous media. …”
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Adaptive path planning for efficient object search by UAVs in agricultural fields by Rick van Essen, Eldert van Henten, Lammert Kooistra, Gert Kootstra

“…We trained a YOLOv8 detection network to detect artificial plants placed in grass fields to showcase the potential of our path planner. We evaluated the effect of different detection certainty measures, optimized the path planning parameters, investigated the effects of localization errors, and different numbers of objects in the field. …”
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A Contribution of Shortest Paths Algorithms to the NetworkX Python Library by Miguel Cruz, Rui Carvalho, André Costa, Luis Pinto, Luis Dias, Paulino Cerqueira, Rodrigo Machado, Tiago Batista, Pedro Castro, Jorge Ribeiro

“…To do this, we first review the literature of the usage and general application of NetworkX in different domains of applicability and then explore their usage in a shortest path context. …”
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Observer of changes in the forest of the shortest paths on dynamic graphs of transport networks by N. V. Khajynova, M. P. Revotjuk, L. Y. Shilin

“…This clearly determines the feasibility of realizing the idea of reoptimizing existing solutions in real time as information is received about disturbances in the structure and parameters of the transport network, various restrictions on the use of existing shortest paths. In contrast to the classical problems of finding shortest paths on static or dynamic graphs, it is proposed to supplement the set of situations controlled by the observer by taking into account the associations of shortest path trees with agents that actually use such paths. …”
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Double-path multiscale adaptive compressed sensing network for electronic data by Lubin Yu, Yongsheng Huang, Yiqiang Cheng, Qiliang Du, Zhenwei Zhou, Lianfang Tian, Shilie He, Honghui Liu

“…In this regard, this study proposes a novel double-path multiscale adaptive compressed sensing network (DMA-CS). …”
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Path Planning of Multiple Quadrotors with Ultrawideband Localization for Warehouse Inventory Management by Carlos James P. De Guzman, Alvin Y. Chua, Timothy Scott C. Chu

“…Ultrawideband (UWB) can be viable for quadrotor navigation with their effectiveness even in nonideal lighting conditions and its relatively inexpensive infrastructure. A path planning algorithm was designed which optimizes quadrotor energy consumption and yaw movement. …”
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Prioritized Experience Replay–Based Path Planning Algorithm for Multiple UAVs by Chongde Ren, Jinchao Chen, Chenglie Du

“…Although UAVs working together on complicated jobs can significantly increase productivity and reduce costs, they can cause major issues with path planning. In complex environments, the path planning problem, which is a multiconstraint combinatorial optimization problem and hard to settle, requires considering numerous constraints and limitations and generates the best paths for each UAV to accomplish group tasks. …”
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Contrastive learning of similarity meta-path clustering for multi-behavior recommendation by Juan Liao, Aman Jantan, Zhe Liu, Himanshu Dhumras, Omed Hassan Ahmed

“…Finally, CSMC jointly optimizes multi-behavior and meta-path contrastive objectives to extract both local and high-order semantic signals within a heterogeneous information network graph. …”
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Using a deep learning neural network to predict flight path by Oleksandr Bezsonov, Serhii Liashenko, Oleg Rudenko, Sofiia Rutska, Kateryna Vashchenko

“…The subject of this paper is a new approach using a deep learning neural network designed for predicting the flight path of an unmanned aerial vehicle (UAV). The purpose of this study was to improve the accuracy of drone flight path prediction by developing a deep learning-based trajectory forecasting model. …”
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Worlds apart: Plant health and One Health and a path to convergence by Solveig Danielsen, Urs Schaffner, Jakob Zinsstag

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Design of path planning robot simulator by applying sampling based method by Heru Suwoyo, Julpri Andika, Andi Adriansyah

“…Although the existing solutions are innovative, comparison between the existing methods is still difficult due to significant differences in convergence speed, implementation complexity, and quality of the resulting paths. …”
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