Path Planning of Mobile Robot in Dynamic Obstacle Avoidance Environment Based on Deep Reinforcement Learning by Qingfeng Zhang, Wenpeng Ma, Qingchun Zheng, Xiaofan Zhai, Wenqian Zhang, Tianchang Zhang, Shuo Wang

“…In this study, to address the issues faced by mobile robots in complex environments, such as sparse rewards caused by limited effective experience, slow learning efficiency in the early stages of training, as well as poor obstacle avoidance performance in environments with dynamic obstacles, the authors proposed a new path planning algorithm for mobile robots by introducing Intrinsic Curiosity Module (ICM) and Long Short-Term Memory (LSTM) into the Proximal Policy Optimization (PPO) algorithm. …”
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The Planners’ Perspective on Train Timetable Errors in Sweden by Carl-William Palmqvist, Nils O. E. Olsson, Lena Winslott Hiselius

“…The errors we identified are (a) crossing train paths at stations, (b) wrong track allocation of trains at stations, especially for long trains, (c) insufficient dwell and meet times at stations, and (d) insufficient headways leading to delays spreading. …”
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Integrating path signature and pen-tip trajectory features for online handwriting Yi text recognition by Wenjun Xiao, Shanxiong Chen, Yuqi Ma, Yongbo Li, Xiaolong Wang, Yaoyao Feng, Weizheng Qiao, Xun Pu

“…YTRN adeptly learns the spatial structure features from path signature feature maps and captures trajectory features from the pen-tip trajectories. …”
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Modeling and analysis of vehicle path dispersion at signalized intersections using explainable backpropagation neural networks by Jing Zhao, Ruoming Ma, Jian Sun, Rongji Zhang, Cheng Zhang

“…The predictive power and transferability of the model were verified by applying the trained model on the four new intersections. The contributions of the influencing factors on the path dispersion were explored based on the neural interpretation diagram, relative importance of influencing factors, and sensitivity analysis to offer explanatory insights for the proposed model. …”
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Metro Passenger Path Choice Behavior during Single-line Operation Interruption in Risk Emergencies by GUO Jingfan, TIAN Yuanyuan, LI Juncheng, HE Jiantao, LUO Qixiang

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At the Traffic Intersection, Stopping, or Walking? Pedestrian Path Prediction Based on KPOF-GPDM for Driving Assistance by Xudong Long, Weiwei Zhang, Bo Zhao, Shaoxing Mo

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The Path Towards Novel Varieties: Investigating Phenotypic-Genetic Diversity in New Promising Egyptian Rice Lines by Waleed A. Almasoud, Mahmoud Abdel-Sattar, Saber Sedeek, Amgad A. Elgammaal, Nouran El-Refaee, Ibrahem A. Ramadan, Dina Abdulmajid, Hail Z. Rihan

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Quadratic Approximation of PV Curve Path Based on Local Phasor Measurements, in Presence of Voltage Dependent Loads. by Shahriar Abasi, Farid Karbalaei

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Multi-UAV Path Planning for Air-Ground Relay Communication Based on Mix-Greedy MAPPO Algorithm by Yiquan Wang, Yan Cui, Yu Yang, Zhaodong Li, Xing Cui

“…The results show that the Mix-Greedy MAPPO algorithm significantly improves communication probability, reduces energy consumption, avoids no-fly zones, and facilitates exploration compared to other algorithms in the multi-UAV ground communication relay path planning task. After training with the same number of steps, the Mix-Greedy MAPPO algorithm has an average reward score that is 45.9% higher than the MAPPO algorithm and several times higher than the multi-agent soft actor-critic (MASAC) and multi-agent deep deterministic policy gradient (MADDPG) algorithms. …”
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Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward Mode and Region Segmentation by Zhipeng Wang, Soon Xin Ng, Mohammed EI-Hajjar

“…Our proposed region segmentation aims to reduce the probability of DRL agents falling into local optimal trap, while our proposed cumulative reward model takes into account the distance from the node to the destination and the density of obstacles near the node, which solves the problem of sparse training data faced by the DRL algorithms in the path planning task. …”
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Path planning of intelligent tennis ball picking robot integrating twin network target tracking algorithm by Zegang Wang

“…The artificial potential field ant colony algorithm optimizes the obstacle avoidance ability and path smoothness. The results showed that in the training dataset, the accuracy of the proposed target tracking algorithm was as high as 0.981, which was 5.40–25.56% higher than existing algorithms such as SiamFC, MORT, SiamRPN, MeMOT, and FROG MOT. …”
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Subjective Outcome Evaluation of the Project P.A.T.H.S. (Secondary 2 Program): Views of the Program Participants by Daniel T. L. Shek, Catalina S. M. Ng

“…A total of 196 secondary schools participated in the Secondary 2 Program of the Full Implementation Phase of the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes). …”
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Path of knowledge: promoting the learning of the first law of thermodynamics and its applications through a serious game by Ruthinéia Alves do Nascimento, Rayanne Carla Alves do Nascimento, Fabiane Rodrigues Fernandes, Vinicius Vescovi

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Secondary 1 Program of Project P.A.T.H.S.: Process Evaluation Based on the Co-Walker Scheme by Daniel T. L. Shek, Catalina S. M. Ng

“…This study examined the implementation quality of the Tier 1 Program (Secondary 1 Curriculum) delivered in the second year of the Full Implementation Phase of the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes). …”
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Multi-scale aware dual path network for face detection in resource-constrained edge computing environment by Qi QI, Yingxin MA, Jingyu WANG, Haifeng SUN, Jianxin LIAO

“…Aiming at the problem that face detectors with complex deep neural structures are difficult to deploy in the resource-constrained edge computing environment,to reduce the resource consumption while maintain the accuracy in complex scenes such as multi-scale face changes,occlusion,blur,and illumination,SDPN(multi-scale aware dual path network) for face detection was proposed.The Face-ResNet (face residual neural network) was improved,and a dual path shallow feature extractor was used to understand the multi-scale information of the image through parallel branches.Then the deep and shallow feature fusion module,a combination of the underlying image information and the high-level semantic feature,was used in conjunction with the multi-scale awareness training strategy to supervise the multi-branch learning discriminating features.The experimental results show that SDPN can extract more diversified features,which effectively improve the accuracy and robustness of face detection while maintaining the efficiency of the model and low inference delay.…”
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Secondary Data Analyses of Subjective Outcome Evaluation Findings of the Project P.A.T.H.S. in Hong Kong by Daniel T. L. Shek, Rachel C.F. Sun

“…The Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) is a positive youth development program in Hong Kong. …”
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Subjective Outcome Evaluation of the Project P.A.T.H.S.: Qualitative Findings Based on the Experiences of Program Implementers by Daniel T. L. Shek, Rachael C. F. Sun

“…A total of 52 schools participated in the experimental implementation phase of the project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes). …”
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Alternative Paths to Hearing (A Conjecture). Photonic and Tactile Hearing Systems Displaying the Frequency Spectrum of Sound by E. H. Hara

“…Photonic and tactile hearing systems displaying the spectrum of sound are proposed as alternative paths to the section of the brain that processes sound. …”
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Subjective Outcome Evaluation Based on Secondary Data Analyses: The Project P.A.T.H.S. in Hong Kong by Daniel T.L. Shek, Rachel C.F. Sun

“…The intent of this study was to evaluate the program effectiveness of the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) (Secondary 1 Curriculum) by analyzing 207 school-based program reports, in which program implementers were invited to write down five conclusions based on an integration of the subjective outcome evaluation data collected from the program participants and program implementers. …”
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Deep reinforcement learning based online lifting path planning for tower cranes in unknown dynamic environments by Kai Wang, Jing Li, Zhiyuan Yin, Jiankang Zhang, Xin Ma

“…A new Hindsight Experience Replay algorithm is proposed to address the reward sparsity problem in lifting path planning, which improves the training speed. …”
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