Yann-Horng Lin¹, Wen-Jer Chang^1,*, Yi-Chen Lee^2,*, Muhammad Shamrooz Aslam³, Cheung-Chieh Ku⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2231-2262, 2025, DOI:10.32604/cmes.2025.067464 - 31 August 2025

Abstract An Interval Type-2 (IT-2) fuzzy controller design approach is proposed in this research to simultaneously achieve multiple control objectives in Nonlinear Multi-Agent Systems (NMASs), including formation, containment, and collision avoidance. However, inherent nonlinearities and uncertainties present in practical control systems contribute to the challenge of achieving precise control performance. Based on the IT-2 Takagi-Sugeno Fuzzy Model (T-SFM), the fuzzy control approach can offer a more effective solution for NMASs facing uncertainties. Unlike existing control methods for NMASs, the Formation and Containment (F-and-C) control problem with collision avoidance capability under uncertainties based on the IT-2 T-SFM… More >

Junling Zhong¹, Furong Geng², Zhixiao Chen¹, Wenbin Hou^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 1-27, 2025, DOI:10.32604/cmes.2025.065664 - 31 July 2025

Abstract This study presents an interpretable surrogate framework for predicting pedestrian-leg injury severity that integrates high-fidelity finite-element (FE) simulations with a TabNet-based deep-learning model. We generated a parametric dataset of 3000 impact scenarios—covering ten vehicle types and various legform impactors—using automated FE runs configured via Latin hypercube sampling. After preprocessing and one-hot encoding of categorical features, we trained TabNet alongside Support-Vector Regression, Random Forest, and Decision-Tree ensembles. All models underwent hyperparameter tuning via Optuna’s Bayesian optimization coupled with repeated four-fold cross-validation (20 trials per model). TabNet achieved the best balance of explanatory power and predictive accuracy, More > Graphic Abstract

Ghulam E Mustafa Abro^1,*, Altaf Mugheri^2,#, Zain Anwar Ali^3,#

Revue Internationale de Géomatique, Vol.34, pp. 301-331, 2025, DOI:10.32604/rig.2025.065595 - 05 June 2025

Abstract Swarm intelligence, derived from the collective behaviour of biological entities, is a novel methodology for overseeing satellite constellations within decentralized control systems. Conventional centralized control systems in satellite constellations encounter constraints in scalability, resilience, and fault tolerance, particularly in extensive constellations. This research examines the use of swarm-based multi-agent systems and distributed algorithms for efficient communication, collision avoidance, and collaborative task execution in satellite constellations. We provide a comprehensive study of current swarm control algorithms, their relevance to satellite systems, and identify areas requiring further research. Principal subjects encompass decentralized decision-making, self-organization, adaptive communication protocols, More >

Tatiana Henriksson^1,*, Katharina Mitchell², Reima El Naili³, Ali Hajiran²

Canadian Journal of Urology, Vol.32, No.2, pp. 95-99, 2025, DOI:10.32604/cju.2025.065002 - 30 April 2025

Abstract Renal cell carcinoma is a heterogeneous group of renal tumors characterized by several histological subtypes. Herein, we discuss an unusual case of a 55-year-old male who presented as a consultation to our urology clinic with an incidentally found renal mass. After shared decision making patient proceeded with a Robotic Assisted Laparoscopy (RAL) left sided partial nephrectomy. Final pathology confirmed the presence of high nuclear grade mixed clear cell and papillary renal cell carcinoma (RCC) of the left kidney (pT3aN0M0). This case elucidates a very rare incidence of a patient seen to have a collision tumor, More >

Qinglei Zhang, Bai Hu^*, Jiyun Qin, Jianguo Duan, Ying Zhou

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1257-1273, 2025, DOI:10.32604/cmc.2025.059955 - 26 March 2025

Abstract Grasping is one of the most fundamental operations in modern robotics applications. While deep reinforcement learning (DRL) has demonstrated strong potential in robotics, there is too much emphasis on maximizing the cumulative reward in executing tasks, and the potential safety risks are often ignored. In this paper, an optimization method based on safe reinforcement learning (Safe RL) is proposed to address the robotic grasping problem under safety constraints. Specifically, considering the obstacle avoidance constraints of the system, the grasping problem of the manipulator is modeled as a Constrained Markov Decision Process (CMDP). The Lagrange multiplier… More >

Jiacheng Luo, Jiahao Wen, Jian Yang^*

Computer Systems Science and Engineering, Vol.49, pp. 301-316, 2025, DOI:10.32604/csse.2025.060757 - 27 February 2025

Abstract Mitigating tag collisions is paramount for enhancing throughput in Radio Frequency Identification (RFID) systems. However, traditional algorithms encounter challenges like slot wastage and inefficient frame length adjustments. To tackle these challenges, the Slot Prediction Q (SPQ) algorithm was introduced, integrating the Vogt-II prediction algorithm and slot grouping to improve the initial Q value by predicting the first frame. This method quickly estimates the number of tags based on slot utilization, accelerating Q value adjustments when slot utilization is low. Furthermore, a Markov decision chain is used to optimize the relationship between the number of slot groupings (x) More >

Mosab Manaseer¹, Maram Bani Younes^2,*

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1699-1721, 2024, DOI:10.32604/csse.2024.055128 - 22 November 2024

Abstract This work aims to examine the vulnerabilities and threats in the applications of intelligent transport systems, especially collision avoidance protocols. It focuses on achieving the availability of network communication among traveling vehicles. Finally, it aims to find a secure solution to prevent blackhole attacks on vehicular network communications. The proposed solution relies on authenticating vehicles by joining a blockchain network. This technology provides identification information and receives cryptography keys. Moreover, the ad hoc on-demand distance vector (AODV) protocol is used for route discovery and ensuring reliable node communication. The system activates an adaptive mode for monitoring More >

Haitao Hei¹, Jian Wang¹, Yonggang Zheng¹, Hongfei Ye^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011298

Abstract Micro- and nano-scale collisions are widely involved in molecular movement, drug delivery, the actuation of micro-nano devices, etc. They often exhibit extraordinary behaviour relative to the common macroscopic collisions. A deep understanding on the scale reduction-induced novel collision phenomenon and the related mechanism is rather crucial. In this work, the comprehensive impact behaviour of metal projectiles on graphene is investigated on the basis of molecular dynamics simulations. It is found that besides the common penetration and rebound behaviours, the impacting metal projectile can also be captured by the ultrasoft two-dimensional materials, i.e., the adhesion behaviour.… More >

Baowei Wang^1,2,*, Wen You²

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1085-1100, 2024, DOI:10.32604/cmc.2024.055538 - 15 October 2024

Abstract As computer graphics technology continues to advance, Collision Detection (CD) has emerged as a critical element in fields such as virtual reality, computer graphics, and interactive simulations. CD is indispensable for ensuring the fidelity of physical interactions and the realism of virtual environments, particularly within complex scenarios like virtual assembly, where both high precision and real-time responsiveness are imperative. Despite ongoing developments, current CD techniques often fall short in meeting these stringent requirements, resulting in inefficiencies and inaccuracies that impede the overall performance of virtual assembly systems. To address these limitations, this study introduces a… More >

Naeem Raza¹, Muhammad Asif Habib¹, Mudassar Ahmad¹, Qaisar Abbas^2,*, Mutlaq B. Aldajani², Muhammad Ahsan Latif³

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 911-931, 2024, DOI:10.32604/cmc.2024.055049 - 15 October 2024

Abstract Vision-based vehicle detection in adverse weather conditions such as fog, haze, and mist is a challenging research area in the fields of autonomous vehicles, collision avoidance, and Internet of Things (IoT)-enabled edge/fog computing traffic surveillance and monitoring systems. Efficient and cost-effective vehicle detection at high accuracy and speed in foggy weather is essential to avoiding road traffic collisions in real-time. To evaluate vision-based vehicle detection performance in foggy weather conditions, state-of-the-art Vehicle Detection in Adverse Weather Nature (DAWN) and Foggy Driving (FD) datasets are self-annotated using the YOLO LABEL tool and customized to four vehicle… More >