Enhancing Crowd Safety at Hajj: Real-Time Detection of Abnormal Behavior Using YOLOv9 by Amani A. Alsabei, Tahani M. Alsubait, Hosam H. Alhakami

“…Leveraging deep learning, this research accurately identifies features of abnormal behavior from the HAJJv2 dataset, specifically curated and annotated for the Hajj context. Optimization of the YOLOv9 algorithm for this scenario demonstrated superior performance metrics (mean Average Precision (mAP@0.5), Recall, and Precision) when compared with its predecessors (YOLOv4, YOLOv5, YOLOv7, and YOLOv8), highlighting significant improvements in detection accuracy and real-time applicability. …”
Get full text

5G-oriented information sharing mechanism within D2D clusters by Shaomin WANG, Bin ZHOU

“…Device-to-Device（D2D）communication is an important technology in 5G network.It helps to improve the transmission efficiency of data dissemination services.However,due to the extra signaling overhead caused by D2D communications,currently most of enhanced-multicast solutions cannot solve the contradiction between high-efficient data transmission and low-efficient signaling procedure,so as to reduce the overall performance gain.An intra-cluster D2D information sharing algorithm based on matrix analysis which includes centralized and distributed modes was proposed.The proposed algorithm could significantly reduce D2D retransmission times in clusters by adaptively selecting the optimal transmitters and data packets for D2D multicast retransmission,achieving the aim of reducing signaling overhead and transmission delay.…”
Get full text

Hybrid Damping Mode MR Damper: Development and Experimental Validation with Semi-Active Control by Jeongwoo Lee, Kwangseok Oh

“…This configuration supports four damping modes—Soft/Soft, Hard/Soft, Soft/Hard, and Hard/Hard—allowing adaptability to varying driving conditions. Magnetic circuit optimization ensures rapid damping force adjustments (≈10 ms), while a semi-active control algorithm incorporating skyhook logic, roll, dive, and squat control strategies was implemented. …”
Get full text

Hardware-in-loop implementation of an adaptive MPPT controlled PV-assisted EV charging system with vehicle-to-grid integration by Surabhi Singh, Hari Om Bansal

“…In addition, the designed bidirectional charging system maximizes solar energy collection, minimizes the charging cost, and improves grid stability through demand balancing. …”
Get full text

Enhancing Lifetime and Reliability in WSNs: Complementary of Dual-Battery Systems Energy Management Strategy by Mehrshad Eskandarpour, Hossein Soleimani

“…Unlike previous approaches, this system enables simultaneous charging and load powering and is specifically optimized for energy-harvesting WSN environments. Simulation results in MATLAB/Simulink demonstrate that the system improves battery lifespan by up to 25% compared to conventional single-battery configurations, while ensuring stable voltage regulation and improved reliability under variable loads. …”
Get full text

A 5G network based conceptual framework for real-time malaria parasite detection from thick and thin blood smear slides using modified YOLOv5 model by Swati Lipsa, Ranjan Kumar Dash, Korhan Cengiz, Nikola Ivković, Adnan Akhunzada

“…Conclusion Our model exemplifies how a generic one-stage object detection algorithm, such as YOLOv5x, can be repurposed to detect objects as small as malaria parasites from microscopic visuals in a cost-effective manner over the 5G network. …”
Get full text

Minimizing the Active Power Losses and Retaining the Voltage Profile of the Distribution System Using Soft Computing Techniques with DG Source by P. Sundararaman, E. Mohan, S. V. Aswin Kumer, Sridhar Udayakumar, Abdissa Fekadu Moti

“…The proposed BAT algorithm gives the optimal locations to place the required amount of DG sources to improve the stability and minimize the power losses and maintain the voltage profile of the systems. …”
Get full text

Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers by Raja Azlina Raja Mahmood, AmirHossien Abdi, Masnida Hussin

“…These evolutionary-based algorithms are known to be effective in solving optimization problems.  …”
Get full text

A Short-Term Load Forecasting Method Considering Multiple Factors Based on VAR and CEEMDAN-CNN-BILSTM by Bao Wang, Li Wang, Yanru Ma, Dengshan Hou, Wenwu Sun, Shenghu Li

“…Finally, the sine–cosine and Cauchy mutation sparrow search algorithm (SCSSA) is used to optimize the parameters of the combinative model to improve the forecasting accuracy. …”
Get full text

QoS Routing in Telecommunications Networks by N. I. Listopad, O. A. Lavshuk

“…With the transition to new generation networks, the issues of improving routing algorithms and protocols seem to be especially relevant. …”
Get full text

Leveraging petrophysical and geological constraints for AI-driven predictions of total organic carbon (TOC) and hardness in unconventional reservoir prospects by Nandito Davy, Ammar El-Husseiny, Umair bin Waheed, Korhan Ayranci, Manzar Fawad, Mohamed Mahmoud, Nicholas B. Harris

“…Petrophysical constraints were derived from triple combo well logs (gamma ray, bulk density, neutron porosity), while geological constraints included stratigraphic data or spatial distance between training and target wells—petrophysical constraints most improved predictions, while stratigraphic and spatial constraints had progressively less impact. …”
Get full text

An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids by Mohammad Mehdi Sharifi Nevisi, Mehrdad Shoeibi, Francisco Hernando-Gallego, Diego Martín, Sarvenaz Sadat Khatami

“…This optimization ensures improved accuracy, faster convergence, and better generalization to unseen data. …”
Get full text

Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward Mode and Region Segmentation by Zhipeng Wang, Soon Xin Ng, Mohammed EI-Hajjar

“…The proposed region segmentation algorithm and cumulative reward model have been tested in different DRL techniques, where we show that the cumulative reward model can improve the training efficiency of deep neural networks by 30.8% and the region segmentation algorithm enables deep Q-network agent to avoid 99% of local optimal traps and assists deep deterministic policy gradient agent to avoid 92% of local optimal traps.…”
Get full text

Random Natural Gradient by Ioannis Kolotouros, Petros Wallden

“…Hybrid quantum-classical algorithms appear to be the most promising approach for near-term quantum applications. …”
Get full text

Maximizing the biochemical resolving power of fluorescence microscopy. by Alessandro Esposito, Marina Popleteeva, Ashok R Venkitaraman

“…We describe optimized imaging protocols, provide optimization algorithms and describe precision and resolving power in biochemical imaging thanks to the analysis of the general properties of Fisher information in fluorescence detection. …”
Get full text

A novel LSTPA methodology for managing energy in electrical/thermal microgrids through CHP, battery resources, thermal storage, and demand-side strategies by Elmira Akhavan Maroofi, Mahmoud Samiei Moghaddam, Azita Azarfar, Reza Davarzani, Mojtaba Vahedi

“…Results indicate that the proposed approach reduces energy losses to 3634 kWh, improves voltage stability to 0.9828 p.u., and lowers operational costs to $2845 in islanded mode. …”
Get full text

Resource Allocation for Edge-enhanced Distributed Power Wireless Sensor Network by Gang WU, Jinhui ZHOU, Hui LI

“…Therefore, this mechanism can effectively improve the communication quality of the sensors and the efficiency of the system, extend the life of the sensor equipment, and reduce the network cost.…”
Get full text

Network Partitioning Domain Knowledge Multiobjective Application Mapping for Large-Scale Network-on-Chip by Yin Zhen Tei, Yuan Wen Hau, N. Shaikh-Husin, M. N. Marsono

“…Besides, the conflicting cost and performance trade-off makes multiobjective application mapping techniques even more complex. …”
Get full text

Prediction of Input–Output Characteristic Curves of Hydraulic Cylinders Based on Three-Layer BP Neural Network by Wei Cai, Yirui Zhang, Jianxin Zhang, Shunshun Guo, Rui Guo

“…In the process of model improvement, a nonlinear adaptive decreasing weight mechanism is introduced to improve the optimization accuracy of the algorithm, facilitating the search for optimal solutions. …”
Get full text

Joint classification and regression with deep multi task learning model using conventional based patch extraction for brain disease diagnosis by Padmapriya K., Ezhumalai Periyathambi

“…Results One of our unique discoveries is that, using our datasets, we verified that our proposed algorithm, DMTCNN, could appropriately categorize dissimilar brain disorders. …”
Get full text