Computational-Based Approaches for Predicting Biochemical Oxygen Demand (BOD) Removal in Adsorption Process by Mohamed K. Mostafa, Ahmed S. Mahmoud, Mohamed S. Mahmoud, Mahmoud Nasr

Get full text

Enhancing remote patient monitoring with AI-driven IoMT and cloud computing technologies by Vijay Kumar Damera, Ramesh Cheripelli, Narsaiah Putta, G. Sirisha, Deepthi Kalavala

“…Furthermore, the model employs an Improved Wild Horse Optimization with Levy Flight Algorithm (IWHOLFA) for hyperparameter tuning, enhancing its predictive performance. …”
Get full text

A data driven approach to urban area delineation using multi source geospatial data by Chenyu Fang, Lin Zhou, Xinyue Gu, Xing Liu, Martin Werner

“…Abstract This study introduces a data-driven, bottom-up approach to urban delineation, integrating feature engineering with the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, which represents a significant improvement in precision and methodology compared to traditional approaches that rely on simplistic OpenStreetMap (OSM) road node data aggregations. …”
Get full text

Deterring Street Crimes Using Aerial Police: Data-Driven Joint Station Deployment and Patrol Path Planning for Policing UAVs by Zuyu Chen, Yan Liu, Shengze Hu, Xin Zhang, Yan Pan

“…Street crime is a critical public concern, attracting wide social and research attention. Conventional solutions to reduce street crimes are dispatching more police force in patrol and installing more cameras for street surveillance, which, however, suffer from huge manpower and financial consumption and limited performance. …”
Get full text

An Enhanced Retrieval Scheme for a Large Language Model with a Joint Strategy of Probabilistic Relevance and Semantic Association in the Vertical Domain by Qi Chen, Weifeng Zhou, Jian Cheng, Ji Yang

Get full text

Primitive-Level vs. Implementation-Level DPA Security: a Certified Case Study by Charles Momin, François-Xavier Standaert, Corentin Verhamme

“…This makes their general comparison difficult and suggests the investigation of relevant case studies to identify when to use one or the other as an interesting research direction. In this paper, we provide such a case study and compare the security that can be obtained by using an unprotected hardware coprocessor, to be integrated into a leakage-resilient PRF, and a certified one, protected with implementation-level countermeasures. …”
Get full text

A Deep Reinforcement Learning Framework for Adaptive Resiliency Enhancement in Smart Power Grids by Boyu Wang, Aliasghar Baziar, Mohammad Reza Askari

Get full text

Automatic Identification Model for Landslide Disaster Using Remote Sensing Images Based on Improved Multiresunet by Zhenyu Zhao, Shucheng Tan, Qinghua Zhang, Hui Chen

“…As a result, efficient and accurate landslide extraction remains a challenging issue within the global research community. To address this problem, a novel automatic landslide hazard remote sensing image identification model, MultiResUNet-BFDC, is proposed. …”
Get full text

Prediction and Optimization of Bolt Parameters for Automotive Fuel Cell Stack under Random Vibration by Yao Junqi, Yin Yan, Wang Bowen, Zhang Fan, Qin Zhikun, Wang Zixuan, Guo Ting

Get full text

Prediction of rock burst risk in underground openings based on intuitionistic fuzzy set by Xin Wang, Kebin Shi, Quan Shi, Heng Zhang, Liqiang Bai

“…The predicted results align well with the actual excavation results, indicating that this model has high accuracy and reliability, and can provide a new research perspective for rock burst prediction.…”
Get full text

Refining daily precipitation estimates using machine learning and multi-source data in alpine regions with unevenly distributed gauges by Huajin Lei, Hongyi Li, Hongyu Zhao

“…This study offers high-quality and long-term alternative data for hydrometeorology research. Meanwhile, XDMF is a promising algorithm for enhancing precipitation in high-altitude mountain areas, which can be flexibly transferred to other regions, different machine learning algorithms, and various hydrometeorological variables.…”
Get full text

Wasserstein GAN for moving differential privacy protection by Enze Liu, Zhiguang Chu, Xing Zhang

“…Balancing data utility with reasonable incorporation of differential privacy is a key challenge in this research area. Traditional differentially private stochastic gradient descent (DP-SGD) algorithms use fixed gradient clipping and noise addition, leading to unstable updates and poor gradient convergence. …”
Get full text

Collaborative optimization of signals and ecological driving speed guidance for buses without dedicated bus lanes in the connected environment by Hui Li, Yunfei Ge, Yuzhou Duan, Xu Zhang

“…Building upon this, optimal timings for phase adjustments and the optimization bus trajectories are calculated using signal control and eco-driving speed guidance models. Then a Genetic Algorithm is used to solve the model. Finally, the effectiveness of the proposed model is verified using Zhengzhou city as a case study and compared against scenarios involving NTSP, TSP, and speed guidance. …”
Get full text

Optimization Model for Safeguarding Vulnerable Components in Integrated Energy Systems Based on Weighted Betweenness by ZHANG Chenwei, WANG Ying, LI Yaping, ZHANG Kaifeng

Get full text

Optimal Cogeneration Scheduling: A Comparison of Genetic and POMDP-Based Deep Reinforcement Learning Approaches by Giorgia Ghione, Vincenzo Randazzo, Eros Pasero, Marco Badami

“…However, scheduling its operation in real-time is challenging. This work compares deep reinforcement learning (DRL) and genetic algorithm (GA) approaches to control a real CHP in a processing facility. …”
Get full text

Parameter identification and sensitivity analysis of a lower-limb musculoskeletal model by Jinghang Li, Keyi Wang, Yi Yuan, Zhipeng Deng, Yi Lui

“…The estimation of joint torque based on wearable sensors is an important content in human–robot interaction research. Despite existing joint torque estimation models providing high accuracy, their application in robotic control is limited due to the number of sensors and real-time output requirements. …”
Get full text

Automatic Registration of Panoramic Images and Point Clouds in Urban Large Scenes Based on Line Features by Panke Zhang, Hao Ma, Liuzhao Wang, Ruofei Zhong, Mengbing Xu, Siyun Chen

“…The average registration error is better than 3 pixels, and the root mean square error (RMSE) is less than 1.4 pixels. Compared with the mainstream methods, it has advantages and can promote the further research and application of panoramic images and laser point clouds.…”
Get full text

Chaotic Image Encryption System as a Proactive Scheme for Image Transmission in FSO High-Altitude Platform by Ping Zhang, Jingfeng Jie, Zhi Liu, Keyan Dong

Get full text

Explainable AI-Based Ensemble Clustering for Load Profiling and Demand Response by Elissaios Sarmas, Afroditi Fragkiadaki, Vangelis Marinakis

“…To address this shortcoming, we applied an advanced ensemble clustering method and compared its performance with traditional algorithms, namely, K-Means++, fuzzy K-Means, Hierarchical Agglomerative Clustering, Spectral Clustering, Gaussian Mixture Models (GMMs), BIRCH, and Self-Organizing Maps (SOMs), across a dataset of 5567 households for a range of cluster counts from three to nine. …”
Get full text

Key technologies and equipment for intelligent sensor network by optical media by Qiang GAO, Wenzhuo LI, Daiyong ZHOU

Get full text