Towards Safer Cities: AI-Powered Infrastructure Fault Detection Based on YOLOv11 by Raiyen Z. Rakin, Mahmudur Rahman, Kanij F. Borsa, Fahmid Al Farid, Shakila Rahman, Jia Uddin, Hezerul Abdul Karim

“…The current infrastructure is crucial to metropolitan improvement. Natural factors, aging, and overuse cause these structures to deteriorate, introducing dangers to public well-being. …”
Get full text

A Novel Self-Attention-Enabled Weighted Ensemble-Based Convolutional Neural Network Framework for Distributed Denial of Service Attack Classification by Shravan Venkatraman, S. Kanthimathi, K. S. Jayasankar, T. Pranay Jiljith, R. Jashwanth

“…The weighted ensemble approach ensures that both prominent and subtle features contribute to the final classification, improving adaptability to evolving attack patterns and novel threats. …”
Get full text

Enhanced NDVI prediction accuracy in complex geographic regions by integrating machine learning and climate data—a case study of Southwest basin by Zehui Zhou, Jiaxin Jin, Bin Yong, Weidong Huang, Lei Yu, Peiqi Yang, Dianchen Sun

“…The LSKRX model demonstrated significant improvements in prediction accuracy compared to single-model approaches, with the most notable enhancement in BIAS. …”
Get full text

Critical review of patient outcome study in head and neck cancer radiotherapy by Jingyuan Chen, Yunze Yang, Chenbin Liu, Hongying Feng, Jason M. Holmes, Lian Zhang, Steven J. Frank, Charles B. Simone, II, Daniel J. Ma, Samir H. Patel, Wei Liu

“…Looking ahead, we envision that combining these complementary approaches, especially the interventional prediction models, will enable more personalized treatment strategies, ultimately improving both tumor control and quality of life for head and neck cancer patients treated with radiation therapy.…”
Get full text

Predictive Study on the Cutting Energy Efficiency of Dredgers Based on Specific Cutting Energy by Junlang Yuan, Ke Yang, Taiwei Yang, Haoran Xu, Ting Xiong, Shidong Fan

“…It reflects the cooperation state between the cutter system and the pump-pipe system and has important reference value for improving construction efficiency. The calculation method of the effective specific cutting energy is given, which is calculated by the cutter motor power, slurry concentration, and slurry flow rate. …”
Get full text

Energy-Efficient Target Area Imaging for UAV-SAR-Based ISAC: Beamforming Design and Trajectory Optimization by Jiayi Zhou, Xiangyin Zhang, Kaiyu Qin, Feng Yang, Libo Wang, Deyu Song

“…Numerical results demonstrate that compared to existing benchmarks and PSO algorithms, the proposed method significantly improves the energy efficiency of UAV-SAR-based ISAC systems through optimized trajectory design.…”
Get full text

Spatial transcriptomic analysis of 4NQO-induced tongue cancer revealed cellular lineage diversity and evolutionary trajectory by Feng Liu, Feng Liu, Xiaojun Wu, Shaoqing Yu, Deqiang Cheng, Jun Pan, Xiaodong Wang, Guanzhen Yu, Guanzhen Yu, Chaofu Li

“…These findings offer novel insights for improving the diagnosis and treatment of tongue cancer.…”
Get full text

A Machine Learning-Based Intelligent Framework for Predicting Energy Efficiency in Next-Generation Residential Buildings by Hafiz Muhammad Shakeel, Shamaila Iram, Richard Hill, Hafiz Muhammad Athar Farid, Akbar Sheikh-Akbari, Farrukh Saleem

“…Improving energy efficiency is a major concern in residential buildings for economic prosperity and environmental stability. …”
Get full text

High-accuracy combustible gas cloud imaging system using YOLO-plume classification network by Jiani Zhou, Yang Liu, Yong Zhang, Haotian Hu, Zenan Leng, Feng Sun, Chen Chen

“…Experimental results show that the proposed model achieves an F1-score of 88.97% and an IoU of 89.74%, improving upon the baseline by 7.37% and 7.59%, respectively, with a detection accuracy reaching 99.78%.…”
Get full text

Scalable Semantic Adaptive Communication for Task Requirements in WSNs by Hong Yang, Xiaoqing Zhu, Jia Yang, Ji Li, Linbo Qing, Xiaohai He, Pingyu Wang

“…The experimental results show that the proposed SSAC is more robust than traditional and other semantic communication algorithms in image classification tasks, and achieves scalable compression rates without sacrificing classification performance, while improving the bandwidth utilization of the communication system.…”
Get full text

R-STELLAR: A Resilient Synthesizable Signature Attenuation SCA Protection on AES-256 With Built-In Attack-on-Countermeasure Detection by Archisman Ghosh, Dong-Hyun Seo, Debayan Das, Santosh Ghosh, Shreyas Sen

“…Signature attenuation often relies on analog techniques, and digital signature attenuation reduces MTD to 20 million, requiring additional methods for high resilience. We focus on improving the digital signature attenuation by an order of magnitude (MTD 200M). …”
Get full text

Evaluation of agriculture land transformations with socio-economic influences on wheat demand and supply for food sustainability by Danish Raza, Hong Shu, Muhsan Ehsan, Hong Fan, Kamal Abdelrahman, Hasnat Aslam, Abdul Quddoos, Rana Waqar Aslam, Majid Nazeer, Mohammed S. Fnais, Azeem Sardar

“…Accurate insights into the spatial distribution of cultivated areas, land use for effective agricultural management, and improvement of food security planning, especially in developing countries. …”
Get full text

Metagenome-Assembled Genomes (MAGs): Advances, Challenges, and Ecological Insights by Salvador Mirete, Mercedes Sánchez-Costa, Jorge Díaz-Rullo, Carolina González de Figueras, Pablo Martínez-Rodríguez, José Eduardo González-Pastor

“…By leveraging high-throughput sequencing, advanced assembly algorithms, and genome binning techniques, researchers can reconstruct microbial genomes without the need for cultivation. …”
Get full text

Boosted-SpringDTW for Comprehensive Feature Extraction of PPG Signals by Jonathan Martinez, Kaan Sel, Bobak J. Mortazavi, Roozbeh Jafari

“…<italic>Conclusion</italic>: Boosted-SpringDTW improves F1-Scores compared to two baseline feature extraction algorithms by 35&#x0025; on average for fiducial point identification and mean percent difference by 16&#x0025; on average for IBI estimation. …”
Get full text

Lightweight Multiscale Spatio-Temporal Graph Convolutional Network for Skeleton-Based Action Recognition by Zhiyun Zheng, Qilong Yuan, Huaizhu Zhang, Yizhou Wang, Junfeng Wang

“…Thirdly, the Spatio-Temporal Location Attention (STLAtt) module is used to identify the most informative joints in the sequence of skeletal information at a specific frame, hence improving the model’s ability to extract features and recognize actions. …”
Get full text

A Deep Learning-Based Echo Extrapolation Method by Fusing Radar Mosaic and RMAPS-NOW Data by Shanhao Wang, Zhiqun Hu, Fuzeng Wang, Ruiting Liu, Lirong Wang, Jiexin Chen

“…Furthermore, as the extrapolation time increases, the smoothing effect inherent to convolution operations leads to increasingly blurred predictions. To address the algorithmic limitations of deep learning-based echo extrapolation models, this study introduces three major improvements: (1) A Deep Convolutional Generative Adversarial Network (DCGAN) is integrated into the ConvLSTM-based extrapolation model to construct a DCGAN-enhanced architecture, significantly improving the quality of radar echo extrapolation; (2) Considering that the evolution of radar echoes is closely related to the surrounding meteorological environment, the study incorporates specific physical variable products from the initial zero-hour field of RMAPS-NOW (the Rapid-update Multiscale Analysis and Prediction System—NOWcasting subsystem), developed by the Institute of Urban Meteorology, China. …”
Get full text

A quantum machine learning framework for predicting drug sensitivity in multiple myeloma using proteomic data by M. Priyadharshini, B. Deevena Raju, A. Faritha Banu, P. Jagdish Kumar, V. Murugesh, Oleg Rybin

“…It demonstrates that quantum algorithms can perform complex biological data suggesting more reliable and accurate drug sensitivity predictions. …”
Get full text

Question-matching approach based on gradual machine learning by Xuejian HE, Anqi CHEN, Zhiqiang GUO, Zhiru WANG, Qun CHEN

“…Extensive experiments demonstrate that compared with pure deep learning models, the proposed solution effectively improves the accuracy of question matching, and its performance advantage generally increases with a decrease in labeled training data. …”
Get full text

Gd-EOB-DTPA-enhanced MRI radiomics and deep learning models to predict microvascular invasion in hepatocellular carcinoma: a multicenter study by Zhu Zhu, Kaiying Wu, Jian Lu, Sunxian Dai, Dabo Xu, Wei Fang, Yixing Yu, Wenhao Gu

“…It will provide valuable information for clinical personalized treatment, thereby improving patient prognosis. Clinical trial number Not applicable.…”
Get full text

Development and validation of machine learning-based diagnostic models using blood transcriptomics for early childhood diabetes prediction by Xin Huang, Xin Huang, Di Ouyang, Weiming Xie, Huawei Zhuang, Siyu Gao, Pan Liu, Lizhong Guo

“…BackgroundEarly identification of Type 1 Diabetes Mellitus (T1DM) in pediatric populations is crucial for implementing timely interventions and improving long-term outcomes. Peripheral blood transcriptomic analysis provides a minimally invasive approach for identifying predictive biomarkers prior to clinical manifestation. …”
Get full text