MACA-Net: Mamba-Driven Adaptive Cross-Layer Attention Network for Multi-Behavior Recognition in Group-Housed Pigs by Zhixiong Zeng, Zaoming Wu, Runtao Xie, Kai Lin, Shenwen Tan, Xinyuan He, Yizhi Luo

“…When evaluated in comparison to leading detectors such as RT-DETR, Faster R-CNN, and YOLOv11n, MACA-Net demonstrates a consistent level of both computational efficiency and accuracy. These findings provide a robust validation of the efficacy of MACA-Net for intelligent livestock management and welfare-driven breeding, offering a practical and efficient solution for modern pig farming.…”
Get full text

Frequency regulation of two-area thermal and photovoltaic power system via flood algorithm by Serdar Ekinci, Davut Izci, Cebrail Turkeri, Aseel Smerat, Absalom E. Ezugwu, Laith Abualigah

“…The innovative use of the FLA ensures robust performance and efficient frequency stabilization under varying operational conditions. …”
Get full text

An AI explained systematic modular approach for enhanced Electricity Theft Detection for urbanized Smart Grid environment by Muhammad Ammar, Nadeem Javaid, Ali Arishi

“…Finally, the proposed SATBlend in the classification module utilizes AlexNet for feature extraction, ShuffleNet for efficient computation, and a temporal convolutional network for temporal correlation detection to enhance the reliability of advanced ETD systems. …”
Get full text

A Novel Multi-Image Encryption Scheme Using Generalized Rectangular Transform and Advanced 5-D Hyperchaotic Map by Yu-Chi Lan, Chung-Ming Wang

“…This paper presents GRTPHM (Generalized Rectangular Transform and Penta-Hyperchaotic Map), a novel multi-image encryption scheme that enhances security, efficiency, and versatility. The encryption process consists of two key phases: pixel permutation and pixel diffusion. …”
Get full text

Deep Learning-Based Detection and Digital Twin Implementation of Beak Deformities in Caged Layer Chickens by Hengtai Li, Hongfei Chen, Jinlin Liu, Qiuhong Zhang, Tao Liu, Xinyu Zhang, Yuhua Li, Yan Qian, Xiuguo Zou

“…Additionally, the standard convolutional blocks in the neck of the original model were replaced with Grouped Shuffle Convolution (GSConv) modules, effectively reducing information loss during feature extraction. …”
Get full text

A method of identification and localization of tea buds based on lightweight improved YOLOV5 by Yuanhong Wang, Yuanhong Wang, Jinzhu Lu, Jinzhu Lu, Qi Wang, Qi Wang, Zongmei Gao

“…The Fuding white tea bud image dataset was established by collecting Fuding white tea images; then the lightweight network ShuffleNetV2 was used to replace the YOLOV5 backbone network; the up-sampling algorithm of YOLOV5 was optimized by using CARAFE modular structure, which increases the sensory field of the network while maintaining the lightweight; then BiFPN was used to achieve more efficient multi-scale feature fusion; and the introduction of the parameter-free attention SimAm to enhance the feature extraction ability of the model while not adding extra computation. …”
Get full text

Deployable Deep Learning for Cross-Domain Plant Leaf Disease Detection via Ensemble Learning, Knowledge Distillation, and Quantization by Mohammad Junayed Hasan, Suvodeep Mazumdar, Sifat Momen

“…Our four-model ensemble (DenseNet-121, ResNet-101, DenseNet-201, EfficientNet-B4) achieves 99.15% accuracy via soft-voting. …”
Get full text

DA+BMAC: Distance-Aware Bidirectional Medium Access Control for Mesh Wireless Network-on-Chip by Mohd Shahrizal Rusli, Asrani Lit, Muhammad Nadzir Marsono, Ab Al-Hadi Ab Rahman, Shahidatul Sadiah, Michael Loong Peng Tan, Suhaila Isaak, Norlina Paraman

“…The lack of intelligent traffic control leads to indiscriminate wireless transmission even when efficient wired paths are available. This paper proposes DA+BMAC, a Distance-Aware (DA) Bidirectional Medium Access Control (BMAC) scheme for mesh WiNoC architecture. …”
Get full text

Automated sleep staging model for older adults based on CWT and deep learning by Qunfeng Niu, Ranran Gui, Hengfang Liu, Liuyi Li, Lei Shi, Kunming Jia, Peng Li, Li Wang

“…Compared with the baseline models GoogLeNet, MobileNetV2, ShuffleNetV2, DenseNet121, RegNet, and ResNet50, RICM-SleepNet exhibited the highest recognition accuracy. …”
Get full text

An RTM-Driven Machine Learning Approach for Estimating High-Resolution FAPAR From LANDSAT 5/7/8/9 Surface Reflectance by Guodong Zhang, Gaofei Yin, Yi Zhang, Jiangchuan Hu, Zongyan Li, Changjing Wang, Dujuan Ma, Jiangliu Xie

“…This study synergized the strengths of RTM and machine learning algorithm while overcoming the limitations of RTM parameterization and generalization, providing an efficient and robust Landsat FAPAR estimation approach. …”
Get full text

Lightweight YOLOv8s-Based Strawberry Plug Seedling Grading Detection and Localization via Channel Pruning by CHEN Junlin, ZHAO Peng, CAO Xianlin, NING Jifeng, YANG Shuqin

“…To further validate the improved model's effectiveness, comparisons were conducted with different lightweight backbone networks, including MobileNetv3, ShuffleNetv2, EfficientViT, and FasterNet, while retaining the Neck and Head modules of the original YOLOv8s model. …”
Get full text

Progressive filling partitioning and mapping algorithm for Spark based on allocation fitness degree by Chen BIAN, Jiong1 YU, Wei-rong XIU, Bin LIAO, Chang-tian YING, Yu-rong QIAN

“…The job execution mechanism of Spark was analyzed,task efficiency model and Shuffle model were established,then allocation fitness degree (AFD) was defined and the optimization goal was put forward.On the basis of the model definition,the progressive filling partitioning and mapping algorithm (PFPM) was proposed.PFPM established the data distribution scheme adapting Reducers’ computing ability to decrease synchronous latency during Shuffle process and increase cluster the computing efficiency.The experiments demonstrate that PFPM could improve the rationality of workload distribution in Shuffle and optimize the execution efficiency of Spark.…”
Get full text

Construction of the preoperative staging prediction model for cervical cancer based on deep learning and MRI: a retrospective study by Xuhao Dai, Xiaoxian Ye, Jiangping Ren, Jiming Yang, Yingying Zhou, Zhaoyang Ma, Pengrong Lou

“…Seven deep learning models—DenseNet, FBNet, HRNet, RegNet, ResNet50, ShuffleNet, and ViT—were trained and validated using standardized preprocessing, data augmentation, and manual annotation techniques. …”
Get full text

A 3D lightweight network with Roberts edge enhancement model (LR-Net) for brain tumor segmentation by Qingxu Meng, Weijiang Wang, Hang Qi, Hua Dang, Minli Jia, Xiaohua Wang

“…We propose a 3D Spatial Shift Convolution and Pixel Shuffle (SSCPS) module, the SSCPS module present a low-parameter, low-computational-cost spatial shift convolution that overcomes the limitation of receptive field and improves the ability to extract global contextual information, Pixel Shuffle (PS) module extracts spatial information from feature dimensions, efficiently replacing traditional upsampling module. …”
Get full text

HSF-YOLO: A Multi-Scale and Gradient-Aware Network for Small Object Detection in Remote Sensing Images by Fujun Wang, Xing Wang

“…The C2f_SIS module fuses spatial and improved channel attention with a channel shuffle strategy to enhance feature interaction and suppress background noise. …”
Get full text

MFPI-Net: A Multi-Scale Feature Perception and Interaction Network for Semantic Segmentation of Urban Remote Sensing Images by Xiaofei Song, Mingju Chen, Jie Rao, Yangming Luo, Zhihao Lin, Xingyue Zhang, Senyuan Li, Xiao Hu

“…The Swin Transformer efficiently extracts multi-level global semantic features through its hierarchical structure and window attention mechanism. …”
Get full text

基于混合蛙跳算法的齿轮传动优化设计 by 何兵, 车林仙, 刘初升

“…The hybrid optimization algorithm（HODEFL） overcame the disadvantages on low precision and premature convergence of shuffled frog leaping algorithm（SFLA） for high-dimensional optimization by taking advantages of strong global search and rapid convergence of DE/best/2/bin（DEb2） in differential evolution algorithm（SDE）.The SFLA and DE are hybridized to form a hybrid optimization algorithm（HODEFL） in order to overcome the disadvantages of the SFLA.The study object is the optimization design of the cylindrical helical gear reducer,establishing minimum volume.By comparing with the improved particle swarm optimization（LWPSO）,SFLA and with DEb2 evolutionary algorithm,the HODEFL algorithm is superior to other three algorithms in terms of optimization efficiency,computational accuracy and robustness.…”
Get full text

Comparison of Support Vector Machine-Based Techniques for Detection of Bearing Faults by Lijun Wang, Shengfei Ji, Nanyang Ji

“…This paper presents a method that combines Shuffled Frog Leaping Algorithm (SFLA) with Support Vector Machine (SVM) method in order to identify the fault types of rolling bearing in the gearbox. …”
Get full text

Runoff simulation of Mengjiang River Basin based on distributed hydrological model by Chen Xueqiu, Zhang Wenming, Zou Yanghuan, Lan Yuxi

“…The runoff simulation results at Taiping Station shown that the model achieved a Nash-Sutcliffe efficiency coefficient above 0.8 for all years except 2018, which indicated a good simulation performance in the study area. …”
Get full text

Identification of Megaconstellations in Wide-field Astronomical Images with Machine Learning by Liu Liu, Rongyu Sun, He Zhao

“…Here an automatic identification pipeline based on machine learning model ShuffleNet V2 is developed, after trained with large amount of raw data, high efficiency is achieved. …”
Get full text