Nonlinear Fractional Evolution Control Modeling via Power Non-Local Kernels: A Generalization of Caputo–Fabrizio, Atangana–Baleanu, and Hattaf Derivatives by F. Gassem, Mohammed Almalahi, Osman Osman, Blgys Muflh, Khaled Aldwoah, Alwaleed Kamel, Nidal Eljaneid

“…This framework utilizes a power non-local fractional derivative (PFD), which is a generalized fractional derivative that unifies several well-known derivatives, including Caputo–Fabrizio, Atangana–Baleanu, and generalized Hattaf derivatives, as special cases. It uniquely features a tunable power parameter “<i>p</i>”, providing enhanced control over the representation of memory effects compared to traditional derivatives with fixed kernels. …”
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MM-3D Unet: development of a lightweight breast cancer tumor segmentation network utilizing multi-task and depthwise separable convolution by Xian Wang, Wenzhi Zeng, Junzeng Xu, Senhao Zhang, Yuexing Gu, Benhui Li, Xueyang Wang

“…Background and objectivesThis paper introduces a novel lightweight MM-3DUNet (Multi-task Mobile 3D UNet) network designed for efficient and accurate segmentation of breast cancer tumors masses from MRI images, which leverages depth-wise separable convolutions, channel expansion units, and auxiliary classification tasks to enhance feature representation and computational efficiency.MethodsWe propose a 3D depth-wise separable convolution, and construct channel expansional convolution (CEC) unit and inverted residual block (IRB) to reduce the parameter count and computational load, making the network more suitable for use in resource-constrained environments. …”
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Lightweight detection and segmentation of crayfish parts using an improved YOLOv11n segmentation model by Wei Shi, Jun Zhang, YunFan Fu, DanWei Chen, JianPing Zhu, ChunFeng Lv

“…First, the proposed D-HGNetV2 backbone integrates DynamicConv modules into the HGNetV2 architecture, reducing parameters by 31% (from 2.9 M to 2.0 M) and computational cost by 9.8% (10.2 GFLOPs to 9.2 GFLOPs) through input-dependent kernel aggregation, which enhances multiscale feature extraction for occluded or overlapping parts. …”
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EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments by Asfandyar Khan, Faizan Ullah, Dilawar Shah, Muhammad Haris Khan, Shujaat Ali, Muhammad Tahir

“…In its optimal configuration, the EcoTaskSched model is successfully applied to fog-cloud computing environments, increasing task handling efficiency and reducing energy consumption while maintaining the required QoS parameters. …”
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DSR-YOLO: A lightweight and efficient YOLOv8 model for enhanced pedestrian detection by Mustapha Oussouaddi, Omar Bouazizi, Aimad El mourabit, Zine el Abidine Alaoui Ismaili, Yassine Attaoui, Mohamed Chentouf

“…Additionally, we enhance the initial C2f layers with a modified block that integrates SimAM and DCNv4, minimizing the background noise and sharpening the focus on the relevant features. A second version of the C2f block using SimAM and standard convolutions ensures robust feature extraction in deeper layers with optimized computational efficiency. …”
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Radiomics approach for identifying radiation-induced normal tissue toxicity in the lung by Olivia G. G. Drayson, Pierre Montay-Gruel, Charles L. Limoli

“…Abstract The rapidly evolving field of radiomics has shown that radiomic features are able to capture characteristics of both tumor and normal tissue that can be used to make accurate and clinically relevant predictions. …”
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An Easily Scalable Docker-Based Privacy-Preserving Malicious Traffic Detection Architecture for IoT Environments by Tong Niu, Yaqiu Liu, Qingfeng Li, Qichi Bao

“…The payload of the data packets is encoded to enhance the feature extraction capability of the model. The model is then trained using federated learning/edge computing to ensure data privacy. …”
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Accurately Identifying Different Ripening Stages of Strawberry Fruits in Complex Agricultural Scenarios by Xuefeng Ren, Yang Gan, Huan Liu, Yongming Chen, Ping Lin

“…Third, in the neck network, a multi-scale attention mechanism is introduced to preserve channel information and reduce computational overhead by reshaping selected channels into the batch dimension and grouping them into multiple sub-features, thereby facilitating the model’s perception of evenly distributed semantic features. …”
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AUHF-DETR: A Lightweight Transformer with Spatial Attention and Wavelet Convolution for Embedded UAV Small Object Detection by Hengyu Guo, Qunyong Wu, Yuhang Wang

“…In the backbone, we introduce a novel WTC-AdaResNet paradigm that utilizes reversible connections to decouple small-object features. We further replace the original global attention mechanism with the PSA module to strengthen inter-feature relationships within each ROI, thereby resolving the embedded challenges posed by RT-DETR’s complex token computations. …”
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An AI-Based Horticultural Plant Fruit Visual Detection Algorithm for Apple Fruits by Bin Yan, Xiameng Li, Rongshan Yan

“…The Depthwise Separable Convolution (DWConv) module has many advantages: (1) It has high computational efficiency, reducing the number of parameters and calculations in the model; (2) It makes the model lightweight and easy to deploy in hardware; (3) DWConv can be combined with other modules to enhance the multi-scale feature extraction capability of the detection network and improve the ability to capture multi-scale information; (4) It balances the detection accuracy and speed of the model; (5) DWConv can flexibly adapt to different network structures. …”
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Preoperative multiclass classification of thymic mass lesions based on radiomics and machine learning by Yan Zhu, Li Wang, Aichao Ruan, Zhiyu Peng, Zhenzhong Zhang

“…Therefore, the objective of this study is to rely on clinical parameters and radiomic features extracted from chest computed tomography (CT) scans to facilitate the preoperative classification of TMLs. …”
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No-Reference High Dynamic Range Omnidirectional Image Quality Metric: From the Perspective of Global and Local Statistical Characteristics by Rongyao Yu, Fang Yang, Yi Liu, Jianghui He, Qingjiang Pang, Yang Song

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Direction-Aware Lightweight Framework for Traditional Mongolian Document Layout Analysis by Chenyang Zhou, Monghjaya Ha, Licheng Wu

“…Our framework introduces three key innovations: a modified MobileNetV3 backbone with asymmetric convolutions for efficient vertical feature extraction, a dynamic feature enhancement module with channel attention for adaptive multi-scale information fusion, and a direction-aware detection head with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><mo form="prefix">sin</mo><mi>θ</mi><mo>,</mo><mo form="prefix">cos</mo><mi>θ</mi><mo>)</mo></mrow></semantics></math></inline-formula> vector representation for accurate orientation modeling. …”
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Low illumination image enhancement algorithm of CycleGAN coal mine based on attention mechanism and Dilated convolution by Yuanbin WANG, Yaru GUO, Jia LIU, Xu WANG, Bingchao WU, Meng LIU

“…The complex underground environment, filled with a large amount of dust and water vapor, and uneven illumination of artificial light source, leads to problems such as low illumination and loss of detail features in images collected by underground monitoring equipment, which seriously affects the real-time performance of mining safety monitoring equipment, is not good for subsequent computer vision tasks, and it is difficult to collect underground data. …”
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Application of Improved Multi-Fractal Trend Removing Wave Model in the Analysis of Multi-Fractal Characteristics of Harmonic Signals by Jiebin Wen

“…In the analysis of even harmonics, the computational efficiency, resource consumption, stability, and parameter sensitivity of the research method were 96.6%, 31.2%, 93.7%, and 98.7%. …”
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Wavefront Sensor for the Determination of Nanostructured Surface Defects by V.V. Buchenko, A.A. Goloborodko, V.V. Lendel, O.S. Oberemok

“…The feature of the original wave formation in the system of double Fourier transform with the reflection of light from the surface with structured local inhomogeneities of the refractive index is shown. …”
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COMPLEXITY IN A COURNOT DUOPOLY GAME WITH DIFFERENTIATED GOODS BETWEEN SEMI-PUBLIC AND PRIVATE FIRMS by Georges SARAFOPOULOS, Kosmas PAPADOPOULOS

“…Numerical simulations are carried out to show the complex behaviour. The chaotic features are justified numerically via computing Lyapunov numbers, sensitive dependence on initial conditions, bifurcation diagrams and strange attractors.…”
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Optimization of a multi-environmental detection model for tomato growth point buds based on multi-strategy improved YOLOv8 by Jiang Liu, Jingxin Yu, Changfu Zhang, Huankang Cui, Jinpeng Zhao, Wengang Zheng, Fan Xu, Xiaoming Wei

“…Three key innovations address YOLOv8’s limitations: (1) an SE attention module boosts feature representation in cluttered environments, (2) GhostConv replaces standard convolution to reduce computational load by 19% while preserving feature discrimination, and (3) a scale-adaptive WIoU_v2 loss function optimizes gradient allocation for variable-quality data. …”
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Exact collective occupancies of the Moshinsky model in two-dimensional geometry by Arkadiusz Kuroś, Adam Pieprzycki, Edyta Gawin, Przemysław Kościk

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NuCap: A Numerically Aware Captioning Framework for Improved Numerical Reasoning by Yuna Jeong, Yongsuk Choi

“…Despite the significant improvement in numerical reasoning power, our proposed approach has significantly fewer parameters and lower inference latency than large-scale vision language models, demonstrating both computational efficiency and stability. …”
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