A retina-inspired pathway to real-time motion prediction inside image sensors for extreme-edge intelligence by Subhradip Chakraborty, Shay Snyder, Md Abdullah-Al Kaiser, Maryam Parsa, Gregory Schwartz, Akhilesh R Jaiswal

“…The ability to predict motion in real time is fundamental to many maneuvering activities in animals, particularly those critical for survival, such as attack and escape responses. …”
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A Lightweight Network for Water Body Segmentation in Agricultural Remote Sensing Using Learnable Kalman Filters and Attention Mechanisms by Dingyi Liao, Jun Sun, Zhiyong Deng, Yudong Zhao, Jiani Zhang, Dinghua Ou

“…When transferred to a self-constructed UAV dataset, it achieves an IoU of 96.28%, demonstrating strong generalization ability. All experiments are conducted on RGB optical imagery, confirming that LKF-DCANet offers an efficient and highly versatile solution for water body segmentation in precision agriculture.…”
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Improving Fire and Smoke Detection with You Only Look Once 11 and Multi-Scale Convolutional Attention by Yuxuan Li, Lisha Nie, Fangrong Zhou, Yun Liu, Haoyu Fu, Nan Chen, Qinling Dai, Leiguang Wang

“…The model demonstrates a stronger ability to identify small fire and smoke objects. …”
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DBF‐Net: A Deep Bidirectional Fusion Network for 6D Object Pose Estimation with Sparse Linear Transformer by Xuan Fan, Tao An, Hongbo Gao, Tao Xie, Lijun Zhao, Ruifeng Li

“…A deep bidirectional fusion network is developed, DBF‐Net, achieving efficient yet accurate 6D object pose estimation. Specifically, a sparse linear Transformer (SLT) with linear computation complexity is introduced to effectively leverage cross‐modal semantic resemblance during the feature extraction stage, such that it fully models semantic associations between various modalities and efficiently aggregates the globally enhanced features of each modality. …”
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Development of a Correlation Model of Adherence to Sports With the Mental Health of Students Participating in Sports Leisure Time by Ahmad Mahmoudi, Mohammad Ghasemi, Reza Amin Zadeh, Danesh Zamani Rad

“…Today's sedentary lifestyle contributes to disorders such as cardiovascular diseases, poor ability to cope with stress, higher risk of depression, low productivity at work, and more absenteeism at work. …”
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Algorithms to Identify Copied and Manipulated Spectrum Occupancy Data in Cognitive Radio Networks by Joseph Tolley, Carl B. Dietrich

“…Spectrum Access Systems (SASs) and similar systems coordinate access to shared radio frequency bands to efficiently allocate the use of spectrum between users in a locality. …”
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GNSTAM: Integrating Graph Networks With Spatial and Temporal Signature Analysis for Enhanced Android Malware Detection by Yogesh Kumar Sharma, Deepak Singh Tomar, R. K. Pateriya, Surendra Solanki

“…To model the intricate relationships between applications, an efficient Graph Neural Network (GNN) process is utilized. …”
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Research on the Real-Time Scoring of Chest Ring Target Based on Transfer Learning and Improved Lightweight Neural Network by Minghui Meng, Chuande Zhou

“…Additionally, to enhance the model’s ability to extract local feature information, the efficient channel attention (ECA) mechanism is integrated to replace the PSA attention mechanism in the backbone network, strengthening the edge features of bullet holes on chest ring targets and improving the recall rate for small target detection. …”
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Experimental Investigation of a Direct Evaporative Cooling System for Year-Round Thermal Management with Solar-Assisted Dryer by Sujatha Abaranji, Karthik Panchabikesan, Velraj Ramalingam

“…To alleviate environmental degradation, the need for energy-efficient and eco-friendly systems for building cooling becomes essential. …”
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Strategic slot-pole optimization in electromagnetic coupling with random forest regressor model inspired by response surface methodology by Garbe Chukulu Jarso, Ramesh Babu Nallamothu, Rajendiran Gopal, Gang Gyoo Jin

“…This work provides: (1) a novel framework combining data-driven modeling with classical optimization for electromechanical systems, and (2) practical guidelines for balancing performance and manufacturability in pole-slot design. The methodology's ability to efficiently explore high-dimensional design spaces while maintaining physical interpretability represents a significant advancement for developing next-generation vehicles and industrial power transmission systems.…”
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YOLOv8-DEE: a high-precision model for printed circuit board defect detection by Feifan Yi, Ahmad Sufril Azlan Mohamed, Mohd Halim Mohd Noor, Fakhrozi Che Ani, Zol Effendi Zolkefli

“…Firstly, an improved backbone network incorporating depthwise separable convolution (DSC) modules is designed to enhance the network’s ability to extract PCB defect features. Secondly, an efficient multi-scale attention (EMA) module is introduced in the network’s neck to improve contextual information interaction within complex PCB images. …”
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Adaptive gradient scaling: integrating Adam and landscape modification for protein structure prediction by Vitalii Kapitan, Michael Choi

“…LM dynamically adjusts gradients using a threshold parameter and a transformation function, thereby improving the optimizer’s ability to avoid local minima, more efficiently traverse flat or rough landscape regions, and potentially converge faster to global or high-quality local optima. …”
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Biologically inspired hybrid model for Alzheimer’s disease classification using structural MRI in the ADNI dataset by Houmem Slimi, Imen Cherif, Sabeur Abid, Mounir Sayadi

“…Classification metrics (precision, recall, F1-score) highlight the model’s ability to disentangle complex spatiotemporal patterns in neurodegeneration. …”
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Skin-lesion segmentation using boundary-aware segmentation network and classification based on a mixture of convolutional and transformer neural networks by Javaria Amin, Marium Azhar, Habiba Arshad, Amad Zafar, Seong-Han Kim

“…This leads to accurate early diagnosis, improved treatment outcomes, and efficient clinical workflows. We further propose a compact convolutional transformer model (CCTM) based on convolution and transformers for classification. …”
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Investigating the Capabilities of Ensemble Machine Learning Model in Identifying Near-Fault Pulse-Like Ground Motions by Jafar Al Thawabteh, Jamal Al Adwan, Yazan Alzubi, Ahmad Al-Elwan

“…The study evaluates the effectiveness of these ensemble models in comparison to traditional methods, focusing on their ability to manage the unique attributes of pulse-like ground motions. …”
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Lessons learned from RadiologyNET foundation models for transfer learning in medical radiology by Mateja Napravnik, Franko Hržić, Martin Urschler, Damir Miletić, Ivan Štajduhar

“…We used the RadiologyNET dataset to pretrain several popular architectures (ResNet18, ResNet34, ResNet50, VGG16, EfficientNetB3, EfficientNetB4, InceptionV3, DenseNet121, MobileNetV3Small and MobileNetV3Large). …”
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Smart village construction and college students’ skills entrepreneurship path based on LSTM and simulated annealing algorithm by Xueli Dong

“…However, there are obvious shortcomings in the data prediction and decision support of smart rural construction, especially in the ability to accurately model and efficiently process complex rural environmental data. …”
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ENHANCEMENT OF CODE DIVISION MULTIPLE ACCESS (CDMA) WITHIN THE GSM SYSTEM IN IRAQ by Nabil Abdulwahab Abdulrazaq Baban

“…Additionally, CDMA's ability to dynamically allocate resources based on user demand ensures efficient spectrum utilization and improved capacity. …”
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A cost-effective load side management solution based on power line carrier communication i-PLCC. by Maria Ashraf, Abdul Rafay Khan, Syed Sajjad Haider Zaidi, Asif Gulraiz, Bilal Muhammad Khan

“…Rapid and wide deployment of Load side management, which is a smarter and modern way to ensure efficient and economical use of power, is a classic example. …”
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Deep learning based identification of rock minerals from un-processed digital microscopic images of undisturbed broken-surfaces by M.A. Dalhat, Sami A. Osman

“…Performance analysis revealed that the Simple model had limited ability to isolate fine-grained details, producing broad and less specific activations (0.84 test accuracy). …”
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