Hybrid attention transformer integrated YOLOV8 for fruit ripeness detection by Jianyin Tang, Zhenglin Yu, ChangShun Shao

“…This model improves the ability to capture complex dependencies by integrating the Shuffle Attention (SA) module while maintaining low computational complexity. …”
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Influence of Rare Earth Elements on the Radiation-Shielding Behavior of Serpentinite-Based Materials by Ayşe Didem Kılıç, Demet Yılmaz

“…In this study, the neutron and gamma radiation-shielding properties of serpentinites from the Guleman ophiolite complex were investigated, and results were evaluated in comparison with rare earth element (REE) content. …”
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A Hybrid Deep Learning Model for UAV Path Planning in Dynamic Environments by Junchi Zhang, Yanning Xian, Xun Zhu, Hongtao Deng

“…Thus, an effective path-planning algorithm is essential for navigating UAVs through complex terrains. However, the commonly used Rapidly-exploring Random Tree (RRT) algorithm for UAV path planning often generates suboptimal paths that require extensive post-processing to improve. …”
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Real-time Detection of Imperfect Wheat Grains on Wheat Pile Surface Based on IDS-YOLO by FAN Jiawei, WU Lan, YAN Jingjing

“…First, a small target detection layer was added to enhance the utilization of high semantic information. …”
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G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection by Jimeng Bai, Guohua Cao

“…First, a channel and spatial attention mechanism is introduced to improve the network’s capability to extract target features, significantly enhancing grasp detection performance in complex backgrounds. Second, an efficient attention module search strategy is proposed to replace traditional fully connected layer structures, which not only increases detection accuracy but also reduces computational overhead. …”
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IoT-Edge Hybrid Architecture with Cross-Modal Transformer and Federated Manifold Learning for Safety-Critical Gesture Control in Adaptive Mobility Platforms by Xinmin Jin, Jian Teng, Jiaji Chen

“…The system architecture establishes a three-tier IoT network: a perception layer with 60 GHz FMCW radar and TOF infrared arrays (12-node mesh topology, 15 cm baseline spacing) for real-time motion tracking; an edge intelligence layer deploying a time-aware neural network via NVIDIA Jetson Nano to achieve up to 99.1% recognition accuracy with latency as low as 48 ms under optimal conditions (typical performance: 97.8% ± 1.4% accuracy, 68.7 ms ± 15.3 ms latency); and a federated cloud layer enabling distributed model synchronization across 32 edge nodes via LoRaWAN-optimized protocols (κ = 0.912 consensus). …”
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Method of investigating thermal fluctuation processes in problems of diagnostics and prediction of insulating materials by Marina N. Dubyago, Nikolay K. Poluyanovich, Vyacheslav Kh. Pshikhopov

“…Mathematical models that describe the layer-by-layer temperature distribution of the cable line in accordance with the theory of thermal conductivity using Fourier differential equation are proposed. …”
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Modern state of irrigated soils at the south of the Volga upland by E. V. Zinchenko, I. N. Gorokhova, N. G. Kruglyakova, N. B. Khitrov

“…Detailed morphological description of soil profiles, granulometric composition, content of soluble salts in soils and sediments of the vadoze zone up to the depth of 3.5 m, dynamics of salts in the layer of 0-50 cm for 2011-2019 are presented. Until the autumn of 2015, the studied soils were deep saline, being no saline in the layer of 0-100 cm. …”
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Multi-Modal Temporal Dynamic Graph Construction for Stock Rank Prediction by Ying Liu, Zengyu Wei, Long Chen, Cai Xu, Ziyu Guan

“…The framework of the MTDGraph method consists of the stock-level sequential embedding layer, the inter-stock relation embedding layer based on temporal dynamic graph construction and the multi-model information fusion layer. …”
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Bilevel Programming Model of Urban Public Transport Network under Fairness Constraints by Jingjing Hao, Xinquan Liu, Xiaojing Shen, Nana Feng

“…In this paper, the bilevel programming model of the public transport network considering factors such as the per capita occupancy area and travel cost of different groups was established, to alleviate the urban transportation equity and optimize the urban public transport network under fairness constraints. The upper layer minimized the travel cost deprivation coefficient and the road area Gini coefficient as the objective function, to solve the optimization scheme of public transport network considering fairness constraints; the lower layer was a stochastic equilibrium traffic assignment model of multimode and multiuser, used to describe the complex selection behavior of different groups for different traffic modes in the bus optimization scheme given by the upper layer. …”
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Underground helmet detection algorithm based on improved YOLOv8s by Jiaru YANG, Yinan QIN, Tianxu LI, Han ZHUANG

“…The safety helmet belongs to small target detection, and the underground operation environment is complex, and dust and light noise have a great impact on camera detection. …”
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Construction and Validation of a Digital Twin-Driven Virtual-Reality Fusion Control Platform for Industrial Robots by Wenxuan Chang, Wenlei Sun, Pinghui Chen, Huangshuai Xu

“…The high-precision twin environment is constructed from the three dimensions of the physical layer, digital layer, and information fusion layer. …”
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Results of Experimental Studies of the Seed Drill for Row Sowing SZD­4.0 by S. I. Kambulov, G. G. Parkhomenko, I. V. Bozhko, A. A. Boyko

“…Sowing units are considered to be the most complex agricultural machines, as they perform many operations - both sequentially and simultaneously. …”
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iNClassSec-ESM: Discovering potential non-classical secreted proteins through a novel protein language model by Yizhou Shao, Taigang Liu

“…Existing NCSP prediction methods mainly use traditional handcrafted features to represent proteins from sequence information, which limits the models' ability to capture complex protein characteristics. In this study, we proposed a novel NCSP predictor, iNClassSec-ESM, which combined deep learning with traditional classifiers to enhance prediction performance. iNClassSec-ESM integrates an XGBoost model trained on comprehensive handcrafted features and a Deep Neural Network (DNN) trained on hidden layer embeddings from the protein language model (PLM) ESM3. …”
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Cheating Detection in Online Exams Using Deep Learning and Machine Learning by Bahaddin Erdem, Murat Karabatak

“…As a result of this study, it has been shown that the application of the most appropriate layer functions and parameter selection that will increase performance can be effective in estimating complex problems and target values that cannot be solved using classical mathematical models. …”
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CombinatorixPy: Advancing mixture descriptors for computational chemistry by Rahil Ashtari Mahini, Gerardo Casanola-Martin, Stephen Szwiec, Simone A. Ludwig, Bakhtiyor Rasulev

“…Quantitative Structure-Activity/Property Relationship (QSAR/QSPR) is a machine learning approach to predict chemical and physical properties of pure compounds; however, it has limited application in multi-component compounds. The complex and layered nature of multi-component materials presents challenges in computing molecular representation, thus limiting the application of QSAR and QSPR. …”
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Laser-Induced Graphene RF Tags for Authentication Applications by Antonio Lazaro, Marco Rodrigo Cujilema, Foad Salehnia, Ramon Villarino, Marc Lazaro, David Girbau

“…Preliminary results obtained with simple resonators and complex images show the feasibility of this technology.…”
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Cytoneme-mediated intercellular signaling in keratinocytes is essential for epidermal remodeling in zebrafish by Yi Wang, Thomas Nguyen, Qingan He, Oliver Has, Kiarash Forouzesh, Dae Seok Eom

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Advancing personalized diagnosis and treatment using deep learning architecture by Rahat Ullah, Nadeem Sarwar, Mohammed Naif Alatawi, Abeer Abdullah Alsadhan, Hathal Salamah Alwageed, Maqbool Khan, Aitizaz Ali

“…Autoimmune disorders (AID) present significant challenges due to their complex etiologies and diverse clinical manifestations. …”
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Machine Learning‐Driven Surrogate Modeling for Optimization of Triboelectric Nanogenerator Design Parameters by Mohammad Abrar Uddin, Myeongju Lim, Rubiga Kim, Barrett London Burgess, Ken Roberts, Junghyun Kim, Taeil Kim

“…Due to the absence of effective analytical models for TENG systems, the complex relationship among these variables and the effect of these variables cannot be easily boiled down into a conventional theoretical framework. …”
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