ARSOD-YOLO: Enhancing Small Target Detection for Remote Sensing Images by Yijuan Qiu, Xiangyue Zheng, Xuying Hao, Gang Zhang, Tao Lei, Ping Jiang

“…Moreover, our proposed ARSOD-YOLO optimized the network architecture, component modules, and loss functions based on YOLOv8, enhancing outstanding small target detection capabilities while preserving model efficiency. …”
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MRSNet: Multi-Resolution Scale Feature Fusion-Based Universal Density Counting Network by Yi Zhang, Wei Song, Mingyue Shao, Xiangchun Liu

“…Lower-resolution features are more sensitive to larger objects closer to the camera, while higher-resolution features are more efficient for smaller objects further away. …”
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A Hierarchical Control Framework for Coordinating CAV-Dedicated Lane Allocation and Signal Timing at Isolated Intersections in Mixed Traffic Environments by Feng Chen, Cunbao Zhang, Yu Cao

“…The framework employs two collaborative agents based on the dueling double deep Q-network (D3QN) algorithm. The upper-level agent recommends optimal CAV-DLs configurations based on long-term traffic flow patterns, while the lower-level agent focuses on real-time signal control by adjusting signal parameters and green time allocations in response to current traffic demand. …”
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High Precision Navigation and Positioning for Multisource Sensors Based on Bibliometric and Contextual Analysis by Jiayi Wei, Min Song, Yunbin Yuan

“…By reviewing the evolution of integrated navigation technology, the study examines four typical integration modes: GNSS/INS, INS/visual, GNSS/INS/visual, and GNSS/INS/visual/LiDAR, discussing their complementarity, fusion algorithm optimization, and emerging application scenarios. …”
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Dual Strategy of Reconfiguration with Capacitor Placement for Improvement Reliability and Power Quality in Distribution System by Ali Nasser Hussain, Wathiq Rafa Abed, Mohanad Muneer Yaqoob

“…The MOF was formulated to improve the power quality by increasing the voltage buses and reducing the power losses. While the constraints include limits of system reliability indices to provide optimal constraints on negative interactions of power quality. …”
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A techno‐economic model for enhancing PV hosting capacity through capabilities of smart inverters and soft open points by Rezvaneh Golnazari, Saeed Hasanzadeh, Ehsan Heydarian‐Forushani, Hamid Reza Sezavar, Navid Fahimi

“…While the desired objective function is optimized, the optimality of the PV locations and contribution of smart inverters and SOP is ensured through GA optimization. …”
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SpecPCM: A Low-Power PCM-Based In-Memory Computing Accelerator for Full-Stack Mass Spectrometry Analysis by Keming Fan, Ashkan Moradifirouzabadi, Xiangjin Wu, Zheyu Li, Flavio Ponzina, Anton Persson, Eric Pop, Tajana Rosing, Mingu Kang

“…We further optimize multilevel PCM devices for different tasks by using different materials. …”
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A Design Framework for Scalable and Adaptive Multi-Agent Coordination in Dynamic Environments: Addressing Concurrent Agent and Environment Interactions by Raza Muhammad Kazim, Guoxin Wang, Zhenjun Ming, Jinhui Cao, Janet K. Allen, Farrokh Mistree

“…In this study, we explore the integration of surrogate response surface modeling (SRSM) with optimization algorithms, comparing Stochastic Gradient Descent (SGD) with a fixed learning rate, and adaptive learning rate (ALR) optimizers—including Adaptive Moment Estimation (ADAM) and Adaptive Approximate Direction Method Algorithm (AADMA)—to enhance MAS performance metrics, such as Agent Collision Rate (ACR), Agent Movement Frequency (AMF), and Task Completion Time (TCT). …”
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Learning efficient haptic shape exploration with a rigid tactile sensor array. by Sascha Fleer, Alexandra Moringen, Roberta L Klatzky, Helge Ritter

“…This environment contains a set of rigid static objects representing a selection of one-dimensional local shape features embedded in a 3D space: an edge, a flat and a convex surface. The proposed algorithm simultaneously optimizes main perception-action loop components: feature extraction, integration of features over time, and the control strategy, while continuously acquiring data online. …”
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DeepSARFlood: Rapid and automated SAR-based flood inundation mapping using vision transformer-based deep ensembles with uncertainty estimates by Nirdesh Kumar Sharma, Manabendra Saharia

“…Additionally, we develop a novel gain algorithm to identify diverse ensemble members and estimate uncertainty through deep ensembles. …”
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Machine learning, clinical-radiomics approach with HIM for hemorrhagic transformation prediction after thrombectomy and treatment by Sheng Hu, Junyu Liu, Jiayi Hong, Yuting Chen, Ziwen Wang, Jibo Hu, Shiying Gai, Xiaochao Yu, Jingjing Fu

“…The support vector machine (SVM) was the optimal ML algorithm for constructing the models. …”
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Enhanced Spectral Efficiency in RIS-Assisted MIMO Systems Through Joint Precoding and RIS Configuration by Mohammed Adil Abbas, Aqiel N. Almamori, Ahmed Jumaa Lafta, Asaad H. Sahar

“…Water-filling is used for power allocation across channel eigenmodes, while manifold optimization ensures efficient phase shift updates under unit-modulus constraints. …”
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Innovative Treatment of Combat-Related Extraperitoneal Penetrating Rectal Injury with Intraluminal Vacuum Therapy: A Case Report by Yafa Shani Parnasa, Oded Cohen-Arazi, Gad Marom, Mahmoud Abu-Gazala, Noam Shussman, Miklosh Bala

“…This case highlights ILVT as a novel method for managing complicated blast-related rectal injuries. While there are limited publications on combat-related penetrating rectal injuries that provide evidence-based guidelines, we suggest an aggressive surgical approach combined with negative pressure wound therapy for optimal patient outcomes.…”
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Research on the integrated "cloud-edge-end" intelligent and precise management and control technology system for coal mine disasters by LIU Yubing, LI Yiteng, LI Zhonghui, YIN Shan, JING Chao, LI Kai, LI Zhenxing, ZHAO Shenglei, LIU Chengfei

“…Existing research mainly focuses on monitoring and early warning technologies or algorithm optimization for individual disasters, lacking a coordinated mechanism for multi-disaster monitoring and early warning, as well as disaster avoidance path planning under emergency response. …”
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Implementation of XGBoost Models for Predicting CO₂ Emission and Specific Tractor Fuel Consumption by Nebojša Balać, Zoran Mileusnić, Aleksandra Dragičević, Mihailo Milanović, Andrija Rajković, Rajko Miodragović, Olivera Ećim-Đurić

“…The CO₂ prediction model achieved an accuracy exceeding 80%, while the model for fuel consumption reached over 65%. …”
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Semantic RF Waveform Adaptation in Flying Ad Hoc Networks via Hybrid Knowledge Bases and Deep Reinforcement Learning by Weiqiang Lyu, Linsheng He, Jiamiao Zhao, Fei Hu

“…We propose a framework that jointly optimizes modulation order and cyclic prefix length while considering the semantic importance of transmitted data. …”
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Evolution of Computer-Aided Process Planning for Hybrid Additive/Subtractive Process by Osama Abdulhameed, Abdulrahman Al-Ahmari, Syed Hammad Mian, Abdulmajeed Dabwan, Hisham Alkhalefah

“…Additionally, the genetic algorithm has been employed to obtain the best path with minimum inspection time. …”
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Enhancing Power Allocation in DAS: A Hybrid Machine Learning and Reinforcement Learning Model by S. Gnanasekar, K. C. Sriharipriya

“…ML models utilize historical data to forecast optimal power levels, while MARL agents dynamically adjust power allocation based on real-time conditions, aiming to enhance spectral efficiency, minimize interference, and optimize energy efficiency. …”
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Development of Low-Cost Single-Chip Automotive 4D Millimeter-Wave Radar by Yongjun Cai, Jie Bai, Hui-Liang Shen, Libo Huang, Bing Rao, Haiyang Wang

“…This study focuses on developing single-chip 4D automotive millimeter-wave radar, covering system architecture design, antenna optimization, signal processing algorithm creation, and performance validation. …”
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Accuracy Assessment of Tomato Harvest Working Time Predictions from Panoramic Cultivation Images by Hiroki Naito, Tomohiko Ota, Kota Shimomoto, Fumiki Hosoi, Tokihiro Fukatsu

“…This study highlights the system’s potential to optimize harvesting plans and labor allocation, providing a novel tool for reducing labor costs while maintaining efficiency in large-scale tomato greenhouse production.…”
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