Research on SeaTreasure Target Detection Technology Based on Improved YOLOv7-Tiny by Xiang Shi, Yunli Zhao, Jinrong Guo, Yan Liu, Yongqi Zhang

“…Experimental results demonstrate that our optimized algorithm achieves a mAP0.5 of 79.5%, representing a 2.0 percentage point improvement over the baseline YOLOv7-tiny model (77.5%) while maintaining computational efficiency at 45.2 GFLOPs. …”
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Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points by Jiajie HAN, Qingyang YUAN, Yu LI, Bo ZHANG, Ke XUE, Tian LAN

“…This database captures essential thermal characteristics of the battery module, allowing for accurate temperature predictions without exhaustive simulations. The Gappy POD algorithm is further enhanced by incorporating a correlation coefficient filtering technique, which identifies a minimal set of optimal measurement points to ensure high accuracy in the reconstructed temperature field while reducing sensor requirements. …”
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Conceptual Framework of Energy-and-Ecology of Indoor Plant Lighting by Sergei A. Rakut’ko

“…(Conclusions) For the first time, the author raises a question about the development of structural elements of the BAT formation algorithm in lighting horticulture in terms of energy-ecological indicators as an integrative optimality criterion of the system. …”
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An online tool based on the Internet of Things and intelligent blockchain technology for data privacy and security in rural and agricultural development by Krishnaprasath Vellimalaipattinam Thiruvenkatasamy, Hayder M. A. Ghanimi, Sudhakar Sengan, Meshal Ghalib Alharbi

“…Central to this model is the proposed Quantum Neural Network + Bayesian Optimization (QNN + BO), a practiced algorithm that, when combined with methods like the Elliptic Curve Cryptography (ECC) and Coyote Optimization Algorithm (COA), guarantees secure data flow, processing, and storage. …”
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STUDY OF THE INFLUENCE OF THE COMPOSITION OF CULTURAL MEDIUM ON THE BASIS OF A WHITE CABBAGE ON DEVELOPMENT OF LEUCONOSTOC MESENTEROIDES AT THE PRE-FERMENTATION STAGE by V. V. Kondratenko, O. Yu. Lyalina, N. E. Posokina, A. Yu. Kolokolova, V. I. Tereshonok

“…In connection with this, an algorithm was developed to determine the optimal duration of pre-fermentation – «stop points». …”
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An Efficient Fine-Grained Access Control Scheme Based on Policy Protection in SGs by Xiaoqing Guo, Huayi Wu, Zhen Qin, Ruonan Ying, Jilai Yang

“…Security analysis demonstrates that the proposed scheme meets the defined security requirements, while performance evaluation indicates that it incurs minimal computational overhead while achieving enhanced privacy protection.…”
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ApproximateSecret Sharing in Field of Real Numbers by Jiaqi Wan, Ziyue Wang, Yongqiang Yu, Xuehu Yan

“…To address these issues, this paper proposes an innovative algorithm to optimize SSS via type-specific coding for real numbers. …”
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Task offloading and resource allocation for blockchain‐enabled mobile edge computing by Renbin Fang, Peng Lin, Yize Liu, Yan Liu

“…To manage the allocation of computing resources between task offloading and blockchain consensus, the task offloading and resource allocation are formulated as a joint optimization problem. The aim of the problem is to minimize the energy consumption of UTs while guaranteeing the delay requirement. …”
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Wide-Range Variable Cycle Engine Control Based on Deep Reinforcement Learning by Yaoyao Ding, Fengming Wang, Yuanwei Mu, Hongfei Sun

“…To solve this problem, this paper adopts a deep reinforcement learning method based on a deep deterministic policy gradient algorithm, and it applies an action space pruning technique to optimize the controller, which significantly improves the convergence speed of network training. …”
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Integrating distributed photovoltaic and energy storage in 5G networks for sustainable IoT applications by Yi Zhong, Yiting Wu, Yi Zheng, Xiaohu Ge

“…This paper explores the integration of distributed photovoltaic (PV) systems and energy storage solutions to optimize energy management in 5G base stations. By utilizing IoT characteristics, we propose a dual-layer modeling algorithm that maximizes carbon efficiency and return on investment while ensuring service quality. …”
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Development and evaluation of a triplex real-time PCR assay for enhanced plague diagnostics in Madagascar. by Beza Ramasindrazana, Zoé A Rahalison, Philippe Gauthier, Guillain Mikaty, Zaina I Bodoarison, Lanto A Maminirina, Soloandry Rahajandraibe, Mamy G Randriamanantsoa, Gilbert Kayoko, Jean-Claude Manuguerra, Anne-Sophie Le Guern, Andriamiliharison J Rasamindrakotroka, Minoarisoa Rajerison

“…Notably, the new assay resolved 100% of previously inconclusive cases from the duplex qPCR test targeting only pla and caf1.<h4>Discussion</h4>While a new plague diagnostic algorithm has been set up after the outbreak in 2017, the present study suggests a real-time PCR assay based on three genes to improve the speed and accuracy of plague diagnostic. …”
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Assessing ornamental tree maturity and spray requirements using depth sensing and LiDAR technologies by Aleena Rayamajhi, Guoyu Lu, Ernest William Tollner, Jean Williams-Woodward, Md Sultan Mahmud

“…Effective assessment of tree maturity and agrochemical application requirements is important for optimizing resource use and sustainability in woody ornamental nurseries. …”
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Scalable Hyperspectral Enhancement via Patch-Wise Sparse Residual Learning: Insights from Super-Resolved EnMAP Data by Parth Naik, Rupsa Chakraborty, Sam Thiele, Richard Gloaguen

“…The spectral and spatial characteristics of the scene encoded in the dictionary enable reconstruction through a first-order optimization algorithm to ensure an efficient sparse representation. …”
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Global air quality index prediction using integrated spatial observation data and geographics machine learning by Tania Septi Anggraini, Hitoshi Irie, Anjar Dimara Sakti, Ketut Wikantika

“…The GML considers geographical characteristics in the analysis by calculating the optimal bandwidth area in its algorithm. The study employs nine scenarios to identify which parameters significantly contribute to the model and determine the best parameter combinations. …”
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Autonomous air combat decision making via graph neural networks and reinforcement learning by Lin Huo, Chudi Wang, Yue Han

“…To address these challenges, we propose a novel multi-aircraft autonomous decision-making approach based on graphs and multi-agent reinforcement learning (MADRL) under zero-order optimization, implemented through the GraphZero-PPO algorithm. …”
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Biopharmaceutical aspects of the development of transdermal forms of Lisinopril dihydrate by Shyteyeva Tatyana, Bezchasnyuk Elena, Kryskiv Oleg, Baranova Inna

“…Optimization of the algorithm for the development of transdermal drugs involves in vitro preformulation studies of the membrane permeability of APIs and the identification of factors that affect this process.…”
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Prediction of compressive strength and characteristics analysis of semi-flexible pavement desert sand grouting material based upon hybrid-BP neural network by Wenbang Zhu, Yuhang Li, Xiumei Zheng, Enze Hao, Dali Zhang, Zhen Wang

“…To precisely obtain DSGM exhibiting exceptional mechanical properties, the Backpropagation Neural Network (BPNN) model was optimized through the utilization of Particle Swarm Optimization (PSO), Sparrow Search Algorithm (SSA), and Genetic Algorithm (GA). …”
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An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage by German Gramajo, Praveen Shankar

“…The computed trajectory maximizes spatial coverage while closely satisfying terminal constraints on the position of the vehicle and minimizing the time of flight. …”
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A Full-Life-Cycle Modeling Framework for Cropland Abandonment Detection Based on Dense Time Series of Landsat-Derived Vegetation and Soil Fractions by Qiangqiang Sun, Zhijun You, Ping Zhang, Hao Wu, Zhonghai Yu, Lu Wang

“…Compared to the traditional yearly land cover-based approach (with an overall accuracy of 77.39%), this algorithm can overcome the propagation of classification errors (with product accuracy from 74.47% to 85.11%), especially in terms of improving the ability to capture changes at finer spatial scales. …”
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Mapping the air temperature in China from time-normalized MODIS land surface temperature data via zone-based stacking ensemble models by Yan Xin, Yongming Xu, Xudong Tong, Yaping Mo, Yonghong Liu, Shanyou Zhu

“…First, Terra/MODIS LST was temporally normalized using ERA5 reanalysis data to eliminate the uncertainty caused by differences in observation times. Then, the whole study area was divided into subzones, and nine base models were developed in each zone using machine learning (ML) methods to estimate Ta. …”
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