AI-Enabled Smart Irrigation for Climate-Resilient Agriculture by Khan Roohee, Sharma Pooja

“…Among others, this research proposes and develops an AI enabled smart irrigation system meant to improve climate resilience of agriculture. The system tries to achieve reduction in waste, optimized water usages and enhancement of crop yield by assimilating advanced machine learning algorithms with real time sensor data. …”
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Automated segmentation of brain metastases in T1-weighted contrast-enhanced MR images pre and post stereotactic radiosurgery by Hemalatha Kanakarajan, Wouter De Baene, Patrick Hanssens, Margriet Sitskoorn

“…Abstract Background and purpose Accurate segmentation of brain metastases on Magnetic Resonance Imaging (MRI) is tedious and time-consuming for radiologists that could be optimized with deep learning (DL). Previous studies assessed several DL algorithms focusing only on training and testing the models on the planning MRI only. …”
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Neural network technologies for forecasting and controlling electricity consumption in energy systems by the genetic method by Nikolay K. Poluyanovich, Oleg V. Kachelaev, Marina N. Dubyago, Talia Hernandez Falcón

“…Based on the results of training and testing, the genetic algorithm confirmed the possibility of automating the selection of optimal hyperparameters and obtaining forecasts of greater accuracy and the possibility.…”
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UAV as a Bridge: Mapping Key Rice Growth Stage with Sentinel-2 Imagery and Novel Vegetation Indices by Jianping Zhang, Rundong Zhang, Qi Meng, Yanying Chen, Jie Deng, Bingtai Chen

“…The optimal model, incorporating 300 features, achieved an F1 score of 0.864, representing a 2.5% improvement over models based on original spectral bands and a 38.8% improvement over models using a single feature. …”
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An Application of Site Selection for Solid Waste Management System Using Neutrosophic Set by A.Savitha Mary, D. Sarukasan, C. Kayelvizhi, L. Jethruth Emelda Mary, F. Josephine Daisy, K. Pitchaimani

“…These factors significantly influence waste collection, processing, and disposal methods. To improve the efficiency and accuracy of waste management site selection, novel computational algorithms have been developed using a proposed distance formula. …”
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Modified Сomplex Treatment of the Cirhotic Patients with the Hepatopulmonary Syndrome of the Different Severity Degrees: Pathogenetic Reasoning and Efficiency by Abrahamovych M., Abrahamovych O., Tolopko S., Ferko M.

“…The modified by us method of the treatment of the patients considering the investigated pathogenic mechanisms of the liver cirrhosis and the HPS, its severity, as well as the conventional one, gave the positive result, but by its quality parameters the conventional medical complex significantly yielded comparing to the modified by us algorithm. Statistical analysis of the questionnaires MOS SF­36 before and after the treatment indicated a significant (p < 0.05) improvement of the physical activity, vitality, mental and general health, reducing of the pain and the role of the emotional stress in disability, resulting into the improvement of the physical and mental status of the patients treated by the modified by us technique and shows its effectiveness. …”
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Prevalence and patterns of antiretroviral resistance in HIV-infected Latin American asylum seekers by Samuel Manzano, Juan Torres-Macho, Neda Deihim-Rahampour, Guillermo Cuevas, Felipe Perez-Garcia, Luz Balsalobre, Salvador Resino, Matilde Sanchez-Conde, Jorge Valencia, Pablo Ryan

“…These findings underscore the need for optimized treatment strategies and improved healthcare access for migrant populations with HIV.…”
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A Composite Network for CS ISAR Integrating Deep Adaptive Sampling and Imaging by Lianzi Wang, Ling Wang, Miguel Heredia Conde, DaiYin Zhu

“…However, the existing CS ISAR imaging methods based on deep learning (DL) mainly focus on improving the performance of the reconstruction algorithm while ignoring the potential room for improvement given by the design of the measurement matrix. …”
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Can Stereoscopic Density Replace Planar Density for Forest Aboveground Biomass Estimation? A Case Study Using Airborne LiDAR and Landsat Data in Daxing’anling, China by Xuan Mu, Dan Zhao, Zhaoju Zheng, Cong Xu, Jinchen Wu, Ping Zhao, Xiaomin Li, Yong Pang, Yujin Zhao, Tianyu An, Yuan Zeng, Bingfang Wu

“…The results of 10-fold cross-validation demonstrated the superiority of the stereo method over the planar method, with RF outperforming SLR. The optimal RF-based stereo model of H_AM (R² = 0.65, rRMSE = 26.05%) significantly improved AGB estimation compared to the planar model (R² = 0.59, rRMSE = 30.41%). …”
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Advanced Estimation of Winter Wheat Leaf’s Relative Chlorophyll Content Across Growth Stages Using Satellite-Derived Texture Indices in a Region with Various Sowing Dates by Jingyun Chen, Quan Yin, Jianjun Wang, Weilong Li, Zhi Ding, Pei Sun Loh, Guisheng Zhou, Zhongyang Huo

“…Following a two-step variable selection method, Random Forest (RF)-LassoCV, five machine learning algorithms were applied to develop estimation models. …”
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Detection Method for Safety Helmet Wearing on Construction Sites Based on UAV Images and YOLOv8 by Xin Jiao, Cheng Li, Xin Zhang, Jian Fan, Zhenwei Cai, Zhenglong Zhou, Ying Wang

“…To address these issues, this study proposes a helmet detection method based on unmanned aerial vehicles (UAVs) and the YOLOv8 object detection algorithm. The method utilizes UAVs to flexibly capture construction site images, combined with the optimized YOLOv8s model, and employs transfer learning to annotate and train labels for “person” and “helmet”. …”
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Analysis of Blockchain-Technology by Danylo Dvorchuk, Iryna Shpinareva

“…The research also highlights emerging trends in blockchain development, particularly hybrid models and AI-driven optimization techniques, which can enhance blockchain efficiency and security. …”
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Application of artificial intelligence in the diagnosis of malignant digestive tract tumors: focusing on opportunities and challenges in endoscopy and pathology by Yinhu Gao, Peizhen Wen, Yuan Liu, Yahuang Sun, Hui Qian, Xin Zhang, Huan Peng, Yanli Gao, Cuiyu Li, Zhangyuan Gu, Huajin Zeng, Zhijun Hong, Weijun Wang, Ronglin Yan, Zunqi Hu, Hongbing Fu

“…Results In the field of endoscopy, multiple deep learning models have significantly improved detection rates in real-time polyp detection, early gastric cancer, and esophageal cancer screening, with some commercialized systems successfully entering clinical trials. …”
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Large-scale S-box design and analysis of SPS structure by Lan ZHANG, Liangsheng HE, Bin YU

“…A class of optimal linear transformation P over a finite field<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> <msup> <mrow> <mrow><mo>(</mo> <mrow> <msubsup> <mi>F</mi> <mn>2</mn> <mi>m</mi> </msubsup> </mrow> <mo>)</mo></mrow></mrow> <mn>4</mn> </msup> </mrow></math></inline-formula> was constructed based on cyclic shift and XOR operation.Using the idea of inverse proof of input-output relation of linear transformation for reference, a proof method was put forward that transformed the objective problem of optimal linear transformation into several theorems of progressive relation, which not only solved the proof of that kind of optimal linear transformation, but also was suitable for the proof of any linear transformation.By means of small-scale S-box and optimal cyclic shift-XOR linear transformation P, a large-scale S-box model with 2-round SPS structure was established, and a series of lightweight large-scale S-boxes with good cryptographic properties were designed.Only three kind of basic operations such as look-up table, cyclic shift and XOR were used in the proposed design scheme, which improved the linearity and difference uniformity of large-scale S-boxes.Theoretical proof and case analysis show that, compared with the existing large-scale S-box construction methods, the proposed large-scale S-box design scheme has lower computational cost and better cryptographic properties such as difference and linearity, which is suitable for the design of nonlinear permutation coding of lightweight cryptographic algorithms.…”
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Multi-Source, Fault-Tolerant, and Robust Navigation Method for Tightly Coupled GNSS/5G/IMU System by Zhongliang Deng, Zhichao Zhang, Zhenke Ding, Bingxun Liu

“…Compared with standard Kalman filtering (EKF) and advanced multi-rate Kalman filtering (MRAKF), the proposed algorithm achieved 28.3% and 53.1% improvements in its <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mi>σ</mi></mrow></semantics></math></inline-formula> error, respectively, significantly enhancing the accuracy and reliability of the multi-source fusion navigation system.…”
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From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications by Evgenia Gkintoni, Anthimos Aroutzidis, Hera Antonopoulou, Constantinos Halkiopoulos

“…High computational cost is prohibitive to the use of deep learning models in real-world applications, therefore indicating a need for the development and application of optimization techniques. …”
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ES-Net Empowers Forest Disturbance Monitoring: Edge–Semantic Collaborative Network for Canopy Gap Mapping by Yutong Wang, Zhang Zhang, Jisheng Xia, Fei Zhao, Pinliang Dong

“…Canopy gaps are vital microhabitats for forest carbon cycling and species regeneration, whose accurate extraction is crucial for ecological modeling and smart forestry. However, traditional monitoring methods have notable limitations: ground-based measurements are inefficient; remote-sensing interpretation is susceptible to terrain and spectral interference; and traditional algorithms exhibit an insufficient feature representation capability. …”
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Design and trial of precision spraying system for weeds in winter wheat field at tillering stage by Bo Li, Peijie Guo, Yu Chen, Jun Chen, Haiying Wang, Jing Zhang, Zhixing Zhang

“…In this study, a precision spraying control method is proposed to reduce the effect of camera frame rate on weed localization failure through three sets of position determination regions, and to address the effect of solenoid valve response frequency on precision spraying by controlling the spray nozzle to continuously spray herbicides on clustered weeds through a velocity-adaptive dynamic overlap region. To improve the accuracy of weed detection, GCGS-YOLO is proposed as a weed target detection model, and we integrate the Global Context (GC) attention mechanism with the traditional C3 module to optimize the backbone feature extraction network, and introduce the GSConv module to improve the neck network. …”
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The application of blockchain with a comparative approach and its impact on risk, flexibility and internal control evaluation by mohammadsadegh aminipoor, HamidReza GholamniaRoshan, azadeh kiapour, Iman Dadashi

“…Overall, blockchain can help improve risk, flexibility and internal control assessment. …”
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Flexible imputation toolkit for electronic health records by Alireza Vafaei Sadr, Jiang Li, Wenke Hwang, Mohammed Yeasin, Ming Wang, Harold Lehmann, Ramin Zand, Vida Abedi

“…Our findings validate that Pympute’s Flexible method significantly improves imputation performance compared to the single model approach. …”
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