Blockchain Technology in Supply Chain Management Prospects and Challenges for Implementation by Peshattiwar Atish, P Mohanraj, A Anand Gerald, S Dharmalingam, Tiwari Mohit, G Swarnalakshmi

“…In response, this research presents a next-gen blockchain framework leveraging hybrid blockchain architectures, AI-integrated smart contracts, green consensus algorithms, and cross-platform interoperability strategies to bridge the gaps of the existing systems. …”
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Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition by Yu Ding, Wenjia Ni, Jiaxin Dong, Jie Yang, Shiyao Meng, Siwei Li

“…However, satellite-derived AOD datasets frequently suffer from missing values due to factors such as cloud cover, algorithmic limitations, and various atmospheric conditions. …”
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Spatiotemporal Dynamics of Urban Green Spaces and Climatic Vulnerability of Togolese Cities in the Context of Rapid Urbanisation: The Case of Lome and Kara by Yetondé Deton, Hodabalo Kamou, Abalo Atato, Bimare Kombate, Abalo Mabafei, Josef Yoka, Marra Dourma, Atsu Kudzo Guelly, Komlan Batawila, Koffi Akpagana

“…This study examines UGS spatiotemporal dynamics using Landsat imagery from 1988, 2000, 2012, and 2022, applying a supervised image classification approach with the maximum likelihood algorithm. Post-classification change detection quantified UGS loss. …”
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Optimum Combination of Spectral Variables for Crop Mapping in Heterogeneous Landscapes based on Sentinel-2 Time Series and Machine Learning by J. G. de Oliveira Júnior, J. C. D. M. Esquerdo, J. C. D. M. Esquerdo, R. A. C. Lamparelli, R. A. C. Lamparelli

“…First, we applied a data dimensionality reduction analysis using the PCA (Principal Component Analysis) method. …”
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Techno-economic analysis of a hybrid thermal desalination system integrated with a PVT collector by S. Rajesh, C. Chiranjeevi, Saboor Shaik, Pethurajan Vigneshwaran, Fayaz Hussain, C Ahamed Saleel, Asif Afzal

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Synchrony of Nitrogen Wet Deposition Inputs and Watershed Nitrogen Outputs Using Information Theory by Desneiges S. Murray, Edom Moges, Laurel Larsen, Michelle D. Shattuck, William H. McDowell, Adam S. Wymore

“…Information theoretic algorithms facilitated data‐driven inferences on the hydro‐biogeochemical processes influencing the fate of N wet deposition. …”
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Metastatic bone lesions of men in combination with an increase in serum PSA from the point of view of diagnosing carcinomas of unknown primary localization by O. V. Poslavska, I. S. Shponka, P. O. Hritsenko, M. Yu. Petrova

“…The aim of the work is to improve diagnostic algorithms, to investigate a complex of morphological, morphometric and immunohistochemical characteristics of metastatic foci in the bones, which are represented by adenocarcinomas of unknown primary localization in men with increased serological marker PSA, compared with primary carcinomas of the prostate gland. …”
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Visual impairment prevention by early detection of diabetic retinopathy based on stacked auto-encoder by Shagufta Almas, Fazli Wahid, Sikandar Ali, Ahmed Alkhyyat, Kamran Ullah, Jawad Khan, Youngmoon Lee

“…Unlike traditional CNN approaches, our method offers improved reliability by reducing time complexity, minimizing errors, and enhancing noise reduction. Leveraging a comprehensive dataset from KAGGLE containing 35,126 retinal fundus images representing one healthy (normal) stage and four DR stages, our proposed model demonstrates superior accuracy compared to existing deep learning algorithms. …”
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Effectiveness of AI for Enhancing Computed Tomography Image Quality and Radiation Protection in Radiology: Systematic Review and Meta-Analysis by Subo Zhang, Zhitao Zhu, Zhenfei Yu, Haifeng Sun, Yi Sun, Hai Huang, Lei Xu, Jinxin Wan

“…However, these results should be interpreted with caution due to the limited number of studies and the variability in AI algorithms. Further research is needed to clarify AI’s impact on radiation reduction and to establish clinical standards.…”
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Principles of physical factor selection in the early postoperative period of breast cancer treatment: a randomized controlled study by Inna S. Evstigneeva

“…Current models of onco-rehabilitation do not consider the patient’s functional impairment during combined treatment until the patient becomes incapacitated and the impairment develops into a chronic condition. AIM. To develop algorithms for selecting physical factors depending on the clinical and functional state of patients after radical surgical treatment of breast cancer (BC) in the early postoperative period. …”
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Quantum-Inspired Control Strategies for Reducing DC-Link Voltage Fluctuations in DFIG Wind Energy Converters by Sarika Shrivastava, Saifullah Khalid, Dinesh Kumar Nishad

“…By incorporating quantum-inspired algorithms into the Grid-Side Converter (GSC) control framework, the strategy dynamically adjusts PI gains using qubit-based probabilistic modeling—where control parameters exist simultaneously in multiple potential states, similar to quantum bits existing in both 0 and 1 states concurrently. …”
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Symmetrical Components Digital Filters for Microprocessor-Based Protection Input Signals by F. A. Romaniuk, V. Yu. Rumiantsev, Yu. V. Rumiantsev

“…Of all the varieties of digital filters of symmetrical components, filters of the negative and zero sequences are mainly used. As for the known algorithms of their software implementation, it is advisable to use filters that form orthogonal components of the required sequence from orthogonal components of phase or phase-to-phase values of signals. …”
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Task based evaluation of sparse view CT reconstruction techniques for intracranial hemorrhage diagnosis using an AI observer model by Matthew Tivnan, Irene Désirée Kikkert, Dufan Wu, Kai Yang, Jelmer M. Wolterink, Quanzheng Li, Rajiv Gupta

“…Traditional reconstruction algorithms, including Filtered Backprojection (FBP) and Model-Based Iterative Reconstruction (MBIR), often produce artifacts in sparse-view data. …”
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Iris: A Next Generation Digital Pathology Rendering Engine by Ryan Erik Landvater, Ulysses Balis

“…Further, it is able to buffer and compute high-fidelity reduction-enhancements for viewing low-power cytology with increased visual quality at a rate of 100–160 μs per slide tile, and with a cumulative median buffering rate of 1.36 GB of decompressed image data per second. …”
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Design of an intelligent AI-based multi-layer optimization framework for grid-tied solar PV-fuel cell hybrid energy systems by Prashant Nene, Dolly Thankachan

“…The results validate its capability when compared against traditional methods such as Genetic Algorithms and Particle Swarm Optimization. With this, we now have a scalable and real-time energy-efficient solution for future smart grid systems. • Integrated Intelligence Stack: Combines RL-ENN, T-STFREP, FL-DEO, GNNHSCO, and Q-GAN-ESO into a unified architecture for real-time control, forecasting, decentralized optimization, network routing, and synthetic scenario generation. • Real-Time, Scalable, and Privacy-Preserving: Enables adaptive energy dispatch, federated optimization without compromising data privacy, and graph-based power routing, making it suitable for large-scale, smart grid deployments. • Proven Long-Term Performance: Achieved significant improvements over traditional methods (GA, PSO) with 27.5 % lower NPC, 18.2 % reduction in COE, and 30.2 % increase in battery life, validated using 30 years of meteorological data.…”
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Planificación y optimización asistida por computadora de secuencias de ensamble mecánico. by L. L. Tomás García

“…The generated assembly sequences are preprocessed and optimized for the assembly Process Planning using Genetic Algorithms. This approach integrates the geometric and technological information of the assembly process, which allows reducing the number of elements and sequences to be processed with the consequent processing time and cost reduction.…”
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Life cycle assessment and multicriteria decision making analysis of additive manufacturing processes towards optimal performance and sustainability by Jayant M. Raut, Prashant B. Pande, Kamlesh V. Madurwar, Rajesh M. Bhagat, Satyajit S. Uparkar, Nilesh Shelke, Haytham F. Isleem, Arpita, Vikrant S. Vairagade

“…Experimental results prove that predictive accuracy can be achieved up to 85–90% by GPR, which reduces material wastage by 12%. …”
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Statistical Evaluation of Smartphone-Based Automated Grading System for Ocular Redness Associated with Dry Eye Disease and Implications for Clinical Trials by Rodriguez JD, Hamm A, Bensinger E, Kerti SJ, Gomes PJ, Ousler III GW, Gupta P, De Moraes CG, Abelson MB

“…The model utilizes the DeepLabV3 architecture for image segmentation, extracting two key features—horizontality and redness. The algorithm then uses these features to predict eye redness, validated by comparison with expert grader scores.Results: The bivariate model using both redness and horizontality performed best, with a Mean Absolute Error (MAE) of 0.450 points (SD=0.334) on the redness scale relative to expert scores. …”
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Forecasting Insurance Company Commitments with Long Short-Term Memory Models by Negar Tehraniyazdi, Reza Vaezi, Saeed Setayeshi, Iman Raeesi Vanani

“…A Long Short-Term Memory (LSTM) neural network algorithm is employed, recognized for its strong predictive capability in time series data. …”
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Enhancing Regional Topsoil Total Nitrogen Mapping Through Differentiated Fusion of Ground Hyperspectral Data and Satellite Images Under Low Vegetation Cover by Rongpeng He, Jihua Meng, Yanfei Du, Zhenxin Lin, Xinyan You, Xinyu Gao

“…Therefore, a differentiated fusion of enhanced multispectral image bands (DFE_MSIBs) method combined with Random Forest (RF) algorithms was developed for spectral inversion of STN content. …”
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