Impact of Artificial Intelligence and Virtual Reality on Educational Inclusion: A Systematic Review of Technologies Supporting Students with Disabilities by Angelos Chalkiadakis, Antonia Seremetaki, Athanasia Kanellou, Maria Kallishi, Anastasia Morfopoulou, Marina Moraitaki, Sofia Mastrokoukou

“…Ethical concerns such as privacy and algorithmic bias are cited as key areas that need careful consideration. …”
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HSI Reconstruction: A Spectral Transformer With Tensor Decomposition and Dynamic Convolution by Le Sun, Xihan Ma, Xinyu Wang, Qiao Chen, Zebin Wu

“…Conversely, traditional iterative optimization algorithms are built upon sound mathematical derivations. …”
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UAV-based remote sensing of chlorophyll-a concentrations in inland water bodies: a systematic review by Nobubelo Ngwenya, Tsitsi Bangira, Mbulisi Sibanda, Seifu Kebede Gurmessa, Tafadzwanashe Mabhaudhi

“…Monitoring chlorophyll-a content is crucial for irrigation water quality, as excessive levels can harm water bodies and reduce their volumetric capacity due to algal growth. While satellite data enhances monitoring, its coarse resolution limits application in small water bodies. …”
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An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change by J. D. Jakeman, M. Perego, D. T. Seidl, T. A. Hartland, T. R. Hillebrand, M. J. Hoffman, S. F. Price

“…<p>This study investigated the computational benefits of using multi-fidelity statistical estimation (MFSE) algorithms to quantify uncertainty in the mass change of Humboldt Glacier, Greenland, between 2007 and 2100 using a single climate change scenario. …”
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Application and Challenges of Artificial Intelligence in Different Branches of Dentistry by Ali Mirzaei, Melika Mollaei, Anahita Lotfizadeh, Mehdi Aryana, Alireza Ebrahimpour

“…Current challenges include data security, algorithmic bias, and ethical compliance. Conclusion: While AI shows promise in advancing dental diagnostics and treatment accuracy, successful clinical integration requires addressing privacy concerns, establishing regulatory standards, and developing comprehensive professional training programs. …”
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Sparse Linear Discriminant Analysis With Constant Between-Class Distance for Feature Selection by Shuangle Guo, Yongxia Li, Jianguang Zhang, Yue Liu, Tian Tian, Mengchen Guo

“…These two drawbacks of TR-LDA significantly reduce the performance of feature selection algorithms based on it. To overcome these drawbacks, this paper proposes the sparse LDA with constant between-class distance (SLDA-CBD) model to select relavant features. …”
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Butterfly magnetoreception based neighbour awareness strategy protocol for autonomous aerial vehicles by Janjhyam Venkata Naga Ramesh, C. Dastagiraiah, Suraya Mubeen, W. Deva Priya, M. Kameswara Rao, B. H. K. Bhagat Kumar

“…ML algorithms ensure optimal energy consumption and risk mitigation by dynamically selecting the shortest path, even under abrupt environmental changes. …”
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Open-Source vs. Commercial Photogrammetry: Comparing Accuracy and Efficiency of OpenDroneMap and Agisoft Metashape by A. Kostrzewa, A. Płatek-Żak, P. Banat, Ł. Wilk

“…Commercial software typically offers higher accuracy but comes at a high cost, while open-source solutions provide a free alternative, though they are less intuitive for some users. …”
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A new approach for diabetes risk detection using quadratic interpolation flower pollination neural network by Yulianto Triwahyuadi POLLY, Adriana FANGGIDAE, Juan Rizky Mannuel LEDOH, Clarissa Elfira AMOS PAH, Bertha S. DJAHI, Kisan Emiliano Rape TUPEN

“…These algorithms were tested on a diabetes risk dataset divided into training, validation, and testing subsets. …”
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A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

“…The classical models utilized Genetic Algorithms (CGA) and Particle Swarm Optimization (CPSO) for hyperparameter tuning, while the quantum-inspired models employed Quantum Genetic Algorithms (QGAs) and Quantum Particle Swarm Optimization (QPSO). …”
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Integrating machine learning and sentiment analysis in movie recommendation systems by Amany M. Sarhan, Hager Ayman, Mariam Wagdi, Bassant Ali, Aliaa Adel, Rahf Osama

“…Abstract The fast growth of the film business, along with an ever-increasing number of movie options, has highlighted the need for better recommendation algorithms. This study investigates the application of sentiment analysis in a movie recommendation system with the goal of improving the user experience. …”
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Procuring flexibility in power systems with incentive-based grid access requests by Mohsen Banaei, Francesco D’Ettorre, Razgar Ebrahimy, Mads R. Almassalkhi, Henrik Madsen

“…The proposed method includes algorithms at both the end-user level for controllable device operation and the aggregator level for managing the grid access requests. …”
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PV Module Soiling Detection Using Visible Spectrum Imaging and Machine Learning by Boris I. Evstatiev, Dimitar T. Trifonov, Katerina G. Gabrovska-Evstatieva, Nikolay P. Valov, Nicola P. Mihailov

“…In this study, visible spectrum data and machine learning algorithms were used for the identification of soiling. …”
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Computational Linguistics Applications in AI-Based Investment and Cost Structuring Models by Miralieva Dilafruz, Ramatov Jumaniyoz, Azimova Lola, Khusamiddinova Malika, Alimbaeva Shahlo, Omonova Laylo

“…Computational linguistics is deeply embedded in algorithmic financial models and reshapes cost forecasting frameworks through data-driven semantic interpretation. …”
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GA-TongueNet: tongue image segmentation network using innovative DiFP and MDi for stable generalization ability by Zhiyu Dong, Le Zhao, Yajun Fan, Haihua Ma, Changle Shao, Yiran Zhang, Peng Li

“…Due to challenges such as insufficient available sample size and complex background, the generalization and robustness of current tongue segmentation algorithms are usually poor, which seriously hinders the practicality of tongue diagnosis. …”
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Improving Disparity Consistency With Self-Refined Cost Volumes for Deep Learning-Based Satellite Stereo Matching by Jiyong Kim, Seoyeon Cho, Minkyung Chung, Yongil Kim

“…Stereo matching algorithms are considered one of the most important subtasks in 3-D reconstruction, as 3-D coordinates are derived from the disparity values of pixels obtained through stereo matching. …”
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MolNexTR: a generalized deep learning model for molecular image recognition by Yufan Chen, Ching Ting Leung, Yong Huang, Jianwei Sun, Hao Chen, Hanyu Gao

“…Scientific contribution MolNexTR is a novel image-to-graph model that incorporates a unique dual-stream encoder to extract complex molecular image features, and combines chemical rules to predict atoms and bonds while understanding atom and bond layout rules. In addition, it employs a series of novel augmentation algorithms to significantly enhance the robustness and performance of the model.…”
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A Feature-Driven Inception Dilated Network for Infrared Image Super-Resolution Reconstruction by Jiaxin Huang, Huicong Wang, Yuhan Li, Shijian Liu

“…Image super-resolution (SR) algorithms based on deep learning yield good visual performances on visible images. …”
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APPLICATION OF ARTIFICIAL NEURON NETWORK AND FUZZY INFERENCE IN THE HOUSEPLANT WATERING INTELLIGENT SYSTEM by Roman Korostenskyi, Igor Olenych

“…Moreover, the proposed algorithms can be implemented on low-power computational platforms commonly used in automation and IoT systems. …”
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A comparative study of deepfake facial manipulation technique using generative adversarial networks by Wasin Al Kishri, Jabar H. Yousif, Mahmood Al Bahri, Muhammad Zakarya, Naveed Khan, Sanad Sulaiman Al Maskari, Ahmet Gurhanli

“…In recent years, Deepfake algorithms have been designed to exchange faces or modify facial features, potentially leading to more severe problems in this context. …”
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