Comprehensive Review and Analysis of Cryptography Techniques in Cloud Computing by K. Sasikumar, Sivakumar Nagarajan

“…Cloud computing is a fast-growing industry that offers various online services, including software, computing resources, and databases. Its payment model is usage-based, whereas consistency is based on resource-sharing. …”
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SVF: Support Vector Federation by Mirko Polato, Roberto Esposito, Lorenzo Sciandra

“…Simple random perturbation works remarkably well in practice, and indeed we provide a bound on the approximation error of the learnt model which goes to zero as the number of input features grows. …”
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Artificial Neural Network Framework for Hybrid Control and Monitoring in Turning Operations by Bogdan Felician Abaza, Vlad Gheorghita

“…This paper proposes a hybrid control and monitoring framework designed to enhance turning operations by integrating artificial neural networks (ANNs) for predictive modeling and adaptive recalibration. The system leverages machine learning (ML) to improve machining efficiency, tool longevity, and energy consumption optimization. …”
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Zero-Shot Learning for Accurate Project Duration Prediction in Crowdsourcing Software Development by Tahir Rashid, Inam Illahi, Qasim Umer, Muhammad Arfan Jaffar, Waheed Yousuf Ramay, Hanadi Hakami

“…The implementation of the proposed automated duration prediction model is crucial for enhancing the success rate of crowdsourcing projects, optimizing resource allocation, managing budgets effectively, and improving stakeholder satisfaction.…”
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A deep learning approach for blood glucose monitoring and hypoglycemia prediction in glycogen storage disease by Ji Seung Ryu, Jang Hoon Ru, Yunkoo Kang, Sejung Yang

“…First, the models were used to predict the patients’ Glucose levels for the next hour. …”
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A Comparative Study in Fuzzy Control Systems for Cruise Control Vehicles by Adnan Shaout, Malek I El Amr

“…This paper pre-sents the state of the art in fuzzy models implementing adaptive cruise control (ACC) for vehicles and com-pares their respective results. …”
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Rolling window for detecting multiple Chan signatures to diagnose excessive water production by Ahmed MohamedSalih Musa Hamdoon, A. P. Mohammed Abdalla Ayoub Mohammed, A. P. Khaled Abdalla Elraies

“…A successful interactive model with the rolling window feature was developed to track slope changes in Chan signatures, resulting in a 7–10% improvement in pattern detection accuracy compared to static features. …”
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Sample-Efficient Multi-Agent DQNs for Scalable Multi-Domain 5G+ Inter-Slice Orchestration by Pavlos Doanis, Thrasyvoulos Spyropoulos

“…For (ii), we explore multi-agent DQN algorithms that can reduce action space complexity by orders of magnitude compared to standard DQN. …”
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Three-Stage Channel Split Dense Fusion Network for Single Image Deraining by ZHANG Shuting, WANG Changyue, WANG Changzhong, LENG Qiangkui

“…CSB uses channel split operation to split the rainy image into multiple channels, and applies different rain streaks removal methods according to different levels of features to reduce redundant features and network parameters, and improve the performance ability and computational efficiency of the model. …”
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Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction by Kuo-Yang Huang, Ying-Lin Hsu, Che-Liang Chung, Huang-Chi Chen, Ming-Hwarng Horng, Ching-Hsiung Lin, Ching-Sen Liu, Jia-Lang Xu

“…This paper details the model evaluation and demonstrates the feasibility and efficiency of edge intelligence in ventilator weaning decision support.…”
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Artificial Intelligence-based Approaches for Characterizing Plaque Components From Intravascular Optical Coherence Tomography Imaging: Integration Into Clinical Decision Support Sy... by Michela Sperti, Camilla Cardaci, Francesco Bruno, Syed Taimoor Hussain Shah, Konstantinos Panagiotopoulos, Karim Kassem, Giuseppe De Nisco, Umberto Morbiducci, Raffaele Piccolo, Francesco Burzotta, Fabrizio D’Ascenzo, Marco Agostino Deriu, Claudio Chiastra

“…Deep learning models, particularly convolutional neural networks, further improve performance by enabling automatic feature extraction. …”
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Pharmacological potential of 6,11-dihydro[1,2,4]triazolo[4’,3’:1,6]-pyrido[3,4-b]-5-carboxylic acid and its esters by S. O. Fedotov, A. S. Hotsulia

“…MarvinSketch 6.3.0, Hyper Chem 8, and AutoDock Tools-1.5.6 were used for creating ligand models. The enzymes had been prepared for analysis using Discovery Studio 4.0 and AutoDock Tools-1.5.6. …”
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Emerging Diagnostic Approaches for Musculoskeletal Disorders: Advances in Imaging, Biomarkers, and Clinical Assessment by Rahul Kumar, Kiran Marla, Kyle Sporn, Phani Paladugu, Akshay Khanna, Chirag Gowda, Alex Ngo, Ethan Waisberg, Ram Jagadeesan, Alireza Tavakkoli

“…Furthermore, reimbursement models have not caught up with many of these innovations, limiting access in resource-constrained healthcare settings. …”
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Optimizing Gammatone Cepstral Coefficients for Gear Fault Detection by Zrar Kh Abdul, Abdulbasit K. Al-Talabani, Wisam Hazim Gwad, Entisar Alkayal, Halgurd S. Maghdid, Safar Maghdid Asaad

“…Furthermore, optimizing the number of GTCC coefficients helps reduce model complexity. Experimental results demonstrate that optimizing GTCC parameters with GWO improves fault detection performance using an SVM classifier, achieving over 1% and 3% accuracy improvements on the PHM09 and DDS datasets, respectively.…”
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A HRWS SAR Motion Compensation Method with Multichannel Phase Correction by Liming Zhou, Minglong Deng, Jing He, Bing Wang, Shengmiao Zhang, Xuanyu Liu, Shunjun Wei

“…Many motion compensation algorithms have been used to improve the quality of single-channel SAR images, while fewer studies have been conducted on multichannel SAR motion compensation methods. …”
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Reactive power optimization via deep transfer reinforcement learning for efficient adaptation to multiple scenarios by Congbo Bi, Di Liu, Lipeng Zhu, Chao Lu, Shiyang Li, Yingqi Tang

“…Existing reinforcement learning algorithms alleviate the computational complexity in optimization but suffer from the inefficiency of model retraining for different operating scenarios. …”
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SC-Route: A Scalable Cross-Layer Secure Routing Method for Multi-Hop Inter-Domain Wireless Networks by Yanbing Li, Yang Zhu, Shangpeng Wang

“…Experimental results demonstrated that the proposed method achieves at least 28% improvement in effective throughput, reduces average authentication delay by approximately 30%, and increases the secure link ratio by at least 10%, outperforming mainstream routing algorithms under multi-constraint conditions.…”
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Research and application of mining AI video edge computing technology by ZHANG Liya, HAO Bonan, MA Zheng, YANG Zhifang

“…A lightweight software development kit (SDK) framework based on the register machine was proposed to decouple operators, improving the parallel computing ability of the algorithms and reducing the storage requirements of the SDK. …”
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CareNexus: Integrated solutions for Healthcare Communication by Alexandru Ioan BULZAN

“…A secure authentication based on multiple factors and the use of encryption algorithms, an interface based on different user roles and a prediction system based on model training had been implemented. …”
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CNN–Transformer gated fusion network for medical image super-resolution by Juanjuan Qin, Jian Xiong, Zhantu Liang

“…The global branch uses the self-attention mechanism of Transformer network, which can effectively mine the large-scale global information in the image and improve the overall quality of the image. The local branch uses the characteristic of dynamic convolution to adaptively adjust the convolution kernel parameters, which can enhance the feature extraction ability of convolutional neural network for multi-scale information and improve the detail restoration ability of the image without significantly increasing the network model size. …”
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