Innovative computing and blockchain technologies in agriculture for accelerating economic integration among Russia, China, and the Republic of Belarus by A. Yu. Mikhailov

“…Cloud computing refers to distributed computing technologies that use algorithms for network access to shared computing resources. …”
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Thermally Stable Ag2Se Nanowire Network as an Effective In‐Materio Physical Reservoir Computing Device by Takumi Kotooka, Sam Lilak, Adam Z. Stieg, James K. Gimzewski, Naoyuki Sugiyama, Yuichiro Tanaka, Takuya Kawabata, Ahmet Karacali, Hakaru Tamukoh, Yuki Usami, Hirofumi Tanaka

“…This study explored a material physical reservoir consisting of a material random network, called in‐materio physical reservoir computing (RC) to achieve efficient hardware systems. …”
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Transforming Precision Agriculture with Quantum Computing: A Novel Algorithm for Boosting Crop Yields and Optimizing Resources by Mukherjee Anshit, Basu Mallik Biswadip

“…The algorithm makes use of qubits to allow the real time data processing through IoT sensors to allow for real time monitoring and decision making. …”
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Smart distributed data factory volunteer computing platform for active learning-driven molecular data acquisition by Tsolak Ghukasyan, Vahagn Altunyan, Aram Bughdaryan, Tigran Aghajanyan, Khachik Smbatyan, Garegin A. Papoian, Garik Petrosyan

“…SDDF uses volunteer computing, leveraging the processing power of personal computers worldwide to accelerate quantum chemistry (DFT) calculations. …”
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Enhancing DDoS Attacks Mitigation Using Machine Learning and Blockchain-Based Mobile Edge Computing in IoT by Mahmoud Chaira, Abdelkader Belhenniche, Roman Chertovskih

“…In this paper, we present a novel approach to DDoS attack detection and mitigation that integrates state-of-the-art machine learning techniques with Blockchain-based Mobile Edge Computing (MEC) in IoT environments. Our solution leverages the decentralized and tamper-resistant nature of Blockchain technology to enable secure and efficient data collection and processing at the network edge. …”
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Quantifying the Impacts of Land Use and Land Cover Change on Watershed Hydrology Using Spatial Cloud Computing by Anwarelsadat Eltayeb Elmahal, Wifag Hassan Mahmoud, Ahmed Abdalla, Mohammed Mahmoud Ibrahim

“…We combined spatial cloud computing with hydrological analysis to investigate the relationship between LULCC and peri‐hydrological processes for four decades. …”
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Optimizing drawing frame variables to enhance polyester spun yarn quality using soft computing techniques by Mohsen Rezahasani, Habib Amiri Savadroodbari, Milad Razbin, Majid Safar Johari

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A Systematic Literature Review on Load-Balancing Techniques in Fog Computing: Architectures, Strategies, and Emerging Trends by Danah Aldossary, Ezaz Aldahasi, Taghreed Balharith, Tarek Helmy

“…Fog computing has emerged as a promising paradigm to extend cloud services toward the edge of the network, enabling low-latency processing and real-time responsiveness for Internet of Things (IoT) applications. …”
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Communication-efficient and privacy-preserving federated learning for medical image classification in multi-institutional edge computing by Nithin Melala Eshwarappa, Hojjat Baghban, Ching-Hsien Hsu, Po-Yen Hsu, Ren-Hung Hwang, Mu-Yen Chen

“…This indicates reduced processing time, which is particularly crucial in the field of medical diagnostics. …”
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Hardware-friendly implementation of physical reservoir computing with CMOS-based time-domain analog spiking neurons by Nanako Kimura, Ckristian Duran, Zolboo Byambadorj, Ryosho Nakane, Tetsuya Iizuka

“…Moreover, another technical advantage thanks to the bottom–up integration is the capability of dynamically capturing every neuron state in the network, which can significantly contribute to finding guidelines on how to enhance the performance for various computational tasks in temporal information processing. …”
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Developing an explainable machine learning and fog computing-based visual rating scale for the prediction of dementia progression by Zainab H. Ali, Esraa Hassan, Shimaa Elgamal, Nora El-Rashidy

“…Abstract Recently, dementia research has primarily concentrated on using Magnetic Resonance Imaging (MRI) to develop learning models in processing and analyzing brain data. However, these models often cannot provide early detection of affected brain regions. …”
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Soft Computing Solutions for Reducing the Carbon Footprint of Fly Ash Based Concrete. Advances in Civil Engineering by Awoyera, Paul O., Adetola, Joshua, Nayeemuddin, Mohammed, Mewada, Hiren, George Fadugba, Olaolu

“…The construction industry significantly contributes to environmental degradation,with many structures exhibiting high carbon footprints throughout their construction processes and lifespans.Activities such as cement hydration and other commoncon-struction practices substantially influence environmental conditions overtime,necessitating a critical evaluation of material and design choices.This study reported the environmental impact of fly ash(FA),which is largely used to enhance concrete strength.A prediction of two end point indicators,that is,global warming potential(GWP)and CO2 emission using soft computing methods are presented,which are particularly effective for handling complex,non linear relationships in environmental data.To achieve this, two machine learning approaches,the random forest(RF)and decision tree(DT)models,are employed to assess the environ- mental impact of structural materials and designs.Two data sets were obtained from reputable databases,including ResearchGate, Science Direct, Semantic Scholar,and Mendeley Data.The models are trained to explore the potential for optimizing structural designs and material selection stominimize environmental impacts.Feature importance is analyzed using Shapley values,providing insights into the most influential factors affecting GWP and CO2 emission Model performance is evaluated using R2 and root mean square error(RMSE) metrics. …”
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Structural knowledge-driven meta-learning for task offloading in vehicular networks with integrated communications, sensing and computing by Ruijin Sun, Yao Wen, Nan Cheng, Wei Wang, Rong Chai, Yilong Hui

“…Task offloading is a potential solution to satisfy the strict requirements of computation-intensive and latency-sensitive vehicular applications due to the limited onboard computing resources. …”
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The Effect of Trap Design on the Scalability of Trapped-Ion Quantum Technologies by Le Minh Anh Nguyen, Brant Bowers, Sara Mouradian

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Improvement of study process of mathematics in Vilnius College in higher education by Jovita Saldauskienė, Vytautas Virkutis

“…There are also analyzed the improvement of study process as well as the improvement of computing and trainings in the mathematics lessons. …”
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Characterizing the Inter-Core Qubit Traffic in Large-Scale Quantum Modular Architectures by Sahar Ben Rached, Isaac Lopez Agudo, Santiago Rodrigo, Medina Bandic, Artur Garcia-Saez, Sebastian Feld, Hans van Someren, Eduard Alarcon, Carmen G. Almudever, Sergi Abadal

“…Modular quantum processor architectures are envisioned as a promising solution for the scalability of quantum computing systems beyond the Noisy Intermediate Scale Quantum (NISQ) era. …”
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Compiler Optimization of Wide Memory Access for Aarch64 by Viacheslav Chernonog, Emin Gadzhiev, Andrey Dobrov

“…The popularity of ARM-based processors in HPC and cloud computing is gradually increasing and the development of compilers and code optimizations is important to achieve better use of hardware resources. …”
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SYSTEM AND ACTIVITY APPROACH TO THE PROBLEMS SOLUTION OF COMPUTER COMPETENCE DEVELOPMENT OF FUTURE TEACHERS OF VOCATIONAL EDUCATION by Yelena E. Neupokoeva, Nikolaj K. Chapaev

“…The scientific specification of system and activity approach in relation to conditions of the educational process aimed at the development of computer competence is presented in the article. …”
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Image Visual Quality: Sharpness Evaluation in the Logarithmic Image Processing Framework by Arnaud Pauwelyn, Maxime Carré, Michel Jourlin, Dominique Ginhac, Fabrice Meriaudeau

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Replicability Analysis for Natural Language Processing: Testing Significance with Multiple Datasets by Rotem Dror, Gili Baumer, Marina Bogomolov, Roi Reichart

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