Towards a minimum universal features set for IoT DDoS attack detection by Osama Ebrahem, Salah Dowaji, Suhel Alhammoud

“…Abstract Dimensionality reduction is one basic and critical technology for data mining, especially in the current “big data” era. …”
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Parametric Analysis of Control Techniques for 15 MW Semi-Submersible Floating Wind Turbine by Taesu Jeon, Byung-Soo Kim, Jaecheon Kim, Insu Paek, Chang-Hyuck Lim

“…In this study, a composite control algorithm based on classical control methods is developed to achieve all control objectives, such as power production, load reduction, and motion reduction, for the floating wind turbine. …”
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Human footprint with machine learning identifies risks of the invasive weed Conyza sumatrensis across land-use types under climate change by Hua Cheng, Kasper Johansen, Baocheng Jin, Shiqin Xu, Xuechun Zhao, Liqin Han, Matthew F. McCabe

“…E.Walker. Different algorithms yielded large variations in the predicted area of C. sumatrensis. …”
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CNN Based Fault Classification and Predition of 33kw Solar PV System with IoT Based Smart Data Collection Setup by K. Punitha, G. Sivapriya, T. Jayachitra

“…Therefore, CNN is used as the fault prediction also. The model is implemented using Python programming language and demonstrated its effectiveness on test cases. …”
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Enabling Power Systems With SQKD in Presence of Remote Nodes by Mariam Gado, Muhammad Ismail

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Chronic Fibrosing Interstitial Lung Disease with Progressive Phenotype by L. P. Ananieva, S. N. Avdeev, I. Е. Tyurin, A. М. Lila, A. I. Zagrebneva, А. L. Maslyanskiy, S. A. Terpigorev, I. V. Stepanyan, E. L. Lashina, O. V. Vasilieva, O. S. Lukina, E S. Pershina, А. А. Klimenko, N. A. Shostak, E. L. Nasonov

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PRINCIPLES OF ANTIBIOTIC TREATMENT OF OUT-OF-HOSPITAL UPPER RESPIRATORY TRACT INFECTIONS IN CHILDREN by A. L. Zaplatnikov, N. V. Koroid, A. A. Girina, I. V. Neyman

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On novel security systems based on the 2-cyclic refined integers and the foundations of 2-cyclic refined number theory by Mohammad Abobala, Hasan Sankari, Mohamed Zeina

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Detection of Substation Pollution in District Heating and Cooling Systems: A Comprehensive Comparative Analysis of Machine Learning and Artificial Neural Network Models by Emrah ASLAN, Yıldırım ÖZÜPAK

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Solving non-binary constraint satisfaction problems using GHD and restart. by Fatima AIT HATRIT, Kamal AMROUN, Professor

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Research on Migration Strategy of Mobile Agent in Wireless Sensor Networks by Dai Ting, Huang Haiping, Lu Yang, Wang Ruchuan, Pan Xinxing

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To the 110 anniversary since the birth of professor E.A.Vasyukova by Alexandr Sergeevich Ametov, Elena Valerievna Doskina, Irina Ivanovna Kochergina, Olga Mikhailovna Smirnova, Ekaterina Evgenyevna Mishina

“…Ekaterina Alekseevna had long and difficult career path - from research assistant to the director of the All-Russian Institute of Experimental Endocrinology(now Endocrinology Research Centre), was head of it for 10 years, a long time was head of the Department of Endocrinology at the Central Institute of Advanced Medical Ministry of Health (now the Academy of Postgraduate Education). She had more than 200 publications, including 14 monographs, collections and algorithms in endocrinology. …”
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Carbon Sequestration Strategies in Regenerative Agricultural Systems by Leveraging Wireless Sensor Networks for Precision Carbon Management by Al-Jawahry Hassan M., AI_Sadi Hafidh l., Rajasekhar Boddu

“…In this study, a total approach towards optimizing carbon sequestration strategies using advanced technologies like Wireless Sensor Network (WSN), Digital Twin model, and predictive algorithms like Random Forest Regression and gradient boosting are presented. …”
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Effective Dose Estimation in Computed Tomography by Machine Learning by Matteo Ferrante, Paolo De Marco, Osvaldo Rampado, Laura Gianusso, Daniela Origgi

“…E calculated by DTS was chosen as the target value for prediction. Different machine learning algorithms were selected, optimizing parameters to achieve the best performance for each algorithm. …”
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Analysis and Identification of Factors Influencing the Survival of Burn Injury Patients with an Artificial Intelligence Approach by Sara Hashemi, Shahla Faramarzi, Laya Rahmani Pirouz, Azita Yazdani

“…Conclusion: The use of machine learning algorithms in predicting the survival of burn patients is promising. …”
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A Novel Approach to Faster Convergence and Improved Accuracy in Deep Learning-Based Electrical Energy Consumption Forecast Models for Large Consumer Groups by A. Jayanth Balaji, Binoy B. Nair, D. S. Harish Ram, Kuruvachan Kalluvelil George

“…Effectiveness of models is validated with eight deep learning algorithms trained for two forecasting horizons. Results demonstrate a 93.74% improvement on an average in convergence compared to conventional mini-batch sizes, achieving one among top three accuracy across various prediction horizons and user categories. …”
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Pix2Pix-Based Modelling of Urban Morphogenesis and Its Linkage to Local Climate Zones and Urban Heat Islands in Chinese Megacities by Mo Wang, Ziheng Xiong, Jiayu Zhao, Shiqi Zhou, Qingchan Wang

“…This study employed the Conditional Generative Adversarial Network (cGAN) of the Pix2Pix algorithm as a predictive model to simulate 3D urban morphologies aligned with Local Climate Zone (LCZ) classifications. …”
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Intersections of Big Data and IoT in Academic Publications: A Topic Modeling Approach by Diana-Andreea Căuniac, Andreea-Alexandra Cîrnaru, Simona-Vasilica Oprea, Adela Bâra

“…Topic 6 focuses on technical aspects such as <i>modeling, system performance and prediction algorithms</i>. It delves into the efficiency of IoT networks with terms like “accuracy”, “power” and “performance” standing out.…”
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An automated network-based tool to search for metabolic vulnerabilities in cancer by Luis V. Valcárcel, Edurne San José-Enériz, Raquel Ordoñez, Iñigo Apaolaza, Danel Olaverri-Mendizabal, Naroa Barrena, Ana Valcárcel, Leire Garate, Jesús San Miguel, Antonio Pineda-Lucena, Xabier Agirre, Felipe Prósper, Francisco J. Planes

“…Here, we present gmctool, a freely accessible online tool that allows us to accomplish this task in a simple, efficient and intuitive environment. gmctool exploits the concept of genetic Minimal Cut Sets (gMCSs), a theoretical approach to synthetic lethality based on genome-scale metabolic networks, including a unique database of synthetic lethals computed from Human1, the most recent metabolic reconstruction of human cells. gmctool introduces qualitative and quantitative improvements over our previously developed algorithms to predict, visualize and analyze metabolic vulnerabilities in cancer, demonstrating a superior performance than competing algorithms. …”
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Bio inspired optimization techniques for disease detection in deep learning systems by A. Ashwini, Vanajaroselin Chirchi, S. Balasubramaniam, Mohd Asif Shah

“…This work assists researchers in selecting the most effective bio-inspired algorithm for disease categorization, prediction, and the analysis of high-dimensional biomedical data.…”
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