On the Achievable User Number of the Downlinks in Cellular-Based Machine-to-Machine Communications by Yingbo Li, Chen Chen, Lin Bai, Ye Jin

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Medical Device Failure Predictions Through AI-Driven Analysis of Multimodal Maintenance Records by Noorul Husna Abd Rahman, Khairunnisa Hasikin, Nasrul Anuar Abd Razak, Ayman Khallel Al-Ani, D. Jerline Sheebha Anni, Prabu Mohandas

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An Integrated Strategy for Interpretable Fault Diagnosis of UAV EHA DC Drive Circuits Under Early Fault and Imbalanced Data Conditions by Yang Li, Zhen Jia, Jie Liu, Kai Wang, Peng Zhao, Xin Liu, Zhenbao Liu

“…This process effectively saves computational resources while significantly reducing the risk of overfitting. …”
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Bayesian adaptation in Poisson cognitive systems by Aleksander A. Solodov

“…In particular, to describe the stochastic properties of cognitive systems and the possibility of creating an optimal algorithm, the Bayesian approach recognized in a number of philosophical works is applied.The optimal estimate by the criterion of the minimum standard error is, as is known, a posteriori mathematical expectation of a random estimated value, which is applied in this work. …”
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Machine learning approaches reveal methylation signatures associated with pediatric acute myeloid leukemia recurrence by Yushuang Dong, HuiPing Liao, Feiming Huang, YuSheng Bao, Wei Guo, Zhen Tan

“…Incremental Feature Selection was performed to evaluate these results, and optimal subsets were identified using Decision Tree and Random Forest methods. …”
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Electric Boats and Electric Vehicles Data-Driven Approach for Enhanced Resilience in Power Distribution Networks by Abdullah Ali M. Alghamdi, Dilan Jayaweera

“…These include advanced EV and E-Boat dispatch models that use changing geospatial data to approximate motion conditions and charging/discharging requirements, enabling energy-efficient and optimized dispatch. Detailed simulations with comprehensive performance analysis demonstrate the proposed algorithm’s superiority in achieving optimal solutions within shorter computational times. …”
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Impact of Parameters and Tree Stand Features on Accuracy of Watershed-Based Individual Tree Crown Detection Method Using ALS Data in Coniferous Forests from North-Eastern Poland by Marcin Kozniewski, Łukasz Kolendo, Szymon Chmur, Marek Ksepko

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Ensemble learning guided survival prediction and chemotherapy benefit analysis in high-grade chondrosarcoma: A study based on the surveillance, epidemiology, and end results (SEER)... by Xu Zheng, Longqiang Shu, Shanyi Lin, Hanqiang Jin, Xiaoyu Wang, Ting Yuan

“…Ensemble learning has better overall performance than single computational approaches for clinical decision. The primary objective was to select prognostic variables and develop optimal ensemble learning algorithms for survival prediction and analyzing chemotherapy benefit in high-grade chondrosarcoma. …”
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Rail Transit Prediction Based on Multi-View Graph Attention Networks by Li Wang, Xin Wang, Jiao Wang

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Ai-powered digital twin in the industrial IoT by Željko Bolbotinović, Saša D. Milić, Žarko Janda, Dragan Vukmirović

“…According to DT needs and hierarchical data processing, as well as edge, fog, and cloud computing, the paper presents state-of-the-art ML models and algorithms. …”
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A Review on the Advances, Applications, and Future Prospects of Post-Quantum Cryptography in Blockchain and IoT by Yong Wang, Eddie Shahril Ismail

“…This framework combines hybrid key exchange mechanisms, dual-signature schemes, and PQC-compatible Merkle trees, supported by a discrete multi-objective optimization model to select algorithms that meet real-world constraints. …”
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The robustness of popular multiclass machine learning models against poisoning attacks: Lessons and insights by Majdi Maabreh, Arwa Maabreh, Basheer Qolomany, Ala Al-Fuqaha

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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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Prediction of Thermal and Optical Properties of Oxyfluoride Glasses Based on Interpretable Machine Learning by Yuhao Xie, Xiangfu Wang

“…Based on the components of glasses, four algorithms, namely K-Nearest Neighbor, Random Forest, Support Vector Machine, and eXtreme Gradient Boosting, were used to construct an optimal machine learning model to predict the thermal and optical properties of oxyfluoride glass, namely glass transition temperature, density, Abbe number, liquidus temperature, thermal expansion coefficient, and refractive index. …”
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How low can you go: evaluating electrode reduction methods for EEG-based speech imagery BCIs by Maurice Rekrut, Maurice Rekrut, Johannes Ihl, Tobias Jungbluth, Antonio Krüger, Antonio Krüger

“…In this study, we evaluated several electrode reduction algorithms in combination with various feature extraction and classification methods across three distinct EEG-based speech imagery datasets to identify the optimal number and position of electrodes for SI-BCIs. …”
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Skip-Connected CNN Exploiting BNN Surrogate for Antenna Modelling by Yubo Tian, Jinlong Sun, Zhiwei Zhu

“…The combination of evolutionary algorithms with full-wave electromagnetic (EM) simulation software is an effective method for antenna optimal design. …”
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Approach to knowledge management and the development of a multi-agent knowledge representation and processing system by E. I. Zaytsev, E. V. Nurmatova

“…Methods for distribution of intelligent software agents on the MKRPS nodes are proposed along with algorithms for optimizing the logical structure of the distributed knowledge base (DKB) to improve the performance of the MKRPS in terms of volume, cost and time criteria.Conclusions. …”
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Multi-objective artificial-intelligence-based parameter tuning of antennas using variable-fidelity machine learning by Slawomir Koziel, Anna Pietrenko-Dabrowska, Stanislaw Szczepanski

“…Due to the reliance on computationally-expensive electromagnetic (EM) simulations, the use of conventional algorithms is prohibitive. …”
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Study on the parameters of the matrix NTRU cryptosystem by LI Zichen, WU Qinghao, SONG Jiashuo, PENG Haipeng

“…With the rapid development of quantum computers， post-quantum cryptography has emerged as a prominent area of research in cryptography.ObjectivesIn order to avoid the decryption failure in matrix NTRU as NTRU， the Matrix NTRU algorithm was optimized.MethodsBased on the method of constraining the parameter space in congruent cryptographic algorithms， a method for optimal selection of the parameter space of matrix NTRU cryptographic regimes was proposed. …”
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State-of-the-Art on IoV-Based Deep Learning Framework for Enhanced Driving Behavior Recognition: Recent Progress, Technology Updates, Challenges, and Future Direction by Hongguang Li, Shafrida Sahrani, Mahidur R. Sarker, Yinglin Xiao

“…However, these advanced algorithms still face several challenges. We analyze relevant literature from 2015 to 2024, to uncover key trends and gaps in the development of applications for identifying dangerous driving behaviors, with a primary focus on optimizing integration to improve the accuracy and real-time capability of driving behavior prediction. …”
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