Risk prediction method for power Internet of Things operation based on ensemble learning by Chao Hong, Xiaoyun Kuang, Yiwei Yang, Yixin Jiang, Yunan Zhang

“…Compared with traditional models, the accuracy was 98.61%, and the overall accuracy was improved by 0.60%. …”
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Role,application and challenges of IoT in smart EV charging management:a review by Tripti Kunj, Kirti Pal

“…Additionally, the paper emphasizes the importance of adaptive algorithms and machine learning models for predictive maintenance and efficient resource allocation. …”
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Emerging and Pioneering AI Technologies in Aesthetic Dermatology: Sketching a Path Toward Personalized, Predictive, and Proactive Care by Diala Haykal

“…Results: This piece highlights how AI-based imaging and predictive tools enable more precise diagnostics and tailored treatment protocols, leading to improved patient outcomes and satisfaction. Some of the key benefits of AI in aesthetic dermatology include the ability to detect subtle skin changes, simulate treatment outcomes, and adjust interventions in real time. …”
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Beyond purchase patterns: harnessing predictive analytics to anticipate unarticulated consumer needs by Khaled Alshaketheep, Hind Al-Ahmed, Ahmad Mansour

“…The findings reveal that predictive analytics serves as a powerful mediator between heterogeneous data inputs and improved organizational responsiveness, significantly contributing to the identification of unexpressed needs and enhancement of market performance. …”
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Water Quality Monitoring: A Water Quality Dataset from an On-Site Study in Macao by Jiawei Gao, Bochao Chen, Su-Kit Tang

“…Among these models, Random Forest exhibited the best overall performance, achieving an accuracy of 98.10% and an F1 score of 98.99%. …”
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Artificial Intelligence in Gastroenterology: A Comprehensive Review by Raju Vaishya, Mahesh Kumar Goenka, Anupam Sibal, Sujoy Kar, Sangita Reddy

“…In capsule endoscopy, AI can significantly reduce reading time with improved algorithms to increase sensitivity and specificity in identifying gastrointestinal abnormalities. …”
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High-accuracy prediction of vessels’ estimated time of arrival in seaports: A hybrid machine learning approach by Sunny Md. Saber, Kya Zaw Thowai, Muhammad Asifur Rahman, Md. Mehedi Hassan, A.B.M. Mainul Bari, Asif Raihan

“…Compared to existing machine learning algorithms, our stacking model exhibits superior prediction performance. …”
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Absence and Blow-Up of Solutions to Singular Perturbation Problems in the Case of Exchange of Stabilities by M. A. Terentyev

“…Such problems often occur as models in chemical kinetics. There are lots of works that establish the existence and asymptotic behavior of solutions to such problems. …”
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Future Era of Accountants under the Impact of AI by Guan Ran

“…As AI reshapes the industry, accountants must develop expertise in data analytics, predictive modeling, and cybersecurity to remain competitive. …”
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Operational factors influencing quality control in ore milling: a systematic review by Eliana de Jesus Lopes, Guilherme Graciano dos Santos, Adriano Ricardo Almeida Alexandre

“…The identified studies explore advanced techniques such as algorithms and mathematical modeling to optimize the grinding process and improve product quality. …”
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Studies on Underwater Image Processing Using Artificial Intelligence Technologies by Sugunapriya A, Markkandan S

“…The findings of this survey suggest promising directions for future research, particularly in the development of more sophisticated deep learning models that can further improve image quality and contribute to the underwater exploration and monitoring system.…”
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An Overview of the Empirical Evaluation of Explainable AI (XAI): A Comprehensive Guideline for User-Centered Evaluation in XAI by Sidra Naveed, Gunnar Stevens, Dean Robin-Kern

“…Recent advances in technology have propelled Artificial Intelligence (AI) into a crucial role in everyday life, enhancing human performance through sophisticated models and algorithms. However, the focus on predictive accuracy has often resulted in opaque black-box models that lack transparency in decision-making. …”
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Impacts of noise and interference on the bit error rate of the FBMC-OQAM modulation scheme in 5G systems by A. Androon, O. V. Tikhonova

“…The graphical and numerical data obtained through computer modeling demonstrates improved BER in 5G networks using FBMC-OQAM. …”
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The role of physical metallurgical relationships in enhancing alloy properties prediction and design: A case study on Q&P steel by Yong Li, Hua Li, Chenchong Wang, Pedro Eduardo Jose Rivera‐Diaz‐del‐Castillo

“…To address this, this study proposes a novel framework that combines PM knowledge graphs (PMKGs) with graph neural networks (GNNs) to predict the tensile properties of quenching and partitioning steels, using genetic algorithms for dual‐objective optimization. Compared to traditional artificial intelligence (AI) models, this framework shows significant advantages in predicting ultimate tensile strength (UTS) and total elongation (TEL) with higher accuracy and stability. …”
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An Unmanned Delivery Vehicle Path-Planning Method Based on Point-Graph Joint Embedding and Dual Decoders by Jiale Cheng, Zhiwei Ni, Wentao Liu, Qian Chen, Rui Yan

“…Hence, a path-planning model is presented to tackle the routing dilemma of UDVs in logistics. …”
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Advancing Spike Sorting Through Gradient‐Based Preprocessing and Nonlinear Reduction With Agglomerative Clustering by Mohammad Amin Lotfi, Fatemeh Zareayan Jahromy, Mohammad Reza Daliri

“…In the challenging portion of the dataset, our models demonstrated a 12% improvement in accuracy. …”
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APT Adversarial Defence Mechanism for Industrial IoT Enabled Cyber-Physical System by Safdar Hussain Javed, Maaz Bin Ahmad, Muhammad Asif, Waseem Akram, Khalid Mahmood, Ashok Kumar Das, Sachin Shetty

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An Underground Goaf Locating Framework Based on D-InSAR with Three Different Prior Geological Information Conditions by Kewei Zhang, Yunjia Wang, Feng Zhao, Zhanguo Ma, Guangqian Zou, Teng Wang, Nianbin Zhang, Wenqi Huo, Xinpeng Diao, Dawei Zhou, Zhongwei Shen

“…Furthermore, this investigation discusses the influence of deformation spatial resolution, the impacts of azimuth determination methodologies, and performance comparisons between non-hybrid and hybrid optimization algorithms. This study demonstrates that aligning the selection of deformation models with different types of prior geological information significantly improves the accuracy of underground goaf detection. …”
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Breeding of Solanaceous Crops Using AI: Machine Learning and Deep Learning Approaches—A Critical Review by Maria Gerakari, Anastasios Katsileros, Konstantina Kleftogianni, Eleni Tani, Penelope J. Bebeli, Vasileios Papasotiropoulos

“…Through advanced algorithms and predictive models, ML and DL facilitate the identification and optimization of key traits, including higher yield, improved quality, pest resistance, and tolerance to extreme climatic conditions. …”
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Protecting Industrial Control Systems From Shodan Exploitation Through Advanced Traffic Analysis by Sayed Reza Ghazinour Naeini, Alireza Shameli-Sendi, Masoume Jabbarifar

“…This research introduces protocol analysis as a novel feature in network traffic analysis, significantly improving detection accuracy over models that rely solely on traditional network features. …”
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