Research on Feature Extracted Method for Flutter Test Based on EMD and CNN by Hua Zheng, Zhenglong Wu, Shiqiang Duan, Jiangtao Zhou

“…This research explores the connection between structural response signals and flutter from the perspective of artificial intelligence. The method allows for real-time, online prediction with low computational complexity.…”
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Performance comparison of different algorithms to secure the information for Wireless sensor Network by El Gatte Oumayma, El Abbassi Ahmed, Mouhib Omar, Tilioua Amine

“…The integration of blockchain technology with convolutional neural networks (CNNs) represents a promising frontier in decentralized artificial intelligence (AI). However, this fusion has led to considerable security within both the blockchain and AI communities. …”
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Large Language Models for UAVs: Current State and Pathways to the Future by Shumaila Javaid, Hamza Fahim, Bin He, Nasir Saeed

“…Their expanding capabilities present a platform for further advancement by integrating cutting-edge computational tools like Artificial Intelligence (AI) and Machine Learning (ML) algorithms. …”
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Analytical approaches to evaluate risk factors of multimorbidity: a systematic scoping review protocol by Alex Lewin, Poppy Alice Carson Mallinson, Sanjay Kinra, Judith Lieber, Chaisiri Angkurawaranon, Hirotomo Yamanashi, Chanchanok Aramrat, Nutchar Wiwatkunupakarn, Nick Birk, Wenbo Song, Mika Matsuzaki, Elliott Rogers

“…We will screen titles and abstracts using the artificial intelligence-aided software ASReview, followed by screening for eligible articles in full text and extracting data. …”
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Knowledge Driven Machine Learning Towards Interpretable Intelligent Prognostics and Health Management: Review and Case Study by Ruqiang Yan, Zheng Zhou, Zuogang Shang, Zhiying Wang, Chenye Hu, Yasong Li, Yuangui Yang, Xuefeng Chen, Robert X. Gao

“…Finally, we discuss the challenges, potential applications, and usage recommendations of KDML in PHM, with a particular focus on the critical need for interpretability to ensure trustworthy deployment of artificial intelligence in PHM.…”
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SensorDBSCAN: Semi-Supervised Active Learning Powered Method for Anomaly Detection and Diagnosis by Petr Ivanov, Maria Shtark, Alexander Kozhevnikov, Maksim Golyadkin, Dmitry Botov, Ilya Makarov

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Reconfigurable Integrated Photonic Unitary Neural Networks With Phase Encoding Enabled by In-Situ Training by Shengjie Tang, Cheng Chen, Qi Qin, Xiaoping Liu

“…Photonic neural networks are emerging as promising computing platforms for artificial intelligence (AI). Particularly, integrated photonic unitary neural networks (IPUNNs) are capable of mitigating gradient vanishing/explosion problems when deeper neural networks are constructed. …”
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An Integrated Consensus Improving Strategy Based on PL-Wasserstein Distance and Its Application in the Evaluation of Network Public Opinion Emergencies by Shitao Zhang, Zhenzhen Ma, Xiaodi Liu, Zhiying Wang, Lihui Jiang

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The Potential of Deep Learning Object Detection in Citizen-Driven Snail Host Monitoring to Map Putative Disease Transmission Sites by Kin Ho Chan, Julius Tumusiime, Liesbet Jacobs, Tine Huyse

“…However, expert validation is time-consuming and introduces a delay in verified data output. Thus, artificial intelligence could provide a solution by means of automated detection and counting of multiple snails collected from the field. …”
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An explainable deep learning model for diabetic foot ulcer classification using swin transformer and efficient multi-scale attention-driven network by R. Karthik, Armaano Ajay, Anshika Jhalani, Kruthik Ballari, Suganthi K

“…The proposed work also incorporates Grad-CAM-based Explainable Artificial Intelligence (XAI) to visualize and interpret the decision making of the network. …”
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Multi-Sensor Information Fusion with Multi-Scale Adaptive Graph Convolutional Networks for Abnormal Vibration Diagnosis of Rolling Mill by Rongrong Peng, Changfen Gong, Shuai Zhao

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Eco-innovative approaches for recycling non-polyester/cotton blended textiles by Chandra Manivannan Arun, Logeshwaran Panneerselvan, Gunasekhar Nachimuthu, Meredith Conaty, Thava Palanisami

“…In the sorting stage, integrating artificial intelligence (AI) and machine learning (ML) enhances efficiency and accuracy. …”
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Innovation Mirage: The Role of Technological Uncertainty in Military Instability by I. A. Istomin

“…Currently, experts express increasing concerns about the destabilizing effect of new weapons (including anti-missile and anti-satellite weapons, hypersonic missiles, autonomous lethal systems, and artificial intelligence). These assessments are rarely based on solid theoretical foundations. …”
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Association Analysis of Food Risk Factors Based on Improved FP-growth Algorithm by YU Jiabin, MA Xinyue, ZHAO Zhiyao, WANG Xiaoyi, ZHANG Xin, CUI Xiaoyu, BAI Yuting, CHEN Shuaixiang

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Machine Learning Models for Spring Discharge Forecasting by Francesco Granata, Michele Saroli, Giovanni de Marinis, Rudy Gargano

“…Recently, many hydraulic engineering problems have been addressed by means of advanced models derived from artificial intelligence studies. Three different machine learning algorithms were used for spring discharge forecasting in this comparative study: M5P regression tree, random forest, and support vector regression. …”
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Modulating synaptic plasticity with metal−organic framework for information-filterable artificial retina by Seongchan Kim, Ohchan Kwon, Seonkwon Kim, Seonmin Jang, Seungho Yu, Choong Hoo Lee, Yoon Young Choi, Soo Young Cho, Ki Chul Kim, Cunjiang Yu, Dae Woo Kim, Jeong Ho Cho

“…The information-filterable artificial retina system developed here emulates human perception processes and holds promise in the fields of neuroprosthetics and advanced artificial intelligence.…”
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Modelling current and future forest fire susceptibility in north-eastern Germany by K. H. Horn, K. H. Horn, S. Vulova, S. Vulova, H. Li, B. Kleinschmit

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Exploring determinant factors influencing muscle quality and sarcopenia in Bilbao's older adult population through machine learning: A comprehensive analysis approach. by Naiara Virto, Danielle Marie Dequin, Xabier Río, Amaia Méndez-Zorrilla, Begoña García-Zapirain

“…In this context, artificial intelligence opens up new opportunities to identify the key identifying factors of these pathologies, thus facilitating earlier intervention and personalized treatment approaches.…”
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Enhancing Early Breast Cancer Detection with Infrared Thermography: A Comparative Evaluation of Deep Learning and Machine Learning Models by Reem Jalloul, Chethan Hasigala Krishnappa, Victor Ikechukwu Agughasi, Ramez Alkhatib

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Predicting noncoding RNA and disease associations using multigraph contrastive learning by Si-Lin Sun, Yue-Yi Jiang, Jun-Ping Yang, Yu-Han Xiu, Anas Bilal, Hai-Xia Long

“…Predicting associations between noncoding RNAs and diseases can significantly improve the accuracy of early diagnosis.With the continuous breakthroughs in artificial intelligence, researchers increasingly use deep learning methods to predict associations. …”
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