Enhancing Latent Defect Detection in Built-In Spindle Assembly Lines Through Vibration Data Analysis by Kuo-Hao Li, Chao-Nan Wang, Yao-Chi Tang

“…This study utilized the fast Fourier transform (FFT) for precise feature extraction. The integration of these advanced algorithms accurately identified defects and categorized them, thus optimizing manufacturing processes. …”
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Long and short term fault prediction using the VToMe-BiGRU algorithm for electric drive systems by Lihui Zheng, Xu Fan, Zongshan Kang, Xinjun Jin, Wenchao Zheng, Xiaofen Fang

“…The optimized VToMe-BiGRU algorithm combines the Transformer model and the BiGRU network, which effectively captures the critical features in the electric drive system data, thus improving the fault prediction performance. …”
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Decrease of cardiovascular risk in patients with type 2 diabetes: review of the common strategies and clinical studies by Vladimir V. Salukhov, Yurii Sh. Khalimov, Sergey B. Shustov, Dmitriy V. Kadin

“…In many fundamental studies, this feature was associated with a reduction of cardiovascular risks. …”
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Lifetime Prediction Analysis of Proton Exchange Membrane Fuel Cells Based on Empirical Mode Decomposition—Temporal Convolutional Network by Chao Zheng, Changqing Du, Jiaming Zhang, Yiming Zhang, Jun Shen, Jiaxin Huang

“…These results demonstrate the model’s high prediction fidelity and support proactive health management of PEMFC systems.…”
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Enhanced Model for Gestational Diabetes Mellitus Prediction Using a Fusion Technique of Multiple Algorithms with Explainability by Ahmad Hassan, Saima Gulzar Ahmad, Tassawar Iqbal, Ehsan Ullah Munir, Kashif Ayyub, Naeem Ramzan

“…They highlight the most influential features in GDM prediction and ensures transparency. …”
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A convolutional neural network-based deep learning approach for predicting surface chloride concentration of concrete in marine tidal zones by Mohamed Abdellatief, Mahmoud E. Abd-Elmaboud, Mohamed Mortagi, Ahmed M. Saqr

“…This research can enhance durability assessment, proactive maintenance strategies, and service life estimation of RC structures in harsh marine environments. …”
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Fire warning sensing materials: advances, prospects, and challenges by Xinyi Ma, Yingling Fang, Rongkai Wu, Lujia Yang, Yu Wang, Bihe Yuan

“…These materials facilitate proactive alarm systems, thereby enhancing safety in fire prevention and management. …”
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Impulsivity, Craving and Risky-Sexual-Behaviour in Brazilian Substance-Users: An Analytical Cross-Sectional Study by Sarah Naomi Foster, Pegoraro Natália Priolli Jora, Wagstaff Christopher, Adjei Richmond, Sekandi Patrick, Pillon Sandra Cristina

“…Implications for practice centre around synergising mental and physical health promotion via more proactive educational campaigns and accessible, equitable interventions. …”
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MNeuralTab: Integrating meta-modeling and neural networks for customer churn prediction in e-commerce by Arif Mohammad Asfe, Md. Rashadur Rahman, Md. Sabir Hossain

“…Predicting customer churn is paramount for the long-term viability of e-commerce businesses, enabling proactive retention strategies and minimizing costly customer attrition. …”
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Fault diagnosis of inter‐turn short circuits in PMSM based on deep regulated neural network by Ahmed Mesai Belgacem, Mounir Hadef, Enas Ali, Salah K. Elsayed, Prabhu Paramasivam, Sherif S. M. Ghoneim

“…This research highlights the efficacy of data fusion analysis and deep learning in fault diagnosis, facilitating proactive maintenance strategies and improving the reliability of PMSMs in diverse industrial applications and renewable energy systems.…”
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Multimodal Detection of Agitation in People With Dementia in Clinical Settings: Observational Pilot Study by Abeer Badawi, Somayya Elmoghazy, Samira Choudhury, Sara Elgazzar, Khalid Elgazzar, Amer M Burhan

“…This approach represents a significant advancement in the proactive management of behavioral symptoms in dementia care.…”
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Artificial intelligence in suicide prevention: Utilizing deep learning approach for early detection by Vikas Gaur, Gaurav Maggu, Khushboo Bairwa, Suprakash Chaudhury, Sana Dhamija, Tahoora Ali

“…Materials and Methods: An AI model utilizing ANNs is devised for suicide risk prediction among exam-stressed students. A 33-feature input layer is curated based on literature and expert insights, with binary features assigned weighted values. …”
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A Transformer–VAE Approach for Detecting Ship Trajectory Anomalies in Cross-Sea Bridge Areas by Jiawei Hou, Hongzhu Zhou, Manel Grifoll, Yusheng Zhou, Jiao Liu, Yun Ye, Pengjun Zheng

“…Overall, the proposed approach enables early identification and proactive warning of potential risks, contributing to improved maritime traffic safety.…”
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A novel adversarial deep TSK fuzzy classifier with its inverse-free fast training by Limin Mao, Hangming Shi, Yongxin Chou, Jinliang Cong, Mingli Lu, Zekang Bian, Suhang Gu

“…After taking the TSK fuzzy classifier as the subclassifier in each layer of AD-TSK, proactive adversarial example learning is designed based on the adversarial attacks on both the features and labels of the inputs for each subclassifier to generate the adversarial TSK fuzzy classifier (ATSK) with increased robustness to noise. …”
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Multi-Modal Excavator Activity Recognition Using Two-Stream CNN-LSTM with RGB and Point Cloud Inputs by Hyuk Soo Cho, Kamran Latif, Abubakar Sharafat, Jongwon Seo

“…It processes point clouds and RGB images using the two-stream long short-term memory convolutional neural network (CNN-LSTM) method to extract spatiotemporal features, enabling the recognition of excavator activities. …”
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How young people experienced long covid services: a qualitative analysis by Katharine Claire Pike, Olivia Lauryn Taylor, Georgia Treneman-Evans, Madeleine Riley, Jo Bond-Kendall

“…CYP found the waiting times to access long covid services were too long.Conclusions Our results stress the importance to CYP of several features of the care received in the specialist clinics. …”
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Criminal emotion detection framework using convolutional neural network for public safety by Jay Raval, Nilesh Kumar Jadav, Sudeep Tanwar, Giovanni Pau, Fayez Alqahtani, Amr Tolba

“…As our communities evolve and adopt technological advancements, the dynamic landscape of criminal activities becomes an essential aspect that requires careful examination and proactive approaches for public safety application. …”
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The Ecological Impacts and Modeling of the Beaver Dam Distribution: A Study on Habitat Characteristics and Environmental Factors in Romania by Alexandru Gridan, Ovidiu Ionescu, Georgeta Ionescu, Ancuta Fedorca, Elena Ciocirlan, Claudiu Pașca, Darius Hardalau

“…This study aimed to (i) characterize the physical and compositional features of beaver dams in the Râul Negru basin, Romania, (ii) model the environmental variables influencing the dam distribution using MaxEnt, and (iii) evaluate the implications for broader conservation strategies. …”
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Intelligent Thermal Condition Monitoring for Predictive Maintenance of Gas Turbines Using Machine Learning by Sadiq T. Bunyan, Zeashan Hameed Khan, Luttfi A. Al-Haddad, Hayder Abed Dhahad, Mustafa I. Al-Karkhi, Ahmed Ali Farhan Ogaili, Zainab T. Al-Sharify

“…The dataset, collected over six months from strategically placed thermocouples in the exhaust gas section, was processed to extract key statistical features such as mean temperature, standard deviation, and skewness. …”
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A Novel Approach for Evaluating Web Page Performance Based on Machine Learning Algorithms and Optimization Algorithms by Mohammad Ghattas, Antonio M. Mora, Suhail Odeh

“…Employing various classification algorithms, including Support Vector Machines (SVMs), Logistic Regression, and Random Forest, we compare their effectiveness on both original and feature-selected datasets. Our findings reveal that SVMs achieved the highest predictive accuracy of 89% with feature selection, compared to 87% without feature selection. …”
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