Parathyroid Carcinoma: An Up-to-Date Retrospective Multicentric Analysis by Francesco Quaglino, Luca Manfrino, Luca Cestino, Massimo Giusti, Enrico Mazza, Alessandro Piovesan, Nicola Palestini, Corrado Lauro, Elena Castellano

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Influence of the Heterogeneity of Spatial Distribution of Peripheral Radio Equipment of 4G/5G Networks on the Level of Electromagnetic Background Created in Buildings by V. I. Mordachev

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Compositional modeling of solution gas–oil ratio (Rs): a comparative study of tree-based models, neural networks, and equations of state by Aydin Larestani, Sara Sahebalzamani, Abdolhossein Hemmati-Sarapardeh, Ali Naseri

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Hybrid machine learning techniques for knowledge extraction in communication networks and advanced decision based complex q-Rung orthopair fuzzy frameworks by Hushuang Zeng, Yonghua Zhang

“…Abstract Hybrid machine learning techniques for knowledge extraction in communication networks combine the strengths of multiple learning algorithms to analyze complex, high-dimensional, and dynamic network data effectively. …”
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Designing metal halide-based road illumination systems in developing countries using regression and neural networksThe dataset is available through this link by Sourin Bhattacharya, Khondekar Lutful Hassan, Pallav Dutta

“…Photometric simulations were conducted for 80,000 installation combinations considering single-sided arrangements of MH luminaires and candidate models of predicting luminance and energy efficiency parameters were propounded with multiple regression analysis and two-layer feed-forward artificial neural networks (ANNs). …”
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Tilting Pad Thrust Bearing Fault Diagnosis Based on Acoustic Emission Signal and Modified Multi-Feature Fusion Convolutional Neural Network by Meijiao Mao, Zhiwen Jiang, Zhifei Tan, Wenqiang Xiao, Guangchao Du

“…The results show that under consistent operating conditions, the MMFCNN model achieves an average fault diagnosis accuracy of 99.58% when utilizing AE signal data from tilting pad thrust bearings in four states as inputs. …”
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ID3RSNet: cross-subject driver drowsiness detection from raw single-channel EEG with an interpretable residual shrinkage network by Xiao Feng, Xiao Feng, Zhongyuan Guo, Zhongyuan Guo, Sam Kwong

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Impact of meteorological factors on the incidence of hand, foot and mouth disease in Ningbo from 2014 to 2019: a causal convolutional neural networks by Bingqian Du, Zhiqiang Ren, Ziyu Song, Min Yuan, Zhenjun Li

“…The Causal CNNs and the Granger causality test were applied for prediction and analysis. Results From 2014 to 2019, the average annual incidence of HFMD in Ningbo was 398.66 per 100,000. …”
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Ensemble Streamflow Simulations in a Qinghai–Tibet Plateau Basin Using a Deep Learning Method with Remote Sensing Precipitation Data as Input by Jinqiang Wang, Zhanjie Li, Ling Zhou, Chi Ma, Wenchao Sun

“…This study proposed an ensemble streamflow simulation method using remote sensing precipitation data as input. By employing a 1D Convolutional Neural Networks (1D CNN), streamflow simulations from multiple models are integrated and a Shapley Additive exPlanations (SHAP) interpretability analysis was conducted to examine the contributions of individual models on ensemble streamflow simulation. …”
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Integrated assessment of antimicrobial stewardship in carbapenem resistant Klebsiella pneumoniae prevalent hospitals in China: a multidisciplinary surveillance network-based survey by Haishaerjiang Wushouer, Weibin Li, Junxuan Yu, Lin Hu, Xiaodong Guan, Xiaolin Liu, Anhua Wu, Xiaoqiang Yang, Minggui Wang, Yingchun Xu, Yanping Luo, Xun Huang, Luwen Shi

“…Abstract Background China has established an extensive multidisciplinary surveillance network encompassing antimicrobial utilisation, antimicrobial resistance, and nosocomial infections. …”
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Blockchain-Enhanced Attribute-Based Encryption Architecture With Feasibility Analysis by Agustin Ferrer-Rojas, Bodhaswar T. Maharaj, Mduduzi C. Hlophe

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Economic analysis of specialized dairy farms in Croatia according to FADN by Vesna Očić, Branka Šakić Bobić, Zoran Grgić

“…The Farm Accountancy Data Network (FADN) enables analysis and comparison of farms business data, and the dairy sector has been selected because of its great importance in the European Union (EU). …”
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Urban water supply risks assessment under tropical climate by Shahriar Shams, Nabisab Mujawar Mubarak, Nur Aqeelah Binti Ismail, Md Munir Hayet Khan, Abdullah Al-Mamun, Amimul Ahsan

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Comparative Analysis of Train Departure Strategies in a Container Shipment by Alessia Giulianetti, Marco Gotelli, Anna Sciomachen

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Discrimination of the Skin Cells from Cellular-Resolution Optical Coherence Tomography by Deep Learning by Jui-Yun Yi, Sheng-Lung Huang, Shiun Li, Yu-You Yen, Chun-Yeh Chen

“…Based on the ResNet-15 model, the mean accuracy (average accuracy of 10-fold cross-validation) reaches 98.47%, and the standard deviation is only 0.28% with the data augmentation method. …”
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Deep learning based quantitative cervical vertebral maturation analysis by Fulin Jiang, Abbas Ahmed Abdulqader, Yan Yan, Fangyuan Cheng, Tao Xiang, Jinghong Yu, Juan Li, Yong Qiu, Xin Chen

“…Therefore, we designed an advanced two-stage convolutional neural network customized for improved accuracy in cervical vertebrae analysis. …”
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Development of Risk Activity Detection System for Forklifts Based on Inertial Sensors by Luciano Radrigan, Sebastian E. Godoy

“…After field testing with the forklift, the inertial data-based algorithms had an average F1 of 0.93 versus video analysis which had an average F1 of 0.95. …”
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Performance and Improvement Analysis of the Underwater WSN Using a Diverse Routing Protocol Approach by K. Sathish, C. V. Ravikumar, Asadi Srinivasulu, A. Rajesh, Olutayo Oyeyemi Oyerinde

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Design and development of SHINE accelerator fast interlock system by YU Chunlei, CHEN Guanghua, DING Jianguo, LI Ming, XIAO Qingwen, YAN Yingbing

“…Due to 1 MHz repetition rate and thousands of kilometers length of SHINE, the accelerator interlock system should be a large system with response speed in microsecond magnitude and capable of processing tens of thousands of signals simultaneously.PurposeThis study aims to design and implement fast interlock system integrated with the conventional slow interlock system for SHINE accelerator.MethodThrough the analysis of SHINE requirements, FPGA (Field Programmable Gate Array) technology, distributed control technology, and network communication technology were adopted to complete the design of the fast interlock system. …”
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Predictive machine health monitoring using deep convolution neural network for noisy vibration signal of rotating machine using empirical mode decomposition by R. Pavithra, Prakash Ramachandran

“…The study compares all IMFs of clean and noisy signals to quantify the impact of noise on EMD for 8 different specific faults of the CWRU bearing dataset. The analysis of average normalized noise shows that EMD-IMF0 has minimum deviation due to noise for all noise ranges. …”
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