A Resilient Deep Learning Approach for State Estimation in Distribution Grids With Distributed Generation by Ronald Kfouri, Harag Margossian

“…To make the distribution grid observable, researchers resort to pseudomeasurements, which are inaccurate. …”
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Complex networks applied to political analysis: Group voting behavior in the Brazilian congress. by Tiago José de Oliveira Toledo Junior, Diego Raphael Amancio, Roseli Aparecida Francelin Romero

“…Complex networks were shown to be a suitable tool to analyze this type of system. Several researches explored party dynamics in the Chamber of Deputies, however, no attention has been given to the Senate. …”
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Advancements in Image Classification: From Machine Learning to Deep Learning by Cheng Haoran

“…The paper also focuses on discussing classic deep learning models such as AlexNet, VGGNet, ResNet and ViT, analyzing their strengths and weaknesses. By comparing the performance of different methods, this paper aims to provide references for researchers in the realm of image classification, promoting further development in this area.…”
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Modifiable factors and 10-year and lifetime cardiovascular disease risk in adults with new-onset hypertension: insights from the Kailuan cohort by Shouling Wu, Yanxiu Wang, Jiangshui Wang, Jun Feng, Furong Li, Liming Lin, Chunyu Ruan, Zhifang Nie, Jinwei Tian, Cheng Jin

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Development and validation of a machine learning model based on multiple kernel for predicting the recurrence risk of Budd-Chiari syndrome by Weirong Xue, Bing Xu, Hui Wang, Xiaoxiao Zhu, Jiajia Qin, Guangshuang Zhou, Peilin Yu, Shengli Li, Yingliang Jin

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Development and Validation of DIANA (Diabetes Novel Subgroup Assessment tool): A web-based precision medicine tool to determine type 2 diabetes endotype membership and predict indi... by Viswanathan Baskar, Mani Arun Vignesh, Sumanth C Raman, Arun Jijo, Bhavadharini Balaji, Nico Steckhan, Lena Maria Klara Roth, Moneeza K Siddiqui, Saravanan Jebarani, Ranjit Unnikrishnan, Viswanathan Mohan, Ranjit Mohan Anjana

“…Its performance was compared with an algorithm determined based on conditional pre-determined cut-offs and weights for each clinical feature [age at diagnosis, BMI, waist, HbA1c, Serum Triglycerides, HDL-Cholesterol, (C-peptide fasting, C-peptide stimulated) - optional. …”
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Variable-Rate Nitrogen Application in Wheat Based on UAV-Derived Fertilizer Maps and Precision Agriculture Technologies by Alexandros Tsitouras, Christos Noulas, Vasilios Liakos, Stamatis Stamatiadis, Miltiadis Tziouvalekas, Ruijun Qin, Eleftherios Evangelou

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Association of white matter hyperintensity burden and infarct volume in the anterior choroidal artery territory with early neurological progression: a dual-center retrospective stu... by Weiwei Gao, Weiwei Gao, Lixue Wang, Junyi Huang, Yitao Yu, Jingjing She, Jingjing She, Jingjing She, Mingyang Wang, Lijuan Cai, Lijuan Cai, Taishan Kang, Xingyu Chen, Xingyu Chen, Jianzhong Lin, Renjing Zhu, Renjing Zhu, Renjing Zhu

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Leveraging automated time-lapse microscopy coupled with deep learning to automate colony forming assay by Anusha Klett, Anusha Klett, Dennis Raith, Dennis Raith, Paula Silvestrini, Paula Silvestrini, Paula Silvestrini, Matías Stingl, Jonas Bermeitinger, Avani Sapre, Avani Sapre, Avani Sapre, Martin Condor, Roman Melachrinos, Mira Kusterer, Alexandra Brand, Guido Pisani, Guido Pisani, Evelyn Ullrich, Evelyn Ullrich, Evelyn Ullrich, Evelyn Ullrich, Marie Follo, Marie Follo, Jesús Duque-Afonso, Roland Mertelsmann, Roland Mertelsmann

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Classification of finger movements through optimal EEG channel and feature selection by Murside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Yalcin Isler

“…Subsequently, these features were tested with eight well-known classifiers, comprising Decision tree, Discriminant analysis, Naive Bayes, Support vector machine, k-nearest neighbor, Ensemble learning, Neural networks, and Kernel approximation.ResultsFor subject-dependent analysis, the maximum accuracy of 59.17% was obtained using the EEG features that were selected the most (including (i) energy and variance of five frequency bands in frequency-domain feature set, (ii) all feature types in time-domain, time-frequency domain, and nonlinear domain feature sets) and all EEG channels by the Support vector machine algorithm. For subject-independent analysis, the maximum accuracy of 39.30% was obtained using the mostly selected EEG features (which are (i) all feature types excluding the waveform length, average amplitude change value, absolute difference in standard deviation, and slope-change value feature types in time-domain feature set, (ii) the energy and variance values of all frequency bands except gamma frequency band in frequency-domain feature set, (iii) the entropy value of five frequency bands in time-frequency-domain feature set, and (iv) SD2 and SD1/SD2 values where lag = 1 in nonlinear feature set) and EEG channels (which are (i) some definite EEG channels including 2nd, 3rd, 7th, 11th, 13th, 14th, and 15th channels in time-frequency-domain feature set and (ii) all EEG channels in time-domain, frequency-domain, and nonlinear feature sets) by the Support vector machine classifier.DiscussionExperimental results demonstrate that despite the high-class number, the proposed approach obtained a modest yet considerable advancement in finger movement prediction when the results are compared to the results of similar studies. …”
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Systemic longitudinal immune profiling identifies proliferating Treg cells as predictors of immunotherapy benefit: biomarker analysis from the phase 3 CONTINUUM and DIPPER trials by Sai-Wei Huang, Wei Jiang, Sha Xu, Yuan Zhang, Juan Du, Ya-Qin Wang, Kun-Yu Yang, Ning Zhang, Fang Liu, Guo-Rong Zou, Feng Jin, Hai-Jun Wu, Yang-Ying Zhou, Xiao-Dong Zhu, Nian-Yong Chen, Cheng Xu, Han Qiao, Na Liu, Ying Sun, Jun Ma, Ye-Lin Liang, Xu Liu

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Compatibility Between OLCI Marine Remote-Sensing Reflectance from Sentinel-3A and -3B in European Waters by Frédéric Mélin, Ilaria Cazzaniga, Pietro Sciuto

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A Gradient Boosting Crash Prediction Approach for Highway-Rail Grade Crossing Crash Analysis by Pan Lu, Zijian Zheng, Yihao Ren, Xiaoyi Zhou, Amin Keramati, Denver Tolliver, Ying Huang

“…The gradient boosting (GB) model has gained popularity in many research areas. In this study, to fully understand the model performance on HRGC accident prediction performance, the GB model with functional gradient descent algorithm is selected to analyze crashes at highway-rail grade crossings (HRGCs) and to identify contributor factors. …”
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Syndromic Diagnostics of Respiratory Infections in Children As One of Antibiotic Management Tools in a Hospital by A. V. Vlasova, P. V. Berezhanskiy, A. B. Malakhov, A. E. Angel, Yu. F. Shubina, E. V. Smirnova, L. V. Dymnova, A. A. Sharshakova, S. B. Asalkhanova

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Thermal analysis and multi-objective optimization of equal-area microfluidic cooling systems by Yucheng Wang, Antong Bi, Yue Yao, Weiting Chen, Kaiyu Chen, Shenxin Yu, Jiangang Yu, Chao Wang, Wei Li, Shaoxi Wang

“…Moreover, An orthogonal experimental design combined with a multi-objective optimization algorithm was applied to minimize both the average heat source temperature and pressure drop. …”
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Analysis of the Impact of Rain on Perception in Automated Vehicle Applications by Tim Brophy, Darragh Mullins, Ashkan Parsi, Jonathan Horgan, Enda Ward, Patrick Denny, Ciaran Eising, Brian Deegan, Martin Glavin, Edward Jones

“…The reliable performance of object detection perception algorithms in automated vehicles under adverse conditions such as rain is critical for maintaining vulnerable road user safety. …”
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ARIMA-Kriging and GWO-BiLSTM Multi-Model Coupling in Greenhouse Temperature Prediction by Wei Zhou, Shuo Liu, Junxian Guo, Na Liu, Zhenglin Li, Chang Xie

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Benchmark Pashto Handwritten Character Dataset and Pashto Object Character Recognition (OCR) Using Deep Neural Network with Rule Activation Function by Imran Uddin, Dzati A. Ramli, Abdullah Khan, Javed Iqbal Bangash, Nosheen Fayyaz, Asfandyar Khan, Mahwish Kundi

“…The reason for the lack of research in Pashto handwritten character data as compared to other languages is because there is no benchmark dataset available for experimental purposes. …”
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Inter-annual changes and growth trends mapping of mangrove using Landsat time series imagery by Xiaohui Huang, Yingchun Fu, Hu Ding, Guoan Tang, Peifeng Ma, Liangyun Liu, Yufei Xue, Shuting Wu, Ye Chen

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Power Wavelet Cepstral Coefficients (PWCC): An Accurate Auditory Model-Based Feature Extraction Method for Robust Speaker Recognition by Youssef Zouhir, Mohamed Zarka, Kais Ouni, Lilia El Amraoui

“…To bridge this gap, researchers investigate the human auditory system to support machine learning algorithm performance. …”
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