Beyond binary: multi-class skin lesion classification with AlexNet transfer learning-towards enhanced dermatological diagnosis by Abida Noaman, Reyaz Ahmad, Muhammad Farhan Khan, Abdul Salam Mohammed, Muhammad Farooq, Khan Muhammad Adnan

“…This proposed model was trained, validated, and tested using ISIC 2019 challenge data with a very abnormal class distribution. …”
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Mid‐Latitude Study of Ionospheric Variation Over Iran Associated With Equatorial Ionization Anomaly (EIA), and Artificial Neural Networks Model Development by M. Vazifehkhah Hafteh, A. Mahmoudian, A. Yoshikawa, K. Girgis

“…Employing Artificial Neural Networks (ANN) for local TEC prediction, Iran is segmented into eight regions based on GNSS receiver distribution. Each region's ANN model, trained during the quiet geomagnetic condition, assesses predictability and accuracy. …”
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Exploring the Impact of Behavioural Factors and Personality Traits on Private Pension System Participation: A Machine Learning Approach by Can Verberi, Muhittin Kaplan

“…The data employed in the empirical analysis is survey data collected from the Şırnak province of Türkiye with a sample size of 449. …”
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Impact of FY-4A Satellite-Based Surface Solar Irradiance on the Classification of Meteorology for Ozone Pollution by Yang Cao, Xiaoli Zhao, Debin Su, Hong Ren, Xiang Cheng, Yuchun Li, Chenxi Wang

“…In general, the FY-4A SSI data are helpful for improving the classification performance of the trained classifier for the meteorology of ozone pollution in the study area.…”
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Association Between Refrigerator Openings and Protein Intake After Hospitalization for Heart Failure Decompensation: Protocol for a Prospective Cohort Pilot Study by Karin Haas, Franziska Scheidegger-Balmer, André Meichtry, Benjamin Vögeli, Nisha Arenja, Philipp Buluschek, Hugo Saner

“…Data analysis will begin after all data have been collected. …”
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Generative AI in Medicine: Pioneering Progress or Perpetuating Historical Inaccuracies? Cross-Sectional Study Evaluating Implicit Bias by Philip Sutera, Rohini Bhatia, Timothy Lin, Leslie Chang, Andrea Brown, Reshma Jagsi

“…Our primary endpoint was to compare the gender distribution of gAI photos to the current distribution in the United States. …”
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Near-instantaneous Atmospheric Retrievals and Model Comparison with FASTER by Anna Lueber, Konstantin Karchev, Chloe Fisher, Matthias Heim, Roberto Trotta, Kevin Heng

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Artificial intelligence aided microwave coagulation therapy: Analysis of heat transfer to tumor tissue via hybrid modeling by Zheng Yang, KeWei Dai, Wujun Zhang, Rui Zhou, QingBin Wu, Liang Liu, HuaiRong Qu

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Macro and Micro Characteristics of Extreme Heavy Rainfall Process in Jincheng of Shanxi Province on 11 July 2021 by Hongxia WANG, Aimei MIAO, Guiqiang QIU, Zhiyong QU, Junmei YANG, Linyi LÜ

“…Using ERA5 reanalysis data， automatic weather station data， FY4A satellite data， Doppler radar and Laser raindrop spectrometer data， the macro and micro characteristics of the extreme rainfall process in Jincheng， Shanxi Province on July 11， 2021 are analyzed. …”
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Optimized ensemble learning for non-destructive avocado ripeness classification by Panudech Tipauksorn, Prasert Luekhong, Minoru Okada, Jutturit Thongpron, Chokemongkol Nadee, Krisda Yingkayun

“…This study focuses on creating a strong ensemble classification model using spectral data from 120 kilogrammes of Buccaneer avocados obtained from the Royal Project in Chiang Mai, Thailand. …”
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CaloDREAM – Detector response emulation via attentive flow matching by Luigi Favaro, Ayodele Ore, Sofia Palacios Schweitzer, Tilman Plehn

“…Namely, we use an autoregressive transformer to simulate the energy of each layer, and a vision transformer for the high-dimensional voxel distributions. We show how dimension reduction via latent diffusion allows us to train more efficiently and how diffusion networks can be evaluated faster with bespoke solvers. …”
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An investigation on solving cooperative problem solving by Masoumeh Sadat Abtahi

“…The study analyzes the data using some basic statistics and the result indicates that teachers maintain an average CPS score of 39.37, which is well above the average level. …”
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Ribosome phenotypes for rapid classification of antibiotic-susceptible and resistant strains of Escherichia coli by Alison Farrar, Piers Turner, Hafez El Sayyed, Conor Feehily, Stelios Chatzimichail, Sammi Ta, Derrick Crook, Monique Andersson, Sarah Oakley, Lucinda Barrett, Christoffer Nellåker, Nicole Stoesser, Achillefs Kapanidis

“…By using ribosome-targeting probes, one fluorescence image provides data for cell segmentation and susceptibility phenotyping. …”
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Predicting the thickness of shallow landslides in Switzerland using machine learning by C. Schaller, C. Schaller, L. Dorren, M. Schwarz, C. Moos, A. C. Seijmonsbergen, E. E. van Loon

“…The models were calibrated using data from two field inventories in Switzerland (HMDB with 709 records and KtBE with 515 records). …”
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Study on the Aerodynamic Wind Pressure Behavior Characteristics of High-Speed Railway Sound Barriers by Rui Zhang, Qingyuan Yang, Hui Li, Dazheng Zhang, Siyu Zheng, Shengyou Yang

“…The accuracy of the model is validated with data from a CRH series train traveling at 350 km/h. …”
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Characteristics of the Main Factors Affecting Prolonged Spring-summer Extreme Drought Events in Northern Drought-prone Belt by Xiaojuan LU, Yiping LI, Jinsong WANG

“…Purposes Methods Extreme weather and climate events have been exhibiting an intensification under global warming.This intensified extremity thus augments the damaging impacts on both society and the economy.In the Northern Drought-prone Belt （NDPB）， extreme drought events are becoming more frequent and more intense with a broader distribution.In this study， by using statistical analysis and composite analysis， characteristics of the main factors affecting prolonged spring-summer extreme drought events in NDPB are analyzed based on the meteorological drought composite index， precipitation and near-surface air temperature data observed by meteorological stations， reanalysis dataset， sea surface temperature， snow cover， and the sea ice concentration data.Findings Conclusions Results show that the main circulation factors are as follows： the eastward propagating wave trains from Baffin Bay in March， a “positive-negative-positive-negative-positive-negative” geopotential height anomaly from the south of Hudson Bay to the east of Lake Baikal in May， an eastward wave train near the 60°N latitude， the Silk Road wave train and the eastward， weak Western Pacific Subtropical High in June； the main external forcing factors are listed below： the phase transition from La Niña to El Niño， warmer sea surface temperature over the Indian Ocean basin and the central North Atlantic； the shrinking snow cover in the mid-to-high latitudes of Eurasia and between 40°N and 60°N of North America， a snow cover reversal from abnormally high to abnormally low over the Qinghai-Tibet Plateau， a “negative-positive” sea ice concentration anomaly with less near Baffin Bay and Davis Strait but more near Greenland Sea， and a “positive-negative-positive” sea ice concentration anomaly from the Barents Sea to the Kara Sea.…”
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Machine learning prediction of pKa of organic acids by Juda Baikété, Alhadji Malloum, Jeanet Conradie

“…Our model (ExTr) outperforms selected models on a range of benchmark data, while offering two unique advantages: (1) full transparency (open descriptors and data) in contrast to proprietary black boxes, and (2) reduced computational cost compared to hybrid QM/ML approaches. …”
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Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach by Ajan Subramanian, Rui Cao, Emad Kasaeyan Naeini, Seyed Amir Hossein Aqajari, Thomas D Hughes, Michael-David Calderon, Kai Zheng, Nikil Dutt, Pasi Liljeberg, Sanna Salanterä, Ariana M Nelson, Amir M Rahmani

“…This gap necessitates the development of robust, multimodal approaches capable of addressing the unique challenges associated with assessing pain in clinical settings, where factors like motion artifacts, imbalanced label distribution, and sparse data further complicate pain monitoring. …”
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Prediction of groundwater level and potential zone identification in Keonjhar, Odisha based on machine learning and GIS techniques by B. Ritushree, Shubhshree Panda, Abinash Sahoo, Sandeep Samantaray, Deba P Satapathy

“…The efficiency of machine learning models ANN, SVM, and LSTM is investigated for forecasting groundwater level (GWL) and to find the best-fit model for the prediction. The models were trained and evaluated using historical GWL data and meteorological parameters such as rainfall, humidity, temperature, and soil moisture. …”
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A Fault Diagnosis Method of Contactor Based on Support Vector Classifier by YANG Jiawei, ZENG Weizhang, ZHU Wenlong, XU Hailong, ZHANG Zhongjing

“…At the same time, combined with the charging process data of train traction converter, the action process of contactor is verified for ten times, and the results show that the diagnosis is accurate.…”
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