Assessing Medical Students’ Learning Style Preferences at Kabale University Medical School, Uganda. by Muhaise, Hussein, Businge, Phelix Mbabazi, Ssemaluulu, Paul, Kyomugisha, Patricia

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Prague Squared by Josef Münzberger

“…The project employs a combination of choropleth and proportional symbol techniques, ensuring multiple data layers are readable. …”
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Low-Voltage Power Restoration Based on Fog Computing Load Forecasting and Data-Driven Wasserstein Distributionally Robust Optimization by Ruoxi Liu, Yifan Song, Yuan Gui, Hanqi Dai, Zhiyong Wang, Chengdong Yin, Qinglei Qin, Wenqin Yang, Yue Wang

“…This forecasting method embeds two weighted ultra-short-term load forecasting techniques of complementary characteristics and mines real-time load to learn incrementally, and thanks to this mechanism, the method can efficiently make predictions of low-voltage loads with trivial computational burden and data storage. …”
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A new integrated neurosymbolic approach for crop-yield prediction using environmental data and satellite imagery at field scale by Khadija Meghraoui, Teeradaj Racharak, Kenza Ait El Kadi, Saloua Bensiali, Imane Sebari

“…In this paper, we introduce a novel integrated neurosymbolic framework that combines knowledge-based approaches with sensor data for crop-yield prediction. This framework merges predictions from vectors generated by modeling environmental factors using a newly developed ontology focused on key elements and evaluates this ontology using quantitative methods, specifically representation learning techniques, along with predictions derived from remote sensing imagery. …”
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Accurate Mapping of Downed Deadwood in a Dense Deciduous Forest Using UAV-SfM Data and Deep Learning by Steffen Dietenberger, Marlin M. Mueller, Boris Stöcker, Clémence Dubois, Hanna Arlaud, Markus Adam, Sören Hese, Hanna Meyer, Christian Thiel

“…By implementing a U-Net architecture with a ResNet-34 backbone and utilizing data augmentation techniques, the model achieved very high classification performance (F1-scores between 73% and 96%). …”
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Systematic Pelvic and Paraaortic Lymph Node Dissection in Advanced Ovarian Cancer—Technical Aspects and Current Evidence-Based Data for Clinical Decision-Making by Traian Dumitrascu

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Machine Learning Modelling for Soil Moisture Retrieval from Simulated NASA-ISRO SAR (NISAR) L-Band Data by Dev Dinesh, Shashi Kumar, Sameer Saran

“…Synthetic aperture radar (SAR) is beneficial for estimating soil moisture at both global and local levels. This study aimed to assess soil moisture and dielectric constant retrieval over agricultural land using machine learning (ML) algorithms and decomposition techniques. …”
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Enhanced HER-2 prediction in breast cancer through synergistic integration of deep learning, ultrasound radiomics, and clinical data by Meijuan Hu, Lianying Zhang, Xiao Wang, Xuehua Xiao

“…Abstract This study integrates ultrasound Radiomics with clinical data to enhance the diagnostic accuracy of HER-2 expression status in breast cancer, aiming to provide more reliable treatment strategies for this aggressive disease. …”
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Unveiling Immune Response Mechanisms in Mpox Infection Through Machine Learning Analysis of Time Series Gene Expression Data by Qinglan Ma, Xianchao Zhou, Lei Chen, Kaiyan Feng, Yusheng Bao, Wei Guo, Tao Huang, Yu-Dong Cai

“…In this study, we used several machine learning algorithms to analyze time series gene expression data from macaques infected with Mpox, aiming to uncover key immune-related genes involved in different stages of infection. …”
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A modified and weighted Gower distance-based clustering analysis for mixed type data: a simulation and empirical analyses by Pinyan Liu, Han Yuan, Yilin Ning, Bibhas Chakraborty, Nan Liu, Marco Aurélio Peres

“…However, most real-world clinical data are mixed type. This study aims to introduce a clustering technique specifically designed for datasets containing both continuous and categorical variables to offer better clustering compatibility, adaptability, and interpretability than other mixed type techniques. …”
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KLASIFIKASI TINGKAT KEBERHASILAN SURVIVAL RATE (SR) PADA PRODUKSI UDANG VANAME MENGGUNAKAN ALGORITMA NAÏVE BAYES by Ar Razi, Desvina Yulisda

“… Data mining is the process of collecting and processing data with the aim of extracting important information from the data. …”
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KLASIFIKASI TINGKAT KEBERHASILAN SURVIVAL RATE (SR) PADA PRODUKSI UDANG VANAME MENGGUNAKAN ALGORITMA NAÏVE BAYES by Ar Razi, Desvina Yulisda

“… Data mining is the process of collecting and processing data with the aim of extracting important information from the data. …”
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Generating graph perturbations to enhance the generalization of GNNs by Sofiane Ennadir, Giannis Nikolentzos, Michalis Vazirgiannis, Henrik Boström

“…Such models need large amounts of training data, however, in several graph classification and regression tasks, only limited training data is available. …”
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Multi-atlas ensemble graph neural network model for major depressive disorder detection using functional MRI data by Nojod M. Alotaibi, Areej M. Alhothali, Manar S. Ali

“…Rest-state functional MRI (rs-fMRI) is among the most popular neuroimaging techniques used to study MDD. Deep learning techniques have been widely applied to neuroimaging data to help with early mental health disorder detection. …”
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EXPLORING THE LINKAGE BETWEEN OIL AND GAS SECTOR AND COMPETITIVENESS: A PANEL DATA ANALYSIS FOR THE COUNTRIES OF THE BLACK SEA REGION by Ioannis ANTONIADIS

“…The aim of this paper is to investigate the impact that oil and gas sector has on the global competitiveness of the economies of the countries of the Black Sea Region, measured by the Global Competitiveness Index, with the use of unbalanced panel data techniques for the period from 2006 to 2015. …”
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Data mining application in unraveling the large-scale teleconnection and flood-inducing extreme precipitation events association in Jeddah City by Hadir Abdelmoneim, Sameh Ahmed Kantoush, Vahid Nourani, Mohamed Saber, Fahad Alamoudi

“…The city of Jeddah recently experienced severe flooding, significantly impacting the community. We employed data mining techniques such as classification and association rules to investigate the complex relationships between large-scale atmospheric teleconnections and extreme precipitation events in Jeddah. …”
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A Study on the Social Perception of Risks From Electromagnetic Wave—Focusing on Big Data-Based Text Mining Analysis by Dong-Hun Kim, Beob-Heon Kim

“…This study applied big-data-based text-mining analysis techniques to collect and analyze 10,681 Korean media reports and portal big data over the last 10 years. …”
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Incorporating Street-View Imagery into Multi-Scale Spatial Analysis of Ride-Hailing Demand Based on Multi-Source Data by Jingjue Bao, Ye Li

“…By combining multi-scale geospatial data and computer vision techniques, the study provides a refined understanding of the spatial dynamics between ride-hailing demand and urban form. …”
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Customer Clustering and Marketing Optimization in Hospitality: A Hybrid Data Mining and Decision-Making Approach from an Emerging Economy by Maryam Deldadehasl, Houra Hajian Karahroodi, Pouya Haddadian Nekah

“…Using a hybrid approach that integrates data mining with multi-criteria decision-making techniques, this study aims to identify valuable customer segments and optimize marketing strategies. …”
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Enhancing preservation: Addressing humidity challenges in Indonesian heritage buildings through advanced detection methods point cloud data by Miktha Farid Alkadri, Yuliana Yuliana, Muhammad Rafif Cahyadi Agung, Muhammad Arif Rahman, Carola Hein

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