Hybrid ML-based predictive modeling and GUI development of calcium aluminate cement hydration and strength optimization for advanced and durable construction applications by Muwaffaq Alqurashi

“…This study employs advanced hybrid machine learning (ML) techniques to predict the compressive strength and porosity of CAC pastes, addressing the limitations of conventional analytical approaches. …”
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A novel multi-step methodology for stochastic simulation of streamflow time series using PcStream clustering by Shalini Balaram, Roshan Srivastav, K Srinivasan

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Enhancing Heart Attack Prediction: Feature Identification from Multiparametric Cardiac Data Using Explainable AI by Muhammad Waqar, Muhammad Bilal Shahnawaz, Sajid Saleem, Hassan Dawood, Usman Muhammad, Hussain Dawood

“…However, timely diagnosis remains a challenge due to the complex and nonlinear relationships between clinical indicators. Machine learning (ML) and deep learning (DL) models have the potential to predict cardiac conditions by identifying complex patterns within data, but their “black-box” nature restricts interpretability, making it challenging for healthcare professionals to comprehend the reasoning behind predictions. …”
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A review of sound-based pig monitoring for enhanced precision production by Md Nasim Reza, Md Razob Ali, Md Asrakul Haque, Hongbin Jin, Hyunjin Kyoung, Young Kyoung Choi, Gookhwan Kim, Sun-Ok Chung

“…Advancements in sensor technology and data analytics have enhanced the capabilities of sound-based precision systems in pig farming. The integration of machine learning and artificial intelligence (AI) is further enhancing the capacity to interpret complex sound patterns, enabling the automated detection of abnormal behaviors or health issues. …”
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Assessing Sleep Quality Using Mobile EMAs: Opportunities, Practical Consideration, and Challenges by Jiyoun Lim, Chi Yoon Jeong, Jeong Muk Lim, Seungeun Chung, Gague Kim, Kyoung Ju Noh, Hyuntae Jeong

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Landscape Metrics as Ecological Indicators for PM₁₀ Prediction in European Cities by Seyedehmehrmanzar Sohrab, Nándor Csikós, Péter Szilassi

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Cyberism: The theory for relationships between human and cyberspace by Huansheng NING

“…New digital phenomena such as livestream commerce, the gig economy, metaverse, virtual humans, online education, and digital social interactions are rapidly expanding the dimensions of human life, leading to unprecedented behavioral patterns and social structures. In traditional Chinese culture, Confucianism studies the relationship between people (social space), Buddhism explores the relationship between individuals and their inner minds (thinking space), and Daoism (or Taoism) focuses on the relationship between humans and nature (physical space). …”
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Exploring ribosome biogenesis in lung adenocarcinoma to advance prognostic methods and immunotherapy strategies by Zipei Song, Yuheng Wang, Miaolin Zhu, Pengpeng Zhang, Zhihua Li, Xin Geng, Xincen Cao, Jianan Zheng, Jianwei Tang, Liang Chen

“…Cells were scored based on the expression patterns of 331 genes associated with RiboSis across different cell types, and monocle2 was employed to analyze the developmental trajectory of CD4+ T cells. …”
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Advances in soil salinity diagnosis for mangrove swamp rice production in Guinea Bissau, West Africa by Gabriel Garbanzo, Jesus Céspedes, Marina Temudo, Maria do Rosário Cameira, Paula Paredes, Tiago Ramos

“…Indices derived from spectral bands and soil texture raster of the Planet Scope project were used to calibrate the three machine learning based models: Random Forest (RF), Support Vector Machine, and Convolutional Neural Networks. …”
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Deep Learning Based Breast Cancer Detection Using Decision Fusion by Doğu Manalı, Hasan Demirel, Alaa Eleyan

“…First, SVM distinguishes between different tumor types using local binary pattern (LBP) features. Second, a pre-trained CNN extracts features, and SVM identifies potential tumors. …”
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A Novel Approach for Tomato Leaf Disease Classification with Deep Convolutional Neural Networks by Gizem Irmak, Ahmet Saygılı

“…Specifically, classical learning methods employed the local binary pattern (LBP) technique for feature extraction, while classification tasks were carried out using extreme learning machines, k-nearest neighborhood (kNN), and support vector machines (SVM). …”
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Breast Cancer Diagnosis Using Bagging Decision Trees with Improved Feature Selection by Deepak Dudeja, Ajit Noonia, S. Lavanya, Vandana Sharma, Varun Kumar, Sumaiya Rehan, R. Ramkumar

“…Machine learning is a science of computer algorithms that enable systems to automatically learn actions and adjust them without explicit programming and improve from experience using pattern recognition. …”
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Multi-body sensor based drowsiness detection using convolutional programmed transfer VGG-16 neural network with automatic driving mode conversion by Meenakshi Malik, Preeti Sharma, Gurpreet Kaur Punj, Supreet Singh, Fikreselam Gared

“…The wavelet time frequency transform model has been used to examine this signal in order to classify patterns of brain activity. A multi-layer convolutional programmed transfer VGG-16 neural network was then used to classify this examined pattern. …”
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MindLift: AI-powered mental health assessment for students by Shanky Goyal, RishiRaj Dutta, Saurabh Dev, Kola Narasimha Raju, Mohammed Wasim Bhatt

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Assessing the Effects of Climate Change and Land‐Use Changes on Extreme Discharge in the Western Watershed of Lake Urmia, Iran by Ghasem Farahmand, Behzad Hessari, Hossein Salehi

“…Modeling with these tools confirmed that climate and land‐use changes synergistically alter flood dynamics, a pattern consistent with regional studies. These findings underscore the urgent need to integrate these factors into flood management strategies for this flood‐prone region, offering a robust framework for sub‐basin‐scale hydrological planning.…”
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Dynamic Monitoring of Ecological Environmental Quality in Arid and Semi-Arid Regions: Disparities Among Central Asian Countries and Analysis of Key Driving Factors by Yue Liu, Jinjie Wang, Jianli Ding, Zipeng Zhang, Zhihong Liu, Zihan Zhang, Jinming Zhang, Liya Shi

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Ordinal METAR Cloud Cover Classification in Sentinel-2 Satellite Data by Markus Gotz, Erik Wessel, Ugur Cayoglu, Babak Jahani, Charlotte Debus, Jan Cermak, Achim Streit

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Neuroimaging and biological markers of different paretic hand outcomes after stroke by Zhujun Wang, Manxu Zheng, Binke Yuan, Yingteng Zhang, Wenjun Hong, Chaozheng Tang, Wen Wu

“…Four rs-fMRI metrics were analyzed, including amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), degree centrality (DC), and voxel-mirrored homotopic connectivity (VMHC). Multivariate pattern analysis was used to classify and predict paretic hand performance. …”
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GNNSeq: A Sequence-Based Graph Neural Network for Predicting Protein–Ligand Binding Affinity by Somanath Dandibhotla, Madhav Samudrala, Arjun Kaneriya, Sivanesan Dakshanamurthy

“…While existing sequence-based machine learning models for binding affinity prediction have shown potential, they lack accuracy and robustness in pattern recognition, which limits their generalizability across diverse and novel binding complexes. …”
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Sex-specific cardiometabolic multimorbidity, metabolic syndrome and left ventricular function in heart failure with preserved ejection fraction in the UK Biobank by Ambre Bertrand, Xin Zhou, Andrew Lewis, Thomas Monfeuga, Ramneek Gupta, Vicente Grau, Blanca Rodriguez

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