HTSA-LSTM: Leveraging Driving Habits for Enhanced Long-Term Urban Traffic Trajectory Prediction by Yiying Wei, Xiangyu Zeng, Xirui Chen, Hui Zhang, Zhengan Yang, Zhicheng Li

“…This paper proposes a Habit-based Temporal–Spatial Attention Long Short-Term Memory (HTSA-LSTM) network, a novel framework that integrates a dual spatiotemporal attention mechanism to capture dynamic dependencies across time and space, coupled with a driving style analysis module. …”
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Nuanced perspectives on the challenges, prospects and opportunities confronting sustainable access to potable water and sanitary services in South Africa’s Nompumelelo community by Shadreck Muchaku, Shadreck Muchaku, Leocadia Zhou

“…ATLAS.ti 24 facilitated theme generation through systematic coding and categorization, while network visualizations were employed to map relationships and uncover patterns within the data, enhancing analytical depth. …”
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Trust-driven approach to enhance early forest fire detection using machine learning by Tayyab Khan, Karan Singh, Bhoopesh Singh Bhati, Khaleel Ahmad, Amal Al-Rasheed, Masresha Getahun, Ben Othman Soufiene

“…These ratings consider communication, energy, and data trust factors to evaluate the reliability of the data being delivered. …”
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The value of the continuous genotyping of multi-drug resistant tuberculosis over 20 years in Spain by María José Iglesias, Daniel Ibarz, Alberto Cebollada, Jéssica Comín, María Soledad Jiménez, María C. Vázquez, Sofía Samper, The Spanish Working Group on MDRTB

“…The Spanish Working Group on multidrug resistant tuberculosis (MDR-TB) is a network that monitors the MDR-TB isolates in Spain since 1998. …”
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Pharmacogenomics and Pharmacometabolomics in Precision Tramadol Prescribing for Enhanced Pain Management: Evidence from QBB and EMR Data by Dhoha Dhieb, Najeha Anwardeen, Dinesh Velayutham, Mohamed A. Elrayess, Puthen Veettil Jithesh, Kholoud Bastaki

“…Additionally, prescription data encompassing tramadol formulations were collected from the electronic medical records (EMR) system of the major public hospital network in Qatar (Hamad Medical Corporation) to discern prescribing patterns. …”
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Fast Anomaly Detection for Vision-Based Industrial Inspection Using Cascades of Null Subspace PCA Detectors by Muhammad Bilal, Muhammad Shehzad Hanif

“…In this study, we introduce a novel anomaly detection framework that leverages feature maps from a lightweight convolutional neural network (CNN) backbone, MobileNetV2, and cascaded detection to achieve notable accuracy as well as computational efficiency. …”
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VPS26A as a Prognostic Biomarker and Therapeutic Target in Liver Hepatocellular Carcinoma: Insights from Comprehensive Bioinformatics Analysis by Hye-Ran Kim, Jongwan Kim

“…<i>Materials and Methods:</i> Multiple databases, including TIMER, UALCAN, HPA, GSCA, KM Plotter, OSlihc, MethSurv, miRNet, OncomiR, LinkedOmics, GeneMANIA, and STRING, were used to evaluate VPS26A expression patterns, prognostic implications, correlations with tumor-infiltrating immune cells (TIICs), epigenetic modifications, drug sensitivity, co-expression networks, and protein–protein interactions in LIHC. …”
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A Multi-Agent and Attention-Aware Enhanced CNN-BiLSTM Model for Human Activity Recognition for Enhanced Disability Assistance by Mst Alema Khatun, Mohammad Abu Yousuf, Taskin Noor Turna, AKM Azad, Salem A. Alyami, Mohammad Ali Moni

“…The effectiveness of this three-stage ensemble strategy is evaluated utilizing various performance metrics and through three distinct experiments. …”
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Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…Spoken languages are classified using Bayesian optimization (BO) in conjunction with a long short-term memory (LSTM) network. The DBODL-MSLIS technique has been experimentally validated using the IIIT Spoken Language dataset. …”
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CGV-Net: Tunnel Lining Crack Segmentation Method Based on Graph Convolution Guided Transformer by Kai Liu, Tao Ren, Zhangli Lan, Yang Yang, Rong Liu, Yuantong Xu

“…To address this issue, this study proposes CGV-Net (CNN, GNN, and ViT networks), a novel tunnel crack segmentation network model that integrates convolutional neural networks (CNNs), graph neural networks (GNNs), and Vision Transformers (ViTs). …”
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Integrating Machine Learning Workflow into Numerical Simulation for Optimizing Oil Recovery in Sand-Shale Sequences and Highly Heterogeneous Reservoir by Dung Bui, Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Adewale Amosu, William Ampomah

“…This paper aims to evaluate the efficiency of various machine learning algorithms integrating with numerical simulations in optimizing oil production for a highly heterogeneous reservoir. …”
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Enhanced MRI brain tumor detection using deep learning in conjunction with explainable AI SHAP based diverse and multi feature analysis by Asif Rahman, Maqsood Hayat, Nadeem Iqbal, Fawaz Khaled Alarfaj, Salem Alkhalaf, Fahad Alturise

“…This study investigates the synergy among multiple feature representation schemes such as local Binary Patterns (LBP), Gabor filters, Discrete Wavelet Transform, Fast Fourier Transform, Convolutional Neural Networks (CNN), and Gray-Level Run Length Matrix alongside five learning algorithms namely: k-nearest Neighbor, Random Forest, Support Vector Classifier (SVC), and probabilistic neural network (PNN), and CNN. …”
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Identification of therapeutic targets in lung adenocarcinoma using Mendelian randomization and multi-omics by Yue Li, Keru Ma, Hao Wang, Zongying Liu, Zhuying Li

“…Functional interactions were explored via protein–protein interaction network analysis, while single-cell analyses were employed to determine cell-specific expression patterns and differentiation trajectories. …”
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Short-term solar irradiance forecasting model based on hyper-parameter tuned LSTM via chaotic particle swarm optimization algorithm by V Ashok Gajapati Raju, Janmenjoy Nayak, Pandit Byomakesha Dash, Manohar Mishra

“…With this incitement, this paper suggests a hybrid deep learning (DL) model via Long Short-Term Memory (LSTM) networks and Chaotic Particle Swarm Optimization (CPSO). …”
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Identifying the Dimensions and Components of a Gamification Model in the Marketing Processes for Sharing Economy Transportation Businesses by Somaye Moradi, Maysam Shafiee

“…Accordingly, gamification in the marketing processes of sharing economy businesses is based on the analysis of user and player behavior, identifying the needs and requirements of users and players, analyzing the competitive space and gamification environment of sharing economy businesses, market planning and determining the appropriate target market, designing accessible channels and operating in designed markets, having a strategic market plan for continuous management of the market, users, and players along the product and business life cycle, designing games that meet market needs and requirements, designing games based on up-to-date standards and professional patterns, meeting the needs of owners and users, owners' participation in game design, owners' participation in promoting and developing gamification networks (volume and physical development), owners' participation in brand development and project promotion (advertising and brand development), players and users' participation in game design, players and users' participation in promoting and developing gamification networks (volume and physical development), and players and users' participation in brand development and project promotion (advertising and brand development). …”
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Prognostic relevance and performance characteristics of serum IGFBP‐2 and PAPP‐A in women with breast cancer: a long‐term Danish cohort study by Ulrick Espelund, Andrew G. Renehan, Søren Cold, Claus Oxvig, Lee Lancashire, Zhenqiang Su, Allan Flyvbjerg, Jan Frystyk

“…We measured the same biomarkers in 531 noncancer individuals to assess multidimensional relationships (MDR), and evaluated additional prognostic models using survival artificial neural network (SANN) and survival support vector machines (SSVM), as these enhance capture of MDRs. …”
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Mask R-CNN aided fruit surface temperature monitoring algorithm with edge compute enabled internet of things system for automated apple heat stress management by Basavaraj R. Amogi, Rakesh Ranjan, Lav R. Khot

“…Therefore, aim of this study was to develop and field evaluate cultivar and color independent mask region-convolution neural network (R-CNN) aided fruit segmentation model and edge compute compatible FST estimation algorithm. …”
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Depression Detection in Social Media: A Comprehensive Review of Machine Learning and Deep Learning Techniques by Waleed Bin Tahir, Shah Khalid, Sulaiman Almutairi, Mohammed Abohashrh, Sufyan Ali Memon, Jawad Khan

“…The rapidly growing world of social media sites such as Twitter, Reddit, Facebook, Instagram, and Weibo has provided new avenues for depression detection using Machine Learning (ML) as well as Deep Learning (DL), which analyze user behavior patterns and linguistic cues for more accurate detection of depression. …”
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EEG-based neurodegenerative disease diagnosis: comparative analysis of conventional methods and deep learning models by B. R. Nayana, M. N. Pavithra, S. Chaitra, T. N. Bhuvana Mohini, Thompson Stephan, Vijay Mohan, Neha Agarwal

“…The study offers a comparative evaluation across three distinct datasets, illustrating that deep learning models, particularly 1D and 2D CNNs, consistently outperform conventional methods in recognizing subtle EEG signal patterns linked to neurodegenerative conditions. …”
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Analysis of meteorological drought using satellite-based rainfall products over southern Ethiopia by T. M. Weldegerima, T. B. Gebresilassie, T. B. Gebresilassie

“…The availability of insufficient ground-based rainfall observatory networks is limiting drought-monitoring and early-warning investigations. …”
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