A Scalable Unsegmented Multiport Memory for FPGA-Based Systems by Kevin R. Townsend, Osama G. Attia, Phillip H. Jones, Joseph Zambreno

“…With banking, memory congestion is unavoidable and we evaluate our multiport memory cores under different memory access patterns to gain insights about different design trade-offs. …”
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Collaborative Advertisement Recommendation System Leveraging User Preferences, Geography, and Demographics by Djalila Boughareb, Hazem Bensalah, Zineddine Kouahla

“…The increasing demand for personalized advertising based on user preferences is driving a surge in popularity. Social networks utilize millions of user’ data to suggest ads based on specific criteria. …”
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Lightweight ECG signal classification via linear law-based feature extraction by Péter Pósfay, Marcell T Kurbucz, Péter Kovács, Antal Jakovác

“…We evaluate the method on two PhysioNet datasets, TwoLeadECG and variable projection networks (VPNet). …”
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Optimizing Energy Forecasting Using ANN and RF Models for HVAC and Heating Predictions by Khaled M. Salem, Javier M. Rey-Hernández, A. O. Elgharib, Francisco J. Rey-Martínez

“…Our approach systematically evaluates and compares the predictive performance of Artificial Neural Networks (ANNs) and Random Forests (RFs) for energy demand forecasting, leveraging each algorithm’s unique characteristics to assess their suitability for this application. …”
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Energy-Efficient Secure Cell-Free Massive MIMO for Internet of Things: A Hybrid CNN–LSTM-Based Deep-Learning Approach by Ali Vaziri, Pardis Sadatian Moghaddam, Mehrdad Shoeibi, Masoud Kaveh

“…However, the increasing demand for high-performance wireless networks necessitates advanced frameworks that optimize both energy efficiency (EE) and security. …”
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A Natural Language Processing Model for Predicting Five-Star Ratings of Video Games on Short-Text Reviews by Piyush Jaiswal, Hardik Setia, Pranshu Raghuwanshi, Princy Randhawa

“…The growing number of people who have access to the internet, the widespread use of smartphones, and the introduction of high-bandwidth networks such as 5G have all contributed to an increase in the demand for gaming around the world. …”
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Adaptive Energy Management for MATTER-Enabled Smart Homes by Navodit Bhardwaj, Pallavi Joshi

“…For anomaly detection, a hybrid multi-stage approach incorporating Long Short-Term Memory (LSTM) networks, One-Class SVMs (OCSVM), and autoencoders delivers a precision of 0.97 and recall of 0.95 in identifying abnormal consumption patterns and potential cybersecurity threats. …”
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A Closest Resemblance Classifier with Feature Interval Learning and Outranking Measures for Improved Performance by Nabil Belacel

“…We evaluate our classifiers on multiple UCI repository datasets and compare them with established methods, including k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), Random Forest (RF), Neural Networks (NNs), Naive Bayes (NB), and Nearest Centroid (NC). …”
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Improving the criteria of electricity consumptionforecasting in petrochemical industrial units based ondeep learning by Ehsan Tavakoli Garmaserh, Mehran Emadi

“…This study presents a novel deep learning framework that integrates advanced feature engineering and Long Short-Term Memory (LSTM) networks to address the challenges posed by irregular seasonal trends and dynamic consumption patterns. …”
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Vaginal bacteria and cervical cancer: a bibliometric analysis of trends and themes by Xiaoxia Liu, Yinghui Zhao, Xianhua Meng, Zheng Gao, Xiaohong Wang, Fengyong Yang

“…Bibliometric analysis was performed using VOSviewer, CiteSpace, and R-bibliometrix to evaluate publication patterns, research collaboration networks, and emerging trends.ResultsA total of 372 publications were identified, showing an annual growth rate of 8.41%. …”
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An Integrated Preprocessing and Drift Detection Approach With Adaptive Windowing for Fraud Detection in Payment Systems by Hadi M. R. Al Lawati, Anazida Zainal, Bander Ali Saleh Al-Rimy, Mohammad Al-Azawi, Mohamad Nizam Kassim, Sultan Ahmed Almalki, Tami Abdulrahman Alghamdi

“…The method uses Mutual Information and SelectKBest for selecting important features, applies ADASYN to handle class imbalance, and adopts Convolutional Neural Networks (CNN) to capture complex transaction patterns. …”
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Advanced Deep Learning Approaches for Forecasting High-Resolution Fire Weather Index (FWI) over CONUS: Integration of GNN-LSTM, GNN-TCNN, and GNN-DeepAR by Shihab Ahmad Shahriar, Yunsoo Choi, Rashik Islam

“…Based on this, our study developed a hybrid modeling framework to forecast FWI over a 14-day horizon, integrating Graph Neural Networks (GNNs) with Temporal Convolutional Neural Networks (TCNNs), Long Short-Term Memory (LSTM), and Deep Autoregressive Networks (DeepAR). …”
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Smart E-Tongue Based on Polypyrrole Sensor Array as Tool for Rapid Analysis of Coffees from Different Varieties by Alvaro Arrieta Almario, Oriana Palma Calabokis, Eisa Arrieta Barrera

“…The results demonstrate that the polypyrrole sensors can generate distinct electrochemical patterns, serving as “fingerprints” for each coffee variety. …”
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The Effect of Nestle Product Bundling Sales Accompanied with Discounts and Gifts on the Increase in the Number of SKUs Sold in the Sales Area of PT Anugerah Bina Usaha Nusantara La... by Raissa Kurnia Adha, Albari Albari

“…The findings of the study recommend that the company modify the strategy to be more flexible and sustainable, with periodic evaluations to avoid store dependence on promotions.   …”
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Static and Dynamic User Portraits by Ko-Hsun Huang, Yi-Shin Deng, Ming-Chuen Chuang

“…User modeling and profiling has been used to evaluate systems and predict user behaviors for a considerable time. …”
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Cognitive difference text classification in online knowledge collaboration based on SA-BiLSTM hybrid model by Fengjun Liu, Na Zhao, Guoqing Zhu

“…However, accurate extraction of semantic features and contextual patterns from such texts remains challenging in multi-dimensional discourse contexts. …”
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A GPT-Based Approach for Cyber Threat Assessment by Fahim Sufi

“…It utilizes a hybrid methodology combining spectral residual transformation and Convolutional Neural Networks (CNNs) to identify anomalies in time-series cyber event data, alongside regression models for evaluating the significant factors associated with cyber events. …”
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Explainable Artificial Intelligence for predicting the compressive strength of soil and ground granulated blast furnace slag mixtures by Ahmed Mohammed Awad Mohammed, Omayma Husain, Muyideen Abdulkareem, Nor Zurairahetty Mohd Yunus, Nadiah Jamaludin, Elamin Mutaz, Hashim Elshafie, Mosab Hamdan

“…A database of 200 samples was compiled from the literature, and six ML models—linear regression, decision trees, random forest, artificial neural networks, gradient boosting, and extreme gradient boosting were developed and evaluated. …”
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Integrative bulk and single-cell transcriptomic analysis identifies a migrasome-associated lncRNA signature predictive of prognosis and immune landscape in clear cell renal cell ca... by Junlin Shen, Chun Wang, Mingpeng Zhang, Bin Chen, Liwei Liu, Jing Tian, Zhiqun Shang

“…The associations between the model and overall survival (OS), functional enrichment, tumor mutation burden (TMB), tumor microenvironment (TME) characteristics, immune evasion, and drug sensitivity were evaluated. Single-cell transcriptomic analysis was performed to determine cell type–specific expression patterns and intercellular communication networks. …”
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Identification of a deubiquitinating gene-related signature in ovarian cancer using integrated transcriptomic analysis and machine learning framework by Suwan Hu, Mengting Wang

“…High-risk patients, as classified by the DRS, showed significantly poorer survival outcomes and distinct immune infiltration patterns compared to low-risk patients. Conclusion This study provides comprehensive insights into DUB gene expression patterns across different cell populations in ovarian carcinoma. …”
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