Magnitude Comparison and Sign Detection based on the 4-Moduli Set {2n+1, 2nâ1, 2n+3, 2nâ3} by Mohsen Mojahed, Amir Sabbagh, Azadeh Emrani

“…The 4-moduli set residue number system (RNS),{2n+1, 2nâ1, 2n+3, 2nâ3}, with a wide dynamic range, has recently been proposed as a balanced 4-moduli set for utilizing the cases that demand fast calculations such as deep learning and implementation of asymmetric cryptographic algorithms. Up to now, only an unsigned reverse converter has been designed for this moduli set. …”
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Backfire Effect Reveals Early Controversy in Online Media by Songtao Peng, Tao Jin, Kailun Zhu, Qi Xuan, Yong Min

“…The rapid development of online media has significantly facilitated the public’s information consumption, knowledge acquisition, and opinion exchange. However, it has also led to more violent conflicts in online discussions. …”
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IMPLEMENTATION OF LEARNING MANAGEMENT SYSTEMS WITH GENERATIVE ARTIFICIAL INTELLIGENCE FUNCTIONS IN THE POST-PANDEMIC ENVIRONMENT by Denis-Cătălin Arghir

“…This choice not only streamlines instructor support but also facilitates the creation of courses using an adapted and coherent language. …”
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Solid breast tumors phantom emulating oxy and deoxyhemoglobin concentrations for near infrared imaging. by María Victoria Waks-Serra, Demián Augusto Vera, Nicolás Abel Carbone, Héctor Alfredo García, Pamela Alejandra Pardini, Juan Antonio Pomarico, Daniela Inés Iriarte

“…CW transmittance NIRS experiments were carried out to evaluate the approach which was also compared with Monte Carlo (MC) simulations.<h4>Results</h4>Results show that the constructed tumor phantoms are feasible to reproduce the desired targets. …”
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Enhancing Streamflow Prediction in Ungauged Basins Using a Nonlinear Knowledge‐Based Framework and Deep Learning by Parnian Ghaneei, Ehsan Foroumandi, Hamid Moradkhani

“…Besides UMAP‐GNG, the integration of Principal Component Analysis (PCA) as a linear method to reduce dimensionality with common clustering methods are also assessed to serve as benchmarks. The results reveal that the combination of clustering algorithms with the PCA method may lead to loss of information while the nonlinear method (UMAP) can extract more informative features. …”
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Cyber-Secure IoT and Machine Learning Framework for Optimal Emergency Ambulance Allocation by Jonghyuk Kim, Sewoong Hwang

“…Supervised regression algorithms—Random Forest, XGBoost, and LightGBM—were trained on 2061 center-month observations. …”
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A Novel Toolbox for Generating Realistic Biological Cell Geometries for Electromagnetic Microdosimetry by Mehrdad Saviz, A.H. Buchali Safiee, Elham Sharifi

“…We have designed a free, user-friendly tool in MATLAB that combines several known or new algorithms for easy production of three-dimensional complex cell shapes based on minimum data. …”
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Impact of EU Laws on AI Adoption in Smart Grids: A Review of Regulatory Barriers, Technological Challenges, and Stakeholder Benefits by Bo Nørregaard Jørgensen, Saraswathy Shamini Gunasekaran, Zheng Grace Ma

“…Technological challenges are also addressed, ranging from the integration of distributed energy resources and real-time data processing to cybersecurity and standardization issues. …”
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The Impact of AI-Personalized Recommendations on Clicking Intentions: Evidence from Chinese E-Commerce by Jiwang Yin, Xiaodong Qiu, Ya Wang

“…It offers valuable insights for e-commerce platforms to continuously optimize personalized recommendation algorithms and boost the click conversion rate of online shopping.…”
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Self-calibrated acceleration and detail preserving for semantic segmentation of lactating sows and piglets under low-light conditions by Aqing Yang, Yueju Xue, Na Han, Jiabi Zheng, Lei Zhang, Yizhi Luo

“…However, semantic segmentation algorithms do not yield satisfactory results under low-light conditions because these methods are highly dependent on image quality. …”
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Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal. by Susana Lavado, Eduardo Costa, Niclas F Sturm, Johannes S Tafferner, Octávio Rodrigues, Pedro Pita Barros, Leid Zejnilovic

“…Logistic regression models with variables selected through low-variance filtering and recursive feature elimination outperformed various others trained with complex machine learning algorithms based on precision@k metric, outperforming also random selection and expert rule-based models in identifying students with poor oral health. …”
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HERGAI: an artificial intelligence tool for structure-based prediction of hERG inhibitors by Viet-Khoa Tran-Nguyen, Ulrick Fineddie Randriharimanamizara, Olivier Taboureau

“…It also demonstrated superior screening power compared to virtual screening schemes that used existing scoring functions. …”
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Predicting adherence to gamified cognitive training using early phase game performance data: Towards a just-in-time adherence promotion strategy. by Yuanying Pang, Ankita Singh, Shayok Chakraborty, Neil Charness, Walter R Boot, Zhe He

“…<h4>Research design and method</h4>Using machine learning algorithms including logistic regression, ridge regression, support vector machines, classification trees, and random forests, we predicted adherence from weeks 3 to 12. …”
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Aspiring to clinical significance: Insights from developing and evaluating a machine learning model to predict emergency department return visit admissions. by Yiye Zhang, Yufang Huang, Anthony Rosen, Lynn G Jiang, Matthew McCarty, Arindam RoyChoudhury, Jin Ho Han, Adam Wright, Jessica S Ancker, Peter Ad Steel

“…These machine learning models were also compared against an existing clinical risk score. …”
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Security and Privacy in the Internet of Everything (IoE): A Review on Blockchain, Edge Computing, AI, and Quantum-Resilient Solutions by Haluk Eren, Özgür Karaduman, Muharrem Tuncay Gençoğlu

“…In addition to the proposed multi-layered architecture, the study also structures solution methods and technology integrations specific to IoE environments. …”
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Stability indicators in network reconstruction. by Michele Filosi, Roberto Visintainer, Samantha Riccadonna, Giuseppe Jurman, Cesare Furlanello

“…The number of available algorithms to infer a biological network from a dataset of high-throughput measurements is overwhelming and keeps growing. …”
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Optimizing Personalized and Context-Aware Recommendations in Pervasive Computing Environments by A. C. Kaladevi, V. Vinoth Kumar, T. R. Mahesh, Suresh Guluwadi

“…Reinforcement learning algorithms optimize the recommendation policy based on user feedback. …”
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Year-round daily wildfire prediction and key factor analysis using machine learning: a case study of Gangwon State, South Korea by Chanjung Lee, Eun Hyoung Choi, Youngju Han, Yohan Lee

“…We compare multiple algorithms, including Logistic Regression, XGBoost, and Random Forest, and use SHAP (SHapley Additive exPlanations) to enhance interpretability. …”
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Using landscape and bioclimatic features to predict the distribution of lions, leopards and spotted hyaenas in Tanzania's Ruaha landscape. by Leandro Abade, David W Macdonald, Amy J Dickman

“…Net primary productivity and tree cover also exerted some influence on habitat suitability. …”
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The transformative power of artificial intelligence in pharmaceutical manufacturing: Enhancing efficiency, product quality, and safety by Mukesh Vijayarangam Rajesh, Karthikeyan Elumalai

“…The combination of big data and AI applications through machine learning algorithms analyzes manufacturing inefficiencies and recommends improvements for both medicine formulation and packaging as well as quality control measures. …”
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