An innovative approach to urban parks and perception: a cross-cultural analysis using big and small data by Siqi Lai, Brian Deal

“…This study integrates big data (online reviews, images) and small data (survey results) with large language models (LLMs) and object detection algorithms to analyze public perceptions of urban parks in Stockholm, New York, and Shanghai. …”
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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

“…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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A happy place to be in: how beliefs about living places influence depression in Chinese international student returnees by Ruining Jin, Meiling Yin, Qiang Shen, Tam-Tri Le

“…Depression levels were measured using the Patient Health Questionnaire-9 (PHQ-9), and Bayesian analysis with Markov Chain Monte Carlo (MCMC) algorithms was employed for statistical examination. …”
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Quantum annealing feature selection on light-weight medical image datasets by Merlin A. Nau, Luca A. Nutricati, Bruno Camino, Paul A. Warburton, Andreas K. Maier

“…Abstract We investigate the use of quantum computing algorithms on real quantum hardware to tackle the computationally intensive task of feature selection for light-weight medical image datasets. …”
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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

“…However, biological shapes are often extremely irregular, while conventional geometrical modeling tools on the market cannot meet the demand for fast and efficient construction of irregular geometries. …”
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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

“…The analysis delves into regulatory barriers such as data protection requirements, algorithmic transparency mandates, and liability concerns that can limit the scope and scale of AI deployment. …”
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Deep-Learning-Based Solar Flare Prediction Model: The Influence of the Magnetic Field Height by Lei Hu, Zhongqin Chen, Long Xu, Xin Huang

“…With the accumulation of solar observation data and the development of data-driven algorithms, deep learning methods have been widely used to build solar flare prediction models. …”
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Emotion-Based Music Recommendation System Integrating Facial Expression Recognition and Lyrics Sentiment Analysis by V. S. G. S. Phaneendra Bottu, K. Ragavan

“…These systems can improve adaptable user interfaces and support music therapy. While prior research has explored algorithms for FER and their effectiveness in identifying emotions, existing solutions often lack optimal accuracy in pairing emotion recognition with music recommendations, particularly in real-world contexts with diverse user preferences. …”
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Integrating dimension reduction and out-of-sample extension in automated classification of ex vivo human patellar cartilage on phase contrast X-ray computed tomography. by Mahesh B Nagarajan, Paola Coan, Markus B Huber, Paul C Diemoz, Axel Wismüller

“…However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. …”
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Dynamic Collaborative Optimization Method for Real-Time Multi-Object Tracking by Ziqi Li, Dongyao Jia, Zihao He, Nengkai Wu

“…Experiments conducted on multiple public datasets, including MOT17, MOT20, and VisDrone-MOT, demonstrate that this method remarkably improves tracking accuracy while maintaining real-time performance. On the MOT17 test set, it achieves 63.7% in HOTA, 61.4 FPS in processing speed, and 79.4% in IDF1, outperforming current state-of-the-art tracking algorithms.…”
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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

“…Multiple machine learning algorithms were evaluated, including deep significance clustering (DICE), regularized logistic regression (LR), Gradient Boosting Decision Tree, and XGBoost. …”
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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

“…Comparative analyses are provided based on metrics such as energy consumption, latency, computational load, and security level, while centralized and decentralized models are evaluated through a multi-layered security lens. …”
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Optimized DINO model for accurate object detection of sesame seedlings and weeds by Yong Wang, ShunFa Xu, ZhenYuan Ye, KongHao Cheng

“…Specifically, $$\text {AP}_{S}$$ and $$\text {AP}_{M}$$ increased by 3.3% and 3.8%, respectively, while $$\text {AP}_{50}$$ and $$\text {AP}_{75}$$ increased by 2.3% and 3.2%. …”
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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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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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Predicting the animal hosts of coronaviruses from compositional biases of spike protein and whole genome sequences through machine learning. by Liam Brierley, Anna Fowler

“…More widely, this work demonstrates the potential in combining genetic resources with machine learning algorithms to address long-standing challenges in emerging infectious diseases.…”
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Benefits and Challenges of AI-Based Digital Twin Integration in the Saudi Arabian Construction Industry: A Correspondence Analysis (CA) Approach by Aljawharah A. Alnaser, Haytham Elmousalami

“…This progress is mainly driven by the emergence of innovative technologies, including artificial intelligence (AI) and digital twins (DTs). While global research has extensively explored the benefits and challenges of AI-based DTs, the rapid growth of Saudi Arabia’s construction sector—fueled by substantial local investments and international partnerships—underscores the urgent need to examine their specific impact within this context. …”
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A Flow Cytometry Protocol for Measurement of Plant Genome Size Using Frozen Material by Abhishek Soni, Lena Constantin, Agnelo Furtado, Robert J Henry

“…With the addition of specific debris compensation algorithms, coefficient of variation (CV%) can be maintained below 5%. …”
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Advancements in Retinal Tissue-Mimicking Optical Coherence Tomography Phantoms: Materials, Properties, and Applications by Mukhit Kulmaganbetov

“…Optical coherence tomography (OCT) phantoms are essential tools for calibrating imaging systems, validating diagnostic algorithms, and bridging technological advancements with clinical applications. …”
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