Vertical two-phase flow regimes in an annulus image dataset - Texas A&M universityMendeley Data by Kaushik Manikonda, Chinemerem Obi, Aarya Abhay Brahmane, Mohammad Azizur Rahman, Abu Rashid Hasan

“…This dataset results from meticulous experimental work in the 140 ft Tower Lab, utilizing a combination of water and air flows to simulate real-world conditions and employing high-quality video recordings to document flow regime transitions. …”
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Application of IoT-Based Drones in Precision Agriculture for Pest Control by Mohamad Reda. A. Refaai, Vinjamuri SNCH Dattu, N. Gireesh, Ekta Dixit, CH. Sandeep, David Christopher

“…Unmanned aerial vehicles (UAVs), commonly known as drones, have been progressively prevalent due to their capability to operate quickly and their vast range of applications in a variety of real-world circumstances. The utilization of UAVs in precision farming has lately gained a lot of attention from the scientific community. …”
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E-Commerce Fraud Detection Based on Machine Learning Techniques: Systematic Literature Review by Abed Mutemi, Fernando Bacao

“…However, research on fraud detection systems has struggled to keep pace due to limited real-world datasets. Advances in artificial intelligence, Machine Learning (ML), and cloud computing have revitalized research and applications in this domain. …”
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Attention-enhanced corn disease diagnosis using few-shot learning and VGG16 by Ruchi Rani, Jayakrushna Sahoo, Sivaiah Bellamkonda, Sumit Kumar

“…. • By applying Few-Shot Learning, the system avoids the significant challenges of requiring extensively annotated datasets, making it feasible for real-world agricultural applications. • Incorporating a fine-tuned VGG16 backbone along with an attention mechanism and prototypical Few-Shot Learning results in a robust and scalable solution with high accuracy for classifying corn diseases.…”
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A Multimodal Passenger-and-Package Sharing Network for Urban Logistics by Yuxiong Ji, Yujing Zheng, Jizhou Zhao, Yu Shen, Yuchuan Du

“…The model is implemented based on the real-world data in Shanghai (China) under a series of scenarios to evaluate the network performance from two perspectives: the number of hubs and the proportion of taxi drivers who are willing to carry packages. …”
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Integrating Human Learning Factors and Bayesian Analysis Into Software Reliability Growth Models for Optimal Release Strategies by Chih-Chiang Fang, Liping Ma, Wenfeng Kuo

“…This results in parameter estimates that more accurately represent real-world scenarios, making the model more intuitive for experts to apply. …”
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sAMDGCN: sLSTM-Attention-Based Multi-Head Dynamic Graph Convolutional Network for Traffic Flow Forecasting by Shiyuan Zhang, Yanni Ju, Weishan Kong, Hong Qu, Liwei Huang

“…To validate the effectiveness of sAMDGCN, we perform extensive experiments on four real-world traffic flow datasets. Experimental results show that our proposed sAMDGCN model outperforms the advanced baseline methods in long-term traffic flow prediction tasks, demonstrating its superior performance in capturing complex and dynamic traffic patterns.…”
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Reimagining Student Success through Engagement and Soft Outcomes: Learning from a Capstone Course in a Canadian Polytechnic by Clare Mulcahy, Ashique Khan

“…In this course, students, guided by faculty advisors, work in teams to address real-world projects solicited by individuals or organizations. …”
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A quantitative model of hierarchical product design by Ferdinand Wöhr, Simon Königs, Max Stanglmeier, Markus Zimmermann

“…The results show the following phenomena observed in real-world product design: design iterations occur naturally as a consequence of the designers’ individual behaviour; inconsistencies in designs emerge and are resolved. …”
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A Bayesian Best-Worst Method-Based Multicriteria Competence Analysis of Crowdsourcing Delivery Personnel by Longxiao Li, Xu Wang, Jafar Rezaei

“…To illustrate the MCCA approach, a real-world case study is conducted involving a Chinese takeaway delivery platform, where the Bayesian best-worst method is used to determine the weights of the criteria based on the data collected from managers of the platform company. …”
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A comprehensive review of fiber-reinforced topology optimization for advanced polymer composites produced by automated manufacturing by Bence Szederkenyi, Norbert Krisztian Kovacs, Tibor Czigany

“…We emphasize practical considerations such as manufacturing constraints and algorithmic efficiency, addressing real-world usability aspects [2]. The analysis underscores the necessity for universally applicable benchmark methods and standardization to facilitate direct comparisons among various methodologies [3]. …”
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Invisible Scout: A Layer 2 Anomaly System for Detecting Rogue Access Point (RAP) by Diki Arisandi, Nazrul M. Ahmad, Subarmaniam Kannan

“…This study aimed to develop and validate a mechanism capable of accurately detecting RAPs in controlled setups, real-world environments, and under de-authentication attack scenarios. …”
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The recent landscape of RSV vaccine research by Karen Kelleher, Nadisha Subramaniam, Simon B. Drysdale

“…Recent advancements include nirsevimab, a long-acting mAb that has shown substantial efficacy in reducing medically attended RSV-related disease in infants, in phase III clinical trials, early regional and national real-world data. In addition, three new vaccines have been approved: two protein subunit vaccines and a messenger RNA vaccine. …”
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Analysis of postmarketing neuropsychiatric adverse events of avapritinib based on the FDA adverse event reporting system by Wei Mao, Junyan Jiang, Yanping Xia, Lin Zhang

“…However, the majority of current data comes from pre-marketing, with limited real-world studies. Our research aimed to explore post-marketing data of avapritinib. …”
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High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats by Erin McDonald, Eric Kehoe, Darcy Deines, Mary McCarthy, Brie Wright, Susan Huse

“…To enhance our understanding of cat and dog biology and test the unsupervised clustering approach on real-world samples, we performed in-depth profiling of immune cell populations in blood collected from client-owned and laboratory animals [dogs (n = 55) and cats (n = 68)]. …”
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Innovative Application of Nano-Organic Photochromic New Materials in Hakka Traditional Decorative Pattern Design by HuiJuan Lai

“…The themes of Hakka traditional decorative patterns come from the real world or the imaginary world, expressing the expectation and beautiful vision of life. …”
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Machine and deep learning performance in out-of-distribution regressions by Assaf Shmuel, Oren Glickman, Teddy Lazebnik

“…While the degradation in OOD performance is well acknowledged, to the best of our knowledge, this is one of the first studies to quantify it for various models on a large benchmark n  = 15 real-world regression datasets. We extensively ( $n \gt 40\,000$ runs) compare the ID versus OOD performance of XGBoost, random forest, K-nearest-neighbors, support vector machine, and linear regression models, as well as AutoML models (Tree-based Pipeline Optimization Tool and AutoKeras). …”
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Application of machine learning in asphalt and concrete material testing: A comprehensive review by Khorshidi Meisam, Dave Eshan, Sias Jo

“…The review concludes by emphasizing the potential of hybrid and ensemble models to improve prediction accuracy and reduce computational costs, highlighting the need for further research to address data availability, model interpretability, and practical implementation challenges in real-world applications.…”
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Think4SCND: Reinforcement Learning With Thinking Model for Dynamic Supply Chain Network Design by Pan Li, Shaochen Ren, Qun Zhang, Xuran Wang, Yang Liu

“…Extensive experiments on both synthetic and real-world datasets show that Think4SCND significantly outperforms state-of-the-art baselines, achieving near-optimal solutions with a fraction of the computational cost. …”
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Accelerating Multilingual Cryptocurrency Forensics: An NLP-Driven Approach for Efficient Mnemonic Identification by Hsin-Hsiung Kao

“…We trained and compared four NLP deep learning models: RNN, LSTM, BiLSTM, and TextCNN, on a large-scale, real-world dataset. Our analysis reveals that the Text Convolutional Neural Network (TextCNN) model exhibits superior performance, achieving a 99.9993% accuracy rate, nearly matching the 100% accuracy of the Mnemonic Library Matching Method. …”
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