The Themes of Entrepreneurship Discourse: A Data Analytics Approach by Philip T. Roundy, Arben Asllani

“…To map the themes in entrepreneurs’ language, we use data analytic techniques coupled with text mining algorithms to analyze a longitudinal corpus of entrepreneurial discourse. …”
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Recurrent neural networks for aerodynamic parameter estimation with Lyapunov stability analysis by Sara Mohan George, S. S. Selvi, J. R. Raol

“…The estimated parameters were also compared with estimates obtained from Unscented Kalman Filter (UKF). …”
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Advancements in Parkinson’s Disease Diagnosis: A Comprehensive Survey on Biomarker Integration and Machine Learning by Ruchira Pratihar, Ravi Sankar

“…This comprehensive review explores the advancements in machine learning algorithms in the diagnosis of Parkinson’s disease (PD) utilizing different biomarkers. …”
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Purine metabolism-associated key genes depict the immune landscape in gout patients by Lin-na Li, Hao Wang, Lu-shan Xiao, Wei-nan Lai

“…Most importantly, they were also partially dysregulated in a wide range of malignancies and exerted a notable influence on the survival of tumor patients, especially LIHC (Liver hepatocellular carcinoma). …”
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AI-driven biomarker discovery: enhancing precision in cancer diagnosis and prognosis by Esther Ugo Alum

“…Existing gaps include data quality, algorithmic transparency, and ethical concerns around privacy, among others. …”
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DLLabelsCT: Annotation tool using deep transfer learning to assist in creating new datasets from abdominal computed tomography scans, case study: Pancreas. by Henrik Mustonen, Antti Isosalo, Minna Nortunen, Mika Nevalainen, Miika T Nieminen, Heikki Huhta

“…However, training DL algorithms to clinical standards requires extensive datasets, and their processing is labor-intensive. …”
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Ctta: a novel chain-of-thought transfer adversarial attacks framework for large language models by Xinxin Yue, Zhiyong Zhang, Junchang Jing, Weiguo Wang

“…However, this capability also introduces the potential for more covert and effective adversarial attack methods. …”
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Performance of 2D Compressive Sensing on Wide-Beam Through-the-Wall Imaging by Edison Cristofani, Mathias Becquaert, Marijke Vandewal

“…Conventional through-the-wall imaging using a synthetic aperture configuration can also take advantage of compressive sensing by reducing data acquisition rates and omitting certain azimuth scanning positions. …”
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Unpacking Performance Variability in Deep Reinforcement Learning: The Role of Observation Space Divergence by Sooyoung Jang, Ahyun Lee

“…Deep Reinforcement Learning (DRL) algorithms often exhibit significant performance variability across different training runs, even with identical settings. …”
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Underwater Image Enhancement Methods Using Biovision and Type-II Fuzzy Set by Yuliang Chi, Chao Zhang

“…The framework not only adjusts the overall image features, but also finely handles the local details, resulting in a significant enhancement of both the overall quality and the local detail clarity of underwater images. …”
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The distribution of shared parking use in time and space: A case study in Guangzhou, China by Juan Wang, Pengyu Zhu

“…In recent years, increasingly more research investigated people’s intentions to participate in shared parking schemes as well as optimization algorithms to match shared parking supplies and demands. …”
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Improving Time Series Data Quality: Identifying Outliers and Handling Missing Values in a Multilocation Gas and Weather Dataset by Ali Suliman AlSalehy, Mike Bailey

“…First, outliers were identified via statistical methods like Interquartile Range and Z-Score. Machine learning algorithms like Isolation Forest and Local Outlier Factor were also used, chosen for their robustness to non-normal data distributions, significantly improving subsequent imputation accuracy. …”
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RRMSE-enhanced weighted voting regressor for improved ensemble regression. by Shikun Chen, Wenlong Zheng

“…Our approach not only fills a gap in current ensemble regression techniques but also provides a reliable and adaptable method for boosting prediction performance in various machine learning tasks. …”
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Evaluating remote photoplethysmography: A 10-minute video dataset in uncontrolled lightingMendeley Data by Gonçalo Rodrigues, Nuno M. Garcia

“…The dataset aims to support the development and benchmarking of rPPG algorithms under realistic webcam conditions. Baseline heart rate estimations using standard rPPG methods are also provided.…”
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History of Location Objectives (Hilal Tracker): Development of Astronomical Observations from 2015-Present by Marataon Ritonga, Alya Fathi Muhammad Hasibuan, Rizqan Arya Perdana Nazara

“…Therefore, Hilal Tracker is not just a technical device, but also a means of education and diplomacy in creating a unified Hijri calendar worldwide with an observational approach. …”
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Approaches for Localizing the Origin of PVCs in the Outflow Tract: Future Perspectives and Challenges by Baiping Sui, Yingjie Ji, Ying Wang, Ling Gao, Minghao Li

“…Future directions and trends in this field are also discussed.…”
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Solving differential‐algebraic equations in power system dynamic analysis with quantum computing by Huynh T. T. Tran, Hieu T. Nguyen, Long T. Vu, Samuel T. Ojetola

“…This paper demonstrates the use of quantum computing algorithms to solve DAEs for power system dynamic analysis. …”
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Enhancing Coverage and Efficiency in Wireless Sensor Networks: A Review of Optimization Techniques by Rajasekaran S, Shaik Mastan Vali

“…Key findings emphasize the effectiveness of various techniques in enhancing coverage, such as mobility-based approaches and energy-aware algorithms, while also addressing practical challenges like sensor redundancy and environmental unpredictability. …”
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Computational toolkit for predicting thickness of 2D materials using machine learning and autogenerated dataset by large language model by Chinedu E. Ekuma

“…The thickness of 2D materials not only plays a crucial role in determining the performance of nanoelectronic and optoelectronic devices but also introduces complexities in predicting volume-dependent properties, such as energy storage capacity, due to the intrinsic vacuum within these materials. …”
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Artificial Intelligence in Journalism: Bibliometric Analysis of Publication Activity by Violetta A. Zorina

“…Artificial intelligence is changing the algorithms for the development of various spheres of society, is actively being introduced into the media industry, producing new opportunities and social risks. …”
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