Unsupervised Image Super-Resolution for High-Resolution Satellite Imagery via Omnidirectional Real-to-Synthetic Domain Translation by Minkyung Chung, Yongil Kim

“…While deep-learning networks have significantly improved SR performance, obtaining paired low-resolution (LR) and high-resolution (HR) images for supervised learning remains challenging in real-world scenarios. In this article, we propose a novel unsupervised image super-resolution model for real-world remote sensing images, specifically focusing on HR satellite imagery. …”
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A novel quantile regression for fractiles based on unit logistic exponential distribution by Hanan Haj Ahmad, Kariema A. Elnagar

“…However, challenges persist in diverse dispersion characteristics in real-world scenarios. This study introduces the unit logistic-exponential (ULE) distribution, a flexible probability model built upon the logistic-exponential distribution and designed for data confined to the unit interval. …”
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Improved Coupled Tensor Factorization with Its Applications in Health Data Analysis by Qing Wu, Jie Wang, Jin Fan, Gang Xu, Jia Wu, Blake Johnson, Xingfei Li, Quan Do, Ruiquan Ge

“…For this reason, approximate coupling or partial coupling is widely used in real-world data fusion, with exact coupling as a special case of these techniques. …”
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Steganography based on parameters’ disturbance of spatial image transform by Xi SUN, Wei-ming ZHANG, Neng-hai YU, Yao WEI

“…In the research of state-of-the-art steganography algorithms,most of image sources were natural images in laboratory environment.However,with the rapid development of image process tools and applications,images after image processing were widely used in real world.How to use image process to improve steganography has not been systematically studied.Taking spatial image transform for consideration,a parameters’ disturbance model was presented,which could hide the noise taken by steganography in the pixel fluctuation due to the disturbance.Meanwhile,it would introduce cover source mismatch for a steganalyzer.The experimental results show that,compared with using traditional image database,it can significantly enhance the security of steganography algorithms and accommodative to the real world situation.…”
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A multi-label classification method for disposing incomplete labeled data and label relevance by Lina ZHANG, Lingpeng DAI, Tai KUANG

“…Multi-label classification methods have been applied in many real-world fields，in which the labels may have strong relevance and some of them even are incomplete or missing.However，existing multi-label classification algorithms are unable to handle both issues simultaneously.A new probabilistic model that can automatically learn and exploit multi-label relevance was proposed on label relevance and missing label classification simultaneously.By integrating out the missing information，it also provides a disciplined approach to handle missing labels.Experiments on a number of real world data sets with both complete and incomplete labels demonstrated that the proposed method can achieve higher classification and prediction evaluation scores than the existing multi-label classification algorithms.…”
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The Implications of Weather and Reflectivity Variations on Automatic Traffic Sign Recognition Performance by Mudasser Seraj, Andres Rosales-Castellanos, Amr Shalkamy, Karim El-Basyouny, Tony Z. Qiu

“…Automatic recognition of traffic signs in complex, real-world environments has become a pressing research concern with rapid improvements of smart technologies. …”
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Robust Malware identification via deep temporal convolutional network with symmetric cross entropy learning by Jiankun Sun, Xiong Luo, Weiping Wang, Yang Gao, Wenbing Zhao

“…In the experiments, the proposed method is compared with several traditional statistical methods and more recent neural networks on a synthetic Malware dataset and a real‐world dataset. The performance comparisons demonstrate the better performance and noise robustness of their proposed method, especially that the proposed method can yield the best identification accuracy of 98.75% in real‐world scenarios.…”
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Complexity in Individual Trajectories toward Online Extremism by Z. Cao, M. Zheng, Y. Vorobyeva, C. Song, N. F. Johnson

“…Society faces a fundamental global problem of understanding which individuals are currently developing strong support for some extremist entity such as ISIS (Islamic State), even if they never end up doing anything in the real world. The importance of online connectivity in developing intent has been confirmed by recent case studies of already convicted terrorists. …”
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DynamicVLN: Incorporating Dynamics into Vision-and-Language Navigation Scenarios by Yanjun Sun, Yue Qiu, Yoshimitsu Aoki

“…Traditional Vision-and-Language Navigation (VLN) tasks require an agent to navigate static environments using natural language instructions. However, real-world road conditions such as vehicle movements, traffic signal fluctuations, pedestrian activity, and weather variations are dynamic and continually changing. …”
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The Effect of Delay Techniques on a Lassa Fever Epidemic Model by Ali Raza, Eugenio Rocha, Emad Fadhal, Rashid I. H. Ibrahim, Eman Afkar, Muhammad Bilal

“…The delayed intervention techniques in real-world problem modelling have a significant role in behavioural, social, physical, and biological engineering, biomathematical sciences, and many more disciplines. …”
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Experiences and overall impact reported by people living with obesity: results from a multinational study by Esther Artime, Swarna Khare, Sarah Zimner-Rapuch, Josefine Redig, Caragh Flannery, Victoria Higgins, Andrea Leith, Ashley Mortimer, Bruno Halpern, Nasreen Alfaris

“…Objectives: To explore the impact of obesity on clinical outcomes, health-related quality of life, emotional well-being, and work productivity in people/patients with obesity across six countries by body mass index and the presence of complications. Methods: Adelphi Real World Obesity Disease Specific Programme™ captured data related to physicians and their consulting people/patients with obesity on a weight management program or anti-obesity medication in Brazil, Canada, China, Japan, Kingdom of Saudi Arabia, and the United Arab Emirates from April to December 2022. …”
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A new extended Chen distribution for modelling COVID-19 data. by Amani S Alghamdi, Lulah Alnaji

“…In this paper, we propose a new flexible statistical distribution, the Topp-Leone Exponentiated Chen distribution, to model real-world data effectively, with a particular focus on COVID-19 data. …”
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Property Graph Framework for Geographical Routes in Sports Training by Alen Rajšp, Iztok Fister

“…Presenting real-world paths in property graphs is a complex challenge of identifying and representing the properties of routes and their environments. …”
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3D Interactions between Virtual Worlds and Real Life in an E-Learning Community by Ulrike Lucke, Raphael Zender

“…The primary advantages of this interconnection are a spatial extension of face-to-face and online learning scenarios and a closer relationship between virtual learners and the real world.…”
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Social Contribution-Based Routing Protocol for Vehicular Network with Selfish Nodes by Haigang Gong, Lingfei Yu, Xue Zhang

“…Routing in vehicular network is a challenging task due to the characteristic of intermittent connectivity, especially when nodes behave selfishly in the real world. Previous works usually assume that all nodes in the network are willing to forward packets for others, which is impractical in real world. …”
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Using synthetic data for the dissemination of computational geospatial models by Kostas CHELIOTIS

“… Detailed datasets of real-world systems are becoming more and more available, accompanied by a similar increased use in research. …”
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Spectral Bidirectional Reflectance Distribution Function Simplification by Shubham Chitnis, Aditya Sole, Sharat Chandran

“…., metallic inks, varnishes, and paints) are widely used in real-world applications. Accurate <i>spectral</i> rendering relies on the bidirectional reflectance distribution function (BRDF). …”
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I learned a lot about my classmates …’. Exploring focus group discussions as learning environment to raise controversial issues in geography and economic education. by Christiane Hintermann, Heidrun Edlinger, Matthias Fasching, Thomas Jekel

“…Focus groups are seen as a tool to enable real-world complexity in the classroom, and to prepare students for participatory, active citizenship. …”
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A Practical Prognostics Method Based on Stepwise Linear Approximation of a Nonlinear Degradation Model by Dawn An

“…Existing methods, such as artificial neural networks (ANNs) and their variations, often face challenges in real-world applications due to their complexity and the lack of sufficient data. …”
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A Wireless Sensor Network Testbed for the Evaluation of Energy-Aware Routing Schemes by Magdalena J. Grobler, Henri-Jean Marais, Joubert G. J. Krige

“…It was found that the real-world performance of these energy-aware protocols was significantly lower than that predicted by simulation models. …”
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