Analyzing and forecasting under-5 mortality trends in Bangladesh using machine learning techniques. by Shayla Naznin, Md Jamal Uddin, Ishmam Ahmad, Ahmad Kabir

“…<h4>Methods</h4>Data from the 1993-94 to 2017-18 Bangladesh Demographic and Health Survey (BDHS) was analyzed using advanced machine learning algorithms. Key metrics, including Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), R-squared, and Mean Absolute Percentage Error (MAPE), were employed to evaluate model performance. …”
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Impact of stain variation and color normalization for prognostic predictions in pathology by Siyu Lin, Haowen Zhou, Mark Watson, Ramaswamy Govindan, Richard J. Cote, Changhuei Yang

“…This highlights the need to develop an entirely new way to process and collect consistent microscopy images from histologic slides that can be used to both train and allow for the general application of predictive DNN algorithms.…”
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Processing streams in a monitoring cloud cluster by Alexey N. Nazarov

“…Hadoop web-programming environment is the technological basis for the development of algorithmic and software solutions for the synthesis of monitoring clusters, including information security and information counteraction systems. …”
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FusionScan: accurate prediction of fusion genes from RNA-Seq data by Pora Kim, Ye Eun Jang, Sanghyuk Lee

“…Although a number of algorithms have been developed thus far, most programs produce too many false-positives, thus making experimental confirmation almost impossible. …”
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Research of Regenerative Braking Strategy for Electric Vehicles by Van Nghia Le, Hoang Phuc Dam, Trong Hoan Nguyen, S. V. Kharitonchik, V. A. Kusyak

“…The carried out investigations confirm the available significant potential for improving the efficiency of the electric vehicles usage by developing the control strategy and algorithms of the braking energy regeneration.…”
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PHILOSOPHY OF EDUCATION IN THE DIGITAL AGE: TRANSFORMATION OF KNOWLEDGE AND LEARNING by Марина ШУЛЬГА, Інна КУЗНЄЦОВА, Наталія ПОЛІЩУК

“…Traditional educational hierarchies give way to hypertextual and multi-agent forms of knowledge transmission, where the authenticity and credibility of knowledge increasingly depend on dynamic algorithmic and simulacral constructs. The practical significance of this work lies in defining new axiological imperatives for education that focus on enhancing adaptability and critical reflexivity in the learner. …”
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Energy-aware feature and classifier for behaviour recognition of laying hens in an aviary system by X. Yang, Q. Hu, L. Nie, C. Wang

“…The study might provide insights into developing onboard behaviour recognition algorithms for laying hens.…”
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A comprehensive review of energy harvesting and routing strategies for IoT sensors sustainability and communication technology by Hesam Nejati Sharif Aldin, Mostafa Razavi Ghods, Farnoush Nayebipour, Masoud Niazi Torshiz

“…Furthermore, the study explores routing algorithms within the IoT network context, recognizing their crucial role in addressing challenges related to sensor battery lifespan and energy conservation. …”
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Peculiarities of acoustic diagnostic methods in pediatric practice (literature review, own research) by Yu.V. Marushko, O.V. Khomych

“…The conducted experimental studies demonstrated the ability of the "Trembita-Corona" device to accurately diagnose and localize lung lesions in community-acquired pneumonia, confirming the effectiveness of the developed methods and algorithms. No conflict of interests was declared by the authors.…”
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Artificial intelligence may affect diversity: architecture and cultural context reflected through ChatGPT, Midjourney, and Google Maps by Ingrid Campo-Ruiz

“…These AI perspectives on cultural context can broaden the understanding of the urban environment and facilitate a deeper insight into the prevailing ideas behind the data that train these algorithms. Results suggest that the generative AI systems analysed convey a narrow view of the cultural context, prioritising buildings and a sense of cultural context that is curated, exhibited and commercialised. …”
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Effects of image compression on face image manipulation detection: A case study on facial retouching by Christian Rathgeb, Kevin Bernardo, Nathania E. Haryanto, Christoph Busch

“…Subsequently, reference images are compressed applying JPEG and JPEG 2000 at compression levels recommended for face image storage in electronic travel documents. Novel detection algorithms utilising texture descriptors and deep face representations are proposed and evaluated in a single image and differential scenario. …”
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THE ACCEPTANCE OF AN EDUCATIONAL INTEGRATED DEVELOPMENT ENVIRONMENT TO LEARN PROGRAMMING FUNDAMENTALS by Nor Farahwahida Mohd Noor, Aslina Saad, Abu Bakar Ibrahim, Norashady Mohd Noor

“…The goal is to guide the users in problem-solving and help them write C programs based on problem-solving algorithms. The Rapid Application Development (RAD) Model was employed in the C-SOLVIS development process. …”
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Construction and validation of a senescence-related gene signature for early prediction and treatment of osteoarthritis based on bioinformatics analysis by Yonggang Wang, Zhihao Li, Xiaolong Xu, Xin Li, Rongxiang Huang, Guofeng Wu

“…CIBERSORTx and ssGSEA algorithms were then used to assess immune cell infiltration and to analyse the correlation between key DESRGs and immune infiltration. …”
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Blood-based biomarkers in patients with non-small cell lung cancer treated with immune checkpoint blockade by Yo-Ting Tsai, Jeffrey Schlom, Renee N. Donahue

“…Integration of multiple blood-based biomarkers into comprehensive panels or algorithms also has the potential to enhance predictive accuracy. …”
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Cryptanalysis of hyperchaotic S-box generation and image encryption by Mohammad Mazyad Hazzazi, Gulraiz, Rashad Ali, Muhammad Kamran Jamil, Sameer Abdullah Nooh, Fahad Alblehai

“…Because they feature substitution boxes, substitution-permutation networks (SPNs) are crucial for cryptographic algorithms such as the popular Advanced Encryption Standard (AES). …”
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Constructing a machine learning model for systemic infection after kidney stone surgery based on CT values by Jiaxin Li, Yao Du, Gaoming Huang, Yawei Huang, Xiaoqing Xi, Zhenfeng Ye

“…Five machine learning algorithms and ten preoperative or intraoperative variables were used to develop a predictive model for SIRS. …”
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ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool by D. Di Santo, C. He, F. Chen, L. Giovannini

“…This tool leverages the strengths of multiple regression-based and probabilistic machine learning methods, including LASSO (see the list of abbreviations in Appendix B), support vector machine, classification and regression trees, random forest, extreme gradient boosting, Gaussian process regression, and Bayesian ridge regression. These regression algorithms are used to construct computationally inexpensive surrogate models to effectively predict the impact of input parameter variations on model output, thereby significantly reducing the computational burden of running high-fidelity models for sensitivity analysis. …”
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Theoretical and Methodological Framework of Typologization of Digital Identity by O.A. Persidskaya

“…</strong>The theoretical and methodological framework for typologizing the digital identity of a person based on criteria of the role of the digital environment and digital device; the position of the event center of a person; the position of the center of human self-determination is presented A number of types of digital identity are described through set of appropriate scenarios of human behavior in the digital environment: 1) a person with a completed mind; 2) a person with digital physicality; 3) an algorithmic person; 4) a returning person and 5) an information tramp.…”
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Versatile waste sorting in small batch and flexible manufacturing industries using deep learning techniques by Arso M. Vukicevic, Milos Petrovic, Nebojsa Jurisevic, Marko Djapan, Nikola Knezevic, Aleksandar Novakovic, Kosta Jovanovic

“…Such a pipeline brings two key advantages that make it more applicable in industry practice by: 1) eliminating the necessity for developing dedicated waste detection and segmentation algorithms for waste object localization, and 2) significantly reducing the time and costs required for adapting the solution to different use cases. …”
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Uniform Quantization for Multi-Antenna Amplify&#x2013;Quantize&#x2013;Forward Relay by Gangsan Jeong, Xianglan Jin

“…Given the challenge of finding optimal step sizes for the MIMO AQF relay, comparing outcomes across different determination algorithms proves to be a significant obstacle. To address this, we evaluate error performance at the destination for the entire AQF relay communication system by introducing a linear detection method with significantly reduced complexity in the MIMO AQF relay channel. …”
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