CONSTRUCTION OF SUBSTITUTION BOX (S-BOX) BASED ON IRREDUCIBLE POLYNOMIALS ON GF(2^8) by Faldy Tita, Adi Setiawan, Bambang Susanto

“…The main goal is to determine the most optimal S-Box structure to minimize correlation, thereby improving the security and unpredictability of the cryptographic system. …”
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ML-Based Materials Evaluation in 3D Printing by Izabela Rojek, Dariusz Mikołajewski, Krzysztof Galas, Jakub Kopowski

“…This predictive ability helps in selecting the most suitable materials for specific printing tasks, optimizing the mechanical, chemical, and overall quality of the final product. …”
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Pertinence of contact duration as edge feature for epidemic spread analysis by Ramya D. Shetty, Shrutilipi Bhattacharjee

“…Existing studies consider the edges mostly equally while designing the algorithms for the unweighted contact networks, where each connection explicitly shows whether the individuals are in contact or not. …”
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A Comprehensive Review of the Diagnostics for Pediatric Tuberculosis Based on Assay Time, Ease of Operation, and Performance by Soumya Basu, Subhra Chakraborty

“…The review highlights emerging molecular methods and artificial intelligence-based detection methods, which offer promising improvements in both speed and sensitivity. The review also addresses the challenges of implementing these technologies in resource-limited settings, where most pediatric TB cases occur. …”
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Dynamic Skin: A Systematic Review of Energy-Saving Design for Building Facades by Jian Wang, Shengcai Li, Peng Ye

“…Parametric modeling, computer simulation, and multi-objective algorithms are commonly used to optimize the performance of dynamic skin. …”
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Analysis of the state of geometrization development and digital modeling in open-pit mining enterprises by M.S. Kunytska, D.S. Polishchyk, O.V. Shapochnikov

“…Key development trends are identified: integration of digital technologies, improvement of methods of collecting and processing geospatial data, introduction of machine learning algorithms for risk prediction. …”
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Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery by Fouad Trad, Bassel Isber, Ryan Yammine, Khaled Hatoum, Dana Obeid, Mohammad Chahine, Rachid Haidar, Ghada El-Hajj Fuleihan, Ali Chehab

“…In this study, we developed machine learning (ML) algorithms to estimate 30-day mortality risk post-hip fracture surgery in the elderly using data from the National Surgical Quality Improvement Program (NSQIP 2012–2017, n = 62,492 patients). …”
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A prediction method for radiation proctitis based on SAM-Med2D model by Ning Zhang, Haifeng Ling, Wenyu Zhang, Mei Zhang

“…Accurate diagnosis are crucial for optimizing treatment strategies and improving patient outcomes. …”
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Energy Efficient Heat Exchange Network for the Oil Vacuum Distillation Facility by Ved V.E., Ilchenko M.V., Myronov A.N.

“…The task is achieved by applying design algorithms of a pinch analysis. The most important result of the work is the proven possibility of reducing the external heat carriers’ energy by 1.87 MW and increasing the thermal energy recovery inside the system to 11.26 MW. …”
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Energy-Efficient model for integrated berth allocation and quay crane management by Saeedeh Khalilpoor, Mehdi A. Kamran, Reza Babazadeh, Reza Kia

“…The challenge of allocating berths and assigning as well as scheduling quay cranes (QCs) is identified as one of the most important concerns of port operations, given that it involves many trade-offs for the improvement of efficiency. …”
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Predicting child mortality determinants in Uttar Pradesh using Machine Learning: Insights from the National Family and Health Survey (2019–21) by Pinky Pandey, Sacheendra Shukla, Niraj Kumar Singh, Mukesh Kumar

“…Policy measures targeting critical factors, such as promoting breastfeeding, optimizing birth intervals, and improving maternal health and antenatal care, can significantly enhance childhood survival rates in Uttar Pradesh.…”
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The future of critical care: AI-powered mortality prediction for acute variceal gastrointestinal bleeding and acute non-variceal gastrointestinal bleeding patients by Zhou Liu, Guijun Jiang, Liang Zhang, Palpasa Shrestha, Yugang Hu, Yi Zhu, Guang Li, Yuanguo Xiong, Liying Zhan

“…BackgroundAcute upper gastrointestinal bleeding (AUGIB) is one of the most common critical diseases encountered in the intensive care unit (ICU), with a mortality rate ranging from 15 to 20%. …”
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A Review of Passenger Counting in Public Transport Concepts with Solution Proposal Based on Image Processing and Machine Learning by Aleksander Radovan, Leo Mršić, Goran Đambić, Branko Mihaljević

“…The accurate counting of passengers in public transport systems is crucial for optimizing operations, improving service quality, and planning infrastructure. …”
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Comparative Analysis of Machine Learning Models for Predicting Innovation Outcomes: An Applied AI Approach by Marko Martinović, Kristian Dokic, Dalibor Pudić

“…Logistic regression proved to be the most computationally efficient model despite its weaker predictive power. …”
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Integrating Sentiment Analysis With Machine Learning for Cyberbullying Detection on Social Media by Maram Fahaad Almufareh, Noor Zaman Jhanjhi, Mamoona Humayun, Ghadah Naif Alwakid, Danish Javed, Saleh Naif Almuayqil

“…Furthermore, we provide the most optimal text preprocessing steps which are ordered in a way that improves text quality for cyberbullying detection. …”
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Non-operative management of locally advanced rectal cancer with an emphasis on outcomes and quality of life: a narrative review by In Ja Park

“…Total neoadjuvant therapy increases cCR rates to 30%–60% and expands the pool of WW candidates, but also intensifies the need for standardized response definitions and surveillance algorithms. WW offers organ preservation and quality‑of‑life improvements without compromising survival in carefully selected patients, provided that multidisciplinary teams ensure rigorous response assessment and lifelong monitoring. …”
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Carbon Sequestration Strategies in Regenerative Agricultural Systems by Leveraging Wireless Sensor Networks for Precision Carbon Management by Al-Jawahry Hassan M., AI_Sadi Hafidh l., Rajasekhar Boddu

“…In this study, a total approach towards optimizing carbon sequestration strategies using advanced technologies like Wireless Sensor Network (WSN), Digital Twin model, and predictive algorithms like Random Forest Regression and gradient boosting are presented. …”
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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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Solving Linear Programming Problems by Reducing to the Form with an Obvious Answer by Gleb D. Stepanov

“…At the third stage the matrix is transformed into a matrix that provides non-negativity and optimality of the basic solution. For the second stage the analog of which in the simplex method uses an artificial basis and is the most time-consuming, two variants without artificial variables are given. …”
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Predicting anemia management in dialysis patients using open-source machine learning libraries by Takahiro Inoue, Norio Hanafusa, Yuki Kawaguchi, Ken Tsuchiya

“…Performance metrics were compared across models, including XGBoost and LightGBM, to identify the most accurate algorithms. Results LightGBM and XGBoost outperformed logistic regression in predicting ESA and iron dosage changes, achieving high accuracy (e.g., area under the curve (AUC) = 0.86 for iron dosing). …”
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