Outpatient Testing for HIV in Italy, 2018–2023—Preliminary Data by Claudio Galli, Vincenza Regine, Anna Caraglia, Francesca Centrone, Maria Chironna, Gianluca Cruschelli, Massimo Farinella, Valentina Annachiara Orlando, Chiara Pasqualini, Monia Puglia, Lucia Pugliese, Laura Rancilio, Lara Tavoschi, Fabio Voller, Barbara Suligoi

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Machine Learning and Deep Learning Models for Dengue Diagnosis Prediction: A Systematic Review by Daniel Cristobal Andrade Girón, William Joel Marín Rodriguez, Flor de María Lioo-Jordan, Jose Luis Ausejo Sánchez

“…In response to this crisis, there has been a notable increase in research employing machine learning and deep learning algorithms to anticipate diagnosis in patients with suspected dengue. …”
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Analysis of the existing approaches to in-flight aircraft rerouting by M. A. Kiselev, Yu. S. Kalyuzhny, A. V. Karpov, Yu. V. Petrov

“…The current level of avionics development provides situational awareness necessary for obstacles avoidance but requires timely, correct and sometimes non-obvious flight crew rerouting decisions. The algorithms used with robotic packages of various applications in related fields ensure the automatic rerouting for obstacle avoidance. …”
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Current Applications, Challenges, and Future Directions of Artificial Intelligence in Emergency Medicine: A Narrative Review by Mehrdad Farrokhi, Amir H Fallahian, Erfan Rahmani, Ali Aghajan, Morteza Alipour, Parisa Jafari Khouzani, Hossein Boustani Hezarani, Hamed Sabzehie, Mohammad Pirouzan, Zahra Pirouzan, Behnaz Dalvandi, Reza Dalvandi, Parisa Doroudgar, Habib Azimi, Fatemeh Moradi, Amitis Nozari, Maryam Sharifi, Hamed Ghorbani, Sara Moghimi, Fatemeh Azarkish, Soheil Bolandi, Hooman Esfahani, Sara Hosseinmirzaei, Arezou Niknam, Farzaneh Nikfarjam, Parham Talebi Boroujeni, Mahyar Noorbakhsh, Parham Rahmani, Fatemeh Rostamian Motlagh, Khadijeh Harati, Masoud Farrokhi, Sina Talebi, Lida Zare Lahijan

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Artificial Intelligence Applied in Legal Information: A Systematic Mapping Study by Juan DAlotto DAlotto, Claudia Pons, Leandro Antonelli

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A Novel Long Short-Term Memory Seq2Seq Model with Chaos-Based Optimization and Attention Mechanism for Enhanced Dam Deformation Prediction by Lei Wang, Jiajun Wang, Dawei Tong, Xiaoling Wang

“…To address these issues, this study aimed to improve the predictive accuracy and interpretability in dam deformation modeling by proposing a novel LSTM seq2seq model that integrates a chaos-based arithmetic optimization algorithm (AOA) and an attention mechanism. The AOA optimizes the model’s learnable parameters by utilizing the distribution patterns of four mathematical operators, further enhanced by logistic and cubic mappings, to avoid local optima. …”
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Multi-Objective Optimization of Urban Gas Station Site Selection Under Territorial Spatial Planning Constraints by Jie Zhu, Mengyao Zhu, Li Chen, Li Luo, Weihua Wang, Xueming Zhu, Yizhong Sun

“…A multi-objective optimization model employing genetic algorithms was utilized to maximize fuel demand coverage, minimize inter-station redundancy, and achieve optimal site coverage. …”
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The Possibility and Necessity of the Human-Centered AI in Legal Theory and Practice by A. V. Rezaev, N. D. Tregubova

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Multimedia privacy protection: an N-round cascaded cryptosystem based on merged multi-chaotic maps under various image attacks by Tarek Srour, Ali M. El-Rifaie, Mohsen A. M. El-Bendary, Mostafa Eltokhy, Atef E. Abouelazm, Bilel Neji

“…Based on the results from the standard database (Hlevkin, USA CANVAS), the proposed algorithm is robust and suitable for applications in noise/attack environments. …”
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Automatic detection of trapping events of postnatal piglets in loose housing pen: comparison of YOLO versions 4, 5, and 8 by Taeyong Yun, Jinsul Kim, Jinhyeon Yun, Tai-Won Um

“…This study employed three deep learning object recognition algorithms–– You Only Look Once (YOLO)v4-Tiny, YOLOv5s and YOLOv8s––followed by a performance analysis. …”
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The hermeneutical challenge of reading digital biblical texts in Africa by Marius J. Nel

“…The article proposes several avenues for African scholarship, including the creation of open-source online commentaries, increased online availability of African biblical scholarship, intentional engagement with international platforms from an African hermeneutical perspective and critical awareness of the algorithms that govern online content. Contribution: The article emphasises the need for a balanced and contextually relevant approach to interpreting digital biblical texts in Africa.…”
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Bootstrap for finite N lattice Yang-Mills theory by Vladimir Kazakov, Zechuan Zheng

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Recent Developments in Path Planning for Unmanned Ground Vehicles in Underground Mining Environment by Abdurauf Abdukodirov, Jörg Benndorf

“…The most favorable and relevant algorithms, including A*, Rapidly-exploring Random Tree (RRT*), Dijkstra’s, Ant Colony Optimization (ACO), were identified. …”
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Mixed-Embeddings and Deep Learning Ensemble for DGA Classification With Limited Training Data by Christian Morbidoni, Alessandro Cucchiarelli, Luca Spalazzi

“…Recent papers in the cybersecurity research field of Domain Generation Algorithms (DGAs) detection show the increase of performances associated with the introduction of unsupervised neural vectorized representation of domain names in the supervised classification process. …”
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Improving quantum metrology protocols with programmable photonic circuits by de las Heras Alberto Muñoz, Porras Diego, González-Tudela Alejandro

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Multi-objective Windy Postman Problem in a Fuzzy Transportation Network by Debosree PAL, Haresh Kumar SHARMA, Olegas PRENTKOVSKIS, Falguni CHAKRABORTY, Lijana MASKELIŪNAITĖ

“…Subsequently, the epsilon-constraint method, a classical multi-objective solution methodology, is used to solve the deterministic transformation of the relevant CCPM. Moreover, the model is solved using two multi-objective genetic algorithms (MOGAs): fast Pareto genetic algorithm (FastPGA) and nondominated sorting genetic algorithm II (NSGAII). …”
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Redefining IoT networks for improving energy and memory efficiency through compressive sensing paradigm by S. Balamurali, M. Kathirvelu, SatheeshKumar Palanisamy, Ines Hilali Jaghdam

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State-of-the-Art Fault Detection and Diagnosis in Power Transformers: A Review of Machine Learning and Hybrid Methods by Lebo Dina Mashifane, Bongumsa Mendu, Bessie Baakanyang Monchusi

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Evolving Hybrid Deep Neural Network Models for End-to-End Inventory Ordering Decisions by Thais de Castro Moraes, Jiancheng Qin, Xue-Ming Yuan, Ek Peng Chew

“…However, current approaches predominantly rely on feed-forward networks, which may have difficulty capturing temporal correlations in time series data and identifying relevant features, resulting in less accurate predictions. …”
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Data-Driven Computational Methods in Fuel Combustion: A Review of Applications by Jacek Lukasz Wilk-Jakubowski, Lukasz Pawlik, Damian Frej, Grzegorz Wilk-Jakubowski

“…This review article provides a comprehensive analysis of the recent advancements in combustion science and engineering, focusing on the application of machine learning and genetic algorithms from 2015 to 2024. The study examines the integration of computational methods, including computational fluid dynamics, neural networks, and genetic algorithms, with various fuel types such as biodiesel, biomass, coal, gasoline, hydrogen, and natural gas. …”
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