OPACITY INFLUENCED INCONSTANT METHOD FOR 3D HOLOGRAPHIC PYRAMID RENDERING by Sarah َQahtan Mohammed Salih, Puteri Suhaiza Sulaiman, Abdul Sattar Arif Khammas, Ramlan Mahmod, Rahmita Wirza O.K. Rahmat

“…The rapid growth of computer graphics in human daily life has inspired researchers to maximize image understanding and discover new methods for visualizing 3D objects. …”
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Diagnostic Accuracy of a Machine Learning-Derived Appendicitis Score in Children: A Multicenter Validation Study by Emrah Aydın, Taha Eren Sarnıç, İnan Utku Türkmen, Narmina Khanmammadova, Ufuk Ateş, Mustafa Onur Öztan, Tamer Sekmenli, Necip Fazıl Aras, Tülin Öztaş, Ali Yalçınkaya, Murat Özbek, Deniz Gökçe, Hatice Sonay Yalçın Cömert, Osman Uzunlu, Aliye Kandırıcı, Nazile Ertürk, Alev Süzen, Fatih Akova, Mehmet Paşaoğlu, Egemen Eroğlu, Gülnur Göllü Bahadır, Ahmet Murat Çakmak, Salim Bilici, Ramazan Karabulut, Mustafa İmamoğlu, Haluk Sarıhan, Süleyman Cüneyt Karakuş

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Symmetric Grayscale Image Encryption Based on Quantum Operators with Dynamic Matrices by Luis Olvera-Martinez, Manuel Cedillo-Hernandez, Carlos Adolfo Diaz-Rodriguez, Leonardo Faustinos-Morales, Antonio Cedillo-Hernandez, Francisco Javier Garcia-Ugalde

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Continuous wavelet based transfer function analysis of cerebral autoregulation dynamics for neuromonitoring using near-infrared spectroscopy by Marcus Thudium, Evgeniya Kornilov, Evgeniya Kornilov, Stefan Moestl, Fabian Hoffmann, Fabian Hoffmann, Alex Hoff, Surat Kulapatana, Surat Kulapatana, Surat Kulapatana, Vasile Urechie, Vasile Urechie, Maximilian Oremek, Stefano Rigo, Stefano Rigo, Stefano Rigo, Karsten Heusser, Italo Biaggioni, Jens Tank, André Diedrich, André Diedrich

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Understanding levels of best practice: An empirical validation. by Huy P Phan, Bing H Ngu, Hui-Wen Wang, Jen-Hwa Shih, Sheng-Ying Shi, Ruey-Yih Lin

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Classifying detrital zircon U-Pb age distributions using automated machine learning by Jack W. Fekete, Glenn R. Sharman, Xiao Huang

“…Specifically, we hypothesize that automated machine learning (AutoML), which optimizes algorithm selection and hyperparameters, will outperform an unoptimized Random Forest (RF) classifier and the cross-correlation coefficient (R2), a commonly used metric for comparing age distributions. …”
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A Systematic Literature Review of Concept Drift Mitigation in Time-Series Applications by Mujaheed Abdullahi, Hitham Alhussian, Norshakirah Aziz, Said Jadid Abdulkadir, Yahia Baashar, Abdussalam Ahmed Alashhab, Afroza Afrin

“…To address this issue, researchers have developed several CD detection and adaptation techniques. …”
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Impact of germline BRCA1/2 status on outcomes for patients with HR+/HER2- metastatic breast cancer treated with CDK4/6 inhibitors: a systematic review and meta-analysis by Michele Bottosso, Christian Zurlo, Federica Miglietta, Anna Chiara Cattelan, Daniela Iannaccone, Maria Vittoria Dieci, Gaia Griguolo, Fabio Girardi, Valentina Guarneri

“…Conclusions: Emerging data suggest that gBRCAm patients with advanced HR+/HER2- BC may experience shorter PFS and OS with CDK4/6 inhibitor compared to gBRCAwt. Given the low level of evidence and the high risk of bias in available studies, further research is needed to understand molecular mechanisms and identify the optimal treatment sequence.…”
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Strata pressure behavior law and regional-level intelligent early warning for high-intensity mining in extended working faces of medium-thick coal seams in Yuheng mining area by Feng CUI, Cheng ZONG, Xingping LAI, Tao XIE, Yunhu BAI, Yi ZHANG, Chong JIA, Hao WANG, Zhong LUO, Hao LIU

“…The spatio-temporal correlation characteristics of the support in the working face were extracted by using the unsupervised clustering algorithm, forming a spatio-temporal linkage support resistance analysis method. …”
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Analisis Perbandingan Algoritma Machine Learning dan Deep Learning untuk Klasifikasi Citra Sistem Isyarat Bahasa Indonesia (SIBI) by Mohammad Farid Naufal, Selvia Ferdiana Kusuma

“…In previous studies, no one has compared machine learning and deep learning classification algorithms for the classification of SIBI. …”
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Hyperspectral and LiDAR space-borne data for assessing mountain forest volume and biomass by Rodolfo Ceriani, Sebastian Brocco, Monica Pepe, Silvio Oggioni, Giorgio Vacchiano, Renzo Motta, Roberta Berretti, Davide Ascoli, Matteo Garbarino, Donato Morresi, Francesco Bassi, Francesco Fava

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Automated Video Assistant Referee in Lead Climbing by Eliane Künzler, David Roder, Urs Stöcker, Peter Wolf

“…The video would also have to be cropped before each pose estimation, otherwise few (BlazePose) or incorrect (RTMO) poses would be detected caused by picture content being more contrasting and larger than the athlete. Next, we will compare our scoring algorithm representing given regulations with scores awarded. …”
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Predicting Protein Interactions Using a Deep Learning Method-Stacked Sparse Autoencoder Combined with a Probabilistic Classification Vector Machine by Yanbin Wang, Zhuhong You, Liping Li, Li Cheng, Xi Zhou, Libo Zhang, Xiao Li, Tonghai Jiang

“…Although high-throughput experimental techniques have matured, enabling researchers to detect large amounts of PPIs, it has unavoidable disadvantages, such as having a high cost and being time consuming. …”
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Large Language Model-Assisted Reinforcement Learning for Hybrid Disassembly Line Problem by Xiwang Guo, Chi Jiao, Peng Ji, Jiacun Wang, Shujin Qin, Bin Hu, Liang Qi, Xianming Lang

“…Additionally, we introduce large language model-assisted reinforcement learning to solve this model, which employs a Dueling Deep Q-Network (Duel-DQN) to tackle the problem and integrates a large language model (LLM) into the algorithm. The experimental results show that compared to solutions that solely use reinforcement learning, large language model-assisted reinforcement learning reduces the number of iterations required for convergence by approximately 50% while ensuring the quality of the solutions. …”
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Platelet mass cytometry reveals dysregulation of prothrombotic pathways in essential thrombocythemia by Veronika Dill, Kilian Kirmes, Jiaying Han, Melissa Klug, Marc Rosenbaum, Giacomo Viggiani, Moritz von Scheidt, Markus List, Peter Herhaus, Jürgen Ruland, Florian Bassermann, Karl-Ludwig Laugwitz, Katharina S. Götze, Philipp J. Jost, Stefanie Jilg, Conor J. Bloxham, Philip W.J. Raake, Isabell Bernlochner, Dario Bongiovanni

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Artificial intelligence in hospital infection prevention: an integrative review by Rabie Adel El Arab, Zainab Almoosa, May Alkhunaizi, May Alkhunaizi, Fuad H. Abuadas, Joel Somerville, Joel Somerville

“…Advanced algorithms, including neural networks, decision trees, and random forests, significantly improved detection rates when integrated with EHRs, enabling real-time surveillance and timely interventions. …”
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A robust and efficient approach to estimating the age of secondary mangrove forests employing time-series Landsat images and the CCDC model by Yue Zhang, Xiaoyan Li, Rong Zhang, Lina Cheng, Mingming Jia, Chuanpeng Zhao, Xianxian Guo, Haihang Zeng, Wensen Yu, Qian Shi, Zongming Wang

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Comparison of Recent Remote Sensing Data Using an Artificial Neural Network to Predict Soil Moisture by Focusing on Radiometric Indices by Miraç Kılıç, Recep Gündoğan

“…The aim of this study, quite recently made available to researchers Operational Land Imager 2 (OLI–2) have structure Landsat 9 and Landsat 8 (OLI) and Sentinel 2A (MSI) to compare the performance of soil moisture estimation in multi-layer perceptron network (MLP) artificial intelligence algorithm of image data. …”
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Externally bonded reinforcement side extended (EBRSE) technique to postpone debonding of FRP laminates in strengthened concrete elements by Mehdi Aghabagloo, Laura Carreras, Cristina Barris, Alba Codina, Marta Baena

“…In this work, single shear tests were conducted on concrete specimens using both EBRSE and conventional EBR techniques to compare their performance. Additionally, a numerical approach was applied, combining the finite difference method with a metaheuristic optimization algorithm, to derive the bond-slip law governing the constitutive behavior of both systems. …”
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Development and validation of novel machine learning-based prognostic models and propensity score matching for comparison of surgical approaches in mucinous breast cancer by Chunmei Chen, Jundong Wu, Yutong Fang, Yong Li, Qunchen Zhang

“…Ten machine learning algorithms were utilized to develop prognostic models, which were further validated using MBC patients from two Chinese hospitals. …”
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