Efficient Resource Allocation for Blockchain-Enabled Mobile Edge Computing: A Joint Optimization Approach by Moein Valitabar, Mohammad Fathi, Keivan Navaie

“…Performance evaluation results demonstrate the effectiveness of these algorithms, achieving significant reductions in total energy consumption while maximizing the efficiency of communication and computational resources. …”
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Preface to Special Issue on AI-Based Future Intelligent Networks and Communication Security by Sunil Kumar, Glenford Mapp, Abhay Bansal, Korhan Cengiz

“… Recent advancements in science focus on the study and development of algorithms that can learn from and make predictions and decisions based on data collected through intelligent devices. …”
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Identification of biomarkers associated with inflammatory response in Parkinson's disease by bioinformatics and machine learning. by Yatan Li, Wei Jia, Chen Chen, Cheng Chen, Jinchao Chen, Xinling Yang, Pei Liu

“…LASSO, SVM-RFE and Random Forest algorithms were used to screen biomarker genes. Then, ROC curves were drawn and PD risk predicting models were constructed on the basis of the biomarker genes. …”
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Efficient topology control for time-varying spacecraft networks with unreliable links by Wei Zhang, Hong Ma, Tao Wu, Xueshu Shi, Yiwen Jiao

“…Simulation results demonstrate the efficiency of our model and topology control algorithms.…”
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A novel deep learning approach to identify embryo morphokinetics in multiple time lapse systems by Guillaume Canat, Antonin Duval, Nina Gidel-Dissler, Alexandra Boussommier-Calleja

“…Today, most of the literature has characterized algorithms that predict pregnancy, ploidy or blastocyst quality, leaving to the side the task of identifying key morphokinetic events. …”
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A Comprehensive Survey on AI in Counter-Terrorism and Cybersecurity: Challenges and Ethical Dimensions by Ioannis Syllaidopoulos, Klimis S. Ntalianis, Ioannis Salmon

“…This paper provides a comprehensive overview of AI methodologies, such as predictive analytics, Natural Language Processing (NLP), and machine learning architectures (e.g., Support Vector Machines – SVM and Long Short-Term Memory – LSTM), and optimization algorithms (e.g., Particle Swarm Optimization – PSO), assessing their effectiveness in security applications. …”
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Sensor Image, Anomaly Detection Method for Hydroelectric Dam Structure Using Sensors Measurements and Deep Learning by Van-Phuong Ha, Dinh-Van Nguyen, Trong-Chuong Trinh, Duc-Cuong Quach, Van HuyBui

“…To better prevent future disasters, machine-learning algorithms have been employed. Often, these algorithms are trained on historical sensor data to predict future events. …”
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Integrating deep learning in public health: a novel approach to PICC-RVT risk assessment by Yue Li, Yue Li, Shengxiao Nie, Lei Wang, Dongsheng Li, Shengmiao Ma, Ting Li, Hong Sun

“…Stability varied with the number of predictive factors, with Cox-Time showing the highest ICC (0.974) with 16 predictive factors, and DeepSurv the most stable with 26 predictive factors (ICC: 0.983). …”
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Using AI in Optimizing Oral and Dental Diagnoses—A Narrative Review by Amelia Surdu, Dana Gabriela Budala, Ionut Luchian, Liliana Georgeta Foia, Gina Eosefina Botnariu, Monica Mihaela Scutariu

“…AI technologies, such as machine learning, deep learning, and computer vision, are increasingly being integrated into dental practice to analyze clinical images, identify pathological conditions, and predict disease progression. By utilizing AI algorithms, dental professionals can detect issues like caries, periodontal disease and oral cancer at an earlier stage, thus improving patient outcomes.…”
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Artificial Intelligence in Uropathology by Katia Ramos Moreira Leite, Petronio Augusto de Souza Melo

“…AI, especially deep learning algorithms, has shown significant potential in improving the accuracy and efficiency of pathology workflows. …”
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COMPLEXITY EVALUATION IN THE PROJECTS INVOLVING MOBILE HETEROGENEOUS OBJECTS by A. I. Kuzmich, S. C. Mochulsky, A. N. Valvachev

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What Strategy Central Nervous System Uses to Perform a Movement Balanced? Biomechatronical Simulation of Human Lifting by Ali Leylavi Shoushtari

“…The results show that the simulated postures are normal and the predicted motion is performed completely balanced.…”
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A Statistical Framework for Modeling Behavioral Engagement via Topic and Psycholinguistic Features: Evidence from High-Dimensional Text Data by Dan Li, Yi Zhang

“…This approach offers practical implications for optimizing algorithmic content ranking and fostering equitable visibility for marginalized digital labor groups.…”
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Understanding HLA-DQ in renal transplantation: a mini-review by Rajdeep Das, Neil S. Greenspan

“…Traditional serological or low-resolution typing often misclassifies mismatches, leading to inaccuracies in assessing immunogenicity and predicting outcomes. Emerging molecular mismatch algorithms refine immunogenicity assessments by analyzing amino acid differences and structural interactions. …”
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A Review of Generative Design Using Machine Learning for Additive Manufacturing by Parankush Koul

“…Generative design uses complex algorithms to automate the process of designing best-fit designs, mass customization, and customization to suit specific customer requirements with high efficiency and quality. …”
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Autoregressive integrated moving average model–based secure data aggregation for wireless sensor networks by Hongtao Song, Shanshan Sui, Qilong Han, Hui Zhang, Zaiqiang Yang

“…This fact calls for special requirements for network protocol design, security assessment models, and energy-efficient algorithms. Data aggregation is an effective energy conservation technique, which removes redundant information from the data aggregated from neighbor sensor nodes. …”
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Data-Driven Approaches for Estimation of EV Battery SoC and SoH: A Review by Shahid Gulzar Padder, Jayesh Ambulkar, Atul Banotra, Sudhakar Modem, Sidharth Maheshwari, Kolleboyina Jayaramulu, Chinmoy Kundu

“…In this study, machine learning algorithms exhibited substantial enhancements in predicting and maintaining the lifespan of electric vehicle batteries. …”
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Large‐scale identification of genetic design strategies using local search by Desmond S Lun, Graham Rockwell, Nicholas J Guido, Michael Baym, Jonathan A Kelner, Bonnie Berger, James E Galagan, George M Church

“…Thus, GDLS is able to find genetic designs with greater in silico production of desired metabolites than can feasibly be found using a globally optimal search and performs favorably in comparison with heuristic searches based on evolutionary algorithms and simulated annealing.…”
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The Impact of Snow Cover on River Discharge Simulation: Insights from the Barandozchay River Basin by Haleh Hashemi, Hossein Rezaie, Keivan Khalili, Amin Amini

“…This study presents a comprehensive analysis aimed at predicting the discharge of the Barandozchay River using machine learning algorithms and meteorological data from both satellite and ground sources over the period from 2002 to 2022. …”
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Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence–Enabled ECGs by Scott Anjewierden, Donnchadh O'Sullivan, Kathryn E. Mangold, Grace Greason, Itzhak Zachi Attia, Francisco Lopez‐Jimenez, Paul A. Friedman, Samuel J. Asirvatham, Jason Anderson, Benjamin W. Eidem, Jonathan N. Johnson, Shisheer Havangi Prakash, Talha Niaz, Malini Madhavan

“…We aimed to develop novel artificial intelligence–enabled ECG algorithms for LVSD and RVSD detection in pediatric patients. …”
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