Constrained Bayesian Optimization: A Review by Sasan Amini, Inneke Vannieuwenhuyse, Alejandro Morales-Hernandez

“…Though it has been widely used to solve various optimization tasks, most of the literature has focused on unconstrained settings, while many real-world problems are characterized by constraints. …”
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Edge of excellence: JEC's Scopus achievement, doors 2025 breakthroughs, and Volume 4 Issue 1 (2025) highlights by Serhiy O. Semerikov, Tetiana A. Vakaliuk

“… This editorial highlights recent edge computing advancements from the doors 2025 workshop and JEC Volume 4, Issue 1, while celebrating the journal's acceptance into Scopus. …”
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Privacy-Preserving Data Sharing and Computing for Outsourced Policy Iteration with Attempt Records from Multiple Users by Bangyan Chen, Jun Ye

“…The proposed scheme has provably security, and the experimental results show that it has an acceptable impact on performance while ensuring privacy protection.…”
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Neural network compression for reinforcement learning tasks by Dmitry A. Ivanov, Denis A. Larionov, Oleg V. Maslennikov, Vladimir V. Voevodin

“…This work presents a systematic study on the applicability limits of using pruning and quantization to optimize neural networks in RL tasks, with a perspective of deployment in hardware to reduce power consumption and latency, while increasing throughput.…”
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Flood detection and mapping through multi-resolution sensor fusion: integrating UAV optical imagery and satellite SAR data by Mulham Fawakherji, Leila Hashemi-Beni

“…Data fusion enhances environmental monitoring by addressing challenges such as cloud cover, inundated vegetation, and complex urban landscapes. While most studies have focused on satellite data fusion, combining high-resolution UAV optical imagery with Sentinel-1 SAR data remains underexplored. …”
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Causal processes of shallow and deep seismicity at Campi Flegrei caldera by Genny Giacomuzzi, Rossella Fonzetti, Aladino Govoni, Pasquale De Gori, Claudio Chiarabba

“…Here, we show that detailed imaging of seismicity, improved by phase detection with machine-learning algorithms, and velocity models shed light on the active processes at the unresting caldera. …”
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Artificial Intelligence in Cardiovascular Diagnosis: Innovations and Impact on Disease Screenings by Amber Ahmad, Sahil Ahmad, Rida Ahmad, Jahnavi Bodi, Abdulla Mohamed, Ahmad Wasim

“…Materials and methods: Various AI models as well as algorithms, such as machine learning (ML) and deep learning (DL) algorithms, have shown good results in the detection of diseases like heart failure, atrial fibrillation, coronary artery disease, and valvular heart disease. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti, Hafsa Binte Kibria, Zareen Tasnim Pear, Md Nahiduzzaman, Md. Faysal Ahamed, Khandaker Reajul Islam, Jaya Kumar, Muhammad E. H. Chowdhury

“…This study focuses on optimizing and comparing various machine learning models for ASD diagnosis, while incorporating explainable AI techniques to ensure model transparency and interpretability. …”
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Utilizing Artificial Intelligence (AI) for the optimal design of geothermal cogeneration systems in zero energy building by Ehsanolah Assareh, Mohammad Zoghi, Ali Zare, Hassan Bazazzadeh, Adnan Alboghobeysh, Saleh Mobayen, Nima Izadyar, Siamak Hoseinzadeh

“…Modeling was conducted using the widely recognized EES software, while system optimization employed a combination of neural networks and intelligent optimization algorithms. …”
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Humpback whales (Megaptera novaeangliae) in Hervey Bay, Australia: a stopover for females early in their southern migration by Lyndon Brooks, Lyndon Brooks, Trish Franklin, Trish Franklin, Wally Franklin, Wally Franklin, Peter Harrison, Peter Corkeron, Kenneth H. Pollock

“…The development of AI algorithmic matching software may enable further research in future.…”
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Construction of a risk model associated with tryptophan metabolism and identification of related molecular subtypes in laryngeal squamous cell carcinoma by Feng Liu, Yanchao Qin, Wei Luo, XianHui Ruan, Lifang Lu, Bowei Feng, Jianfei Yu

“…A risk model was established based on the expressions of prognostic genes and survival information of LSCC samples while that were divided into high and low risk groups. …”
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Artificial Intelligence in Education: Global Trends, Clusters, and Perspectives by Cristina Barbu, Corina Sbughea

“…The findings underscore the prominence of adaptive and personalized learning systems as crucial areas of research focus, while also highlighting a growing concern regarding ethical issues such as algorithmic bias and accessibility. …”
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Prediction of Psychoacoustic Metrics Using Combination of Wavelet Packet Transform and an Optimized Artificial Neural Network by Mehdi POURSEIEDREZAEI, Ali LOGHMANI, Mehdi KESHMIRI

“…The model is optimized using the particle swarm optimization (PSO) and the back propagation (BP) algorithms. The obtained results reveal that the proposed model shows the lowest mean square error and the highest correlation with human perception while it has the lowest computational cost compared to those of the other models and software.…”
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Water-Based Metaheuristics: How Water Dynamics Can Help Us to Solve NP-Hard Problems by Fernando Rubio, Ismael Rodríguez

“…Despite the strong similarities of these methods in terms of their underlying natural metaphors (most of them emulate, in some way or another, how drops collaboratively form paths down to the sea), in general the resulting algorithms are quite different in terms of their searching approach or their solution construction approach. …”
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Why are Some Recommendation Systems Preferred? by Gaofeng Yi

“…The majority of the existing researches are concerned with improving the accuracy and effectiveness of the recommendation algorithms, or focusing on how to limit perceived risks, with the aim of increasing consumer satisfaction. …”
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Post-Pandemic Urban Future: Identification of the main trends of change in Latin America, through the application of the Delphi method by Yeimis Milton Palomino Pichihua

“…Inequality is the main topic, while the factors of change are telework, e-commerce and emerging commuting habits. …”
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Modern fixation techniques versus traditional tension band wiring for olecranon fractures: a systematic review and meta-analysis of functional outcomes, healing time, and complicat... by Chengjing Wang, Changqing Li

“…Cable-pin System appears optimal for simple fractures, while Eyelet K-wire System shows advantages for comminuted fractures. …”
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Expression Characteristics and Prognostic Value of KLRG2 in Endometrial Cancer: A Comprehensive Analysis Based on Multi-Omics Data by Xiaoyan Huang, Ailian Li, Dianbo Xu

“…<b>Background</b>: Endometrial cancer (EC) remains a major gynecologic malignancy with limited biomarkers for risk stratification. While killer cell lectin-like receptor G2 (KLRG2) exhibits oncogenic properties in other cancers, its clinical significance and mechanistic roles in EC are unknown. …”
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GAB-YOLO: a lightweight deep learning model for real-time detection of abnormal behaviors in juvenile greater amberjack fish by Mingxin Liu, Mingxin Liu, Chun Zhang, Cong Lin, Cong Lin

“…Meanwhile, existing automated detection algorithms often struggle with a trade-off between detection accuracy and model size. …”
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Optimizing radiomics for prostate cancer diagnosis: feature selection strategies, machine learning classifiers, and MRI sequences by Eugenia Mylona, Dimitrios I. Zaridis, Charalampos Ν. Kalantzopoulos, Nikolaos S. Tachos, Daniele Regge, Nikolaos Papanikolaou, Manolis Tsiknakis, Kostas Marias, ProCAncer-I Consortium, Dimitrios I. Fotiadis

“…Feature selection method impacts radiomics models’ performance more than ML algorithms. Best feature selection methods: RFE, LASSO, RF, and Boruta. …”
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