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

“…This paper reviews the current literature on single-objective constrained Bayesian optimization, classifying it according to three main algorithmic aspects: (i) the metamodel, (ii) the acquisition function, and (iii) the identification procedure. …”
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AI frontiers in emergency care: the next evolution of nursing interventions by Zakaria Mani, Bander Albagawi, Bander Albagawi

“…Further empirical research is called for to confirm the effectiveness of AI applications in the dynamic environment of emergency care setups.…”
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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

“…In the actual use of this process, the computing resources possessed by a single user are limited so that the cooperation of multiple users are needed, but the joint learning of multiple users introduces the problem of privacy leakage. This research proposes a method to safely share the effort of multiple users in an encrypted state and perform the reinforcement learning with outsourcing service to reduce users calculations combined with the homomorphic properties of cryptographic algorithms and multi-key ciphertext fusion mechanism. …”
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Word embedding for social sciences: an interdisciplinary survey by Akira Matsui, Emilio Ferrara

“…Our taxonomy built on the surveyed article provides a concise but comprehensive overview of this emerging trend of intersection between computer science and social science and guides scholars who are going to navigate the use of word embedding algorithms in their voyage of social science research.…”
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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

“…Using machine learning algorithms, the approach effectively extracts inundated and dry vegetation, achieving accuracy up to 97.6% for inundated vegetation and 81.9% for dry vegetation, demonstrating its potential for improving flood mapping precision.…”
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Challenges of Endovascular Treatment in Patients With “False” Left Main Coronary Bifurcation Lesions by D. A. Maximkin, S. K. Loginova, Sh. Sh. Fatulloeva

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Potential Accuracy of Joint Parameter Estimate by Space-Based Radar Altimeter by D. S. Borovitsky, A. E. Zhesterev, V. P. Ipatov, R. M. Mamchur

“…The subject of research is a space-based radar altimeter. Modern satellite altimeters along with the instant distance to an earth surface are to measure the sea wave height and scattering cross section per unit of a probed spot. …”
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A comprehensive review of machine learning for heart disease prediction: challenges, trends, ethical considerations, and future directions by Raman Kumar, Raman Kumar, Sarvesh Garg, Rupinder Kaur, M. G. M. Johar, Sehijpal Singh, Sehijpal Singh, Soumya V. Menon, Pulkit Kumar, Pulkit Kumar, Ali Mohammed Hadi, Shams Abbass Hasson, Jasmina Lozanović

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A comparative analysis of classical machine learning models with quantum-inspired models for predicting world surface temperature by Trilok Nath Pandey, Vishvajeet Ravalekar, Sidharth D. Nair, Sunil Kumar Pradhan

“…Abstract This research paper delves into the realm of quantum machine learning (QML) by conducting a comprehensive study on time-series data. …”
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Fast-converging decentralized alternating direction method of multipliers for consensus optimization by Jeannie He, Ming Xiao, Mikael Skoglund

“…Moreover, we have identified specific conditions under which each of our algorithms is guaranteed to converge faster than the other as well as the classical centralized ADMM. …”
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Machine learning approaches for predicting the link of the global trade network of liquefied natural gas. by Pei Zhao, Hao Song, Guang Ling

“…Utilizing node and edge data from these networks, this research applies machine learning algorithms to predict future links based on local and global similarity-based indices (e.g., CN, JA, PA). …”
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Stock Price Pattern Prediction Based on Complex Network and Machine Learning by Hongduo Cao, Tiantian Lin, Ying Li, Hanyu Zhang

“…In general, the prediction ability of SVM algorithms is better than that of KNN algorithms.…”
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Validation of Reference Genes for Accurate RT-qPCR Normalization in <i>Aeluropus littoralis</i> Under Drought, Cold, and ABA Treatments by Seyyed Hamidreza Hashemipetroudi, Ali Rezaei, Markus Kuhlmann

“…The validation analysis indicates a statistically significant difference (<i>p</i> value < 0.05) between normalization with the most and least stable CRGs. This research suggests reliable tissue-specific RGs for <i>A. littoralis</i> under abiotic stresses that can enhances the accuracy of gene expression quantification.…”
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Design, Fabrication, and Application of Large-Area Flexible Pressure and Strain Sensor Arrays: A Review by Xikuan Zhang, Jin Chai, Yongfu Zhan, Danfeng Cui, Xin Wang, Libo Gao

“…The rapid development of flexible sensor technology has made flexible sensor arrays a key research area in various applications due to their exceptional flexibility, wearability, and large-area-sensing capabilities. …”
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Application of machine learning techniques to predict the compressive strength of steel fiber reinforced concrete by Ala’a R. Al-Shamasneh, Arsalan Mahmoodzadeh, Faten Khalid Karim, Taoufik Saidani, Abdulaziz Alghamdi, Jasim Alnahas, Mohammed Sulaiman

“…By leveraging the predictive power and interpretability of advanced machine learning models, this research promotes a paradigm shift in structural engineering workflows.…”
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The role of artificial intelligence in managing hospitalized patients with mental illness: a scoping review by Md Samiun, Moustaq Karim Khan Rony, Sumaiya Yeasmin, Mia Md Tofayel Gonee Manik, Anupom Debnath, Mustakim Bin Aziz, Afia Fairooz Tasnim, Sadia Islam Nilima

“…Despite these advancements, challenges were noted, such as algorithmic biases due to non-diverse training data, privacy and security risks for sensitive patient information, and clinician resistance stemming from concerns about autonomy and ethical implications of AI-supported clinical decisions. …”
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Software and Hardware Control System for Implementing the Balance Error Scoring System by Oksana Blavt, Gennadii Iedynak, Lesia Galamanzhuk, Tetyana Helzhynska, Yurii Kachurak, Yulia Mykhalskа, Liubov Levandovska, Rostyslav Tymkovych

“…The result of our scientific research was the development of software and hardware control system for the implementation of BESS based on the integration of hardware and data processing algorithms. …”
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Enhancing personalized learning: AI-driven identification of learning styles and content modification strategies by Md. Kabin Hasan Kanchon, Mahir Sadman, Kaniz Fatema Nabila, Ramisa Tarannum, Riasat Khan

“…A custom dataset has been constructed in this research comprising approximately 506 samples and 22 features utilizing the Moodle learning management system (LMS), successfully categorizing students into their respective learning styles. …”
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Leveraging Artificial Intelligence and Data Science for Integration of Social Determinants of Health in Emergency Medicine: Scoping Review by Ethan E Abbott, Donald Apakama, Lynne D Richardson, Lili Chan, Girish N Nadkarni

“…ConclusionsAlthough in its infancy, the convergence of AI and data science techniques, especially ML and NLP, with SDOH in EM offers transformative possibilities for better usage and integration of social data into clinical care and research. With a significant focus on the ED and notable NLP model performance, there is an imperative to standardize SDOH data collection, refine algorithms for diverse patient groups, and champion interdisciplinary synergies. …”
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Artificial Intelligence for Multiclass Rhythm Analysis for Out-of-Hospital Cardiac Arrest During Mechanical Cardiopulmonary Resuscitation by Iraia Isasi, Xabier Jaureguibeitia, Erik Alonso, Andoni Elola, Elisabete Aramendi, Lars Wik

“…A traditional machine learning-based classifier, which incorporates the research conducted over the past two decades in ECG rhythm analysis using more than 90 state-of-the-art features, was used as a point of comparison. …”
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