Multi-strategy cooperative enhancement dung beetle optimizer and its application in obstacle avoidance navigation by Xiaojie Tang, Zhengyang He, Chengfen Jia

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Deep learning for sea surface temperature applications: A comprehensive bibliometric analysis and methodological approach by Redouane Larbi Boufeniza, Luo Jingjia, Kemal Adem Abdela, Karam Alsafadi, Mohammad M Alsahli

“…Abstract This study explored the potential application of deep learning techniques in sea surface temperature (SST) investigations using a mixed method, bibliometric analysis and methodological approach. …”
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Estimation of Hankel inequalities of symmetric starlike functions in crescent-shaped domains and their application in image processing by Bushra Kanwal, Arooj Iman, Shamsa Kanwal, Amal K. Alkhalifa

“…In addition, a comparative study highlights the effectiveness of the proposed algorithm compared to existing methods reported in the literature, demonstrating its potential to enhance image quality in practical applications.…”
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Application of RNA-seq for single nucleotide variation identification in a cohort of patients with hypertrophic cardiomyopathy by Anastasia Chumakova, Ivan Vlasov, Elena Filatova, Anna Klass, Andrey Lysenko, Gennady Salagaev, Maria Shadrina, Petr Slominsky

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Comparison between Logistic Regression and K-Nearest Neighbour Techniques with Application on Thalassemia Patients in Mosul by Mohammed Al jbory, Hutheyfa Taha

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Metal artifact reduction combined with deep learning image reconstruction algorithm for CT image quality optimization: a phantom study by Huachun Zou, Zonghuo Wang, Mengya Guo, Kun Peng, Jian Zhou, Lili Zhou, Bing Fan

“…Background Aiming to evaluate the effects of the smart metal artifact reduction (MAR) algorithm and combinations of various scanning parameters, including radiation dose levels, tube voltage, and reconstruction algorithms, on metal artifact reduction and overall image quality, to identify the optimal protocol for clinical application. …”
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Mean Field Initialization of the Annealed Importance Sampling Algorithm for an Efficient Evaluation of the Partition Function Using Restricted Boltzmann Machines by Arnau Prat Pou, Enrique Romero, Jordi Martí, Ferran Mazzanti

“…So far, the standard application of the AIS algorithm starts from the uniform probability distribution and uses a large number of Monte Carlo steps to obtain reliable estimations of <i>Z</i> following an annealing process. …”
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Application of Energy Dispersive X-ray Fluorescence Spectroscopy in Analysis of Heavy Metals in Soil: A Review by Aosong JIANG, Longhua WU, Zhu LI

“…However, the complexity of the soil matrix and the limitations of the instrument itself will lead to problems such as low accuracy and precision in the determination of target heavy metals by ED-XRF, such as the type and particle size of soil samples and the noise in the instrument and the environment; there are also certain difficulties in the establishment of quantitative analysis model methods, which are still not well applied to laboratories and other environments with high data quality requirements. In this paper, we summarize the application and research progress of XRF in the field of soil heavy metal detection, explore and analyze the influence of different soil sample states and detection conditions on the detection accuracy of ED-XRF instruments, sort out the main pretreatment methods of ED-XRF spectroscopy and the establishment process of quantitative analysis models, and introduce and analyze the application potential of ED-XRF in evaluating the effectiveness of soil heavy metals. …”
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Assessing the Quality of Calyx of Physalis alkekengi L. var. franchetii Based on Quantitative Analysis of Q-Marker Combined with Chemometrics and Machine Learning Algorithms by Meiqi Liu, Ziying Qiu, Xiaoran Zhao, Lili Sun, Lizhi Wang, Xiaoliang Ren, Yanru Deng

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Integrative review of artificial intelligence applications in nursing: education, clinical practice, workload management, and professional perceptions by Rabie Adel El Arab, Omayma Abdulaziz Al Moosa, Mette Sagbakken, Ahmed Ghannam, Fuad H. Abuadas, Joel Somerville, Joel Somerville, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair

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An Analysis on the Applicability of Meta-Heuristic Searching Techniques for Automated Test Data Generation in Automatic Programming Assessment by Musa et al.

“…Nonetheless, thus far the researches on APA have not yet usefully exploited the techniques accordingly to include a better quality program testing coverage. Therefore, this study has conducted a comparative evaluation to identify any applicable MHST to support efficient Automated Test Data Generation (ATDG) in executing a dynamic-functional testing in APA. …”
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Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis by Emre Bilgin

“…Multimodal AI, focusing on collaboration, reliability, transparency, and patient-centered innovation, looks like the future of medical practice. However, data quality, model interpretability, and ethical considerations must be addressed to ensure reliable and equitable applications in clinical practice.…”
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Causal Discovery for Patient Classification Using Health-Related Quality of Life Questionnaires by Maria Ganopoulou, Konstantinos Fokianos, Christos Bakirtzis, Lefteris Angelis, Theodoros Moysiadis

“…This algorithm was evaluated using the correct classification rate (CCR) and the misclassification rate (MR) based on simulated data under conditions of varying sample size and causal structures’ complexity, and within a real-world data application. …”
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A practical guide to optimizing industrial thermal spraying through comparative multi-objective optimization by Wolfgang Rannetbauer, Simon Hubmer, Carina Hambrock, Ronny Ramlau

“…By exploring the performance of these diverse algorithms in an industrial setting, this study offers insights into their practical applicability, guiding both researchers and practitioners in enhancing process efficiency and product quality in the coating industry.…”
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A Novel Adaptive Fine-Tuning Algorithm for Multimodal Models: Self-Optimizing Classification and Selection of High-Quality Datasets in Remote Sensing by Yi Ren, Tianyi Zhang, Zhixiong Han, Weibin Li, Zhiyang Wang, Wenbo Ji, Chenhao Qin, Licheng Jiao

“…The latest research indicates that Large Vision-Language Models (VLMs) have a wide range of applications in the field of remote sensing. However, the vast amount of image data in this field presents a challenge in selecting high-quality multimodal data, which are essential for saving computational resources and time. …”
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Optimizing Rotary Cement Kiln modelling: A comparative analysis of metaheuristics in a real-world application by Miguel Ángel Castán-Lascorz, Antonio Alcaide-Moreno, Jorge Arroyo

“…Results indicate that the adapted MPA is expected to achieve similar error reduction to the other methods but requires 40 % fewer evaluations, thus positioning as the most suitable for the industrial application. …”
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Gamified Engagement for Data Crowdsourcing and AI Literacy: An Investigation in Affective Communication Through Speech Emotion Recognition by Eleni Siamtanidou, Lazaros Vrysis, Nikolaos Vryzas, Charalampos A. Dimoulas

“…This evaluation validated the research questions and hypotheses, demonstrating the application’s diverse benefits. …”
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Detecting Anomalies in CPU Behavior Using Clustering Algorithms from the Scikit-Learn Library in Python Programming Language by Artem Turashev, Vladimir Sukhomlin

“…Classic clustering methods of the Scikit-Learn library in Python programming language are considered, such as KMeans, DBSCAN, Agglomerative Clustering and Affinity Propagation. To evaluate the effectiveness of the proposed algorithms, various quality metrics are used, such as ARI, AMI, Homogeneity Score, Completeness score, V – measure and Silhouette score. …”
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Artificial Intelligence in the Diagnostic Use of Transcranial Doppler and Sonography: A Scoping Review of Current Applications and Future Directions by Giuseppe Miceli, Maria Grazia Basso, Elena Cocciola, Antonino Tuttolomondo

“…AI, particularly machine learning and deep learning algorithms, has emerged as a transformative tool to address these challenges by automating image acquisition, optimizing signal quality, and enhancing diagnostic accuracy. …”
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Comparative performance evaluation of economic load dispatch using metaheuristic techniques: A practical case study for Bangladesh by Sumaiya Janefar, Prangon Chowdhury, Rahbaar Yeassin, Mahmudul Hasan, Nahid-Ur-Rahman Chowdhury

“…PSO emerges as the most effective algorithm for minimizing costs and losses, while HS is suitable for time-sensitive applications. …”
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