Eliciting Emotions: Investigating the Use of Generative AI and Facial Muscle Activation in Children’s Emotional Recognition by Manuel A. Solis-Arrazola, Raul E. Sanchez-Yanez, Ana M. S. Gonzalez-Acosta, Carlos H. Garcia-Capulin, Horacio Rostro-Gonzalez

“…This approach offers new avenues for training and validating AI algorithms, enabling models to be trained with artificial and real-world data interchangeably. …”
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Artificial intelligence as a transforming factor in motility disorders–automatic detection of motility patterns in high-resolution anorectal manometry by Miguel Mascarenhas, Francisco Mendes, Joana Mota, Tiago Ribeiro, Pedro Cardoso, Miguel Martins, Maria João Almeida, João Rala Cordeiro, João Ferreira, Guilherme Macedo, Cecilio Santander

“…A dataset of 701 HR-ARM exams from a tertiary center, classified according to London Classification, was used to develop and test multiple machine learning (ML) algorithms. The exams were divided in a training and testing dataset with a 80/20% ratio. …”
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Tropical cyclone intensity estimation based on YOLO-NAS using satellite images in real time by Priyanka Nandal, Prerna Mann, Navdeep Bohra, Ghadah Aldehim, Asma Abbas Hassan Elnour, Randa Allafi

“…This research presents a novel method for forecasting the strength of tropical storms using the You Only Look Once-Neural Architecture Search (YOLO-NAS) algorithm, leveraging real-time satellite imagery from the INSAT-3D platform. …”
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An Efficient CNN Model for COVID-19 Disease Detection Based on X-Ray Image Classification by Aijaz Ahmad Reshi, Furqan Rustam, Arif Mehmood, Abdulaziz Alhossan, Ziyad Alrabiah, Ajaz Ahmad, Hessa Alsuwailem, Gyu Sang Choi

“…To further prove that the proposed model outperforms other models, a comparative analysis has been done with some of the machine learning algorithms. The proposed model has outperformed all the models generally and specifically when the model testing was done using an independent testing set.…”
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Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes by S. Ubbiali, C. Kühnlein, C. Schär, L. Schlemmer, T. C. Schulthess, T. C. Schulthess, M. Staneker, H. Wernli

“…<p>We explore the domain-specific Python library GT4Py (GridTools for Python) for implementing a representative physical parametrization scheme and the related tangent-linear and adjoint algorithms from the Integrated Forecasting System (IFS) of ECMWF. …”
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Identification of depressive symptoms in adolescents using machine learning combining childhood and adolescence features by Xinzhu Liu, Rui Cang, Zihe Zhang, Ping Li, Hui Wu, Wei Liu, Shu Li

“…Using the maximum relevance-minimum redundancy method and four ML algorithms, we determined the optimal feature subset for identifying depressive symptoms and constructed child-adolescent models. …”
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Ancient and contemporary shellfish cultivation practices bolster bivalve communities and diversity‐biomass relationships by Kieran D. Cox, Hailey L. Davies, Ben Millard‐Martin, Morgan Black, Margot Hessing‐Lewis, Nicole F. Smith, Francis Juanes, Sarah E. Dudas

“…We examined these data using a combination of diversity indices, structural complexity metrics, non‐parametric multivariate statistics and supervised machine learning algorithms. We show that both cultivation methods create distinct biological communities, with community composition proportional to how each cultivation practice alters the habitats' substrate, sediment and physical complexity. …”
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Prediction models used in the progression of chronic kidney disease: A scoping review. by David K E Lim, James H Boyd, Elizabeth Thomas, Aron Chakera, Sawitchaya Tippaya, Ashley Irish, Justin Manuel, Kim Betts, Suzanne Robinson

“…This made it difficult to perform a comparison between ML algorithms, more so when different validation methods were used in different cohort types. …”
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How do electronic risk assessment tools affect the communication and understanding of diagnostic uncertainty in the primary care consultation? A systematic review and thematic synt... by Sarah Gerard Dean, Joshua Feyi-Waboso, Mark Tarrant, Raff Calitri, Elizabeth Shephard, Alex Burns, Brian Donnelly

“…Objectives To conduct a systematic review and synthesise qualitative research of electronic risk assessment tools (eRATs) in primary care, examining how they affect the communication and understanding of diagnostic risk and uncertainty. eRATs are computer-based algorithms designed to help clinicians avoid missing important diagnoses, pick up possible symptoms early and facilitate shared decision-making.Design Systematic search, using predefined criteria of the published literature and synthesis of the qualitative data, using Thematic Synthesis. …”
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Association of Premature Ventricular Contraction (PVC) with hematological parameters: a data mining approach by Nafiseh Hosseini, Sara Saffar Soflaei, Pooria Salehi-Sangani, Mahdiyeh Yaghooti-Khorasani, Bahram Shahri, Helia Rezaeifard, Habibollah Esmaily, Gordon A. Ferns, Mohsen Moohebati, Majid Ghayour-Mobarhan

“…The results show that the Boosting DT was the most effective algorithm. Boosting DT had an accuracy of 98.13% and 96.92% for males and females respectively. …”
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Deep Reinforcemnet Learning for Robust Beamforming in Integrated Sensing, Communication and Power Transmission Systems by Chenfei Xie, Yue Xiu, Songjie Yang, Qilong Miao, Lu Chen, Yong Gao, Zhongpei Zhang

“…Our results demonstrate that DRL-based algorithms significantly improve resource allocation, power management, and information transmission, particularly in dynamic and uncertain environments with imperfect CSI.…”
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ClassWise-SAM-Adapter: Parameter-Efficient Fine-Tuning Adapts Segment Anything to SAR Domain for Semantic Segmentation by Xinyang Pu, Hecheng Jia, Linghao Zheng, Feng Wang, Feng Xu

“…Compared to conventional state-of-the-art semantic segmentation algorithms by extensive experiments, CWSAM showcases enhanced performance with fewer computing resources, highlighting the potential of leveraging foundational models such as SAM for specific downstream tasks in the SAR domain.…”
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A Reproducible Method for Donor Site Computed Tomography Measurements in Abdominally Based Autologous Breast Reconstruction by Damini Tandon, MD, Arthur Sletten, MD, PhD, Austin Ha, MD, Gary B. Skolnick, BA, MBA, Paul Commean, BEE, Terence Myckatyn, MD

“…Larger patient cohorts must be leveraged to determine correlations between abdominal CT scan findings and donor site outcomes using machine learning algorithms that generate models for predicting abdominal donor site complications.…”
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Estimating Complex Signals With a Fuzzy-Enhanced Kalman Filter: A Note on &#x201C;the Output Regulation and the Kalman Filter as the Signal Generator&#x201D; by Jesus Alberto Meda-Campana, Juan Carlos Garcia-Hernandez, Rodolfo Daniel Velazquez-Sanchez, Luis Alberto Paramo-Carranza, Tonatiuh Hernandez-Cortes, Ricardo Tapia-Herrera

“…Furthermore, the result shows that incorporating simple fuzzy logic concepts may substantially enhance the performance of some established algorithms.…”
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Multi Objective Prioritized Workflow Scheduling Using Deep Reinforcement Based Learning in Cloud Computing by Sudheer Mangalampalli, Syed Shakeel Hashmi, Amit Gupta, Ganesh Reddy Karri, K. Varada Rajkumar, Tulika Chakrabarti, Prasun Chakrabarti, Martin Margala

“…Results revealed that our proposed MOPDSWRL outperforms existing state of art algorithms by minimizing makespan, energy consumption.…”
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Implementation of a Smart Home Intruder Detection System using a Vibrometer and ESP 32 CAM by Samuel Owoeye, Folasade Durodola, Adekunle Oyelami, Racheal Oladejo, Samuel Obasuyi, Ademola Qasim, Joshua Ogundairo

“…The ATMega328P contributes to the system's intelligence by supporting motion detection algorithms, which, in turn, trigger automated alerts and activate lighting or alarm systems in response to detected movement. …”
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Infrared dim tiny-sized target detection based on feature fusion by Peng Zhang, Yaman Jing, Guodong Liu, Ziyang Chen, Xiaoyan Wu, Osami Sasaki, Jixiong Pu

“…The comparison of the proposed network with other algorithms are performed on open-source dataset and experimentally generated infrared images. …”
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SpikeDroidDB: AN INFORMATION SYSTEM FOR ANNOTATION OF MORPHOMETRIC CHARACTERISTICS OF WHEAT SPIKE by M. A. Genaev, E. G. Komyshev, Fu Hao, V. S. Koval, N. P. Goncharov, D. A. Afonnikov

“…The effectiveness of ears’ phenotyping can be improved by the introduction of an automated image processing technology, storage of information in databases, use of machine learning algorithms to analyze this information. This paper presents a new approach for collecting, storing and analyzing of information about morphometric characteristics of ears of wheat. …”
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Machine Learning Models for Predicting Thermal Properties of Radiative Cooling Aerogels by Chengce Yuan, Yimin Shi, Zhichen Ba, Daxin Liang, Jing Wang, Xiaorui Liu, Yabei Xu, Junreng Liu, Hongbo Xu

“…A comparative analysis of various machine learning algorithms revealed that an optimized XGBoost model demonstrated superior predictive performance, achieving an R² value of 0.943 and an RMSE of 1.423 for the test dataset. …”
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Diagnosis and detection of bone fracture in radiographic images using deep learning approaches by Theyazn Aldhyani, Zeyad A. T. Ahmed, Bayan M. Alsharbi, Sultan Ahmad, Sultan Ahmad, Mosleh Hmoud Al-Adhaileh, Ahmed Hassan Kamal, Mohammed Almaiah, Jabeen Nazeer

“…In response to this challenge, researchers have turned to deep-learning (DL) algorithms. Recent advancements in sophisticated DL methodologies have helped overcome existing issues in fracture detection.MethodsNevertheless, it is essential to develop an automated approach for identifying fractures using the multi-region X-ray dataset from Kaggle, which contains a comprehensive collection of 10,580 radiographic images. …”
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