Machine Learning Unveils the Impacts of Key Elements and Their Interaction on the Ambient-Temperature Tensile Properties of Cast Titanium Aluminides Employing SHAP Analysis by Shiqiu Liu, Li Liang

“…Comparative analysis of three algorithms within the training dataset proved the random forest regression (RFR) as the optimal modeling approach. …”
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Dynamic Collaborative Optimization Method for Real-Time Multi-Object Tracking by Ziqi Li, Dongyao Jia, Zihao He, Nengkai Wu

“…Thirdly, a Dynamic Motion Model (DMM) is developed, enabling the robust prediction of non-linear motion based on an improved Kalman filter framework. …”
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Real-time mobile broadband quality of service prediction using AI-driven customer-centric approach by Ayokunle A. Akinlabi, Folasade M. Dahunsi, Jide J. Popoola, Lawrence B. Okegbemi

“…Following hyperparameter tuning to improve the model's performance, the selected model was deployed in a real-world network environment to classify QoS into "Above Average," "Average," and "Below Average," categories. …”
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Possibilities of magnet-resonance tomography usage while examining patients with reccurent genital prolapse by Banakhevych R.M.

“…The study showed that the classification of prolapse by stages is useful for standardization of diagnosis, but it is less useful for a differentiated approach to the choice of surgical strategy, since it ignores the nuances of surgical anatomy. The developed algorithm of dynamic magnetic resonance imaging in patients with recurrent pelvic hernia significantly improves the quality of diagnosis. …”
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The Betting Odds Rating System: Using soccer forecasts to forecast soccer. by Fabian Wunderlich, Daniel Memmert

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Transformed L1 Regularization for Sparse Photoacoustic Tomography by Xueyan Liu, Lu Wang, Xin Wang, Ziqi Hao, Xiaolong Hu

“…In this study, a transform L1 (TL1) regularization model was proposed to improve the quality of PAT images, which was evaluated by numerical simulation and tissue phantom experiments. …”
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The use of artificial intelligence for automatic analysis and reporting of software defects by Mark Esposito, Mark Esposito, Saman Sarbazvatan, Terence Tse, Gabriel Silva-Atencio

“…The COVID-19 pandemic marked a before and after in the business world, causing a growing demand for applications that streamline operations, reduce delivery times and costs, and improve the quality of products. In this context, artificial intelligence (AI) has taken a relevant role in improving these processes, since it incorporates mathematical models that allow analyzing the logical structure of the systems to detect and reduce errors or failures in real-time. …”
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Editorial by Christian Gütl

“…And last but not least, Ashish Ranjan Mishra, Rakesh Kumar and Rajkumar Saini from India present their study on the improvement of the effectiveness of person authentication by using deep learning techniques on electroencephalogram (EEG) signals by applying a multiscale convolutional neural network (CNN) and a Bidirectional LSTM (BiLSTM) model to extract features and classify raw EEG data.Enjoy Reading!…”
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Deep Learning and Automatic Detection of Pleomorphic Esophageal Lesions—A Necessary Step for Minimally Invasive Panendoscopy by Miguel Martins, Miguel Mascarenhas, Maria João Almeida, João Afonso, Tiago Ribeiro, Pedro Cardoso, Francisco Mendes, Joana Mota, Patrícia Andrade, Hélder Cardoso, Miguel Mascarenhas-Saraiva, João Ferreira, Guilherme Macedo

“…Background: Capsule endoscopy (CE) improved the digestive tract assessment; yet, its reading burden is substantial. …”
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Research on computing task scheduling method for distributed heterogeneous parallel systems by Xianzhi Cao, Chong Chen, Shiwei Li, Chang Lv, Jiali Li, Jian Wang

“…Then, a dynamic scheduling method based on heuristic and reinforcement learning algorithms is proposed to schedule the task flows. Furthermore, dynamic redundancy is applied to certain tasks based on reliability analysis to enhance system fault tolerance and improve service quality. …”
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Artificial Intelligence for Unstructured Data Processing by Yohanes Bowo Widodo, Febrianti Widyahastuti, Mohammad Narji, Sondang Sibuea

“…By using deep learning models and advanced algorithms, AI can identify patterns and relationships in complex data, thereby providing deeper insights for better decision making. …”
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Evaluation of machine learning methods for forecasting turbidity in river networks using Sentinel-2 remote sensing data by Victor Oliveira Santos, Paulo Alexandre Costa Rocha, Jesse Van Griensven Thé, Bahram Gharabaghi

“…Using all the samples from the monitoring stations, the XGBoost provided a superior output for turbidity modeling, reaching R2 equal to 75.7 %. This represents an improvement of over 16 % compared to the average metric value for the individual stations. …”
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Enhancing Campus Mobility: Simulated Multi-Objective Optimization of Electric Vehicle Sharing Systems Within an Intelligent Transportation System Frameworks by Omar S. Aba Hussen, Shaiful J. Hashim, Nasri Sulaiman Member, S.A.R. Alhaddad, Bassam Y. Ribbfors, Masanobu Umeda, Keiichi Katamine

“…The main objectives are to reduce the number of unserved demands and operational costs. A simulation model was developed in MATLAB, utilizing the Non-dominated Sorting Genetic Algorithm (NSGA-II), a powerful multi-objective optimization technique that balances conflicting objectives to achieve the best trade-offs for operational efficiency. …”
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Symmetry-Based Data Augmentation Method for Deep Learning-Based Structural Damage Identification by Long Li, Xiaoming Tao, Hui Song, Xiaolong Li, Zhilong Ye, Yao Jin, Qiuyu He, Shiyin Wei, Wenli Chen

“…However, data-driven models often struggle to generalize effectively to unseen datasets. …”
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A Machine Learning-Based Real-Time Remaining Useful Life Estimation and Fair Pricing Strategy for Electric Vehicle Battery Swapping Stations by Seyit Alperen Celtek, Seda Kul, A. Ozgur Polat, Hamed Zeinoddini-Meymand, Farhad Shahnia

“…This integrated approach aims to improve user satisfaction and the operational efficiency of swapping stations. …”
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Detection of Wormhole Attack in Vehicular Ad-hoc Network over Real Map using Machine Learning Approach with Preventive Scheme by Shahjahan Ali, Parma Nand, Shailesh Tiwari

“…The collected data is pre-processed and the k-NN & Random Forest algorithms are applied on this data, to make the model such type so that it can memorize the wormhole attack. …”
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Investigating the drivers of long-term trends in the upper atmosphere over Rome across four decades by Spogli Luca, Sabbagh Dario, Perrone Loredana, Scotto Carlo, Cesaroni Claudio

“…The inclusion of CO2 concentration as an additional driver improves the regression model for [O]. However, the effect remains statistically limited, indicating that the impact of CO2 on thermospheric cooling might be of little significance. …”
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Clinical characteristics of COVID-19 in children and adolescents: insights from an Italian paediatric cohort using a machine-learning approach by Carlo Giaquinto, Daniela Paolotti, Daniele Donà, Stefania Fiandrino, Piero Poletti, Michael Davis Tira, Costanza Di Chiara

“…This approach can support public health by clarifying disease burden and improving patient care strategies. Furthermore, it underscores the importance of integrating risk classification models to monitor and manage infectious diseases.…”
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Intelligent Computed Tomography-based Detection Method for Lithium Battery Mylar Film Damage by Menglei LI, Dimeng XIA, Guoyang LIN, Shusen ZHAO

“…Subsequently, by combining image-preprocessing techniques and deep learning algorithms, an intelligent detection model was constructed to efficiently and accurately detect defective batteries. …”
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Enhancing Healthcare With WBAN and Digital Twins: A Machine Learning Approach for Predictive Health Monitoring by Rishit Mahapatra, Deepak Sethi, Kaushik Mishra

“…Integrating digital twins with these models offers an innovative framework to improve healthcare efficiency, allowing for real-time simulation and more accurate forecasting of patient outcomes.…”
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