An Android-Based Heart Monitoring System for the Elderly and for Patients with Heart Disease by Paola Pierleoni, Luca Pernini, Alberto Belli, Lorenzo Palma

“…The system developed by our team uses sophisticated algorithms to detect stress states, detect and classify arrhythmia events, and calculate energy consumption. …”
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Old Wine in New Wineskins: Applying Computational Methods in New Testament Hermeneutics by Christian Houth Vrangbæk, Eva Elisabeth Houth Vrangbæk, Jacob Mortensen

“…This article explores some of the advantages and disadvantages in employing computational/algorithmic approaches, such as so-called semantic models of word embedding and topic modelling analysis. …”
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Innovative Driver Monitoring Systems and On-Board-Vehicle Devices in a Smart-Road Scenario Based on the Internet of Vehicle Paradigm: A Literature and Commercial Solutions Overview by Paolo Visconti, Giuseppe Rausa, Carolina Del-Valle-Soto, Ramiro Velázquez, Donato Cafagna, Roberto De Fazio

“…Moreover, the paper provides a detailed overview of the proposed traffic monitoring and management solutions, along with systems for monitoring road and environmental conditions, including the sensors used and the Machine Learning (ML) algorithms implemented. Finally, this review also presents an overview of innovative commercial solutions, illustrating advanced devices for driver monitoring, vehicle condition assessment, and traffic and road management.…”
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First true blood pressure measurement with micropulse detection of arterial opening achieved by Alan Murray, Dingchang Zheng, Clive J. Griffiths, Chengyu Liu, David J. Graham, Jeff Neasham, Adrian J. Cossor

“…Our solution avoids estimates, mathematical modelling, oscillometric algorithms, and inadequate calibration against numerous private clinical data sets. …”
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Optimization Techniques in Electric Vehicle Charging Scheduling, Routing and Spatio-Temporal Demand Coordination: A Systematic Review by Eiman Elghanam, Akmal Abdelfatah, Mohamed S. Hassan, Ahmed H. Osman

“…In particular, these works are reviewed according to their domains of operation (i.e. time-based scheduling, spatial coordination, and spatio-temporal charging coordination), their respective objectives (user-, grid- and operator-related objectives), and the solution algorithms adopted to provide the corresponding optimal coordination plans. …”
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Control of Discrete Event Systems by Means of Discrete Optimization and Disjunctive Colored PNs: Application to Manufacturing Facilities by Juan-Ignacio Latorre-Biel, Emilio Jiménez-Macías, Mercedes Pérez de la Parte, Julio Blanco-Fernández, Eduardo Martínez-Cámara

“…Furthermore, the metaheuristic of genetic algorithms is applied to the search of the best solutions in the solution space. …”
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Investigation on the thermal characteristics of electronic system and prediction of chip temperature by machine learning by Fanyu Wang, Dongwei Wang, Qiang Deng, Hao Yan, Qi Chen, Yang Zhao

“…Furthermore, three machine learning algorithms are used to predict chips temperatures at different operating conditions. …”
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Prediction of dynamic recrystallization behavior of SAE52100 large section bearing steel based on machine learning by Peiheng Ding, Changqing Shu, Shasha Zhang, Zhaokuan Zhang, Xingshuai Liu, Jicong Zhang, Qian Chen, Shuaipeng Yu, Xiaolin Zhu, Zhengjun Yao

“…Four machine learning algorithms including support vector regression, k‐nearest neighbors, random forest, and extreme gradient boosting were then employed to develop dynamic recrystallization prediction models based on the experimental data and inferred values from the physical model. …”
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A shallow convolutional neural network for cerebral neoplasm detection from magnetic resonance imaging by Hossein Sadr, Zeinab Khodaverdian, Mojdeh Nazari, Mohammad Yamaghani

“…Recently, machine learning algorithms have become increasingly important in medical imaging and information processing, offering a robust alternative to the time-consuming and error-prone manual diagnosis of brain tumors. …”
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A deep multiple instance learning framework improves microsatellite instability detection from tumor next generation sequencing by John Ziegler, Jaclyn F. Hechtman, Satshil Rana, Ryan N. Ptashkin, Gowtham Jayakumaran, Sumit Middha, Shweta S. Chavan, Chad Vanderbilt, Deborah DeLair, Jacklyn Casanova, Jinru Shia, Nicole DeGroat, Ryma Benayed, Marc Ladanyi, Michael F. Berger, Thomas J. Fuchs, A. Rose Brannon, Ahmet Zehir

“…However, low tumor purity, as frequently observed in routine clinical samples, poses a challenge to the sensitivity of existing algorithms. To overcome this critical issue, we developed MiMSI, an MSI classifier based on deep neural networks and trained using a dataset that included low tumor purity MSI cases in a multiple instance learning framework. …”
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Machine learning for predicting strength properties of waste iron slag concrete by Matiur Rahman Raju, Syed Ishtiaq Ahmad, Md Mehedi Hasan, Noor Md. Sadiqul Hasan, Md Monirul Islam, Md. Abdul Basit, Ishraq Tasnim Hossain, Saif Ahmed Santo, Md Shahrior Alam, Mahfuzur Rahman

“…Among the tested ML algorithms, Decision Tree (DT) and XGBoost showed the highest accuracy (R2 = 0.95135) in predicting concrete strength properties, while models like SVM and Symbolic Regression underperformed. …”
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Automatic Generation of Precast Concrete Component Fabrication Drawings Based on BIM and Multi-Agent Reinforcement Learning by Chao Zhang, Xuhong Zhou, Chengran Xu, Zhou Wu, Jiepeng Liu, Hongtuo Qi

“…Finally, the agents collaborate and interact with the environment to find the optimal layout with the guidance of a reward mechanism. Two different algorithms are utilized to validate the efficiency of the proposed method (MADQN). …”
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New Platform Technology for Comprehensive Serological Diagnostics of Autoimmune Diseases by Annika Willitzki, Rico Hiemann, Vanessa Peters, Ulrich Sack, Peter Schierack, Stefan Rödiger, Ursula Anderer, Karsten Conrad, Dimitrios P. Bogdanos, Dirk Reinhold, Dirk Roggenbuck

“…To address the limitations of IIF and to meet the demand for cost-efficient autoantibody screening, automated IIF methods employing novel pattern recognition algorithms for image analysis have been introduced recently. …”
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Bayesian Constrained Energy Minimization for Hyperspectral Target Detection by Jing Zhang, Rui Zhao, Zhenwei Shi, Ning Zhang, Xinzhong Zhu

“…The existing hyperspectral target detection algorithms usually assume that the prior target spectrum is highly reliable. …”
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Advancing Coherent Power Grid Partitioning: A Review Embracing Machine and Deep Learning by Mohamed Massaoudi, Maymouna Ez Eddin, Ali Ghrayeb, Haitham Abu-Rub, Shady S. Refaat

“…Additionally, it assists stakeholders in selecting the most appropriate clustering algorithms for PGP applications.…”
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Automatic Quantification of Atherosclerosis in Contrast-Enhanced MicroCT Scans of Mouse Aortas Ex Vivo by Vincent A. Stadelmann, Gabrielle Boyd, Martin Guillot, Jean-Guy Bienvenu, Charles Glaus, Aurore Varela

“…The walls, lumen, and plaque objects were segmented using dual-threshold algorithms. Aortic and plaque volumes were computed by voxel counting and lesion surface by triangulation. …”
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Large annotated ultrasound dataset of non-alcoholic fatty liver from Saudi hospitals for analysis and applicationsOpen Science framework or (OSF) by Fahad Alshagathrh, Mahmood Alzubaidi, Khalid Alswat, Ali Aldhebaib, Bushra Alahmadi, Meteb Alkubeyyer, Abdulaziz Alosaimi, Amani Alsadoon, Maram Alkhamash, Jens Schneider, Mowafa Househ

“…This resource supports various computer vision tasks, enabling the development of AI algorithms for accurate NAFLD diagnosis and staging. …”
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A Novel Efficient Passive Spatial Orientation Detection Method of UMT Enabled by ISB by Zhengqiang Xiong, Tao Sun, Zhengxing Wang, Yuhao Wu, Jie Yin

“…Simulation experiments demonstrate the efficiency of the ECOD method in passive 3D spatial orientation of underwater acoustic target and show that the ECOD method has a better performance in time consumption compared with general DOA algorithms.…”
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QPPLab: A generally applicable software package for detecting, analyzing, and visualizing large-scale quasiperiodic spatiotemporal patterns (QPPs) of brain activity by Nan Xu, Behnaz Yousefi, Nmachi Anumba, Theodore J. LaGrow, Xiaodi Zhang, Shella Keilholz

“…QPPLab integrates correlation-based iterative algorithms, supports customizable parameter settings, and features automated workflows to simplify analysis. …”
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Enhancing unsupervised learning in medical image registration through scale-aware context aggregation by Yuchen Liu, Ling Wang, Xiaolin Ning, Yang Gao, Defeng Wang

“…Traditional registration algorithms often require significant computational resources due to iterative optimization, while deep learning approaches face challenges in managing diverse deformation complexities and task requirements. …”
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