Assessment and Correction of the Cardiac Complications Risk in Non-cardiac Operations – What's New? by A. N. Sumin

“…Recent years have been characterized by the appearance of national and international guidelines with various algorithms for assessing and correcting cardiac risk, as well as publications on the validation of these algorithms. …”
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Tree-Related High-Impedance Fault in Distribution Systems: Modeling, Detection, and Ignition Risk Assessment (Review) by Chunlan Yang, Wenhai Zhang, Rui Tang, Xianyong Xiao

“…In modeling, there is a lack of frameworks that simultaneously elucidate underlying mechanisms and support detection algorithms. In detection algorithms, the existing methods have not been adequately validated under complex environmental conditions. …”
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Predictive reward-prediction errors of climbing fiber inputs integrate modular reinforcement learning with supervised learning. by Huu Hoang, Shinichiro Tsutsumi, Masanori Matsuzaki, Masanobu Kano, Keisuke Toyama, Kazuo Kitamura, Mitsuo Kawato

“…Although the cerebellum is typically associated with supervised learning algorithms, it also exhibits extensive involvement in reward processing. …”
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Machine learning-based prediction of distant metastasis risk in invasive ductal carcinoma of the breast. by Jingru Dong, Ruijiao Lei, Feiyang Ma, Lu Yu, Lanlan Wang, Shangzhi Xu, Yunhua Hu, Jialin Sun, Wenwen Zhang, Haixia Wang, Li Zhang

“…A risk prediction model was constructed based on four algorithms: Random Forest, XGBoost, Logistic Regression, and SVM. …”
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Beyond the STI clinic: Use of administrative claims data and machine learning to develop and validate patient-level prediction models for gonorrhea by Lorenzo Argante, Germain Lonnet, Emmanuel Aris, Jane Whelan

“…ML classification models were constructed based on logistic regression and tree-based algorithms. Results Models constructed using tree-based algorithms such as XGBoost provided the best discriminatory results, but simpler ridge regressions models with splines also achieved reasonable discrimination, allowing for the identification of population subsets at increased risk of gonorrhea infection. …”
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Investigation of the impact of service parameters on the degree of passenger satisfaction based on the application of the apparatus of neural networks by S. S. Pastukhov, K. V. Stel’Mashenko

“…The approbation results of the apparatus of neural networks on sets of marketing data concerning various aspects of passenger service at stations and in trains are presented, as well as an estimation of the efficiency of using neural networks in comparison with the algorithms of ordinal logistic and linear regression. …”
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Generative AI for drug discovery and protein design: the next frontier in AI-driven molecular science by Uddalak Das

“…Generative artificial intelligence (AI) has emerged as a disruptive paradigm in molecular science, enabling algorithmic navigation and construction of chemical and proteomic spaces through data-driven modeling. …”
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Synchronization method for long-term evolution-based machine-type communication in low-power cellular Internet of Things by Rothna Pec, Joo-Hyung Choi, Chang-Hwan Park, Yong Soo Cho

“…In this article, a complete synchronization and cell search procedure is described for machine-type communication devices in long-term evolution systems. Low-complexity algorithms for primary synchronization signal and secondary synchronization signal detection, which requires the highest computational complexity in synchronization and cell search period, are also proposed for low-power machine-type communication devices. …”
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Improvement of an Edge-IoT Architecture Driven by Artificial Intelligence for Smart-Health Chronic Disease Management by William Alberto Cruz Castañeda, Pedro Bertemes Filho

“…Experimental results in a case study on glucose prediction noninvasively show that the architecture senses and acquires data that capture relevant characteristics. The study also establishes a baseline of twelve regression algorithms to assess the non-invasive glucose prediction performance regarding the mean squared error, root mean squared error, and r-squared score, and the catboost regressor outperforms the other models with 218.91 and 782.30 in MSE, 14.80 and 27.97 in RMSE, and 0.81 and 0.31 in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula>, respectively, on training and test sets. …”
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Vector Autoregressive Hierarchical Hidden Markov Models for Extracting Finger Movements Using Multichannel Surface EMG Signals by Nebojša Malešević, Dimitrije Marković, Gunter Kanitz, Marco Controzzi, Christian Cipriani, Christian Antfolk

“…The choice of the presented methodology for the control of prosthetic hand is also supported by the equal or lower computational complexity required, compared to other algorithms, which enables the implementation on low-power microcontrollers, and the ability to adapt to user preferences of executing individual movements during activities of daily living.…”
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Nuevos modelos para la Caracterización, Detección y Diagnóstico de Fallas en Máquinas Eléctricas Rotativas by Jair Elías Araujo Vargas, Dilan Yesid Franklin Coronel, Victor Manuel Arias Ruiz

“…The main objective is to explore and propose new methodologies for characterizing faults in electric motors through the use of data analysis and machine learning techniques, reviewing traditional and current methods for fault diagnosis, including vibration analysis techniques and supervised and unsupervised learning algorithms. The potential of artificial intelligence algorithms to improve diagnosis and reduce subjectivity in data processing is also examined. …”
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A strategy for network multi-layer information fusion based on multimodel in user emotional polarity analysis by Ronghua Wang, Peng Zhuang

“…Meanwhile, graph embedding algorithms such as DeepWalk and Node2vec were utilized to process node information in graph data. …”
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Automated Synthesis of Fault-Tolerant State Preparation Circuits for Quantum Error-Correction Codes by Tom Peham, Ludwig Schmid, Lucas Berent, Markus Müller, Robert Wille

“…A central ingredient in fault-tolerant quantum algorithms is the initialization of a logical state for a given quantum error-correcting code from a set of noisy qubits. …”
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Joint Channel Assignment and Routing in Multiradio Multichannel Wireless Mesh Networks: Design Considerations and Approaches by Omar M. Zakaria, Aisha-Hassan A. Hashim, Wan H. Hassan, Othman O. Khalifa, M. Azram, Lalitha B. Jivanadham, Mistura L. Sanni, Mahdi Zareei

“…Furthermore, the set of reconfiguration algorithms to adapt the network traffic dynamics is also discussed. …”
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Project quality, regulation quality by Elena Mussinelli

“…This is evident in the relationship between technical regulations and techno-typological innovation for evolutions that move the parameters of regulatory congruity “forward”, but sometimes even “sideways”. This also counteracts the phenomena of norm obsolescence. …”
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The Bright Decade of Ocean Salinity from Space by Roberto Sabia, Jacqueline Boutin, Nicolas Reul, Tong Lee, Simon H. Yueh

“…Finally, short-to-mid-term perspectives, indicating both the expected improvements in terms of algorithms and also looking at novel mission concepts (that will provide continuation of these measurements in the decade to come) have been described.…”
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Comparing traditional and machine learning techniques in apartments mass appraisal in Fortaleza, Brazil by Antônio Augusto Ferreira de Oliveira, Fabián Reyes-Bueno, Marco Aurelio Stumpf Gonzalez, Éverton da Silva

“…The results of the machine learning algorithms were similar. The XGBoost minimized spatial autocorrelation. …”
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Deep-Learning-Based Cognitive Assistance Embedded Systems for People with Visual Impairment by Huu-Huy Ngo, Hung Linh Le, Feng-Cheng Lin

“…In this study, we developed a portable system for not only obstacle avoidance but also identifying people and their emotions. The core of the developed system is a powerful and portable edge computing device that implements various deep learning algorithms for images captured from a webcam. …”
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Algal biomusic generation by Joshua M. Lawrence, Emma Albertini, Alberto Scarampi, Paolo Bombelli, Lucia B. Giron, Lena Kuzmich, Christopher J. Howe

“…To date, most of these efforts have focused on the use of computational algorithms to compose music. Biomusic – music created using biological data – provides an alternative paradigm for the creation of non-human music which can be truly ecocentric. …”
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Scientists yet to consider spatial correlation in assessing uncertainty of spatial averages and totals by Alexandre M.J.-C. Wadoux, Gerard B.M. Heuvelink

“…The remote sensing data typically serve as covariates to deliver spatially explicit information using machine learning algorithms. Often the uncertainty associated with the maps is also quantified, for instance by prediction error variance maps or by maps of the lower and upper limits of a prediction interval. …”
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