Evaluating the Reliability of Powder Bed Fusion for Biomedical Materials: An Experimental Approach by Danut Vasile Leordean, Cosmin Cosma, Nicolae Balc, Mircea Cristian Dudescu

“…This proposed framework integrates multiple aspects into a coherent methodology on how to evaluate the PBF parameters and processing conditions, in order to establish a reliability scale for the PBF process on the Realizer 250 SLM machine. …”
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K-Nearest Neighbors for Anomaly Detection and Predictive Maintenance in Water Pumping Systems by João Pablo Santos da Silva, André Laurindo Maitelli

“…In hydraulic systems, sensor meters are mounted at various sites with distinct physical features, pipe sizes, and vital supply points. The input parameters used for a model are the sensor parameters, and the model analyzes the correlation between the input parameters (sensors) and determines which parameters are the most important, deciding on the output of the model, and thereby building the simplest model, which requires the least input parameters and gives the most accurate prediction results. …”
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On the relationship of Poisson’s ratio with geophysical characteristics of rocks by D. V. Shustov, Yu. A. Kashnikov, A. E. Kukhtinskii, A. A. Efimov

“…This study aims to investigate the influence of geophysical parameters on the Poisson’s ratio for oilfield productive objects using machine learning methods. …”
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Adaptive Cost Model for Query Optimization by N. K. Vasilenko, A. V. Demin, D. K. Ponomaryov

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Performance Analysis of Carbon Fiber Reinforced Epoxy Composites in Particle‐Assisted EDM by Abhijit Bhowmik, Raman Kumar, Ramdevsinh Jhala, Nagaraj Patil, Abinash Mahapatro, Manoj Kumar Ojha, Parveen Kumar, Deepak Gupta, A. Johnson Santhosh

“…The machining parameters were significant, as indicated by the ANOVA, with p‐values below 0.05 for a 95% confidence interval. …”
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Models for analysis of water suitability by L. Makarchuk, T. Likhouzova

“…It is proposed to use models built by machine learning methods so that when analyzing water samples it is possible to focus on the main parameters so that limited resources are not directed unnecessarily to less important features. …”
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Predictive Model of the Effects of Skin Phototype and Body Mass Index on Photobiomodulation Therapy for Orofacial Disorders by Alice Cassemiro, Lara Jansiski Motta, Paulo Fiadeiro, Elsa Fonseca

“…The simulations were used to train a machine learning predictive model aimed at accelerating the treatment planning stage and assessing the importance of patient-specific parameters. …”
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Amplitude-frequency characteristics of the seat vibration protection system with a three-segment static force characteristic with a section of quasi-zero stiffness by Korytov M.S., Sherbakov V.S., Kashapova I.E.

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Design and implementation of online learning assisted intelligent receiver by Lingjin KONG, Kai MEI, Xiaoran LIU, Jun XIONG, Haitao ZHAO, Jibo WEI

“…To address the issue of reliable communication under complicated scenarios, an online learning-assisted intelligent OFDM receiver was proposed.The variations of the channel environment could be precepted by the receiver, and the optimal parameters of the receiver under the current scenario were obtained by collecting data and training online.In the channel estimation module of the OFDM system, a performance comparator based on the mean square error of noisy channel samples was designed as the indicator of channel environment variations.To accelerate the online training progress, a lightweight neural network structure was applied.The proposed method was further implemented and verified based on universal software radio peripherals.The numerical simulation and over-the-air experimental results demonstrate that the proposed receiver can perceive and adapt to new environments effectively, and outperforms existing machine learning methods in terms of receiving performance and convergence rate with a limited number of pilots.…”
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Algorithms for Load Balancing in Next-Generation Mobile Networks: A Systematic Literature Review by Juan Ochoa-Aldeán, Carlos Silva-Cárdenas, Renato Torres, Jorge Ivan Gonzalez, Sergio Fortes

“…The need for enhanced radio resource allocation schemes, improved user mobility and increased throughput, driven by a rising demand for data, has necessitated the development of diverse algorithms that optimize output values based on varied input parameters. In this context, we identify the main topics related to cellular networks and machine learning algorithms in order to pinpoint areas where the optimization of parameters is crucial. …”
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The industry of Penza region at the initial stage of the Great Patriotic War in archival documents and regional historiography (by the example of plant No. 704 in Kamenka village) by E.V. Voeikov

Modeling the Age-related Decrease in Ballistic Limit Velocity of Polycarbonate Vision Panels Using a Johnson-Cook Material Model Coupled with Variable Failure Criteria by Eckart Uhlmann, Mitchel Polte, Nils Bergström, Vu Ninh Le

“…Machine tools are equipped with polycarbonate vision panels that allow the operator to observe the machining process and protect him from ejected fragments. …”
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A Fast and Effective MIMO Algorithm Using CLR-RNN for Hybrid MDM and WDM Optical Communication System by Danni Zhang, Zhongwei Tan, Xinyuan Ma, Shun Lu, Wenhua Ren, Fengping Yan

“…The results show that the introduction of an adaptive machine learning model in MIMO detection for WDM-MDM optical transmission systems can significantly improve the quality of the transmitted signals and achieve better performance than other MIMO detection algorithms while maintaining a faster computational speed and a lower number of parameters.…”
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Advances in Neural Network assisted Tool Pressure Prediction by Göltl Florian, Harst Felix, Birkert Arndt, Stache Nicolaj C.

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Knowledge and Perception of Practicing Anesthetists on Current Techniques, Clinical Applications, and Limitations of Artificial Intelligence in Anesthesiology: An Indian Study by Manasij Mitra, Maitraye Basu, Amrita Ghosh, Ranabir Pal

“…However, the majority was apprehensive on the use of AI aligning it with a machine and expressed ethical concerns. Conclusion: The respondents felt that innovation, integration, and implementation of AI in anesthesia can heighten precision and safety in rural and remote areas of all surgical specialties.…”
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Predicting Noise and User Distances from Spectrum Sensing Signals Using Transformer and Regression Models by Myke Valadão, Diego Amoedo, André Costa, Celso Carvalho, Waldir Sabino

“…Accurately estimating these parameters enables adaptive resource allocation, interference mitigation, and improved spectrum efficiency, ultimately enhancing the performance and reliability of cognitive radio networks.…”
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A Semantic Model to Describe RESTful Services by Luis Antonio de Almeida Rodriguez, Jose Maria Parente de Oliveira

“…Current methods of addressing this issue lack an agreed machine-readable semantic model to define service descriptions that support complex automatic operations via the services. …”
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Parametric evaluation and predictive modelling of formability in μ-SPIF process by Sahu Vijay Kumar, Das Purnendu, Adhikary Avishek, Bandyopadhyay Kaushik

“…The study found correlations of process parameters with forming time, surface roughness and height of the deformed parts. …”
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Artificial Intelligence Approaches for the Detection of Normal Pressure Hydrocephalus: A Systematic Review by Luis R. Mercado-Diaz, Neha Prakash, Gary X. Gong, Hugo F. Posada-Quintero

“…Artificial intelligence (AI), including machine learning (ML) and deep learning (DL), shows promise in diagnosing NPH using medical images. …”
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Structural optimisation of planetary gearbox components by Marinkovic Aleksandar, Sedak Miloš, Lazović Tatjana, Rosić Maja

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