A Storm Frame Optimization Method for Predicting and Warning the Safety Status of a Shearer by Pei Zhang, Yanpeng He, Li Ma, Changkui Cong

“…First, the GRU model is optimized through hyperparameter optimization to achieve adaptive and accurate prediction and early warning of multidimensional state parameters of the shearer. Second, a virtual machine is constructed to host the Storm framework, parallel optimized real‐time processing of data is performed on the Storm framework, and real‐time data flow patterns are constructed to speed up data processing and retrieval, ensuring each tuple is fully processed through the topology structure. …”
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Analysis of the capabilities of an information system for improving sleep quality based on biometric data analysis by M.S. Graf, A.V. Yakoniuk, D.V. Krant, I.I. Golovach

“…AmI systems allow you to automatically adjust environmental parameters such as temperature, lighting and humidity based on individual biometric parameters of the user, which helps to maintain natural circadian rhythms and improve overall comfort during sleep. …”
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Prediction of Right Heart Failure in LVAD Candidates: Current Approaches and Future Directions by Frederick Vogel, Zachary W. Sollie, Arman Kilic, Ethan Kung

“…Multiple predictive models and parameters have been developed to quantify the risk of post-LVAD right heart failure. …”
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FedDBO: A Novel Federated Learning Approach for Communication Cost and Data Heterogeneity Using Dung Beetle Optimizer by Dongyan Wang, Limin Chen, Xiaotong Lu, Yidi Wang, Yue Shen, Jingjing Xu

“…As an emerging distributed machine learning technology, federated learning has gained widespread attention due to its critical privacy protection mechanism. …”
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Optimization of Technological Process Management in Plant Growing by A. Yu. Izmailov, Ya. P. Lobachevsky, V. K. Khoroshenkov, I. G. Smirnov, N. T. Goncharov, Ye. S. Luzhnova

“…(Materials and methods) The elaboration of a centralized unified automated information management system for mobile units and stationary processes incorporates the following components: Automation of the technological process with the possibility of locating every mobile machine, tractor, combiner harvester, any other vehicle, or fixed object in the field; Transferring integrated process parameters to the dispatch center server, transforming these parameters into a convenient form for technologists, agronomists, and managerial staff; Transferring control commands to adjust the process by its performers (operators). …”
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The Influence of Changing Belt Loading Conditions on the Operational Condition of the Belt Transmission by Jozef Mascenik, Tomas Coranic

“…The results of the experimental measurements can contribute to designers choosing a belt drive, for example, even under boundary load parameters and extreme conditions.…”
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Integration of Multiple Models with Hybrid Artificial Neural Network-Genetic Algorithm for Soil Cation-Exchange Capacity Prediction by Mahmood Shahabi, Mohammad Ali Ghorbani, Sujay Raghavendra Naganna, Sungwon Kim, Sinan Jasim Hadi, Samed Inyurt, Aitazaz Ahsan Farooque, Zaher Mundher Yaseen

“…., artificial neural network (ANN) and extreme learning machine (ELM)) were implemented for incorporation into the MM-GANN. …”
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Assessment of Lymphocyte and Neutrophil Concentration with Many Types of Covid-19 Vaccine in Corona Patients by Hayder Nsiefe Jasim, Issam Jumaa Nasser, Ameerah Mrebee Zarzoor

“…The study started from September 2021 to April 2022, and the Present study show there are significant differences (p<0.05) between Neutrophil and Lymphocytes parameters in the studied groups. The WBC count was achieved by full-auto hematology machine manidray technique. …”
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Study of Strength Characteristics of Products Produced by 3D-Printing from PLA by V. A. Ermakova, E. V. Gasperovich, A. I. Ermakov, V. V. Litvyak

“…Tensile testing of the samples have been carried out on a hydraulic tensile machine with a measuring software package in the Kason WDW-5 set. …”
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Downscaling of Soil Moisture Map using Sentinel Radar Satellite Images and Distribution Analysis in the West of Iran by Seyed Hossein Mirmosavi, kohzad Raispour, Muhammad Kamangar

“…The micro-scale backup machine vector algorithm and the high volume resolution soil moisture dispersion map were estimated between 0.18 and 0.46 b. …”
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Expanding the frontiers of additive manufacturing: Higher microstructure identification through probability modeling by Muhammad Shoaib, Muhammad Idrees, Hakeem Ullah, Aasim Ullah Jan, Touqeer Ahmad, Ali Akgül, Magda Abd El-Rahman, Seham M. Al-Mekhlafi

“…Probabilistic models and machine learning methods create a step forward in making predictions for additive manufacturing (AM) microstructure. …”
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The Solution of the Stationary Aeroelasticity Problem for a Separation Channel with Deformable Sinusoidal Walls by Demianenko M., Volf M., Pavlenko V., Liaposhchenko O., Pavlenko I.

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Multiple Regression Prediction Model for Cutting Forces in Turning Carbon-Reinforced PEEK CF30 by Francisco Mata, Elena Beamud, Issam Hanafi, Abdellatif Khamlichi, Abdallah Jabbouri, Mohammed Bezzazi

“…Considering these properties and potential areas of application, it is necessary to investigate the machining of PEEK CF30. In this study, response surface methodology was applied to predict the cutting forces in turning operations using TiN-coated cutting tools under dry conditions where the machining parameters are cutting speed ranges, feed rate, and depth of cut. …”
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Dynamic Coordination Mechanism of DFIGs Based on Inertia Response by Zhaorui LIU, Qi JIA, Gangui YAN, Wenchao ZHAI, Yong SUN, Baoju LI

“…It is then concluded that the inertia response of DFIG can be achieved by optimizing PLL control parameters when unbalanced power disturbance occurs in the system. …”
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Research on Partial Least Squares Method Based on Deep Confidence Network in Traditional Chinese Medicine by Wang-ping Xiong, Tian-ci Li, Qing-xia Zeng, Jian-qiang Du, Bin Nie, Chih-Cheng Chen, Xian Zhou

“…Using Dachengqitang experimental data and data sets in the UCI Machine Learning Repository, the experimental results show that the partial least squares analysis method based on deep belief nets has good adaptability to TCM data.…”
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Partial Discharge Signal Capture of High Voltage Cable Under Deep Belief Network by GAO Baoqi, MA Hanchao, BI Yanbing, ZHANG Xiaojun, WU Suzhou

“… In order to monitor the running state of high-voltage cable in real time and ensure the safe transportation of power, a partial discharge signal capture method of high-voltage cable based on deep belief network is studied.The improved variational modal decomposition algorithm is used to remove the internal noise of the original local signal; the deep belief network capture model is established, and the limited Boltzmann machine is pre trained by contrast divergence algorithm to obtain the pre training network parameters of the capture model; using the global fine tuning capture model of adaptive moment estimation algorithm, the denoised signal is inputted into the trained capture model and the partial discharge signal is outputted.Experimental results show that the proposed method can effectively remove the internal noise from partial discharge signals.In the case of different interferences, the capture probability of this method is above 0.9, which has excellent anti-interference performance and accurately captures the partial discharge signal types caused by insulation defects.…”
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Zoning Elastic Modulus Inversion for High Arch Dams Based on the PSOGSA-SVM Method by Bo Chen, Xiao Fu, Xuyuan Guo, Chongshi Gu, Chenfei Shao, Xiangnan Qin

“…The zoning elastic modulus of a high arch dam is inversed by using deformation safety monitoring data in the operation period, based on the particle swarm optimization with gravitation search algorithm for support vector machine (PSOGSA-SVM) method. Firstly, the measured data of multipoints with a pendulum are separated to construct the initial sample training set; then, an optimal inversion model is established to reflect the complex nonlinear relationship between the mechanical parameters of the high arch dam and the deformation of measured points; finally, the PSOGSA-SVM method is used to train and dynamically update the training set so as to realize the optimization solution of the inversion model. …”
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Single-Molecule Tracking dataset for histone H3 (hht1) from live and fixed cells of Schizosaccharomyces pombe by Akriti Kumari, Nitesh Kumar Podh, Sucharita Sen, Kirti Kashyap, Sahil Islam, Anupam Gupta, Eerappa Rajakumara, Mridula Nambiar, Gunjan Mehta

“…These parameters will be used to differentiate chromatin-bound molecules from unbound (free) molecules of any protein. …”
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Method for collision avoidance based on deep reinforcement learning with path-speed control for an autonomous ship by Do-Hyun Chun, Myung-Il Roh, Hye-Won Lee, Donghun Yu

“…The DRL is actively applied in machine control and artificial intelligence. To verify the proposed method, we applied it to the Imazu problem. …”
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Exploration of genetic algorithms to build a balanced neutron spectra dataset useful to train unfolding techniques based on artificial neural networks by Bouhadida Maha, Hmede Rodayna, Brovchenko Mariya, Monange Wilfried, Vinchon Thibaut, Ducasse Quentin, Trompier François

“…This GA targets optimal combinations of 48 parameters to generate a variety of neutron spectra. …”
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