A Geoanalytical and AI-Driven Approach for Optimising Biomass Energy Generation from Key Economic Crops in Northeastern Thailand by Konyai Supasit, Khuanmar Kulyakorn, Kanarkard Wanida

“…The transition toward renewable energy sources has become a global priority to address climate change and energy security concerns. …”
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Method of vibration diagnostics of the technical condition of electronic equipment structures by S. M. Lyshov, S. U. Uvaysov, V. V. Chernoverskaya, Ph.L. Q. Han

“…The main goal of the research is to improve the accuracy of identification of design defects of on-Board electronic devices. The transition from the analysis of the frequency response to the resonant frequencies that characterize the physical and mechanical parameters of the structure is due to greater stability and lower measurement error of this characteristic. …”
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Analysis of video image compression methods with partial information loss for medical information and measurement systems by Yu.O. Podchashynskyi, A.G. Stupak, L.O. Chepiuk

“…At the same time, it is necessary to ensure distortions are insignificant for visual perception of the images and cause only minor errors in the results of measuring informative parameters of the video signal. …”
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Optimized Ensemble Model to Predict the Compatibility of Automobiles With Hybrid Electric Vehicles by Rohit Bajaj, Deepika Sharma, Ruchika Gupta, Shonak Bansal, Payal Patial, Krishna Prakash

“…The model’s robustness is evidenced by the high W-Saw score of 8.8, indicating its strength, and a low L-Saw Score of 3.3, highlighting minimal errors. The optimized model’s significant W-Saw score emphasizes its reliability and contribution to environmental sustainability.…”
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Comparison of Different Body Mass Index Classification Tools to Identify Underweight and Overweight among Young Girls in Rural Haryana by K Srinath, Ravneet Kaur, Mani Kalaivani, Shashi Kant, Puneet Misra, Sanjeev Kumar Gupta

“…Malnutrition is prevalent and impactful among young Indian girls aged under 18 years. Systematic errors have been observed in body mass index (BMI) classification among these girls. …”
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Role of Voltage Control Devices in Low Voltage State Estimation Process by István Táczi, István Vokony, Lilla Barancsuk, Gábor Mihály Péter, Balázs Tőzsér, Bálint Hartmann

“…The results showed that integrating smart assets could considerably mitigate voltage fluctuations, and reduce estimation errors by two magnitudes on the low voltage network.…”
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INFORMATION USE ABOUT THE LEVEL OF AIRCRAFT FLIGHTS GROUND PROVISION TO PLAN AIR TRAFFIC by D. A. Zatuchny, J. V. Slad

“…The formula to calculate probabilities of obtaining not correct aircraft navigation data is given. The analysis of errors arising while building up the aircraft route linked with both operational navigation and communication equipment faults as well as with a human factor is carried out. …”
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Design and Optimization of Non-Coplanar Orbits for Orbital Photovoltaic Panel Cleaning Robots by Yingjie Zhao, Yuming Qi, Bing Xie

“…Additionally, the ADAMS simulation validation demonstrates that the trajectory errors of the four wheels decreased by a maximum of 8.79 mm, 23.78 mm, 10.11 mm, and 14.97 mm, respectively, thereby confirming the effectiveness of the trajectory optimization.…”
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Optimizing fully-efficient two-stage models for genomic selection using open-source software by Javier Fernández-González, Julio Isidro y Sánchez

“…However, unweighted (UNW) two-stage models assume independent errors among adjusted means, neglecting correlations among estimation errors. …”
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Reinforcement-Learning-Based Trajectory Design and Phase-Shift Control in UAV-Mounted-RIS Communications by Tianjiao Sun, Sixing Yin, Li Deng, F. Richard Yu

“…To cope with the practical issue of inaccessible information on the user terminals’ (UTs) location and channel state, a reinforcement learning (RL)-based solution is proposed to find the optimal policy with finite steps of “trial-and-error”. As the action space is continuous, the deep deterministic policy gradient (DDPG) algorithm is applied to train the RL model. …”
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Data efficient prediction of excited-state properties using quantum neural networks by Manuel Hagelueken, Marco F Huber, Marco Roth

“…For these molecules, we predict the excited state transition energies and transition dipole moments. We show that, in many cases, the procedure is able to outperform various classical models (support vector machines, Gaussian processes, and NNs) that rely solely on classical features, by up to two orders of magnitude in the test mean squared error.…”
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Phase Diagram of Extensive-Rank Symmetric Matrix Denoising beyond Rotational Invariance by Jean Barbier, Francesco Camilli, Justin Ko, Koki Okajima

“…On the theoretical side, we combine mean-field techniques in an interpretable multiscale fashion in order to access the minimum mean-square error and mutual information. Interestingly, our alternative method yields equations reproducible by the replica approach of Sakata and Kabashima. …”
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Nickase fidelity drives EvolvR-mediated diversification in mammalian cells by Juan E. Hurtado, Adam J. Schieferecke, Shakked O. Halperin, John Guan, Dylan Aidlen, David V. Schaffer, John E. Dueber

“…Here, we engineer CRISPR-guided error-prone DNA polymerases (EvolvR) to diversify all four nucleotides within genomic loci in mammalian cells. …”
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Die makromolekulare Charakterisierung der Gelatine by I. Tomka

“…As a conclusion of this results it could be demonstrated that scaling functions, within experimental error, described the gelation kinetics and the solution viscosity of the gelatin-water system. …”
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Multivariate temperature-series analysis of stress-induced ferroelectricity in SrTiO3: a machine learning approach with K-shape clustering and hierarchical Bayesian estimation by Hirotaka Manaka, Kensei Toyoda, Yoko Miura

“…In addition, to obtain the structural and ferroelectric phase transition temperatures, [Formula: see text] and [Formula: see text], hierarchical Bayesian temperature-series estimation was performed at each pixel (as a lower level) constrained over the entire cluster (as a higher level) considering the measurement error. …”
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Analyzing and Forecasting Vessel Traffic Through the Panama Canal: A Comparative Study by Mitzi Cubilla-Montilla, Anabel Ramírez, William Escudero, Clara Cruz

“…The models were compared based on forecasting errors to evaluate their predictive accuracy. Overall, the NNAR model exhibited slightly better predictive performance than the SARIMA (1,0,1) (0,1,1) model in terms of error, with both outperforming the Holt–Winters model by a significant margin.…”
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Research on measurement method of non-synchronous sampling harmonic voltage based on quantum voltage by JIANG Lei, WANG Lei, SHI Zhaomin, WANG Zhijun, XU Suan

“…This will introduce large errors in the measurement results and affect the analysis spectrum of the signal. …”
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Mechanical Behaviors of Electrostatic Microbeams with Nonideal Supports by Yunxia Chang, Qichang Zhang, Wei Wang, Jianxin Han

“…Deviation of the actual system from the ideal supporting conditions caused by micromachining errors and manufacturing defects or the requirement of innovative design and optimization of microelectromechanical systems (MEMS) make the nonideal boundary in the micro-/nanoresonator system receive wide attention. …”
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Deep neural networks have an inbuilt Occam’s razor by Chris Mingard, Henry Rees, Guillermo Valle-Pérez, Ard A. Louis

“…The prior over functions is determined by the network architecture, which we vary by exploiting a transition between ordered and chaotic regimes. For Boolean function classification, we approximate the likelihood using the error spectrum of functions on data. …”
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Anti-Crisis Business Regulation in Russia: New Stage by A.  N. Ryakhovskaya

“…The article regards the error actions of the state during the transition to the market economy including deindustrialization, privatization of the public property, etc., and their economic impact on the market economy agents and population. …”
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