A Conceptual Approach to Complex Model Management with Generalized Modelling Patterns and Evolutionary Identification by Sergey V. Kovalchuk, Oleg G. Metsker, Anastasia A. Funkner, Ilia O. Kisliakovskii, Nikolay O. Nikitin, Anna V. Kalyuzhnaya, Danila A. Vaganov, Klavdiya O. Bochenina

“…One of the important aspects of complex model management is dealing with the uncertainty of various kinds (context, parametric, structural, and input/output) to control the model. In the situation where a system being modeled, or modeling requirements change over time, specific methods and tools are needed to make modeling and application procedures (metamodeling operations) in an automatic manner. …”
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A multi-dimensional student performance prediction model (MSPP): An advanced framework for accurate academic classification and analysis by V. Balachandar, K. Venkatesh

“…Moreover, through adaptive hyper-parameter tuning and advanced graph neural network layers in the MSPP model allow to make output more dense representation for predictions resulting more accurate classification. …”
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Une formation d’éducateur spécialisé en animation socioculturelle et sportive qui prend forme en Belgique francophone by Marianne Block, Marine Fontaine, Lore Martin, Marie Pirotte, Julie Reynaert

“…En 10 ans, la formation s’est progressivement structurée autour de la notion de l’action collective, de projets « co-actifs », du numérique critique et d’une alliance équilibrée entre techniques artistiques et sportives. …”
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Deep learning based analysis of G3BP1 protein expression to predict the prognosis of nasopharyngeal carcinoma. by Linshan Zhou, Mu Yang, Jiadi Luo, Hongjing Zang, Songqing Fan, Yuting Zhan

“…A model was intricately designed and rigorously tested to yield the quantitative data regarding staining intensity and extent. The collective output data was subjected multiplicative analysis, exploring its correlation with the prognosis.…”
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ViPar: High-Level Design Space Exploration for Parallel Video Processing Architectures by Karim M. A. Ali, Rabie Ben Atitallah, Abdessamad Ait El Cadi, Nizar Fakhfakh, Jean-Luc Dekeyser

“…In addition to that, we derived the equations for estimating the hardware utilization and execution time for each design point during the space exploration process. (2) By defining the main characteristics of the parallel video architecture like parallelism level, the number of input/output ports, the pixel distribution pattern, and so on, ViPar tool can automatically generate the dedicated architecture for hardware implementation. …”
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Novel Approach for Endoscopic Management of Duodenal Injury during Perirenal Infected Haematoma Drainage after Shock-Wave Lithotripsy by Nariman Gadzhiev, Dmitry Gorelov, Alexander Smirnov, Salman Al-Shukri, Sergei Petrov

“…Postoperatively duodenal injury was suspected due to amber color, low creatinine, and high bilirubin level in the drainage output. CT demonstrated that the pigtail of the drain had entered the second part of the duodenum. …”
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Research on Road Adhesion Condition Identification Based on an Improved ALexNet Model by QiMing Wang, JinMing Xu, Tao Sun, ZhiChao Lv, GaoQiang Zong

“…Finally, the traditional machine learning and improved ALexNet model are compared, focusing on adaptability, prediction output, and error performance, among others. The results show that the accuracy of the proposed model is better than that of the traditional machine learning method by 10% and the ALexNet model by 3%, and it is 0.3 h faster than ALexNet in training speed. …”
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Adaptive backstepping control for electro-hydraulic servo system in extension sleeve press-fitting process of bearing pressing machine by Chen Hongsheng

“…The analysis results of the numerical examples show that the proposed algorithm can effectively suppress the adverse effects of typical external disturbances and unmodeled dynamic factors and maintain good control accuracy. The output displacement error of the proposed algorithm is smaller and the tracking performance is better. …”
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MIMO Channel Model with Propagation Mechanism and the Properties of Correlation and Eigenvalue in Mobile Environments by Yuuki Kanemiyo, Youhei Tsukamoto, Hiroaki Nakabayashi, Shigeru Kozono

“…This paper described a spatial correlation and eigenvalue in a multiple-input multiple-output (MIMO) channel. A MIMO channel model with a multipath propagation mechanism was proposed and showed the channel matrix. …”
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Entrepreneurial Behaviour and the Performance of Small and Medium Enterprises in South-West, Nigeria by Nafiu Badiru

“…By doing so, they can develop more innovative products and services, outperform competitors, improve output, and retain customers in their operating sector. …”
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Thermodynamic and Techno-Economic Performance Comparison of Methanol Aqueous Phase Reforming and Steam Reforming for Hydrogen Production by Changsong Hu, Chao Xu, Xiaojun Xi, Yao He, Tiejun Wang

“…A techno-economic comparison of APR and SR for a distributed hydrogen production system with a 50 kg/h hydrogen output shows that although APR requires higher fixed operating costs and annual capital charges, it benefits from lower variable operating costs. …”
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Orthogonal Components Forming of the Microprocessor-Based Protection Input Signals by F. A. Romaniuk, V. Yu. Rumiantsev, Yu. V. Rumiantsev, V. S. Kachenya

“…For the construction of high-speed measuring devices, this time of establishing the true output signal is often unacceptable. The article proposes to form the equivalent signal OS in microprocessor defenses based on the values of the cosine and sine axes of the main harmonic formed using a discrete Fourier transform, by multiplying them by a correction factor, which is a function of the values of the input signal amplitude and its main harmonic. …”
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A Decision-Making Approach for Ranking Tertiary Institutions’ Service Quality Using Fuzzy MCDM and Extended HiEdQUAL Model by Olufunke Oladipupo, Taiwo Amoo, Olawande Daramola

“…This study has been able to practically establish Ext-HiEdQUAL as a new service quality model for higher education with six concepts and 33 criteria. The output of the Fuzzy MCDM ranking recommends institution B as the best institution to students based on the Ext-HiEdQUAL measures. …”
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A Universal Source DC–DC Boost Converter for PEMFC-Fed EV Systems With Optimization-Based MPPT Controller by C. H. Hussaian Basha, Shaik Rafikiran, Ezzeddine Touti, Besma Bechir Graba, Mouloud Aoudia

“…Another issue of the fuel cell is high output current generation and less voltage production. …”
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Dynamic Peak Threshold Estimation Method for Noise Mitigation in Hybrid PLC/VLC Systems by Irvine Mapfumo, Thokozani Shongwe

“…The acquired results demonstrate that the proposed method does not only eliminates the need to know impulsive noise parameters, but also enhances the receiver’s output SNR. Moreover, the results showed a clear correlation between the optimal blanking threshold and the peak-to-average power value of the ACO-OFDM symbol which we leveraged to ascertain the optimal blanking threshold.…”
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Deciphering regulatory architectures of bacterial promoters from synthetic expression patterns. by Rosalind Wenshan Pan, Tom Röschinger, Kian Faizi, Hernan G Garcia, Rob Phillips

“…To that end, in this paper we create tens of thousands of synthetic gene expression outputs for bacterial promoters using both equilibrium and out-of-equilibrium models. …”
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Energy Efficiency Analysis of Antenna Selection Techniques in Massive MIMO-OFDM System with Hardware Impairments by Anuj Singal, Deepak Kedia

“…In massive multiple-input multiple-output (M-MIMO) systems, a large number of antennas increase system complexity as well as the cost of hardware. …”
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Privacy leakage risk assessment for reversible neural network by Yifan HE, Jie ZHANG, Weiming ZHANG, Nenghai YU

“…In recent years, deep learning has emerged as a crucial technology in various fields.However, the training process of deep learning models often requires a substantial amount of data, which may contain private and sensitive information such as personal identities and financial or medical details.Consequently, research on the privacy risk associated with artificial intelligence models has garnered significant attention in academia.However, privacy research in deep learning models has mainly focused on traditional neural networks, with limited exploration of emerging networks like reversible networks.Reversible neural networks have a distinct structure where the upper information input can be directly obtained from the lower output.Intuitively, this structure retains more information about the training data, potentially resulting in a higher risk of privacy leakage compared to traditional networks.Therefore, the privacy of reversible networks was discussed from two aspects: data privacy leakage and model function privacy leakage.The risk assessment strategy was applied to reversible networks.Two classical reversible networks were selected, namely RevNet and i-RevNet.And four attack methods were used accordingly, namely membership inference attack, model inversion attack, attribute inference attack, and model extraction attack, to analyze privacy leakage.The experimental results demonstrate that reversible networks exhibit more serious privacy risks than traditional neural networks when subjected to membership inference attacks, model inversion attacks, and attribute inference attacks.And reversible networks have similar privacy risks to traditional neural networks when subjected to model extraction attack.Considering the increasing popularity of reversible neural networks in various tasks, including those involving sensitive data, it becomes imperative to address these privacy risks.Based on the analysis of the experimental results, potential solutions were proposed which can be applied to the development of reversible networks in the future.…”
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Understanding Logical-Shift Error Propagation in Quanvolutional Neural Networks by Marzio Vallero, Emanuele Dri, Edoardo Giusto, Bartolomeo Montrucchio, Paolo Rech

“…Our detailed analysis shows that corruptions in the qubits' state that alter their probability amplitude are more critical than the ones altering their phase, that some object classes are more likely than others to be corrupted, that the criticality of subgrids depends on the dataset, and that the control qubits, once corrupted, are more likely to modify the QNN output than the target qubits.…”
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<i>λ</i> ∼ 4.7 μm Quantum Cascade Distributed-Feedback Lasers for Free-Space Communications by Morgan Turville-Heitz, Robert Marsland, Jae Ha Ryu, Steven A. Jacobs, Jeremy D. Kirch, Tom Earles, Steven Ruder, Kevin Oresick, Benjamin Knipfer, Dan Botez, Luke J. Mawst

“…We report the design and fabrication of 4.7 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi mathvariant="sans-serif">μ</mi></semantics></math></inline-formula>m emitting, 1.5 mm cavity length, single-mode distributed-feedback QCLs, with a CW front-facet output power of 165 mW and a calculated photon lifetime of 11.6 ps, resulting in an electrically limited CW modulation with a 3 dB cutoff at 850 MHz.…”
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