Brain tumor classification using deep convolutional neural networks by M. Nurtay, M. Kissina, A. Tau, A. Akhmetov, G. Alina, N. Mutovina

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Expressing the Author's Position in the English-Language Network Film Review by I. V. Kononova, T. A. Klepikova, E. A. Klenova

“…Research methodology is based on the approaches to classification of modus and evaluation types developed by N.D. Arutyunova. The methodology of describing the author's position in evaluative genres is proposed, which boils down to the following steps: identifying the leading linguistic means of self-nomination; displaying main genre-typical patterns of subject modality (modus types); describing evaluation semantics specificity and linguistic means of dominant evaluative meanings verbalization. …”
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Construction of Ecological Security Pattern in Beijing City Based on Minimum Resistance Model by Han Ruiying, Zhao Zhiping, Xiao Nengwen, Shi Nana, Sun Guang, Gao Xiaoqi

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VA-Creator—A Virtual Appliance Creator based on adaptive Neural Networks to generate synthetic power consumption patterns by Michael Meiser, Benjamin Duppe, Ingo Zinnikus, Alexander Anisimov

“…These VAs synthesize power consumption patterns (PCPs) based on Neural Networks (NNs) which adapt their architecture to the training data structure to simplify the creation of new VAs. …”
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Evaluating the spatiotemporal dynamics and structural resilience of the global titanium industrial chain: Insights from trade network analysis by Wei Chen, Xiquan Zhao, Hu Yu

“…To this end, this paper constructs global trade networks of titanium ore, titanium dioxide, titanium sponge, and titanium products and utilizes various network analysis methods to deeply investigate the spatiotemporal evolution of global titanium trade patterns, the topology of the trade network, and the resilience characteristics. …”
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The structure of the local detector of the reprint model of the object in the image by A. A. Kulikov

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Spatiotemporal evolutionary patterns and influencing factors of urban carbon emissions in China by Qifeng Meng, Chunyi Li

“…On this basis, local Moran’s index, Social Network Analysis (SNA), and the Multiscale Geographically Weighted Regression (MGWR) model were employed to analyze spatial–temporal evolution patterns and influencing factors of urban carbon emissions. …”
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Exploring the performance of LBP-capsule networks with K-Means routing on complex images by Patrick Mensah Kwabena, Benjamin Asubam Weyori, Ayidzoe Abra Mighty

“…Capsule Networks (CapsNets) were proposed to mitigate the shortcomings of Convolutional Neural Networks (CNNs) such as invariance. …”
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Design and Evaluation of Steganographic Channels in Fifth-Generation New Radio by Markus Walter, Jörg Keller

“…The fifth generation of mobile networks (5G) introduced 5G New Radio as a radio access technology that meets current bandwidth, quality, and application requirements. …”
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<p><strong>Evaluation of geostatistical method and hybrid artificial neural network with imperialist competitive algorithm for predicting distribution pattern of <em>Tetranychus</em> <em>urticae</em> (Acari: Tetranychidae) in cucumber field of Behbahan, Iran</strong></p> by Alireza Shabaninejad, Bahram Tafaghodinia, Nooshin Zandi-Sohani

“… In this study, the statistical methods and artificial neural network (ANN) were used to estimate the spatial distribution of Tetranychus urticae in cucumber field of Behbahan, Iran. …”
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Performance Evaluation of Vehicle Ad hoc Networks Under Wi-Fi-6 Technology by Ahmed Salih Hasan, Basim Mahmood

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Impact of Climate Change on Groundwater Level Changes: An Evaluation Based on Deep Neural Networks by Stephen Afrifa, Tao Zhang, Peter Appiahene, Xin Zhao, Vijayakumar Varadarajan, Thomas Atta-Darkwah, Yanzhang Geng, Daniel Gyamfi, Rose-Mary Owusuaa Mensah Gyening

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A causal intervention framework for synthesizing mobility data and evaluating predictive neural networks by Ye Hong, Yanan Xin, Simon Dirmeier, Fernando Perez-Cruz, Martin Raubal

“…These changes result in performance fluctuations in next location prediction networks, revealing impacts of critical mobility behavior factors, including sequential patterns in location transitions, proclivity for exploring new locations, and preferences in location choices at population and individual levels. …”
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Evaluating the Impact of Replay-Based Continual Learning on Long-Term sEMG Pattern Recognition in Instance-Incremental Learning by Yuto Okawa, Suguru Kanoga, Takayuki Hoshino, Shin-Nosuke Ishikawa

“…A convolutional neural network was employed as the backbone model. To evaluate the impact of CL methods, a publicly available sEMG dataset comprising 30-day data from five subjects was used. …”
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Beam Coefficient Prediction for Antenna Arrays Using Physics-Aware Convolutional Neural Networks by Glendyn D. King, Md Asaduzzaman Towfiq, Ali C. Gurbuz, Bedri A. Cetiner

“…This work introduces a novel approach for predicting the complex element weights of a rectangular planar phased array for a desired beam pattern using physics-aware convolutional neural networks (PA-CNN). …”
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Diel and Annual Patterns of Vocal Activity of Three Neotropical Wetland Birds Revealed via BirdNET by Cristian Pérez-Granados, Karl-L. Schuchmann

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Stator Insulation Partial Discharge Test and Reliability Evaluation of Traction Motor by Yuenan LIU, Min GENG, Junfeng GUI, Ruizhen CUI, Xilian WANG

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Hybrid statistical-algorithmic approach using the frog algorithm to optimize blast patterns for reducing blast vibrations by Abbas Khajouei Sirjani, Farhang Sereshki, Mohammad Ataei, Manoj Khandelwal, Hojatollah Mohammadi Anayi, Seyed Mohammad Mehdi Mousavi Nasab, Mohammad Amiri Hosseini

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An Evaluation Method of Road Link Functionality Using Individual Trajectory Data and Weighted Network Analysis by Jisup Shim, Jiho Yeo

“…Those network indices make it possible to evaluate the functioning of roads based on people’s travel patterns and to detect critical links that are irreplaceable and difficult to detour. …”
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Multi-Scale Venation Pattern Analysis for Medicinal Plant Species Recognition by Arnav Sanjay Karnik, Nikhil Nair, Yashas Sagili, P. B. Pb

“…To validate the effectiveness of our approach, we developed and evaluated three distinct model architectures: 1) a modified ResNet-50 model utilizing transfer learning with an adapted input pipeline for venation-aware channels; 2) a custom-built convolutional neural network, VenationNet, explicitly designed for multi-scale venation analysis; and 3) a Dual-Stream CNN architecture that processes leaf texture and venation maps independently before merging via attention-based fusion. …”
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