Energy management in a microgrid equipped with an electric vehicle based on the internet of things considering responsive load by Mohamad Mahdi Erfani Majd, Reza Davarzani, Mahmoud Samiei Moghaddam, Ali Asghar Shojaei, Mojtaba Vahedi

“…The upper layer focuses on energy exchanges between microgrids, while the lower layer manages transactions among local users. …”
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Enhancing Lidar-Based 3D Classification Through an Improved Deep Learning Framework With Residual Connections by Shih-Lin Lin, Jun-Yi Wu

“…Although the increased network complexity and added layers lead to longer training times, the robust performance justifies the computational cost. …”
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Locating garden burial centers in Khodaafrin and Kalibar cities based on Boolean logic model and ANP network analysis in GIS environment by Ali Khodaie, Rahman Zandi

“…The purpose of this research was to locate landfill centers based on ANP network analysis process model and Boolean logic in GIS environment by using the opinions of expert experts in the form of pairwise comparison questionnaires and descriptive-analytical method.Material and methods: In this research, in order to select landfill centers due to the complexity of the influencing factors, the necessity of using geographic information technologies (GIS) and its integration with other management and planning matters has been proposed; Therefore, in this research, ARC GIS software has been used to create databases, spatial analysis and superimposition of information layers, as well as ANP model and Super Decision software to calculate criteria weight and Boolean logic model.Results and discussion: In this research, 17 layers of information include; Surface water resources, slope, city and village areas, protected areas, fault, soil, road network, litology, land use, erosion, NDVI, dem, climate, land side, dam, aspect Then, in the network analysis process model, Super Decision software was used to apply weights for each of the criteria, and in the ArcGIS environment, the information layers were combined with the final weight, and the value of each cell was determined in the final map. …”
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Ultrasound patterns of metastases from papillary thyroid cancer in soft tissues of the neck by V. S. Parshin, A. A. Veselova, P. D. Bespalov, V. V. Polkin, P. I. Garbuzov

“…During the statistical analysis, six most informative criteria were established: calcifications, contours, shape, depth-to-width ratio in the transverse scanning plane, state (differentiation) of the cortical and cerebral layers, echostructure. To create complexes (patterns) of ultrasonic signs, a combination of these signs was used among themselves, and five patterns were established. …”
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Effect of Substrate Temperature on Bead Track Geometry of 316L in Directed Energy Deposition: Investigation and Regression Modeling by Deviprasad Chalicheemalapalli Jayasankar, Stefan Gnaase, Dennis Lehnert, Artur Walter, Robin Rohling, Thomas Tröster

“…As a subset of additive manufacturing (AM), the DED process, also referred to as laser metal deposition (LMD), enables precise, layer-by-layer material deposition, making it highly suitable for complex geometries and part repair applications. …”
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Structural Optimization of p-GaN Gate GaN-Based High Electron Mobility Transistors by GE Mei; LI Yi; WANG Zhiliang; ZHU Youhua

“…In order to simplify the complexity of circuit design and reduce the cost, normally-off high electron mobility transistors are more preferable in the industry. …”
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Experimental and applied research on wellbore water seepage simulation based on hydrophobic depressurization method by Ang LI, Junhao YANG, Wenzhong ZHANG, Yuanmou LI, Zhixuan XUE, Liuyi FAN, Shengqi TIAN

“…With the continuous development of China’s coal resources to the deep end, the complex conditions of rock stratum existence bring great challenges to the construction and use of shafts. …”
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Graph Neural Network Learning on the Pediatric Structural Connectome by Anand Srinivasan, Rajikha Raja, John O. Glass, Melissa M. Hudson, Noah D. Sabin, Kevin R. Krull, Wilburn E. Reddick

“…Two GNN models (GCN simple and GCN residual), a deep neural network (multi-layer perceptron), and two standard machine learning models (random forest and support vector machine) were trained. …”
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Unraveling the laser decal transfer-based printing of ZnO ceramic towards FEP-ZnO-based Piezo-Tribo hybrid nanogenerators by Arpit Kumar Singh, Anshu Sahu, Palani Iyamperumal Anand

“…Initially, a silicon wafer is coated with a sacrificial layer over which a piezo-ceramic (ZnO) is sputtered to develop a seed layer. …”
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Dissipative Magneto-thermo-convection of Nanofluid Past through a Semi-infinite Vertical Surface with Ohmic Heating by Asra Anjum, Shaik Abdul Gaffar, Sateesh Kumar, Samdani Peerusab

“…Comprehensive numerical simulations are conducted to elucidate the complex interactions within the fluid.  A non-similarity solution is offered that is reliant on the thermophoresis number (Nt), buoyancy ratio (Nr), Brownian motion number (Nb), magnetic parameter (M), heat generation and absorption (Δ), viscous dissipation (Ec), and influence of these parameters on velocity, temperature, nanoparticle concentration profiles, in the boundary layer regime is examined in detail graphically. …”
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Spatial structural characteristics of the Deda ancient landslide in the eastern Tibetan Plateau: Insights from Audio-frequency Magnetotellurics and the Microtremor Survey Method by Zhen-dong Qiu, Chang-bao Guo, Yi-ying Zhang, Zhi-hua Yang, Rui-an Wu, Yi-qiu Yan, Wen-kai Chen, Feng Jin

“…The distinctive geological characteristics detectable by MSM in the shallow subsurface and by AMT in deeper layers. The findings include the identification of two sliding zones in the Deda I landslide, the shallow sliding zone (DD-I-S1) depth is approximately 20 m, and the deep sliding zone (DD-I-S2) depth is 36.2–49.9 m. …”
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Surface water mapping from remote sensing in Egypt’s dry season using an improved U-Net model with multi-scale information and attention mechanism by Yong Li, Xiuhui Liu, Vagner Ferreira, Heiko Balzter, Huiyu Zhou, Ying Ge, Meiyun Lai, Simin Chu, Han Ding, Zhenrong Gu

“…The extraction accuracy can be improved by combining convolutional layers for local feature extraction with Vision Transformer using Manhattan self-attention for global context information. …”
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Research on packet convergence sublayer classification algorithm for WiMAX system by ZHANG Qing-bo1, HE Jia-ming1, ZHU Yan3

“…The mapping relation between the higher-layer protocol data and connection was analyzed in WiMAX system.And a packet convergence sublayer classification algorithm based on non-collision hashing and address-blocking XOR look-up was proposed,thus realized the quick look-up and classification of higher-layer protocol data.The complexity and the increase renewal function of algorithm was analyzed quantitatively.The simulation results show that the classifi-cation algorithm satisfies QoS（quality of service） requests with the performances of delay and memory,moreover time-liness is also enhanced greatly.…”
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Fair Resource Allocation Algorithm for OFDMA System with Imperfect CSI by Yaohui Wu, Youming Li, Liping Jin, Pengfei Shao

“…In order to reduce the complexity in the use of dual optimization method for solving the lagrange operator process, an iteration searching method in the same layer was proposed to replace the traditional multi-layer iteration searching method. …”
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Balancing Depth for Robustness: A Study on Reincarnating Reinforcement Learning Models by Gang Li, Zhuxiao Wang, Shaowei He, Xiyuan Chen, Yunlei Xie, Jiajun Hu, Kehe Wu, Jingping Jia

“…The experimental results show that a seven-layer network achieves the best balance between feature extraction, policy learning, and robustness, achieving an IQM score of 1.2 in a pool of 10 games. …”
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The interfacial reactions of Mg battery anodes by Xuehong Luo, Ao Shen, Bo Liu, Junjie Wu, Mengbiao Fan, Na Yang, Gaopeng Zhang, Xi Chen, Qingwei Dai

“…It focuses on critical issues such as the dissolution of Mg anodes, the evolution of hydrogen gas, the formation of a passivation layer that hinders Mg²⁺ migration, and dendrite growth. …”
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Analysis of helio- and geophysical events in October–November 2021 from comprehensive observations of SHICRA SB RAS by Kozlov Vladimir, Starodubtsev Sergei, Grigoryev Vladislav, Baishev Dmitry, Makarov Georgy, Pavlov Egor, Karimov Rustam, Korsakov Aleksey, Stepanov Aleksandr, Koltovskoi Igor, Ammosov Petr, Gavrilieva Galina, Ievenko Igor, Parnikov Stanislav

“…The paper reports the results of comprehensive observations of space weather manifestations during geophysical events at the end of October – beginning of November 2021 at the Yakut meridional geophysical network of SHICRA SB RAS equipped with a complex of various scientific instruments installed at the stations Yakutsk, Maimaga, Zhigansk, and Tixie Bay (neutron monitors, an ionosonde, a riometer, receivers of VLF radio noise and signals from navigation radio stations, magnetometers), as well as a complex of optical instruments installed in Maimaga. …”
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Visualization of High-Intensity Laser–Matter Interactions in Virtual Reality and Web Browser by Martin Matys, James P. Thistlewood, Mariana Kecová, Petr Valenta, Martina Greplová Žáková, Martin Jirka, Prokopis Hadjisolomou, Alžběta Špádová, Marcel Lamač, Sergei V. Bulanov

“…By utilizing interactive 3D visualization, it overcomes the limitations of traditional 2D representations, offering enhanced spatial understanding and real-time manipulation of visualization parameters such as time steps, data layers, and colormaps. Users can interactively explore the visualized data by moving their body or using a controller for navigation, zooming, and rotation. …”
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A multi-omics database of buffaloes from Yangtze valley reveals diversity of water buffalo (Bubalus bubalis) by Yangyang Shen, Zhenjiang An, Shuwen Xia, Qiang Ding, Kunlin Chen, Yilong Miao, Tao Wang, Jifeng Zhong, Jianbin Li, Xiao Wang, Huili Wang

“…Our results revealed the apparent diversity of multi-layer omics profiles between two buffalo species. …”
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Predictive modeling of flexible EHD pumps using Kolmogorov–Arnold Networks by Yanhong Peng, Yuxin Wang, Fangchao Hu, Miao He, Zebing Mao, Xia Huang, Jun Ding

“…Inspired by the Kolmogorov–Arnold representation theorem, KAN replaces fixed activation functions with learnable spline-based activation functions, enabling it to approximate complex nonlinear functions more effectively than traditional models like Multi-Layer Perceptron and Random Forest. …”
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