Research on voxel-based land complex modelling and adaptive resolution expression methodology by D. Sun, T. Shen, L. Huo, F. Kong

“…In order to improve the efficient use of land complex resources, explore the application of voxel model in land complex change monitoring, and propose a voxel-based land complex modelling and adaptive resolution expression method for the problem of large data redundancy and poor expression effect in the dynamic expression of land complex voxel model.Firstly, voxel classification and stratification are carried out through element characteristics to determine the elements suitable for voxel modelling; then, based on the analysis of terrain factors, the adaptive resolution expression method is constructed by optimizing the node evaluation criterion through the comprehensive consideration of sight distance and comprehensive terrain complexity.The results show that the method in this paper can achieve efficient expression and smooth scheduling of land complex voxel models at different resolutions, thus significantly reducing the computational complexity while maintaining the expression accuracy of important features.…”
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Modeling and Neural Network Approximation of Asymptotic Behavior for Delta Fractional Difference Equations with Mittag-Leffler Kernels by Pshtiwan Othman Mohammed, Muteb R. Alharthi, Majeed Ahmad Yousif, Alina Alb Lupas, Shrooq Mohammed Azzo

“…The asymptotic behavior of discrete Riemann–Liouville fractional difference equations is a fundamental problem with important mathematical and physical implications. …”
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Optimization and Validation of Wafer Surface Defect Detection Algorithm Based on RT-DETR by Ao Xu, Yanwei Li, Hongbo Xie, Rui Yang, Jianjie Li, Jiaying Wang

“…Firstly, a dynamic snake convolutional layer is introduced to detect elongated scratches where conventional convolutional kernels fail to extract features effectively. Secondly, to address the problem of information loss in small targets, an attention-based Transformer encoder module and a feature fusion network based on residual thinking are proposed. …”
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Few-shot segmentation based on multi-level and cross-scale clustering by Shuai Yuan, Junhai Qiu, Hongxia Xu, Yan Zhang, Jiaxing Zhang

“…A novel method that consists of two modules is proposed: a multi-level fuzzy clustering guidance module and a cross-scale feature fusion module. The former module can extract image features in a class-independent feature space and fuse them with different scale information, while the latter module can reduce the information loss caused by cross-scale transmission. …”
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The study of promising secure information systems based on signal modeling by V. A. Sizov, D. M. Malinichev, Kh. K. Kuchmezov

“…The transition to the fifth-generation network does not solve the existing problems of information security and leads to the emergence of new threats. …”
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Vibration area localization and event recognition for underground power optical cable in multiple laying scenarios based on deep learning by Wanchang Jiang, Chunzhen Li, Wenlong Zhang, Chunying Xie

“…PGSD-YOLO combines the YOLOv11 with the multi-scale attention of PMSAM to enhance the feature extraction ability. Through the dynamic sampling strategy of DySample, the information loss of signals is reduced, and GSConv and VoVGSCSP are used to optimize feature fusion. …”
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2D affine transform parameters by Gaussian elimination with pivoting by Tariq N. Ataiwe, Israa Hatem, Hisham M. Jawad Al Sharaa

“…In this paper, a new method for computing the 2D affine transform parameters will be introduced, the problem of the 2D affine transform method has been solved by Gaussian elimination with pivoting.We have derived equations by which to find transformation parameters. …”
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The solitary wave phenomena of the fractional Calogero-Bogoyavlenskii-Schiff equation by Hussain Gissy, Abdullah Ali H. Ahmadini, Ali H. Hakami

“…To analyze the detailed features of the wave structures as well as the pattern of dynamics of these solutions, 3D and contour diagrams were plotted by using Wolfram Mathematica. …”
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Multi-source Partial Discharge Pulse Classification Technology Based on t-SNE and CFSFDP Algorithms by Qiang SHI, Kun LIU, Jinsong LI, Fuchao LI

“…When multi-source partial discharge pulses are classified, the pulses cannot be effectively separated due to the distribution overlapping of their equivalent time-frequency features. In order to solve this problem a partial discharge pulse classification technology is proposed based on t-SNE and CFSFDP Algorithms. …”
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Gender Classification With Hand-Wrist Radiographs Using the Deep Learning Method by İbrahim Yücel Özbek, Mustafa Taha Güller, Zeynep Turanli Tosun, Nida Kumbasar, Özkan Miloğlu

“…In the gender classification problem, AlexNet, VGG16 and VGG19 transfer learning methods were both used as separate classifiers, and the features taken from these methods were combined and given to the support vector machine (SVM) classifier.Results: The results revealed that image analysis and deep learning techniques provided 91.1% accuracy in gender determination.Conclusion: Hand-wrist radiographs exhibited sexual dimorphism and could be used in gender prediction.Keywords: Deep learning; İmage analysis; Hand-wrist radiographs; Gender determination…”
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Assessment and Ranking of Effective Factors on Creating Local Identity in Urban Neighborhoods (Case Study: Jiroft City) by Sayyed Ali Alavi, Moosa Pahlavan Darini, Farrokhlagha Bahadori Amjazi

“…Investigating and recognizing the effective factors on local identity sense can be used to solve the problem of cities identity crisis and their neighborhoods. …”
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Three-Dimensional, Real-Time, and Intelligent Data Acquisition of Large Deformation in Deep Tunnels by Yue-Mao Zhao, Yong Han, Yong-Yuan Kou, Lin Li, Jiu-Hua Du

“…Engineering with large deformation is typically characterized by high stress, complex engineering geology, strong disturbance, and squeezing deformation, posing a great challenge to the design of an effective and accurate monitoring system. To address this problem, it is necessary to grasp the three-dimensional features of deformation and establish integrated monitoring of a support system. …”
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Asymmetric Two-Stage CycleGAN for Generation of Faces With Shadow Puppet Style by Jingzhou Huang, Xiaofang Huang, Taixiang Zhang, Jingchao Jiang, Houpan Zhou

“…In this paper, we study the problem of cross-domain image-to-image transformation from real faces to faces with shadow puppet style. …”
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Crystal Plasticity Elastic-Plastic Rate-Independent Numerical Analyses of Pollycrystalline Materials by Marta Wójcik, Andrzej Skrzat, Feliks Stachowicz, Emil Spišák

“…The selected results of elastic-plastic problems obtained using both macro- and micro- scales software for the explicit and implicit integration are featured here. …”
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SCUC Considering Loads and Wind Power Forecasting Uncertainties using Binary Gray Wolf Optimization Method by Majid Moazzami, Sayed Jamal Al-Din Hosseini, Hossein Shahinzadeh, Gevork B. Gharehpetian, Jalal Moradi

“…This fact confronts the solution of unit commitment problem with some challenges when a huge amount of wind resources is penetrated and considerable uncertainties are included in the problem. …”
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A Design Method for Road Vehicles with Autonomous Driving Control by Chunyu Mao, Yuping He, Martin Agelin-Chaab

“…The proposed method features a design framework with two layers: at the upper layer, a particle swarm optimization (PSO) algorithm serves as a solver to a multi-objective optimization problem for desired AV trajectory-tracking performance; at the lower layer, a coupled dynamic analysis is conducted among the three subsystems, i.e., a nonlinear model for the mechanical vehicle, a motion-planning module, and a controller based on nonlinear model predictive control (NLMPC) for direction control. …”
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Cooperative Drone and Water Supply Truck Scheduling for Wildfire Fighting Using Deep Reinforcement Learning by Lin-Yuan Bai, Xin-Ya Chen, Hai-Feng Ling, Yu-Jun Zheng

“…To solve the problem within the limited emergency response time, we propose a deep reinforcement learning method, which consists of an encoder for embedding the input instance features and a decoder for generating a solution by iteratively predicting the subarea selection decision through attention. …”
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Improvement of technology and mechanization means for weed control by M. M. Abdulgalimov, F. M. Magomedov, S. E. Sen'kevich, R. D. Umarov, I. M. Melikov

“…Taking into account biological features of weeds the design of a flame cultivator for weed control in orchards and vineyards is developed and science-based. …”
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Hazardous Gas Emission Monitoring Based on High-Resolution Images by Wenjian Chen, Yi Wang, Xuan Li, Wei Gao, Shiwei Ma, Yuanyuan Duan, Xiaopeng Shao

“…Particularly, multiple dictionary pairs were trained according to the gradient features of samples, and one optimal pair of dictionaries was chosen to reconstruct by judging the weighting of the information in different directions. …”
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Design of MobileNetV3 network accelerator based on dynamic adaptive computing engine by Xiang Haobin, Yang Ruimin, Wu Wentao, Li Chunlei, Dong Yan

“…Existing acceleration methods for efficient and lightweight MobileNetV3 networks usually use highly customized computing engines for model calculations, which limits the scalability of the accelerator and makes it only applicable to small networks or resource-rich hardware platforms. To address this problem, this paper proposes a MobileNetV3 network accelerator based on a dynamic adaptive computing engine. …”
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