Image forgery detection algorithm based on U-shaped detection network by Zhuzhu WANG

“…Aiming at the defects of traditional image tampering detection algorithm relying on single image attribute,low applicability and current high time-complexity detection algorithm based on deep learning,an U-shaped detection network image forgery detection algorithm was proposed.Firstly,the multi-stage feature information in the image by using the continuous convolution layers and the max-pooling layers was extracted by U-shaped detection network,and then the obtained feature information to the resolution of the input image through the upsampling operation was restored.At the same time,in order to ensure higher detection accuracy while extracting high-level semantic information of the image,the output features of each stage in U-shaped detection network would be merged with the corresponding output features through the upsampling layer.Further the hidden feature information between tampered and un-tampered regions in the image upon the characteristics of the general network was explored by U-shaped detection network,which could be realized quickly by using its end-to-end network structure and extracting the attributes of strong correlation information among image contexts that could ensure high-precision detection results.Finally,the conditional random field was used to optimize the output of the U-shaped detection network to obtain a more exact detection results.The experimental results show that the proposed algorithm outperforms those traditional forgery detection algorithms based on single image attribute and the current deep learning-based detection algorithm,and has good robustness.…”
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Image forgery detection algorithm based on U-shaped detection network by Zhuzhu WANG

“…Aiming at the defects of traditional image tampering detection algorithm relying on single image attribute,low applicability and current high time-complexity detection algorithm based on deep learning,an U-shaped detection network image forgery detection algorithm was proposed.Firstly,the multi-stage feature information in the image by using the continuous convolution layers and the max-pooling layers was extracted by U-shaped detection network,and then the obtained feature information to the resolution of the input image through the upsampling operation was restored.At the same time,in order to ensure higher detection accuracy while extracting high-level semantic information of the image,the output features of each stage in U-shaped detection network would be merged with the corresponding output features through the upsampling layer.Further the hidden feature information between tampered and un-tampered regions in the image upon the characteristics of the general network was explored by U-shaped detection network,which could be realized quickly by using its end-to-end network structure and extracting the attributes of strong correlation information among image contexts that could ensure high-precision detection results.Finally,the conditional random field was used to optimize the output of the U-shaped detection network to obtain a more exact detection results.The experimental results show that the proposed algorithm outperforms those traditional forgery detection algorithms based on single image attribute and the current deep learning-based detection algorithm,and has good robustness.…”
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SPECIALIZED MAPPING OF CRUSTAL FAULT ZONES. PART 2: MAIN STAGES AND PROSPECTS by K. Zh. Seminsky

“…There are three stages in the special mapping method (Fig. 3) as follows:Stage I: Preparation and analysis of previously published data on the regional fault structure (Fig. 1, А–Г), establishment of a networks of stations to conduct structural geological monitoring and mass measurements of joints, re­cord of rock data (Fig. 2, А), general state of the fault network (Fig. 1, Д–З), fracture density (Fig. 2, Б) and, if any, structures of the above-jointing level (Fig. 1, Е, З; Fig. 2, А).Stage II is aimed at processing of field data and includes activities in four groups (II.1–II.4) as follows: Group II.1: construction of circle diagrams, specification of characteristics of joint systems and their typical scatters (Fig. 4, А), identification of simple (generally tipple) paragenesises, and determination of dynamic settings of their formation (translocal rank) (Table 1), evaluation of densities and complexity of the joint networks, analysis of their spacial patterns within the site under mapping, and identification of the most intensively destructed zones in the rock massif (Fig. 2, Б–В). …”
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Study of the properties of pectin substances for the production of healthy food products by A. V. Tarasenko

“…The article is devoted to the research in the field of using frozen grapes in the technology of production of products for a healthy diet. …”
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Bayesian Inference for Long Memory Stochastic Volatility Models by Pedro Chaim, Márcio Poletti Laurini

“…The logarithmic variance persistence in these models is represented by a Fractional Gaussian Noise process, which we approximate as a linear combination of independent first-order autoregressive processes, lending itself to a Gaussian Markov Random Field representation. …”
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Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points by Jiajie HAN, Qingyang YUAN, Yu LI, Bo ZHANG, Ke XUE, Tian LAN

“…However, obtaining comprehensive real-time temperature data for large-scale battery systems is challenging due to the high costs, complexity, and impracticality of deploying extensive sensor networks. …”
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Study on the Applicability of 316L Stainless Steel Coiled Tubing in the Tarim Oilfield by HU Fangting, ZHAO Mifeng, GENG Hailong, LONG Yan, KUANG Xianren

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Scattering and stress concentration of SH guided waves by a semicircular hole on the boundary of an infinite piezoelectric ceramic plate by Enxiang Qu, Hui Qi, Jing Guo, Shuang Liu, Ying Li

“…The fundamental mechanical problems of dynamic stress concentration factor and electric field intensity concentration factor are addressed using the complex function approach, wave function expansion method, and repeated mirror method, and the analytical expressions for the relevant stress concentration are presented. …”
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Models and Problems in Electrohydrodynamics by V.A. Polyansky, I.L. Pankratieva

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Explainable Artificial Intelligence for State of Charge Estimation of Lithium-Ion Batteries by Ho Tung Jeremy Chan, Jelena Rubeša-Zrim, Franz Pichler, Amil Salihi, Adam Mourad, Ilija Šimić, Kristina Časni, Eduardo Veas

“…Additionally, the simulated nature of laboratory settings cannot guarantee robustness when the same method is applied to field data collected from real-world scenarios. A suitable alternative to this problem is the use of data-driven approaches. …”
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Simulation of Electromagnetic Wave Resistivity Logging While Drilling Based on the Physical-Informed Neural Network by LIU Yang, WANG Jian, XU Delong

“…In order to simulate the response of electromagnetic wave resistivity logging while drilling efficiently in complex media and accelerate the inversion of logging data, the physical-informed neural network (PINN) is used to simulate the response of electromagnetic wave resistivity logging while drilling. …”
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Developing a Unified Framework for PMSM Speed Regulation: Active Disturbance Rejection Control via Generalized PI Control by Huanzhi Wang, Yuefei Zuo, Chenhao Zhao, Christopher H. T. Lee

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TWO-PARAMETER IRT MODEL APPLICATION TO ASSESS PROBABILISTIC CHARACTERISTICS OF PROHIBITED ITEMS DETECTION BY AVIATION SECURITY SCREENERS by A. K. Volkov, D. V. Aidarkin, A. K. Volkov

“…Test x-ray images have to be selected in the ascending order of their complexity taking into consideration the influence of various factors.The suggested model may be applied both in the field of improving of aviation security screeners’ training methods to provide screening procedures, and while solving problems of increasing the efficiency of the screening system functioning.…”
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Dynamic path planning of UAV with least inflection point based on adaptive neighborhood A* algorithm and multi-strategy fusion by Longyan Xu, Mao Xi, Ren Gao, Ziheng Ye, Zaihan He

“…Abstract Planning a safe and efficient global path in a complex three-dimensional environment is a complex and challenging optimization task. …”
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Progress and direction of 3D seismic exploration in Qintong Sag of Subei Basin by LIU Ming,XUE Ye,LIU Tiantian,ZHAO Sucheng,LAN Jiada,SHI Mengjun,YANG Fan

“…The analysis shows that the high SNR, high resolution and amplitude-preserving processing effect are limited by the large difference of multi-phase data collection, narrow frequency band of original data and low sampling density of wave field. In order to solve the further problems of the complex subtle reservoir seismic exploration, wireless single-point receiving, single-point broadband excitation, small surface element, high coverage density, wide azimuth seismic acquisition, amplitude quantization quality control, broadband omni-directional processing and five-dimensional interpretation should be explored.…”
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Lightweight construction safety behavior detection model based on improved YOLOv8 by Kan Huang, Mideth B. Abisado

“…At the same time, the receptive field is expanded by combining the Receptive Field Block (RFB) module, the ability to capture multi-scale features is enhanced, and the Global Attention Mechanism (GAM)-Attention mechanism is introduced to enhance the recognition ability of local features. …”
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Shield tunneling efficiency and stability enhancement based on interpretable machine learning and multi-objective optimization by Wenli Liu, Yang Chen, Tianxiang Liu, Wen Liu, Jue Li, Yangyang Chen

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Environmental impact assessment in the Caspian region by E. M. Aliyev, V. Yu. Kerimov, Yu. A. Lobanov

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Hooks, Lines, and Sinkers: How Active Galactic Nucleus Feedback and Cosmic-Ray Transport Shape the Far-infrared–Radio Correlation of Galaxies by Sam B. Ponnada, Rachel K. Cochrane, Philip F. Hopkins, Iryna S. Butsky, Sarah Wellons, N. Nicole Sanchez, Cameron Hummels, Yue Samuel Lu, Dušan Kereš, Christopher C. Hayward

“…The far-infrared–radio correlation (FRC) is one of the most promising empirical constraints on the role of cosmic rays (CRs) and magnetic fields in galaxy formation and evolution. While many theories have been proposed in order to explain the emergence and maintenance of the FRC across a gamut of galaxy properties and redshift, the nonlinear physics at play remain unexplored in full complexity and within a cosmological context. …”
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Wind Turbine Aerodynamics Simulation Using the Spectral/<i>hp</i> Element Framework Nektar++ by Hamidreza Abedi, Claes Eskilsson

“…However, accurately simulating wind turbine aerodynamics, particularly in offshore wind farms, remains challenging due to complex environmental factors such as the marine atmospheric boundary layer. …”
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