Research on intrusion detection method of marine meteorological sensor network based on anomalous behaviors by Xin SU, Tian TIAN, Gong Ziyang, Yiqing ZHOU

“…To deal with the abnormal data flow attacks faced by the marine meteorological sensor network (MMSN), analyze the security mechanism, and aim at the complex and huge network structure and the extremely imbalanced data flow in the nodes, the intrusion detection method of marine meteorological sensor network based on anomalous behaviors was studied, and intrusion detection system (IDS) was built.The imbalance of dataset was considered emphatically, and the effective data generation was realized by using depth generation network CVAE-GAN to learn the distribution of minority classes in the dataset.OPTICS-based denoising algorithm was used to remove the noise points in majority classes and clarify the category boundaries.From the data perspective, the imbalance rate of dataset was reduced, the influence of imbalanced dataset on IDS was reduced, and the ability of classifier to identify minority classes of abnormal traffic was improved.The simulation results show that the proposed system can effectively identify all kinds of abnormal traffic, especially minority classes of them, and the imbalanced dataset processing method can significantly improve the detection ability of the classifier.…”
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Energy efficiency-based downlink resource allocation in cognitive small cell networks by Ya-nan JIA, Dian-wu YUE

“…Simulation results show the proposed algorithm can converge to a Nash equilibrium and effectively improve system resources utilization and EE in interference-limited communication environments.…”
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Parabolic Equation Modeling of Propagation over Terrain Using Digital Elevation Model by Xiao-Wei Guan, Li-Xin Guo, Ya-Jiao Wang, Qing-Liang Li

“…Starting from a parabolic approximation to the Helmholtz equation, a wide-angle parabolic equation is deduced under the assumption of forward propagation and the split-step Fourier transform algorithm is used to solve it. The application of DEM is extended to the Cartesian coordinate system and expected to provide a precise representation of a three-dimensional surface with high efficiency. …”
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Flocking Behavior of Boids Driven by Hyperchaotic MACM System by Rosa Martha López-gutiérrez, Lılıana Cardoza Avendaño, Ana Medina, Cesar Cruz Hernández

“…A measure of chaotic compound will be introduced to the algorithm by means of a new four-dimensional autonomous hyperchaotic system based on the 3D Méndez-Arellano-Cruz-Martínez (MACM) system. …”
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An Improved Test Selection Optimization Model Based on Fault Ambiguity Group Isolation and Chaotic Discrete PSO by Xiaofeng Lv, Deyun Zhou, Yongchuan Tang, Ling Ma

“…The improved chaotic discrete particle swarm optimization (PSO) algorithm is adopted to solve the improved test selection optimization model. …”
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An Investigation on Gas Lift Performance Curve in an Oil-Producing Well by Deni Saepudin, Edy Soewono, Kuntjoro Adji Sidarto, Agus Yodi Gunawan, Septoratno Siregar, Pudjo Sukarno

“…It is also constructed here a numerical scheme based on genetic algorithm to compute the optimum oil production.…”
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Optimal Design and Acoustic Assessment of Low-Vibration Rotor Blades by G. Bernardini, E. Piccione, A. Anobile, J. Serafini, M. Gennaretti

“…Blade shape and structural properties are the design parameters to be identified within a binary genetic optimization algorithm under aeroelastic stability constraint. The process exploits an aeroelastic solver that is based on a nonlinear, beam-like model, suited for the analysis of arbitrary curved-elastic-axis blades, with the introduction of a surrogate wake inflow model for the analysis of sectional aerodynamic loads. …”
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A COMPUTATIONAL SYSTEM FOR EVALUATING HUMAN PERCEPTION IN VIDEO STEGANOGRAPHY by Marcin PERY, Robert WASZKOWSKI

“…Experimental results revealed the thresholds of human-level undetectability and automated decoding for each technique, enabling the identification of critical differences between human and algorithmic detection capabilities. This research contributes to the field of steganography by offering a novel framework for evaluating the trade-offs between human perception and automated decoding in video-based information hiding. …”
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A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression by Chi-Jie Lu, Chi-Chang Chang

“…The extracted features are then applied to K-means algorithm for clustering the sales data into several disjoined clusters. …”
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Prescribed Performance Tracking Control for the Hypersonic Vehicle with Actuator Faults by Zhenghui Yang, Wentao He, Yushan He, Yaen Xie, Jun Li, Shuo Song

“…Simultaneously, radial basis function neural networks (RBFNNs) are adopted for approximating the unavailable dynamics, in which the minimum learning parameter (MLP) algorithm brilliantly alleviates the excessive occupation of the computational resource. …”
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Peer-to-Peer Multicasting Inspired by Huffman Coding by Bartosz Polaczyk, Piotr Chołda, Andrzej Jajszczyk

“…The multicast tree construction is based on the Huffman source coding algorithm. First, a centrally managed version is presented, and then an effective use of a distributed paradigm is shown. …”
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Game-Theory-Based Multi-Objective Optimization for Enhancing Environmental and Social Life Cycle Assessment in Steel–Concrete Composite Bridges by David Martínez-Muñoz, Jose V. Martí, Víctor Yepes

“…The optimization process considered four criteria simultaneously, using a discrete version of the SCA algorithm and a transfer function for discretization. …”
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Retrieving and Identifying Remnants of Artefacts on Local Devices Using Sync.com Cloud by Abdulghani Ali Ahmed, Khalid Farhan, Mohd Izuan Hafez Ninggal, Ghadir Alselwi

“…The proposed technique is implemented and tested by applying a forensics investigation algorithm on Sync.com cloud storage using the Microsoft Windows 10 operating system.…”
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Slot Parameter Optimization for Multiband Antenna Performance Improvement Using Intelligent Systems by Erdem Demircioglu, Ahmet Fazil Yagli, Senol Gulgonul, Haydar Ankishan, Emre Oner Tartan, Murat H. Sazli, Taha Imeci

“…To achieve the best ANN performance, Particle Swarm Optimization (PSO) and Differential Evolution (DE) are applied with ANN’s conventional training algorithm in optimization of the modeling performance. …”
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Homeomorphism Mapping Based Neural Networks for Finite Time Constraint Control of a Class of Nonaffine Pure-Feedback Nonlinear Systems by Jianhua Zhang, Quanmin Zhu, Yang Li, Xueli Wu

“…Furthermore, by combining finite time adaptive law and Lyapunov-based arguments, a valid finite time adaptive neural networks controller design algorithm is presented to ensure that system is practical finite stable (PFS) rather than uniformly ultimately bounded (UUB). …”
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Convergent Power Series of sech⁡(x) and Solutions to Nonlinear Differential Equations by U. Al Khawaja, Qasem M. Al-Mdallal

“…The method provides also a robust and very efficient numerical algorithm for solving nonlinear differential equations numerically. …”
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Reduced‐order multisensory fusion estimation with application to object tracking by Vladimir Shin, Vahid Hamdipoor, Yoonsoo Kim

“…Also, unlike existing suboptimal fusion filters such as the covariance intersection, the proposed ROF algorithm makes use of nonzero cross‐covariances between local filters that greatly improve its estimation accuracy. …”
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Research on Fault Feature Extraction of Hydropower Units Based on Adaptive Stochastic Resonance and Fourier Decomposition Method by Yan Ren, Jin Huang, Lei-Ming Hu, Hong-Ping Chen, Xiao-Kai Li

“…In order to effectively extract the characteristics of nonstationary vibration signals from hydropower units under noise interference, an adaptive stochastic resonance and Fourier decomposition method (FDM) based on genetic algorithm (GA) are proposed in this paper. Firstly, GA is used to optimize the resonance parameters so that the signal can reach the optimal resonance and the signal-to-noise ratio (SNR) can be improved. …”
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THz-SAR Vibrating Target Imaging via the Bayesian Method by Bin Deng, Xin-yun Wang, Cheng-guang Wu, Yu-liang Qin, Hong-qiang Wang

“…In this paper, the imaging characteristics of vibrating targets with THz-SAR are at first analyzed. An improved algorithm based on an excellent Bayesian approach, that is, the expansion-compression variance-component (ExCoV) method, has been proposed for reconstructing scattering coefficients of vibrating targets, which provides more robust and efficient initialization and overcomes the deficiencies of sidelobes as well as artifacts arising from the traditional correlation method. …”
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Denoising of Mechanical Vibration Signals Using Quantum-Inspired Adaptive Wavelet Shrinkage by Yan-long Chen, Pei-lin Zhang, Bing Li, Ding-hai Wu

“…This quantum-inspired shrinkage algorithm combines three elements: an adaptive non-Gaussian statistical model of dual-tree complex wavelet transform (DTCWT) coefficients proposed to improve practicability of prior information, the quantum superposition introduced to describe the interscale dependencies of DTCWT coefficients, and the quantum-inspired probability of noise defined to shrink wavelet coefficients in a Bayesian framework. …”
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