Research on GNNs with stable learning by Wenbin Li, Wenxuan Wei, Peiyang Wang, Li Pan, Bo Yang, Yanling Xu

“…The aim is to extract genuine causal features while eliminating spurious causal features. By introducing a feature sample weighting decorrelation technique in the random Fourier transform space and combining it with a baseline GNN model, a Stable-GNN model and a constrained sampling weight gradient update algorithm are designed. …”
Get full text

Research on filter-based adversarial feature selection against evasion attacks by Qimeng HUANG, Miaomiao WU, Yun LI

“…With the rapid development and widespread application of machine learning technology, its security has attracted increasing attention, leading to a growing interest in adversarial machine learning.In adversarial scenarios, machine learning techniques are threatened by attacks that manipulate a small number of samples to induce misclassification, resulting in serious consequences in various domains such as spam detection, traffic signal recognition, and network intrusion detection.An evaluation criterion for filter-based adversarial feature selection was proposed, based on the minimum redundancy and maximum relevance (mRMR) method, while considering security metrics against evasion attacks.Additionally, a robust adversarial feature selection algorithm was introduced, named SDPOSS, which was based on the decomposition-based Pareto optimization for subset selection (DPOSS) algorithm.SDPOSS didn’t depend on subsequent models and effectively handles large-scale high-dimensional feature spaces.Experimental results demonstrate that as the number of decompositions increases, the runtime of SDPOSS decreases linearly, while achieving excellent classification performance.Moreover, SDPOSS exhibits strong robustness against evasion attacks, providing new insights for adversarial machine learning.…”
Get full text

Three-Dimensional Extended Target Tracking and Shape Learning Based on Double Fourier Series and Expectation Maximization by Hongge Mao, Xiaojun Yang

“…Specifically, the 3D shape is modeled using a radial function estimated via double Fourier series (DFS) expansion, and orientation is represented using the compact, singularity-free axis-angle method. The ECM algorithm facilitates this joint estimation: an Unscented Kalman Smoother infers kinematics in the E-step, while the M-step estimates DFS shape parameters and rotation angles by minimizing regularized cost functions, promoting robustness and smoothness. …”
Get full text

Generalized Singular Value Decomposition-Based Secure Beam Hybrid Precoding for Millimeter Wave Massive Multiple-Input Multiple-Output Systems by Boqing Chen, Lijun Yang, Meng Wu

“…In a hybrid precoding system, the low-complexity GSVD-Sparsity algorithm can achieve a spectral efficiency close to that of the GSVD-based scheme in a fully digital system while maintaining anti-eavesdropping capabilities.…”
Get full text

Key Nodes Identification Method in Scale-Free Network Based on Structural Holes by Weiyan Liu

“…The proposed algorithm achieves higher accuracy in structural hole-aware ranking compared to benchmarks while maintaining <inline-formula> <tex-math notation="LaTeX">${ O}\left ({{ m+n.logn }}\right)$ </tex-math></inline-formula> complexity. …”
Get full text

Calibration and Uncertainty Analysis of Freundlich and Langmuir Isotherms Using the Markov Chain Monte Carlo (MCMC) Approach by Haniyeh Sharifi Moghadam, Saeed Alimohammadi

“…First, their parameters were estimated and calibrated using a simple optimization model. To analyze parameter uncertainty, a Bayesian approach employing the Markov Chain Monte Carlo method was adopted, utilizing the Metropolis-Hastings and Gibbs algorithms, and the results were compared. …”
Get full text

Adaptive dimensionality reduction for neural network-based online principal component analysis. by Nico Migenda, Ralf Möller, Wolfram Schenck

“…While the continuous update of the principal components is widely studied, the available algorithms for dimensionality adjustment are limited to an increment of one in neural network-based and incremental PCA. …”
Get full text

Analysis of Encrypted Network Traffic for Enhancing Cyber-security in Dynamic Environments by Faeiz Alserhani

“…User selection is accomplished through robust Deep Reinforcement Learning with the Tabu Search (DRL-TS) algorithm, while channel selection is optimized through rigorous training employing Proximal Policy Optimization (PPO). …”
Get full text

A Lightweight, Intelligent Autonomous Exploration System for Indoor Robots Using Improved Random Walk With Back-Off Strategies by Blesson Mathews Luke, S. Abraham Sampson

“…The algorithm maintained a reliable average localization error of 0.005 m while exhibiting memory efficiency by the reduced memory usage by up to 13.7% relative to TB3. …”
Get full text

A Hybrid Dynamic Path-Planning Method for Obstacle Avoidance in Unmanned Aerial Vehicle-Based Power Inspection by Zheng Huang, Chengling Jiang, Chao Shen, Bin Liu, Tao Huang, Minghui Zhang

“…Simulation results show that, compared to traditional algorithms, the proposed method achieves an 8% to 12% optimization in path length, more than 50% in node optimization, and over 95% in planning time optimization. …”
Get full text

Online Autonomous Motion Control of Communication-Relay UAV with Channel Prediction in Dynamic Urban Environments by Cancan Tao, Bowen Liu

“…The method mainly consists of two parts: wireless channel parameter estimation and optimal relay position search. Considering that in practical applications, the radio frequency (RF) channel parameters in complex urban environments are difficult to obtain in advance and are constantly changing, an estimation algorithm based on Gaussian process learning is proposed for online evaluation of the wireless channel parameters near the current position of the UAV; for the optimal relay position search problem, in order to improve the real-time performance of the method, a line search algorithm and a general gradient-based algorithm are proposed, which are used for point-to-point communication and multi-node communication scenarios, respectively, reducing the two-dimensional search to a one-dimensional search, and the stability proof and convergence conditions of the algorithm are given. …”
Get full text

Research on Automotive Radar Mutual Interference Mitigation Method based on V2X Communication Assistance by Yangshui Gao, Liping Kui, Qinbiao Yang, Lei Xiong, Rong Zhang, Zhenting Chen

“…To solve mixed integer nonlinear programming optimization problems, Q-learning algorithm is introduced. …”
Get full text

Blood Scattering Model for Pulsed Doppler by Piotr KARWAT, Andrzej NOWICKI, Marcin LEWANDOWSKI

“…Generated data are used for optimization and validation of Doppler signals processing algorithms. …”
Get full text

A global object-oriented dynamic network for low-altitude remote sensing object detection by Daoze Tang, Shuyun Tang, Yalin Wang, Shaoyun Guan, Yining Jin

“…This study introduces the Global Object-Oriented Dynamic Network (GOOD-Net) algorithm, comprising three fundamental components: an object-oriented, dynamically adaptive backbone network; a neck network designed to optimize the utilization of global information; and a task-specific processing head augmented for detailed feature refinement. …”
Get full text

Synthesizing Sum and Difference Patterns with Low Complexity Feeding Network by Sharing Element Excitations by Jafar Ramadhan Mohammed

“…Unlike the standard optimization approaches such as genetic algorithm (GA), the described algorithm performs repeatedly deterministic transformations on the initial field until the prescribed requirements are satisfied. …”
Get full text

Distributed Formation Control with Obstacle and Collision Avoidance for Hypersonic Gliding Vehicles Subject to Multiple Constraints by Zhen Zhang, Yifan Luo, Yaohong Qu

“…The actual control input solver adopts a feasible solution process to calculate the actual control signals while dealing with constraints. Finally, extensive numerical simulations are implemented to unveil the proposed algorithm’s performance and superiority.…”
Get full text

Robust sparse smooth principal component analysis for face reconstruction and recognition. by Jing Wang, Xiao Xie, Li Zhang, Jian Li, Hao Cai, Yan Feng

“…Consequently, the proposed RSSPCA algorithm generally outperforms existing algorithms in face reconstruction and recognition. …”
Get full text

IoT intrusion detection method for unbalanced samples by ANTONG P, Wen CHEN, Lifa WU

“…In recent years, network traffic increases exponentially with the iteration of devices, while more and more attacks are launched against various applications.It is significant to identify and classify attacks at the traffic level.At the same time, with the explosion of Internet of Things (IoT) devices in recent years, attacks on IoT devices are also increasing, causing more and more damages.IoT intrusion detection is able to distinguish attack traffic from such a large volume of traffic, secure IoT devices at the traffic level, and stop the attack activity.In view of low detection accuracy of various attacks and sample imbalance at present, a random forest based intrusion detection method (Resample-RF) was proposed, which consisted of three specific methods: optimal sample selection algorithm, feature merging algorithm based on information entropy, and multi-classification greedy transformation algorithm.Aiming at the problem of unbalanced samples in the IoT environment, an optimal sample selection algorithm was proposed to increase the weight of small samples.Aiming at the low efficiency problem of random forest feature splitting, a feature merging method based on information entropy was proposed to improve the running efficiency.Aiming at the low accuracy problem of random forest multi-classification, a multi-classification greedy transformation method was proposed to further improve the accuracy.The method was evaluated on two public datasets.F1 reaches 0.99 on IoT-23 dataset and 1.0 on Kaggle dataset, both of which have good performance.The experimental results show that the proposed model can effectively identify the attack traffic from the massive traffic, better prevent the attack of hackers on the application, protect the IoT devices, and thus protect the related users.…”
Get full text

Efficient multiplication for finite fields of p characteristic by LI Yin 1, CHEN Gong-liang1, LI Jian-hua1

“…Based on residue arithmetic,a new form of polynomial named PAPB in Fp[x] had been constructed.The amount and distribution of such irreducible polynomials had also been investigated.Then,an efficient algorithm for multiplication modulo PAPB had been proposed using residue arithmetic and Chinese remainder theorem.In the end,the result analysis was given.The theoretic analysis and simulation experiment show that for some finite field of medium prime characteristic,the given algorithm only costs O（k1.5） operations in Fp while the multiplication modulo irreducible binomial cost O（k2） operations,which shows a better performance.As a result,the work presents an interesting perspective for optimal extension field and elliptic curve cryptography.…”
Get full text

Analysis of Two-Grid Characteristic Finite Element Methods for Convection-Diffusion Equations by Keyan Wang, Boxia Hu

“…We present an optimal error estimate in Lp-norm for the characteristic finite element method unconditionally, while all previous works require certain time-step restrictions. …”
Get full text