Retrieving Aerosol Optical Depth over Land from Landsat-8 Satellite Images with the Aid of Cloud Shadows by Jingmiao Zhu, Congcong Qiao, Minzheng Duan

“…Based on this assumption, an algorithm for AOD retrieval over land is developed and tested using Landsat-8/9 images containing scattered clouds over Xuzhou, China, and Dalanzadgad, Mongolia. …”
Get full text

Digital twin-assisted multi-mode communication resource management methods for smart buildings by Cheng SHI, Pengju LIU, Zhigang DU, Sunxuan ZHANG, Zhenyu ZHOU, Huifeng BAI, Guoqing HE, Wenwen SUN, Yue MA

“…The multi-mode communication network provides communication support for the collection, transmission, and processing of energy regulation data and the training of energy regulation models for smart buildings.Digital twin can provide state estimation of computing resources and channel characteristics, assist in the multi-mode communication resource optimization management, and improve the training precision of energy regulation models.However, the digital twin-assisted multi-mode communication resource management of smart buildings still face challenges such as large training error of energy regulation model, coupling of multi-timescale resource allocation, and contradictions between training precision improvement of energy regulation model and energy consumption optimization.Aiming at the above challenges, a multi-timescale communication resource management optimization algorithm based on digital twin and empirical matching learning was proposed.The weighted sum of global model loss function and energy consumption was minimized by jointly optimizing the large-timescale gateway selection and small-timescale channel allocation and power control.Simulation results show that the proposed algorithm can improve the performance of weighted sum of global model loss function and energy consumption, ensure the precise energy regulation requirement and promote the low-carbon operation of smart buildings.…”
Get full text

Computationally Efficient Compressed Sensing-Based Method via FG Nyström in Bistatic MIMO Radar with Array Gain-Phase Error Effect by Jurong Hu, Evans Baidoo, Lei Zhan, Ying Tian

“…In this paper, a robust angle estimator for uncorrelated targets that employs a compressed sense (CS) scheme following a fast greedy (FG) computation is proposed to achieve improved computational efficiency and performance for the bistatic MIMO radar with unknown gain-phase errors. The algorithm initially avoids the wholly computation of the received signal by compiling a lower approximation through a greedy Nyström approach. …”
Get full text

An Improved Particle Swarm Optimization-Powered Adaptive Classification and Migration Visualization for Music Style by Xiahan Liu

“…Based on the adaptive particle swarm algorithm and error backpropagation neural network, this paper proposes methods for different styles of music classification and migration visualization. …”
Get full text

Automatic Tracking Method of Basketball Flight Trajectory Based on Data Fusion and Sparse Representation Model by Cuiping Cao, Hai Yu, Yun Liu

“…Data fusion technology and particle filter algorithm are combined to realize automatic tracking of basketball flight path. …”
Get full text

Leader-Following Multiple Unmanned Underwater Vehicles Consensus Control under the Fixed and Switching Topologies with Unmeasurable Disturbances by Zheping Yan, Yi Wu, Yibo Liu, Hongliang Ren, Xue Du

“…Finally, simulation results are shown to demonstrate the effectiveness of the algorithm proposed in the paper.…”
Get full text

Target Tracking in 4D Ultrasound using Localization Networks by Krause Cassandra, Wulff Daniel, Ernst Floris

“…The proposed tracking algorithm is real-time capable with a mean runtime per 3D ultrasound image of 68ms.…”
Get full text

STATE PREDICTION OF WIND TURBINE GENERATOR BASED ON K-CNN AND N-GRU (MT) by CHAI Tong, YUAN YiPing, MA JunYan, FAN PanPan

“…Then, to solve the problem of parameter optimization of the traditional GRU algorithm, the neural network architecture search was used to improve the GRU algorithm, and the N-GRU model was obtained. …”
Get full text

BFV-Blockchainvoting: blockchain-based electronic voting systems with BFV full homomorphic encryption by Yatao YANG, Deli LIU, Peihe LIU, Ping ZENG, Song XIAO

“…Current electronic voting systems mostly relied on central server and the trusted third party, this kind system architecture increases the security risks of voting, and even makes voting fail.In order to solve this issue, an electronic voting system BFV-blockchainvoting that supported BFV homomorphic encryption was proposed, and this system applied the blockchain technology to the electronic voting system to replace the trusted third party.Firstly, an open and transparent bulletin board was used to record the vote information, and an intelligent contract was used to realize the functions of verification and self counting.Secondly, in order to further improve the security and reliability of the voting process, the voter’s registration information was signed by SM2 signature algorithm, the ballot was managed by both parties that can supervise each other, and the counting data was encrypted by the BFV full homomorphic encryption algorithm.Finally, the evaluation of performance shows that it only costs 1.69 ms to complete one ballot in the proposed electronic voting system.This electronic voting scheme based on the BFV full homomorphic encryption and blockchain has better security attributes such as manipulation-resistance, anonymity, verifiability, double-voting resistance, coercion-resistance and resistance to quantum attacks.The scheme is suitable for a variety of voting scenarios and can meet the efficiency requirements in large voting scenarios.…”
Get full text

ASSESSMENT AND ANALYSIS OF DIGITAL TRANSFORMATION OF REGIONAL ECONOMIC SYSTEMS OF THE RUSSIAN FEDERATION: METHODOLOGICAL APPROACHES AND THEIR APPROBATION by M. R. Safiullin, A. A. Abdukaeva, L. A. Elshin

“…The article proposes an algorithm for measuring the level of development of the content elements of the digital economy in the regions of the Russian Federation. …”
Get full text

Cooperative spectrum sensing scheme based on crowd trust and decision-making mechanism by Xiao-mao WANG, Chuan-he HUANG, Yi-long LV, Bin WANG, Xi-ying FAN, Hao ZHOU

“…A distributed consensus-based scheme by simulating the crowd trust and decision-making mechanism was proposed.This scheme firstly predicts the dynamic trust value among sensing users by the previous cooperative process,and then generates the user's relative trust value,and makes the data interaction among the users by using the combination of relative trust value and decision-making mechanism.All users' state can reach a consensus as the credible and iterative data interaction.All users get the final results by the determinant algorithm.This new spectrum sensing scheme utilizes the imbalance of each users' sensing ability in the real environment.Each secondary user can maintain cooperation with others only through the local information exchange with the neighbors.It is quite different from traditional spectrum sensing scheme,such as OR-rule,1-out-of-N rule and ordinary iterative method.Three SSDF attacks were analysed,on the basis of the corresponding anti-attack policy was proposed.Theoretical analysis and simulation results show that the new scheme is better than the existing cooperative spectrum sensing algorithm in accuracy and security.New scheme not only can improve the accuracy of spectrum sensing but also has the strong anti-attack capability.…”
Get full text

Explainable AI for DeepFake Detection by Nazneen Mansoor, Alexander I. Iliev

“…This study introduces a deepfake detection technique that enhances interpretability using the network dissection algorithm. This research consists of two stages: (1) detection of forged images using advanced convolutional neural networks such as ResNet-50, Inception V3, and VGG-16, and (2) applying the network dissection algorithm to understand the models’ internal decision-making processes. …”
Get full text

RESEARCH ON ARRAY-ENHANCED SELF-ADAPTIVE STOCHASTIC RESONANCE BASED ON PARTICLE SWARM OPTIMIZATION by ZHANG YongLiang, LI GuoLin, YIN HongWei

“…Aiming at the disadvantages of traditional method of stochastic resonance（SR）,for example,the SNR of output response is low and the self-adaptive time of parameters is long for single self-adaptive SR,and the parameters are hard to set for array-enhanced SR,a array-enhanced self-adaptive SR based on extremum disturbed and simple particle swarm optimization（tsPSO） algorithm was proposed,which has realized an effective and fast detection of the weak signals under conditions of large parameters under high strong noise background. …”
Get full text

Two-Dimensional Direction-of-Arrivals Estimation Based on One-Dimensional Search Using Rank Deficiency Principle by Feng-Gang Yan, Zhi-Kun Chen, Ming-Jian Sun, Yi Shen, Ming Jin

“…A novel efficient method for two-dimensional (2D) direction-of-arrivals (DOAs) estimation is proposed to reduce the computational complexity of conventional 2D multiple signal classification (2D-MUSIC) algorithm with uniform rectangular arrays (URAs). By introducing two electrical DOAs, the formula of 2D-MUSIC is transformed into a new one-dimensional (1D) quadratic optimal problem. …”
Get full text

Spatial Multiple Description Coding for Scalable Video Streams by Roya Choupani, Stephan Wong, Mehmet Tolun

“…The proposed algorithm addresses the quality degradation due to low-pass filtering effect of interpolation methods. …”
Get full text

Two-Round Diagnosability Measures for Multiprocessor Systems by Jiarong Liang, Qian Zhang, Changzhen Li

“…For Qn, we prove that the proposed algorithm is the time complexity of On2n.…”
Get full text

Optimization of Lateral Collision Risk of Aircraft Based on the Skid-Slip Event Model by Hao Liu, Daiwu Zhu, Xiaofan Xie, Jiuhao Chen, Xiaokang Liu

“…Based on the traditional event collision risk assessment model, the collision module is upgraded to an ellipsoid according to the performance of aircraft, integrating the boundary curvature optimization characteristics of the TSRRT (task-space rapidly-exploring random trees) algorithm. An aircraft event lateral conflict resolution model based on the TSRRT algorithm is proposed. …”
Get full text

Evaluating Human Factors in TFM Sizing Accuracy: Statistical Findings from a Round-Robin Programme (Part 2) by Mariana Burrowes M. Guimarães, Edward Ginzel, Gabriela Ribeiro Pereira, Cesar Giron Camerini, Cesar Giron Camerini

“…Their task was to scan the welds using an acquisition format compatible with a TFM algorithm and analyse the data using the TFM algorithm of their choice. …”
Get full text

Maximizing Information Dissemination in Social Network via a Fast Local Search by Lijia Tian, Xingjian Ji, Yupeng Zhou

“…When the algorithm stalls in local optima, a random walk operator reorients the search towards unexplored regions. …”
Get full text

Online Incremental Learning for High Bandwidth Network Traffic Classification by H. R. Loo, S. B. Joseph, M. N. Marsono

“…This paper proposes an algorithm for online network traffic classification based on the concept of incremental k-means clustering to continuously learn from both labeled and unlabeled flow instances. …”
Get full text