最新刊期
卷 49 ， 期 3 ， 2021
- 摘要：With the upgrade of the information system confrontation, the cyberspace has developed to a complicated network electricity environment,composed of kinds of interconnected information platforms and control networks. Its security threats has been more complicated. As the security base of the cyberspace, the fault disturbance to the implementation of the cipher, caused by the environment and the malicious attacker, can not be avoided, so the security problem of the cipher will be induced. In this paper, based on the voltage glitch fault injection, the fault generation and the security disturbance mechanism of the block cipher chip, is analyzed. The fluctuant model, used for characterizing the fault propagation probability of the cipher chip, is constructed. Applying the indistinguishable theory, and the statistical distribution of the propagation probability to the active bytes, the metric model of the actual physical security for the block cipher chip, is proposed. It is experimented that, the relevance, between the actual fault propagation probability and the distinguish advantage, can be reflected by the model, so the security of the block cipher, in the scene of the fault attack, can be analyzed objectively.关键词：voltage glitch;fault injection;fault disturbance;block cipher;security evaluation;information leakage56|25|3更新时间：2025-12-08
- 摘要：In crowdsourcing learning, a certain level of label noise still exists in integrated labels obtained by employing ground truth inference algorithms. Inspired by the tri-training idea, this paper proposes a tri-training-based label noise correction (TTLNC) algorithm for crowdsourcing. TTLNC at first employs a filter to get a clean set and a noisy set and then trains three different classifiers from the bagged clean set. Furthermore, each instance from the noisy set is relabeled by these classifiers and assigned to the corresponding training set according to the designed instance assignment strategy. Finally, three classifiers are retrained on three new training sets and are used to relabel all instances. Experimental results on both simulated benchmark data and real-world crowdsourced data show that TTLNC significantly outperforms other four state-of-the-art noise correction algorithms in team of the noise ratio and the model quality.关键词：crowdsourcing learning;tri-training;integrated labels;label noise;noise correction;noise filtering20|18|0更新时间：2025-12-08
- 摘要：The traditional iterative optimized based video compression sensing algorithms are limited by long running time and low adaptability of parameters,resulting in low practicability and generalization. Taking advantage of the powerful computing power, fast speed and learnable parameters of neural networks, this paper first proposes a group sparse representation network (VGSR-Net), which maps the image block group to a higher-dimensional sparse domain through convolution, and uses a learnable threshold to denoise and extract inter-frame correlation. On this basis, a two-stage recursive enhance reconstruction network (2sRER-VGSR-Net) is proposed. First, we perform VGSR-Net to preliminarily enhance the initial reconstruction and then introduce STMC-Net as motion estimation, and the compensated frames are fed into the residual reconstruction network to further extract the missing detail and enhance the current frame. The second stage of reconstruction adopts a hybrid recursive structure with the aim of making full use of the existing better quality reconstructed frames. The simulation results show that the proposed algorithm improves the PSNR (Reak Signal to Noise Ratio) by 1.99dB compared with the existing state-of-art traditional compressed video sensing reconstruction algorithms SSIM-InterF-GSR, while improves the PSNR by 4.60dB with the comparation of the network-based algorithm CSVideoNet.关键词：compressed video sensing;deep learning;group based sparse representation;hybrid recursive network;motion estimation;enhancement reconstruction9|12|4更新时间：2025-12-08
- 摘要：The existing artificial intelligent (AI) computing platform represented by x86+GPU, limited by power consumption, dimension, bandwidth, environmental adaptability, and other factors, cannot be well adapted to the things and edge intelligent computing scenarios. We proposed an embedded AI computing system based on ARM (Advanced RISC Machine) + DLP (Deep Learning Processor) + SRIO (Serial RapidIO), and elaborated the design methods and technical advantages. In study, three aspects of the system were dissertated: AI computing performance, power efficiency, and IO bandwidth, and the function and performance of the system were verified by experiments. The results show that the peak performance of the embedded AI computing system based on ARM+DLP+SRIO is up to 114.9TOPS, the energy efficiency is up to 1.03TFLOPS/W, and the IO bandwidth is up to 20Gbps. In the field of AI computing systems, its energy efficiency is better than other similar boards or systems in China, and its embedded environmental adaptability is better than that of traditional desktops and servers, so it can provide a general hardware acceleration platform for AI computing tasks in things and edge computing scenarios.关键词：artificial intelligent;deep learning processor;embedded AI computing system;serial RapidIO;power efficiency19|10|1更新时间：2025-12-08
- 摘要：Angle of arrival based positioning technology is commonly used in the field of passive surveillance. However, in a multisensor-multitarget situation, it is difficult to determine the association between measurements directly, and an effective data association is required before target positioning. Aimed to solve the problem, this paper presents a new data association approach of angel of arrival (AOA) based on multidirection-ordered association. Firstly, the approach designs a cost function to describe the possibility of association between measurements, and uses the Jacobian to estimate the variance of components of error vector. Secondly, to compute the association results, the assignment and optimization ideas are used to compute the directions of partial association and the order of association between sensors, respectively. The simulation results show that the approach is effective for the association of measurements of intensive targets and random targets.关键词：angle of arrival(AOA );data association;multidirection-ordered;passive surveillance26|14|0更新时间：2025-12-08
- 摘要：In the bistatic configuration, the micro-motion features can be represented by three types of scattering centers, the localized scattering center located at the target tip, and the two types of sliding scattering centers sliding along the target bottom edge and on the target side face. In this paper, the micro-Doppler of three types of scattering centers is firstly represented by a unified parametric model. Then, the sliding coefficient is defined by two parameters of the parametric model, and it is applied to discriminate scattering center types. At last, electromagnetic simulation results demonstrate that the micro-Doppler parametric model is precise, and the presented sliding coefficient is a reliable feature to recognize the cone-shaped targets.关键词：bistatic radar;cone-shaped targets;scattering center;micro-motion5|6|5更新时间：2025-12-08
- 摘要：In order to solve the problem that the multi-objective workflow scheduling is difficult to optimize in the cloud computing environment, this paper proposes a differential flower pollination algorithm for the multi-objective workflow scheduling. The algorithm models the tasks and virtual machines in the workflow into pollen and models the complete scheduling sequence into flowers. Then it adopts a discrete flower pollination process according to the partial order relationship of the task. The simulation results show that compared with the algorithms NSGA-Ⅱ and MEOA/D, the algorithm can have higher resource utilization under the limited deadline and budget.关键词：workflow scheduling;flower pollination algorithm;multi-objective optimization;cloud computing3|7|1更新时间：2025-12-08
- 摘要：To satisfy the requirement on high-precision differentiation of narrow-band signals and low delay of the differentiator, this paper presents a design method for low-delay finite impulse response flat digital differentiators. The method minimizes the maximum magnitude error subject to flatness and phase-error constraints on the differentiator. By eliminating the flatness constraint with the general solution of linear equations, we ensure that the differentiator has desired flatness degrees. By reweighting the phase error with group-delay error, the method reduces the passband group-delay error of the differentiator. Design examples and comparisons with literature methods show the effectiveness and superiority of the proposed method.关键词：digital differentiator;narrow-band filter;maximally flat filter;Doppler filter;low delay;filter design3|5|0更新时间：2025-12-08
- 摘要：As the development direction of future network architectures, Software Defined Networks can efficiently set routing schemes by separating the data plane and the control plane. In the process of optimizing a routing scheme, it is the key to accurately predict the network performance under a given routing scheme. This paper uses graph neural networks to model the relationship between physical links and routing scheme paths, so that the model can predict various end-to-end performance indicators (such as delay and jitter) in the network under a given routing scheme and network traffic. This paper uses OMNeT ++ to generate datasets. The experimental results show that the model proposed in this paper can accurately predict end-to-end performance indicators such as delay and jitter. The average relative error of the estimate does not exceed 4.1%. The experiment also compares the end-to-end performance of the traditional shortest path routing algorithm with the optimal routing scheme based on the prediction model proposed in this paper. Compared to the traditional shortest path routing algorithm, the average delay and average jitter are reduced by 19.8% and 33.52%, and the maximum delay and maximum jitter are reduced by 36.18% and 35.45%.关键词：software development network(SDN);end-to-end performance prediction;graph neural network;SDN routing optimization6|14|10更新时间：2025-12-08
- 摘要：The new generation enhanced planar gate soft through (Soft Punch Through+, SPT+) IGBT adopts the cathode-side carrier concentration enhancement technology, which reduces the on-state loss. Existing simulation models are mostly based on typical Punch Through (PT) IGBTs, which cannot accurately describe the on-state characteristics of SPT+IGBT. Based on the existing PT model and combining the structural and operating characteristics of SPT+IGBTs, this paper divides the base region into two parts, PIN and PNP regions, and optimizes the cathode-side carrier distribution. An improved steady state model for SPT+IGBT is proposed. The accuracy of the improved model is verified by comparing the simulated and measured waveforms of the old and new models.关键词：insulated gate bipolar transistor;SPT+;carrier storage layer;on-state analytical model4|15|1更新时间：2025-12-08
- 摘要：Aiming at the problem that the existing adaptive prediction methods of remaining useful lifetime (RUL) for the airborne electronic equipment fail to comprehensively consider the hidden degradation modeling and online drift coefficients updating in the condition of newly researched and small sample, an adaptive prediction method for the airborne electronic equipment’s RUL based on the EM-EKF algorithm and hidden degradation model with proportion relationship is proposed. Firstly, based on the nonlinear Wiener process, a hidden degradation model with the proportion relationship is constructed. Next, the degradation state equation of the equipment is established based on the drift coefficient update mechanism, and the EKF algorithm is used to update the degradation status and drift coefficient. And then, the EM-EKF algorithm is used to adaptively estimate the parameters of the degradation model. Finally, based on the full probability formula, the probability density function (PDF) of RUL is derived. By analyzing the measured data of a single micromechanical gyroscope, it is verified that the proposed method has better model fitting and prediction accuracy.关键词：remaining useful lifetime prediction;Wiener process;hidden degradation model;proportion relationship;EM-EKF algorithm3|15|3更新时间：2025-12-08
- 摘要：By studying the existing methods for countering frequency-shift jamming, this paper comes to the conclusion that the applicability of jamming discrimination method based on echo matching output center-frequency is limited and slope varying LFM (SV-LFM), a radar transmitting waveform, can suppress the jamming to some extent, if the agile way is designed reasonable. Meanwhile, a jamming discrimination method jointing coherent integration and two dimensional fractional Fourier transform (2D-FRFT) is proposed on the background of LFM pulse Doppler radar countering self-screening frequency-shift jamming. According to the peak value difference of echo signal under the two processing modes, true and false targets are identified by comparing with a setting threshold. Simulation results show that the conclusion is correct and the proposed method works effectively.关键词：frequency-shift jamming;coherent integration;2D-FRFT;jamming discrimination3|19|4更新时间：2025-12-08
- 摘要：Wireless routers in Wireless Network on Chip confronts more severe congestion problem, so balancing wired/wireless loading has become research focus in WiNoC recently. We propose a priority-based switch arbitration scheme, in which data packets more suitable for transmission through wireless channels are routed to wireless routers; We propose a CARA (congestion-aware routing algorithm) combined with PbSA, which efficiently balance wired/wireless loading and simultaneously avoid deadlock, improving data routing efficiency. Besides, we propose a new virtual channel partition method, which decreases hardware complex for implementing PbSA, and mitigates the adverse effect caused by wireless router congestion. Evaluation shows that the scheme we proposed achieve fine data flow adaptivity with small area and energy overhead, so to improve network performance and routing efficiency under low or high injection rate.关键词：WiNoC;congestion avoidance;switch arbitration;routing algorithm;virtual channel3|17|0更新时间：2025-12-08
- 摘要：With the development of the research on Moving Target Defense (MTD) technique, how to effectively select the optimal strategy of moving target defense has become an urgent issue in the current research. To solve this problem, we propose a MTD optimal strategy selection method based on multi-stage Markov signaling game model. Firstly, combined with the actual attack-defense process, we construct an attack chain model that attackers need to build to carry out the attack. Secondly, due to the random jump between states, we combine multi-stage signaling with Markov Decision Process (MDP) to construct the corresponding MTD model. Meanwhile, we adopt Logistic mapping to characterize the stochastic interference factors that may cause the distortion of the probability updating in the attack-defense process. Additionally, on the basis of formally modeling, we design an objective function with discounted total payoff. Besides, we give a solution method for multi-stage signaling game equilibrium and design an optimal defense strategy selection algorithm for MTD. Finally, the simulation demonstrates the effectiveness and feasibility of the proposed model and method.关键词：moving target defense;Markov decision;multi-stage signaling game;optimal strategy selection;logistic mapping5|11|7更新时间：2025-12-08
- 摘要：A novel calibration method is proposed for active vision systems. Projector projects colored concentric circles to a calibration plane, on which an array of concentric circles is printed. The centers of the circles in image frame are identified with geometry constraints, with which the homographies between the calibration plane, image plane and projector plane are estimated. The method uses color information to separate the image of projected circles and that of the circle patterns on calibration plane, which reduces the number of required images and simplifies the calibration procedure. To avoid manual intervention, cross-ratio invariance is used to match concentric circles automatically. Experimental results prove that the algorithm is simple and efficient.关键词：calibration;active vision system;projector;structured light;concentric circle;3D reconstruction3|5|1更新时间：2025-12-08
- 摘要：The traditional multi-target threat assessment methods are usually two-way decisions, only can obtain the threat ranking of targets, need to subjectively determine the threat level and select the number of combat targets, which is not suitable for the complex dynamic mission environment. This paper proposes a multi-target threat assessment method based on VIKOR and three-way decisions under intuitionistic fuzzy information. Firstly, the dynamic intuitionistic fuzzy threat information is aggregated and attribute weights are obtained. Then, the conditional probability of targets for decision making is obtained by VIKOR method. Finally, the loss function matrices of targets under each attribute are constructed by attribute information, the comprehensive loss function matrix is obtained after aggregation and the comprehensive thresholds and decision rules are obtained. The case studies show that the proposed method can effectively deal with the dynamic uncertain situation information, transform the ranking results of two-way decisions into classification results of three-way decisions, and can objectively select the combat targets via situation information.关键词：threat assessment;three-way decisions;intuitionistic fuzzy information;VIKOR;conditional probability;loss function4|5|4更新时间：2025-12-08
- 摘要：Aiming at the problem of low tracking accuracy and even tracking failure caused by fast motion or occlusion of human targets by small mobile robots, a foot motion model was established to predict the position information of feet, and the target detection region of kernel correlation filter (KCF) was obtained. In this paper, a motion model guided adaptive kernel correlation filtering algorithm is proposed by combining with the output response peak neighborhood correlation detection. Foot tracking experiments were carried out on seven groups of videos under different scenarios. The results show that the average tracking accuracy of the adaptive response KCF algorithm guided by the motion model is the highest, and the tracking precision rate of the algorithm reaches 86% in the case of short-term occlusion, which is significantly higher than that of the adaptive response KCF, BACF and SAMF algorithm. Finally, the proposed algorithm is applied to the target tracking test of a Turtlebot robot under the ROS (Robot Operating System), which successfully overcomes the influence of occlusion on feet tracking, and verifies that the proposed algorithm has strong robustness and real-time performance.关键词：target tracking;motion model;kernel correlation filter;adaptive response;occlusion detection;ROS3|3|5更新时间：2025-12-08
- 摘要：In order to fully utilize the bandwidth of multi-paths of the datacenter network (DCN), existing studies mostly adopt the congestion-aware load-balancing scheme, which forwards traffic along the optimal path after dynamically obtaining global congestion information. However, these works do not consider the non-uniform distribution of flow size and are difficult to strike a balance between the routing cost and the forwarding efficiency. This paper proposes ULFC, a utilization-aware load-balancing mechanism based on flow classification. By analyzing the characteristics of traffic, ULFC classifies the flows based on their sizes and assigns paths to them using different strategies, realizing the best matching between the characteristics of traffic and the advantages of the routing method. We evaluate ULFC with simulation and the results show that it outperforms the existing schemes in average flow-completion time (1.3~1.6×), while the routing cost has been reduced by more than 50%.关键词：datacenter network;load balancing;programmable data plane;flow classification;programming protocol-independent packet processors (P4)30|16|6更新时间：2025-12-08
- 摘要：The existing deinterleaving algorithms have some problems such as difficulty in sorting complex modulation signals, high false alarm or false dismissal rate, poor performance on low repetition frequency signals, and poor real-time performance. In order to solve the above problems, this paper proposes a real-time single pulse signal sorting method based on multi-stations time difference of arrival (TDOA) and multi-parameters information. Firstly, the time difference window is introduced to make rough pairing of pulse signals received by multi-stations to obtain multiple "pulse pair" sequences which may be correctly paired. Then, the "pulse pair" is accurately matched by intra-pulse parameters to obtain the true "pulse pair". Then, the time difference corresponding to the "pulse pair" is calculated and the "time difference pair" sequences are obtained. Finally, within the error tolerance, according to the invariance of time difference, the single pulse signal is sorted in real-time. The simulation results show that compared with the existing algorithms, the algorithm can effectively sort complex inter-pulse or intra-pulse modulated signals and low repetitive frequency signals, with extremely low false alarm, false dismissal rate and high correct sorting rate. At the same time, it is real-time.关键词：electronic reconnaissance;complex system radar;single pulse;multi-parameters information;pairs of time difference of arrival;pulse sorting and pairing20|17|7更新时间：2025-12-08
- 摘要：In order to overcome the large consumption problem of unmanned aerial vehicle (UAV) in the process of data transmission, we first establish the model of transmission energy consumption of UAV, then the model is treated approximately by applying the technology of discrete linear state-space approximation and linearization. Finally, we proposed a CCCP (concave-convex procedure) based algorithm. The numerical simulation results show that the proposed algorithm can quickly converge and can achieve excellent results.关键词：UAV;transmission energy consumption;discrete linear state-space approximation;linearization;CCCP(concave-convex procedure)30|14|0更新时间：2025-12-08
- 摘要：To solve the problem that the global search ability and local search ability of traditional multi-objective evolutionary algorithm cannot be effectively balanced when solving the Pareto solution set, an adaptive cellular differential evolutionary algorithm based on multi-neighborhood structure is proposed. Based on the characteristics of the traditional cellular differential evolutionary algorithm, the improved algorithm uses a richer multi-neighbor structure to replace the original single neighbor structure, and the neighbor structure is adjusted reasonably according to the performance of the corresponding individual. At the same time, in the face of the complex requirements in the whole evolution process, the algorithm defines a mutation strategy with periodic variation to realize the adaptive adjustment in different evolution stages. Finally, the DTLZ series of test functions are used to test the performance of the algorithm. Compared with four classical multi-objective optimization algorithms, it is proved that the improved algorithm has better convergence performance and diversity of solution set.关键词：multi-objective optimization;multi-neighborhood structure;random disturbance;adaptive mutation;cellular automata;evolutionary strategy18|28|0更新时间：2025-12-08
- 摘要：Traditional ransomware dynamic detection methods need to collect software behaviors for a long time, which is difficult to meet the need for timely detection of ransomware. From the perspective of the timely detection of ransomware, this article proposes a concept named "Critical Time Periods for Ransomware Detection (CTP)", and proposes an early ransomware detection method based on short application programming interface (API) sequence (REDMS) to fit the requirement of CTP. REDMS takes the short API sequences that are obtained by software running during the CTP as the analysis object, and calculates these short API sequences through the n-gram model and the term frequency-inverse document frequency algorithm to generate the feature vectors, and then uses a machine-learning algorithm to build a detection model for detecting ransomware. The experimental results show that when the first 7 seconds of API collection period and random forest algorithm are used, REDMS achieves 98.2% and 96.7% accuracy respectively for detecting the known and unknown ransomware samples.关键词：ransomware;early detection;machine learning;API(application programming interface)18|12|3更新时间：2025-12-08
- 摘要：Scene segmentation has always been a key and complicated problem in machine learning. In order to understand the scene and recognize the objects more accurately, this paper adopts human attention mechanism, takes the category semantic information into consideration and merges it into the image feature learning. The Focus+Context semantic representation is proposed, where the context describes the relationship between the focus and different objects in the scene, and the focus shared among the same category are composed of similar clusters. The probabilistic topic model is used to compute the local features as well as their semantic information. The experimental results show that the Focus+Context method increases the recognition rate of the scene objects, and specially, the proposed method, in a local and global understanding way, can simplify the scene recognition greatly under a small sample size.关键词：scene segmentation;Focus+Context;semantic representation;topic model101|15|4更新时间：2025-12-08
- 摘要：With enough labeled data lacking in the target domain, it works well for transfer learning to use the labeled data of the related source domain and help improve the learning performance of the target domain. However, the data of these two domains usually do not satisfy the independently identically distribution, which easily leads to the problem of "negative transfer". Tr-SLDA (Transfer SLDA), a novel transfer topic model based on supervised topic model (Supervised LDA, SLDA) is proposed, which shares topic knowledge by integrating transfer learning. A new Tr-SLDA-Gibbs sampling method is proposed, under the constraints of category labels, different sampling strategies are adopted for words in the documents of different domains without specifying the number of topics. The source domain and target domain share the potential topic space, Tr-SLDA can effectively solve the problem of "negative transfer" by discovering the semantic correlation between the potential shared topics and categories of different domains. The Tr-SLDA-TC (Tr-SLDA-Text Categorization) text classification method is proposed based on the Tr-SLDA model. The comprehensive experiments show that the proposed method can effectively improve the performance of the classification by utilizing the knowledge from the source domain.关键词：text categorization;topic model;Gibbs sampling;transfer learning;negative transfer3|19|1更新时间：2025-12-08
- 摘要：This paper proposes an improved intrusive generalized polynomial chaos expansion (gPCE) method for uncertainty quantification (UQ) in ground penetrating radar (GPR) modeling. The uncertainty in simulation results induced by the uncertain parameters of dispersive and lossy soil is quantified with the auxiliary differential equation (ADE) finite-difference time-domain (FDTD) method combined with gPCE. To avoid the curse of dimensionality in modeling complex systems, the combination of uncertainties is incorporated into the new method to evaluate the interval of the uncertainty of the output. The results from the new method are compared against traditional UQ method Monte Carlo method (MCM). The new method shows its considerable advantage in the computational expense and speed.关键词：ground penetrating radar;dispersive and lossy soil;uncertainty analysis3|19|0更新时间：2025-12-08
- 摘要：The over-reliance on expert experience and model preset errors in traditional precipitation particle classification algorithms are discussed. This paper proposes a dual-polarization hydrometeor classification (HC) method based on discrete attribute Bayesian NeTwork (BNT). Firstly, the value of polarization parameters obtained by the dual-polarization meteorological radar is discretized to generate a discretization standard, and the training data set is made according to the discretization standard. Then the training data set is used to learn the structure of the Bayesian network and the conditional probability table matching the structure of the Bayesian network. At last, additional information is added to calculate the prior probability of each precipitation particle class, and the Bayesian network classifier is composed of Bayesian network structure and conditional probability table. The trained Bayesian network classifier classifies the precipitation particles according to the maximum posterior probability criterion and compares the evaluation results with the fuzzy logic algorithm. Experiments show that this method can effectively distinguish different precipitation particles.关键词：dual polarization radar;hydrometeor classification;Bayesian networks;Bayesian classification;uncertain knowledge;discretization;BNT(Bayesian NeTwork )14|14|2更新时间：2025-12-08
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