共查询到20条相似文献，搜索用时 15 毫秒
1.
A quasi-classical theory of rough surface effect on diamagnetic response is developed for normal-superconducting proximity contact systems with arbitrary concentration of impurities. We calculate the diamagnetic current and the screening length of the normal layer taking into account the surface roughness by use of the thin dirty layer model. We propose an analytic treatment of the thin dirty layer model. The surface roughness has a considerable effect in the clean limit and also when the mean free path is comparable with the normal layer width. In dirty systems, while the diamagnetic current is significantly reduced near the rough surface, the screening fraction is not so much affected by the surface roughness in the whole temperature range. 相似文献
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Hashing technology has the advantages of reducing data storage and improving the efficiency of the learning system, making it more and more widely used in image retrieval. Multi-view data describes image information more comprehensively than traditional methods using a single-view. How to use hashing to combine multi-view data for image retrieval is still a challenge. In this paper, a multi-view fusion hashing method based on RKCCA (Random Kernel Canonical Correlation Analysis) is proposed. In order to describe image content more accurately, we use deep learning dense convolutional network feature DenseNet to construct multi-view by combining GIST feature or BoW_SIFT (Bag-of-Words model+SIFT feature) feature. This algorithm uses RKCCA method to fuse multi-view features to construct association features and apply them to image retrieval. The algorithm generates binary hash code with minimal distortion error by designing quantization regularization terms. A large number of experiments on benchmark datasets show that this method is superior to other multi-view hashing methods. 相似文献
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Chen Zhang Jieren Cheng Xiangyan Tang Victor S. Sheng Zhe Dong Junqi Li 《计算机、材料和连续体（英文）》2019,61(2):657-675
Distributed denial of service (DDoS) attacks launch more and more frequently and are more destructive. Feature representation as an important part of DDoS defense technology directly affects the efficiency of defense. Most DDoS feature extraction methods cannot fully utilize the information of the original data, resulting in the extracted features losing useful features. In this paper, a DDoS feature representation method based on deep belief network (DBN) is proposed. We quantify the original data by the size of the network flows, the distribution of IP addresses and ports, and the diversity of packet sizes of different protocols and train the DBN in an unsupervised manner by these quantified values. Two feedforward neural networks (FFNN) are initialized by the trained deep belief network, and one of the feedforward neural networks continues to be trained in a supervised manner. The canonical correlation analysis (CCA) method is used to fuse the features extracted by two feedforward neural networks per layer. Experiments show that compared with other methods, the proposed method can extract better features. 相似文献
4.
《Quality Engineering》2012,24(4):495-507
Many quality programs prescribe a measurement system analysis (MSA) to be performed on the key quality characteristics. This guarantees the reliability of the acquired data, which serve as the basis for drawing conclusions with respect to the behavior of the key quality characteristics. When dealing with continuous characteristics, the Gauge R&R is regarded as the statistical technique in MSA. For binary characteristics, no such universally accepted equivalent is available. We discuss methods that could serve as an MSA for binary data. We argue that a latent class model is the most promising candidate. 相似文献
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In process industries, the characteristics of industrial activities focus on the integrality and continuity of production process, which can contribute to excavating the appropriate features for industrial anomaly detection. From this perspective, this paper proposes a novel state-based control feature extraction approach, which regards the finite control operations as different states. Furthermore, the procedure of state transition can adequately express the change of successive control operations, and the statistical information between different states can be used to calculate the feature values. Additionally, OCSVM (One Class Support Vector Machine) and BPNN (BP Neural Network), which are optimized by PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) respectively, are introduced as alternative detection engines to match with our feature extraction approach. All experimental results clearly show that the proposed feature extraction approach can effectively coordinate with the optimized classification algorithms, and the optimized GA-BPNN classifier is suggested as a more applicable detection engine by comparing its average detection accuracies with the ones of PSOOCSVM classifier. 相似文献
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This study was conducted to enable prompt classification of malware, which was becoming increasingly sophisticated. To do this, we analyzed the important features of malware and the relative importance of selected features according to a learning model to assess how those important features were identified. Initially, the analysis features were extracted using Cuckoo Sandbox, an open-source malware analysis tool, then thefeatures were divided into five categories using the extracted information. The 804 extracted features were reduced by 70% after selecting only the most suitable ones for malware classification using a learning model-based feature selection method called the recursive feature elimination. Next, these important features were analyzed. The level of contribution from each one was assessed by the Random Forest classifier method. The results showed that System call features were mostly allocated. At the end, it was possible to accurately identify the malware type using only 36 to 76 features for each of the four types of malware with the most analysis samples available. These were the Trojan, Adware, Downloader, and Backdoor malware. 相似文献
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因为传统的连续弯曲辊式矫直理论创建在单一金属反复连续弯曲变形的基础上,所以将该理论应用于双金属复合板连续弯曲矫直时,精度不高且无法保证双金属复合板的矫后平直度。为完善板材矫直力论,分析了双金属复合板矫直弯曲变形时的特点,提出了分层算法,并将模型计算数据与矫直实验数据进行了对比。结果表明:提出的方法可以在不同金属变形层上采用不同的计算方法和材料模型,比较适应于求解双金属复合板的辊式矫直问题;模型计算矫直力误差不大于5.73%。所得结论表明基于分层算法的数学模型在计算双金属复合板时具有良好的效果。 相似文献
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Abdulbasit A. Darem 《计算机、材料和连续体（英文）》2022,72(1):461-479
Malicious software (malware) is one of the main cyber threats that organizations and Internet users are currently facing. Malware is a software code developed by cybercriminals for damage purposes, such as corrupting the system and data as well as stealing sensitive data. The damage caused by malware is substantially increasing every day. There is a need to detect malware efficiently and automatically and remove threats quickly from the systems. Although there are various approaches to tackle malware problems, their prevalence and stealthiness necessitate an effective method for the detection and prevention of malware attacks. The deep learning-based approach is recently gaining attention as a suitable method that effectively detects malware. In this paper, a novel approach based on deep learning for detecting malware proposed. Furthermore, the proposed approach deploys novel feature selection, feature co-relation, and feature representations to significantly reduce the feature space. The proposed approach has been evaluated using a Microsoft prediction dataset with samples of 21,736 malware composed of 9 malware families. It achieved 96.01% accuracy and outperformed the existing techniques of malware detection. 相似文献
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在特定区域环境中,提出了一种基于NLMS自适应滤波的实时声音信号检测识别方法。该方法NLMS对滤波后的误差信号进行双门限检测,并以通过检测的疑似信号所持续的时间,作为其是否为目标信号的评判指标。通过对待处理声音文件的测试,该方法可以有效地去除非期望信号,保留目标信号,从而实现对目标信号的准确检测。 相似文献
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对称结构模态振型的Zernike矩描述方法 总被引：2，自引：0，他引：2
讨论了利用Zernike矩描述对称结构模态振型的方法,通过对结构的模态振型数据进行Zernike矩变换,将其分解成一系列Zernike矩的线性组合,而每一个Zernike矩反映模态振型的一部分形状特征.不同特征矩的线性组合,可以代表各阶模态的振型.在此基础上进一步提出了确定Zernike多项式最高阶数的方法,并讨论了Zernike矩描述对称结构模态振型的方法及其去噪声的能力.通过对简单圆盘结构的仿真实例研究,验证了应用Zernike矩描述对称结构模态振型的优越性.结果表明;利用Zernike矩描述对称结构的模态振型可以更有效地描述对称结构的模态,包括重模态,同时还能有效地消除测试数据中噪声的影响,对进一步实现对称结构有限元模型修正和模型确认具有重要的应用价值. 相似文献
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J. Adler 《Journal of Engineering Mathematics》2000,38(4):427-438
The steady propagation of a thin smouldering front parallel to the faces of a composite reactive slab has been considered. The slab consists of a double layer of solid with differing densities. As the smouldering front progresses into the solid it leaves behind an inert porous medium through which oxidizer is able to diffuse to the front. It is assumed that the reactive solid is sufficiently dense for no oxidizer to be present. The oxidizer concentration on one face of the slab is specified, the other being impervious to the transport of reactants. Dimensionless equations and boundary conditions are obtained for the concentration of oxidizer in the porous medium. These are solved to first order by use of a complex-variable method and a hodograph transformation giving the shape of the smouldering front for various parameter combinations. The analysis is extended to the case where the layers are of unequal thickness. Simple expressions for the shape of the front and the oxidizer concentration are obtained when one layer thickness is large. The model here considered is a first step in a more comprehensive analysis of smouldering in a non-uniform medium. 相似文献
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在干球温度的双正态分布模型的基础上,分析了冬季和夏季气象计算参数的关联特性,并阐述了其在建筑气候分区的应用;根据具体气象计算参数计算出的冬夏参数比,验证了其在建筑气候分区应用中的关联特性。 相似文献
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A new paradigm of VANET has emerged in recent years: Internet of Vehicles (IoV). These networks are formed on the roads and streets between travellers who have relationships, interactions and common social interests. Users of these networks exchange information of common interest, for example, traffic jams and dangers on the way. They can also exchange files such as multimedia files. IoV is considered as part of the Internet of Things (IoT) where objects are vehicles, which can create a multitude of services dedicated to the intelligent transportation system. The interest is to permit to all connected vehicles to communicate with each other and/or with a central server, through other vehicles. Vehicle to Vehicle (V2V) communication is the main component, because the services encompassed in the IoV are based on the vehicles in question, such as transmitter, relay and receiver. This work is focusing on designing and developing a Quality of Service (QoS) routing scheme dedicated to IoV networks. Especially, we aim to improve the Greedy Traffic Aware Routing (GyTAR) protocol to support QoS in IoV networks. To evaluate the proposed approach in terms of QoS in the context of IoV networks, the performance metrics such as average end-to-end delay and packet delivery ratio are taken into consideration to analyse the network situation. 相似文献
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Jieren Cheng Yifu Liu Xiangyan Tang Victor S. Sheng Mengyang Li Junqi Li 《计算机、材料和连续体（英文）》2020,62(3):1317-1333
Distributed Denial-of-Service (DDoS) has caused great damage to the network in the big data environment. Existing methods are characterized by low computational efficiency, high false alarm rate and high false alarm rate. In this paper, we propose a DDoS attack detection method based on network flow grayscale matrix feature via multiscale convolutional neural network (CNN). According to the different characteristics of the attack flow and the normal flow in the IP protocol, the seven-tuple is defined to describe the network flow characteristics and converted into a grayscale feature by binary. Based on the network flow grayscale matrix feature (GMF), the convolution kernel of different spatial scales is used to improve the accuracy of feature segmentation, global features and local features of the network flow are extracted. A DDoS attack classifier based on multi-scale convolution neural network is constructed. Experiments show that compared with correlation methods, this method can improve the robustness of the classifier, reduce the false alarm rate and the missing alarm rate. 相似文献
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制备双金属电极的绿光微腔器件,其结构为Al(15 nm)/MoO3(4 nm)/2T-NATA(10 nm)/NPB(15 nm)/NPB: C545T(x%, 20 nm)/Alq3:C545T(4%, 20 nm)/Bphen(35 nm)/LiF(1 nm)/Al(200 nm),其中x为掺杂浓度。实验表明：当掺杂浓度为3%时,器件有最好的光电性能,记为器件B1。为分析微腔效应,制备基于ITO的参考器件B2。B1和B2色坐标分别为(0.289, 0.620)和(0.317, 0.557),所以微腔器件的发光颜色更绿。在100 mA/cm2时,器件B1和B2的亮度分别为5076 cd/m2和4818 cd/m2,且最大亮度为9277.7 cd/m2,10440 cd/m2;在100 mA/cm2时,器件B1和B2的发光效率为6.0 cd/A和5.61 cd/A,且最大发光效率分别为8.6 cd/A和7.97 cd/A。与参考器件相比,绿光微腔器件具有更好的发光效率和颜色纯度,其主要归因于微腔效应。 相似文献
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Real-time detection of driver fatigue status is of great significance for road traffic safety. In this paper, a proposed novel driver fatigue detection method is able to detect the driver’s fatigue status around the clock. The driver’s face images were captured by a camera with a colored lens and an infrared lens mounted above the dashboard. The landmarks of the driver’s face were labeled and the eye-area wassegmented. By calculating the aspect ratios of the eyes, the duration of eye closure, frequency of blinks and PERCLOS of both colored and infrared, fatigue can be detected. Based on the change of light intensity detected by a photosensitive device, the weight matrix of the colored features and the infrared features was adjusted adaptively to reduce the impact of lighting on fatigue detection. Video samples of the driver’s face were recorded in the test vehicle. After training the classification model, the results showed that our method has high accuracy on driver fatigue detection in both daytime and nighttime. 相似文献