scholarly journals Network Attack Characteristics of Automatic Data Extraction Technology

2013 ◽  
Vol 765-767 ◽  
pp. 1245-1248
Author(s):  
Pu Tian Yin ◽  
Rao Zheng Chan ◽  
Qin Zheng
Keyword(s):  
Feature Extraction ◽  
Data Extraction ◽  
Present Situation ◽  
Development Trend ◽  
Important Research ◽  
Security Technology ◽  
Extraction Technology ◽  
Automatic Data ◽  
Network Attack ◽  
Automatic Feature Extraction

attack automatic feature extraction technology is an important research of network security technology. From the network present situation research proceed with, to attack the automatic feature extraction technology for definition and classifycation, and for each category of technology are introduced in detail, and presents several attacks of automatic feature extraction technology, finally to present these technical deficiencies and the possible development trend are discussed.

Analysis on the Security Assess Requirements of Mobile Banking Based on Mobile Smart Terminal

2013 ◽  
Vol 475-476 ◽  
pp. 1219-1225
Author(s):  
Yan Zhang ◽  
Sha Sha Jiang ◽  
Jun Bin Zhang ◽  
Lei Lu
Keyword(s):  
Rapid Development ◽  
Present Situation ◽  
Mobile Terminal ◽  
Development Trend ◽  
Comprehensive Analysis ◽  
The Internet ◽  
Security Assessment ◽  
Mobile Banking ◽  
Security Technology ◽  
Resources Sharing

With the rising user number of mobile smart terminal and the rapid development of Internet in our country, the demand of resources sharing between mobile terminal and the Internet becomes more and more urgent. However, the mobile banking based on mobile smart terminal is facing increasingly serious security threatens. On the basis of a comprehensive analysis of the development and present situation of mobile banking, this paper describes the related security mechanism and potential security threatens of mobile banking. Furthermore, information security technology and development trend of mobile banking are comparised and summarized in this paper, and the security assessment demand for mobile banking is proposed.

scholarly journals Underwater Acoustic Target Recognition Based on Depthwise Separable Convolution Neural Networks

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1429
Author(s):  
Gang Hu ◽  
Kejun Wang ◽  
Liangliang Liu
Keyword(s):  
Feature Extraction ◽  
Target Recognition ◽  
Target Feature ◽  
Underwater Acoustic ◽  
Radiated Noise ◽  
Automatic Feature Extraction ◽  
Acoustic Target ◽  
And Cluster Analysis ◽  
Underwater Target ◽  
The One

Facing the complex marine environment, it is extremely challenging to conduct underwater acoustic target feature extraction and recognition using ship-radiated noise. In this paper, firstly, taking the one-dimensional time-domain raw signal of the ship as the input of the model, a new deep neural network model for underwater target recognition is proposed. Depthwise separable convolution and time-dilated convolution are used for passive underwater acoustic target recognition for the first time. The proposed model realizes automatic feature extraction from the raw data of ship radiated noise and temporal attention in the process of underwater target recognition. Secondly, the measured data are used to evaluate the model, and cluster analysis and visualization analysis are performed based on the features extracted from the model. The results show that the features extracted from the model have good characteristics of intra-class aggregation and inter-class separation. Furthermore, the cross-folding model is used to verify that there is no overfitting in the model, which improves the generalization ability of the model. Finally, the model is compared with traditional underwater acoustic target recognition, and its accuracy is significantly improved by 6.8%.

scholarly journals Image Classification for the Automatic Feature Extraction in Human Worn Fashion Data

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 624
Author(s):  
Stefan Rohrmanstorfer ◽  
Mikhail Komarov ◽  
Felix Mödritscher
Keyword(s):  
Neural Networks ◽  
Feature Extraction ◽  
Image Classification ◽  
Convolutional Neural Networks ◽  
Data Augmentation ◽  
State Of The Art ◽  
Image Data ◽  
Classification Model ◽  
Upper Body ◽  
Automatic Feature Extraction

With the always increasing amount of image data, it has become a necessity to automatically look for and process information in these images. As fashion is captured in images, the fashion sector provides the perfect foundation to be supported by the integration of a service or application that is built on an image classification model. In this article, the state of the art for image classification is analyzed and discussed. Based on the elaborated knowledge, four different approaches will be implemented to successfully extract features out of fashion data. For this purpose, a human-worn fashion dataset with 2567 images was created, but it was significantly enlarged by the performed image operations. The results show that convolutional neural networks are the undisputed standard for classifying images, and that TensorFlow is the best library to build them. Moreover, through the introduction of dropout layers, data augmentation and transfer learning, model overfitting was successfully prevented, and it was possible to incrementally improve the validation accuracy of the created dataset from an initial 69% to a final validation accuracy of 84%. More distinct apparel like trousers, shoes and hats were better classified than other upper body clothes.

scholarly journals Review on Applications of Lignin in Pavement Engineering: A Recent Survey

2022 ◽  
Vol 8 ◽  
Author(s):  
Hui Yao ◽  
Yiran Wang ◽  
Junfu Liu ◽  
Mei Xu ◽  
Pengrui Ma ◽  
...  
Keyword(s):  
Low Cost ◽  
Asphalt Mixture ◽  
Complex Mixture ◽  
Development Trend ◽  
Environmental Benefits ◽  
Extraction Technology ◽  
Environmental Friendliness ◽  
Modified Asphalt ◽  
Soil Stabilizer ◽  
Pavement Engineering

Lignin is the second-largest plant polymer on Earth after cellulose. About 98% of lignin produced in the papermaking and pulping industry is used for combustion heating or power generation. Less than 2% of lignin is used in more valuable fields, mainly in the formulation of dispersants, adhesives, and surfactants. Asphalt is one of the most important materials in pavement engineering. It is a dark brown complex mixture composed of hydrocarbons with different molecular weights and their non-metallic derivatives. Because the chemical structure of lignin is similar to that of asphalt, it is a carbon-based hydrocarbon material. More researchers studied the application of lignin in pavement engineering. In this paper, the structure, application, and extraction technology of lignin were summarized. This is a review article describing the different applications of lignin in pavement engineering and exploring the prospects of the application. There are three main types of pavement materials that can be used for lignin in pavement engineering, which are asphalt, asphalt mixture, and roadbed soil. In asphalt, lignin can be used as a modifier, extender, emulsifier, antioxidant, and coupling agent. In asphalt mixtures, lignin can be used as an additive. In road base soils, lignin can be used as a soil stabilizer. Furthermore, the article analyzed the application effects of lignin from the life cycle assessment. The conclusions suggest that lignin-modified asphalt exhibits more viscosity and hardness, and its high-temperature resistance and rutting resistance can be significantly improved compared with conventional asphalt. In addition, some lignin-modified asphalt binders exhibit reduced low-temperature crack resistance and fatigue resistance, which can be adjusted and selected according to the climate change in different regions. The performance of lignin as an asphalt mixture additive and asphalt extender has been proved to be feasible. Lignin can also produce good mechanical properties as well as environmental benefits as a soil stabilizer. In summary, lignin plays an important role in asphalt pavement and roadbed soil, and it is likely to be a development trend in the future due to its environmental friendliness and low cost. More research is needed to generalize the application of lignin in pavement engineering.

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