Perspicacious Apprehension of HDTbNB Algorithm Opposed to Security Contravention

The exponential pace of the spread of the digital world has served as one of the assisting forces to generate an enormous amount of informationflow-ing over the network.The data will always remain under the threat of technolo-gical suffering where intruders and hackers consistently try to breach the security systems by gaining personal information insights.In this paper,the authors pro-posed the HDTbNB(Hybrid Decision Tree-based Naïve Bayes)algorithm tofind the essential features without data scaling to maximize the model’s performance by reducing the false alarm rate and training period to reduce zero frequency with enhanced accuracy of IDS(Intrusion Detection System)and to further analyze the performance execution of distinct machine learning algorithms as Naïve Bayes,Decision Tree,K-Nearest Neighbors and Logistic Regression over KDD 99 data-set.The performance of algorithm is evaluated by making a comparative analysis of computed parameters as accuracy,macro average,and weighted average.Thefindings were concluded as a percentage increase in accuracy,precision,sensitiv-ity,specificity,and a decrease in misclassification as 9.3%,6.4%,12.5%,5.2%and 81%.

Capacity Analysis and Sum Rate Maximization for the SCMA Cellular Network Coexisting with D2D Communications

Sparse code multiple access (SCMA) is the most concerning scheme among non-orthogonal multiple access (NOMA) technologies for 5G wireless communication new interface. Another efficient technique in 5G aimed to improve spectral efficiency for local communications is device-to-device (D2D) communications. Therefore, we utilize the SCMA cellular network coexisting with D2D communications for the connection demand of the Internet of things (IOT), and improve the system sum rate performance of the hybrid network. We first derive the information-theoretic expression of the capacity for all users and find the capacity bound of cellular users based on the mutual interference between cellular users and D2D users. Then we consider the power optimization problem for the cellular users and D2D users jointly to maximize the system sum rate. To tackle the non-convex optimization problem, we propose a geometric programming (GP) based iterative power allocation algorithm. Simulation results demonstrate that the proposed algorithm converges fast and well improves the sum rate performance.

Spatial Correlation Characteristics Analysis of Multi-Beam Channels of Mobile Satellite System

Due to the influence of scatterers around the receiving antenna, the multipath signal in satellite mobile communication systems is correlated with each other which would influence the system performance. There is no systematic standard on the channel modelling of the wideband satellite channel at present, so the study of the modelling of the wideband satellite channel is of great importance. In this paper, firstly we created a multi-beam model which can figure out the antenna gain of the nth component beam. Secondly, we combined the characteristics of multi-beam satellite channel and the distribution of the scatterers, and set up a three-dimension random channel model. This model is more realistic for satellite communication system since it considers the height of scatterers. According to the channel models, we had the formula of spatial correlation coefficient. We used the formula to calculate the relationship between spatial correlation coefficient and the interval of antennas. The result shows that the spatial correlation exists and cannot be ignored while modeling for mobile satellite system.

Capacity Analysis and Optimization of Satellite MIMO System

Multiple-Input Multiple-Output (MIMO) technology is widely applied in terrestrial wireless communication system, which greatly increases the system capacity. Satellite communication system has many advantages such as wide coverage and strong flexibility. Therefore, how to make a better use of MIMO technology in satellite communication system has become a research hotspot in recent years. The purpose of this paper is to analysis the relationship between satellite MIMO system capacity and parameters of terrestrial antenna such as angle and distance. The parameters of terrestrial antenna were derived and calculated to keep a higher capacity for satellite MIMO system. Numerical analysis of system capacity performance before and after optimization was obtained, which proved the correctness of the theory proposed in this paper.

Fast Single Image Haze Removal Method for Inhomogeneous Environment Using Variable Scattering Coefficient

The images capture in a bad environment usually loses its fidelity and contrast.As the light rays travel towards its destination they get scattered several times due to the tiny particles of fog and pollutants in the environment,therefore the energy gets lost due to multiple scattering till it arrives its destination,and this degrades the images.So the images taken in bad weather appear in bad quality.Therefore,single image haze removal is quite a bit tough task.Significant research has been done in the haze removal algorithm but in all the techniques,the coefficient of scattering is taken as a constant according to the homogeneous atmosphere but in real time this does not happen.Therefore,this paper introduces a simple and efficient method so that the scattering coefficient becomes variable according to the inhomogeneous environment.Then,this research aims to remove the haze with the help of a fast and effective algorithm i.e.,Prior Color Fading,according to the inhomogeneous environmental properties.Thereby,to filter the depth map,the authors used a weighted guided image filtering which removes the drawbacks of guided image filter.Afterwards the scattering coefficient is made variable according to the inhomogeneous atmosphere and then the Simple Color Balance Algorithm is applied so that the readability property of images can be increased.The proposed method tested on various general outdoor images and synthetic hazy images and analyzed on various parameters Mean Square Error(MSE),Root Mean Square Error(RMSE),Peak Signal to Noise Ratio(PSNR),Mean Structural Similarity(MSSIM)and the Universal Objective Quality Index(UQI).Experimental results for the proposed method show that the proposed approach provides better results as compared to the state-of-the-art haze removal algorithms.

Cloud Det ection Using Super Pixel Classification and Semantic Segmentation

Cloud detection plays a very significant role in remote sensing image processing.This paper introduces a cloud detection method based on super pixel level classification and semantic segmentation.Firstly,remote sensing images are segmented into super pixels.Segmented super pixels compose a super pixel level remote sensing image database.Though cloud detection is essentially a binary classification task,our database is labeled into four categories to improve the generalization ability:thick cloud,cirrus cloud,building,and other culture.Secondly,the super pixel level database is used to train our cloud detection models based on convolution neural network(CNN)and deep forest.Hierarchical fusion CNN is proposed considering super pixel level images contain less semantic information than normal images.Taking full advantage of low-level features like color and texture information,it is more applicable for super pixel level classification.Besides,a distance metric is proposed to refine ambiguous super pixels.Thirdly,an end-to-end cloud detection model based on semantic segmentation is introduced.This model has no restrictions on the input size,and takes less time.Experimental results show that compared with other cloud detection inethods.our proj)osed method acliieves better performance.

Fractional Fourier Transform Based M-ary Chirp Modulation

In this paper,a novel M-ary chirp modulation scheme is proposed on the basis of the energy concen-tration property of chirp signals in fractional domain.In the proposed scheme,chirp signals with diferent phases are multiplexed in the same time frequency bandwidth through reverse chirp rate to increase information rate.In addition,fractional filters based on fractional Fourier transform(FRFT)are designed to separate chirp signals of diferent chirp-rates in the receiver.Moreover,the theoretical performance of fractional filters and the error probability of M-ary chirp system are derived.Both theoretical analysis and simulation prove that the proposed scheme outperforms M-ary quadrature amplitude modulation(QAM)system in the anti-noise performance.