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  • A survey on the Metaheuristics for Cryptanalysis of Substitution and Transposition Ciphers
  • Abstract This paper presents state-of-art cryptanalysis studies on attacks of the substitution and transposition ciphers using various metaheuristic algorithms. Traditional cryptanalysis methods employ an exhaustive search, which is computationally expensive. Therefore, metaheuristics have attracted the interest of researchers in the cryptanalysis field. Metaheuristic algorithms are known for improving the search for the optimum solution and include Genetic Algorithm, Simulated Annealing, Tabu Search, Particle Swarm Optimization, Differential Evolution, Ant Colony, the Artificial Bee Colony, Cuckoo Search, and Firefly algorithms. The most important part of these various applications is deciding the fitness function to guide the search. This review presents how these algorithms…
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  • Inverse Length Biased Maxwell Distribution: Statistical Inference with an Application
  • Abstract In this paper, we suggested and studied the inverse length biased Maxell distribution (ILBMD) as a new continuous distribution of one parameter. The ILBMD is obtained by considering the inverse transformation technique of the Maxwell length biased distribution. Statistical characteristics of the ILBMD such as the moments, moment generating function, mode, quantile function, the coefficient of variation, coefficient of skewness, Moors and Bowley measures of kurtosis and skewness , stochastic ordering, stress-strength reliability, and mean deviations are obtained. In addition, the Bonferroni and Lorenz curves, Gini index, the reliability function, the hazard rate function, the reverse hazard rate function, the…
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  • Cyclic Autoencoder for Multimodal Data Alignment Using Custom Datasets
  • Abstract The subtitle recognition under multimodal data fusion in this paper aims to recognize text lines from image and audio data. Most existing multimodal fusion methods tend to be associated with pre-fusion as well as post-fusion, which is not reasonable and difficult to interpret. We believe that fusing images and audio before the decision layer, i.e., intermediate fusion, to take advantage of the complementary multimodal data, will benefit text line recognition. To this end, we propose: (i) a novel cyclic autoencoder based on convolutional neural network. The feature dimensions of the two modal data are aligned under the premise of stabilizing…
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  • COVID-19 Automatic Detection Using Deep Learning
  • Abstract The novel coronavirus disease 2019 (COVID-19) is a pandemic disease that is currently affecting over 200 countries around the world and impacting billions of people. The first step to mitigate and control its spread is to identify and isolate the infected people. But, because of the lack of reverse transcription polymerase chain reaction (RT-CPR) tests, it is important to discover suspected COVID-19 cases as early as possible, such as by scan analysis and chest X-ray by radiologists. However, chest X-ray analysis is relatively time-consuming since it requires more than 15 minutes per case. In this paper, an automated novel detection…
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  • Mixed Attention Densely Residual Network for Single Image Super-Resolution
  • Abstract Recent applications of convolutional neural networks (CNNs) in single image super-resolution (SISR) have achieved unprecedented performance. However, existing CNN-based SISR network structure design consider mostly only channel or spatial information, and cannot make full use of both channel and spatial information to improve SISR performance further. The present work addresses this problem by proposing a mixed attention densely residual network architecture that can make full and simultaneous use of both channel and spatial information. Specifically, we propose a residual in dense network structure composed of dense connections between multiple dense residual groups to form a very deep network. This structure…
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  • Output Feedback Robust H Control for Discrete 2D Switched Systems
  • Abstract The two-dimensional (2-D) system has a wide range of applications in different fields, including satellite meteorological maps, process control, and digital filtering. Therefore, the research on the stability of 2-D systems is of great significance. Considering that multiple systems exist in switching and alternating work in the actual production process, but the system itself often has external perturbation and interference. To solve the above problems, this paper investigates the output feedback robust H stabilization for a class of discrete-time 2-D switched systems, which the Roesser model with uncertainties represents. First, sufficient conditions for exponential stability are derived via the average…
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  • An Improved Q-RRT* Algorithm Based on Virtual Light
  • Abstract The Rapidly-exploring Random Tree (RRT) algorithm is an efficient path-planning algorithm based on random sampling. The RRT* algorithm is a variant of the RRT algorithm that can achieve convergence to the optimal solution. However, it has been proven to take an infinite time to do so. An improved Quick-RRT* (Q-RRT*) algorithm based on a virtual light source is proposed in this paper to overcome this problem. The virtual light-based Q-RRT* (LQ-RRT*) takes advantage of the heuristic information generated by the virtual light on the map. In this way, the tree can find the initial solution quickly. Next, the LQ-RRT* algorithm…
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  • Pseudonym Mutable Based Privacy for 5G User Identity
  • Abstract Privacy, identity preserving and integrity have become key problems for telecommunication standards. Significant privacy threats are expected in 5G networks considering the large number of devices that will be deployed. As Internet of Things (IoT) and long-term evolution for machine type (LTE-m) are growing very fast with massive data traffic the risk of privacy attacks will be greatly increase. For all the above issues standards’ bodies should ensure users’ identity and privacy in order to gain the trust of service providers and industries. Against such threats, 5G specifications require a rigid and robust privacy procedure. Many research studies have addressed…
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  • Extended Rama Distribution: Properties and Applications
  • Abstract In this paper, the Rama distribution (RD) is considered, and a new model called extended Rama distribution (ERD) is suggested. The new model involves the sum of two independent Rama distributed random variables. The probability density function (pdf) and cumulative distribution function (cdf) are obtained and analyzed. It is found that the new model is skewed to the right. Several mathematical and statistical properties are derived and proved. The properties studied include moments, coefficient of variation, coefficient of skewness, coefficient of kurtosis and moment generating function. Some simulations are undertaken to illustrate the behavior of these properties. In addition, the…
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  • Quantifying the Mechanical Properties of White Sandstone Based on Computer Fractal Theory
  • Abstract The work presented in this paper was conducted to quantify the relationship between the pore characteristics and mechanical properties of white sandstone. The study include tests carried out under the coupling effects of chemical corrosion, temperature, nuclear magnetic resonance, and mechanical tests. Computer fractal theory was employed to describe and quantify the characteristics of the growth of pores in white sandstone under the same coupling effect. A custom developed program code, in the MATLAB software platform, was used for calculating the growths of the pores in white sandstone when subjected to coupling effects. The correlation between the computer fractal dimension…
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