Search

For many years, chaotic maps have been widely used in the design of various algorithms in cryptographic systems. In this paper, a new model (compound chaotic system) of quantum random walks controlled by a hyper-chaotic map is constructed and a novel scheme for constructing a dynamic S-Box based on the new model is proposed. Through aperiodic evaluation and statistical complexity measurement, it is shown that the compound chaotic system has features such as complex structure and stronger randomness than classical chaotic systems. Based on the chaotic sequence generated by the composite system, we design a dynamic S-Box generation mechanism. The mechanism can quickly generate high-security S-Boxes. Then, an example of randomly generating S-Boxes is given alongside an analytical evaluation of S-Box standard performance criteria such as bijection, boomerang uniformity, bit independence, nonlinearity, linear approximate probability, strict avalanche effect, differential uniformity, the and generalized majority logic criterion. The evaluation results confirm that the performance of the S-Box is excellent. Thus, the proposed dynamic S-Box construction technique can be used to generate cryptographically strong substitution-boxes in practical information security systems. [ABSTRACT FROM AUTHOR]

Monitoring the evolution of the state of networks is an important issue to ensure that many applications provide the required quality of service. The first step in network-monitoring systems consists of capturing packets; that is, packets arrive at the system through a network interface card and are placed into system memory. Then, in this first stage, and usually in relation to the operating system, packets are treated and transferred from the capturing buffer to a higher-layer processing, for instance, to be analyzed in the next step of the system. In this work, we focus on the capturing stage. In particular, we focus on a Linux packet-capturing system. We model it as a single server queue. Taking into account that the server can be in charge not only of the capturing process but also of other tasks, we consider that the queue has vacations, i.e., there is some time when the capturing process cannot be carried out. We also assume that the queue has a finite buffer. We consider three different models and present a rigorous analysis of the derived Markov chain of each of the models. We provide standard performance metrics in all cases. We also evaluate the performance of these models in a real packet-capture probe. [ABSTRACT FROM AUTHOR]

A recommender system not only "gains users' confidence" but also helps them in other ways, such as reducing their time spent and effort. To gain users' confidence, one of the main goals of recommender systems in an e-commerce industry is to estimate the users' interest by tracking the users' transactional behavior to provide a fast and highly related set of top recommendations out of thousands of products. The standard ranking-based models, i.e., the denoising auto-encoder (DAE) and collaborative denoising auto-encoder (CDAE), exploit positive-only feedback without utilizing the ratings' ranks for the full set of observed ratings. To confirm the rank of observed ratings (either low or high), a confidence value for each rating is required. Hence, an improved, confidence-integrated DAE is proposed to enhance the performance of the standard DAE for solving recommender systems problems. The correctness of the proposed method is authenticated using two standard MovieLens datasets such as ML-1M and ML-100K. The proposed study acts as a vital contribution for the design of an efficient, robust, and accurate algorithm by learning prominent latent features used for fast and accurate recommendations. The proposed model outperforms the state-of-the-art methods by achieving improved P@10, R@10, NDCG@10, and MAP scores. [ABSTRACT FROM AUTHOR]

Embedded controllers for multivariable processes have become a powerful tool in industrial implementations. Here, the Model Predictive Control offers higher performances than standard control methods. However, they face low computational resources, which reduces their processing capabilities. Based on pipelining concept, this paper presents a new embedded software-based implementation for a constrained Multi-Input-Multi-Output predictive control algorithm. The main goal of this work focuses on improving the timing performance and the resource usage of the control algorithm. Therefore, a profiling study of the baseline algorithm is developed, and the performance bottlenecks are identified. The functionality and effectiveness of the proposed implementation are validated in the NI myRIO 1900 platform using the simulation of a jet transport aircraft during cruise flight and a tape transport system. Numerical results for the study cases show that the latency and the processor usage are substantially reduced compared with the baseline algorithm, 4.6 × and 3.17 × respectively. Thus, efficient program execution is obtained which makes the proposed software-based implementation mainly suitable for embedded control systems. [ABSTRACT FROM AUTHOR]

This study implements various, maximum overlap, discrete wavelet transform filters to model and forecast the time-dependent mortality index of the Lee-Carter model. The choice of appropriate wavelet filters is essential in effectively capturing the dynamics in a period. This cannot be accomplished by using the ARIMA model alone. In this paper, the ARIMA model is enhanced with the integration of various maximal overlap discrete wavelet transform filters such as the least asymmetric, best-localized, and Coiflet filters. These models are then applied to the mortality data of Australia, England, France, Japan, and USA. The accuracy of the projecting log of death rates of the MODWT-ARIMA model with the aforementioned wavelet filters are assessed using mean absolute error, mean absolute percentage error, and mean absolute scaled error. The MODWT-ARIMA (5,1,0) model with the BL14 filter gives the best fit to the log of death rates data for males, females, and total population, for all five countries studied. Implementing the MODWT leads towards improvement in the performance of the standard framework of the LC model in forecasting mortality rates. [ABSTRACT FROM AUTHOR]