REV Journal on Electronics and Communications
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Guest Editorial: Special Issue on Advanced Computational Methods, Systems, and Industrial Engineering Applications
Get PDFPerformance of Sampling/Resampling-based Particle Filters Applied to Non-Linear Problems
Get PDFIn this work, we propose a wireless body area sensor network (WBASN) to monitor patient position. Localization and tracking are enhanced by improving the effect of the received signal strength (RSS) variation. First, we propose a modified particle filter (PF) that adjusts resampling parameters for the Kullback-Leibler distance (KLD)-resampling algorithm to ameliorate the effect of RSS variation by generating a sample set near the high-likelihood region. The key issue of this method is to use a resampling parameter lower bound for reducing both the root mean square error (RMSE) and the mean number of particles used. To determine this lower bound, an optimal algorithm is proposed based on the maximum RMSE between the proposed algorithm and the KLD-resampling algorithm or based on the maximum mean number of particles used of these algorithms. Finally, PFs based on KLD-sampling and KLD-resampling are proposed to minimize the efficient number of particles and to reduce the estimation error compared to traditional algorithms
A Measure of Smoothness in Synthesized Speech
Get PDFThe articulators typically move smoothly during speech production. Therefore, speech features of natural speech are generally smooth. However, over-smoothness causes "muffleness" and, hence, reduction in ability to identify emotions/expressions/styles in synthesized speech that can affect the perception of naturalness in synthesized speech. In the literature, statistical variances of static spectral features have been used as a measure of smoothness in synthesized speech but they are not sufficient enough. This paper proposes another measure of smoothness that can be efficiently applied to evaluate the smoothness of synthesized speech. Experiments showed that the proposed measure is reliable and efficient to measure the smoothness of different kinds of synthesized speech
A Combination of Artificial Neural Network and Artificial Immune System for Virus Detection
Get PDFIn this paper, we propose an Artificial Neural Immune Network (ANIN) for virus detection. ANIN is a combination of Artificial Neural Network (ANN) and Artificial Immune Network (AiNet). In ANIN, each ANN is considered as a detector. A pool of initial detectors then undergoes a mature process, called AiNet, to improve its recognizing ability. Thus, more than one ANN objects can cooperate to detect malicious code. The experimental results show that ANIN can achieve a detection rate of 87.98% on average with an acceptable false positive rate
A Two-Bit Reflectarray Element Using Cut-Ring Patch Coupled to Delay Lines
Get PDFIn this paper, a two-bit element for reflectarray applications is presented. The proposed element is based on the cut-ring patch coupled to delay lines through an annular slot. The four states of the reflection phase with a step of 90◦ are achieved with two switches. This reported work is the first step towards the 2-bit active reflectarray element. Prototypes of the element have been fabricated and characterized in X-band using waveguide simulator. Measured results show good characteristics with low magnitude losses and the bandwidth of 1.7-bit resolution is over 5%
Exploiting Context-Aware Event Data for Fault Analysis
Get PDFFault analysis in communication networks and distributed systems is a difficult process that heavily depends on system administrator’s experience and supporting tools. This process usually requires analytic techniques and several types of event data including log events, debug messages, trace obtained from these systems to investigate the root cause of faults. This paper introduces an approach of exploiting context-aware data and classification technique for improving this process. This approach uses both event data and context-aware data including CPU load, memory, processes, temperature, status to train a decision tree, and then applies the tree to assess suspected events. We have implemented and experimented the approach on the OpenStack cloud computing system with the Hadoop computing service and MELA event collection system. The experimental results reveal that the accuracy score of the approach reaches 85% on average. The paper also includes detailed analysis for the results
FPGA-Based Multiple DDoS Countermeasure Mechanisms System Using Partial Dynamic Reconfiguration
Get PDFIn this paper, we propose a novel FPGA-based high-speed DDoS countermeasure system that can flexibly adapt to DDoS attacks while still maintaining system performance. The system includes a packet decoder module and multiple DDoS countermeasure mechanisms. We apply dynamic partial reconfiguration technique in this system so that the countermeasure mechanisms can be flexibly changed or updated on-the-fly. The proposed system architecture separates DDoS protection modules (which implement DDoS countermeasure techniques) from the packet decoder module. By using this approach, one DDoS protection module can be reconfigured without interfering with other modules. The proposed system is implemented on a NetFPGA 10G board. The synthesis results show that the system can work at up to 116.782 MHz while utilizing up to 39.9% Registers and 49.85% BlockRAM of the Xilinx Virtex xcv5tx240t FPGA device on the NetFPGA 10G board. The system achieves the detection rate of 100% with the false negative rate at 0% and false positive rate closed to 0.16%. The prototype system achieves packet decoding throughput at 9.869 Gbps in half-duplex mode and 19.738 Gbps in full-duplex mode
State Space Reduction on Wireless Sensor Network Verification Using Component-Based Petri Net Approach
Get PDFWith the recent advancement of Internet of Things, the applications of Wireless Sensor Networks (WSNs) are increasingly attracting attention from of both industry and research communities. However, since the deployment cost of a WSN is relatively large, one would want to make a logic model of a WSN and have the model verified beforehand to ensure that the WSN would work correctly and effectively once practically employed. Petri Net (PN) is very suitable to model a WSN, since PN strongly supports modeling concurrent and ad-hoc systems. However, verification of a PN-modeled system suffers from having to explore the huge state space of the system. In order to overcome it, in this paper we suggest a novel component-based approach to model and verify a PN-modeled WSN system. First of all, the original WSN system is divided into components, which can be further abstracted to reduce the model size. Moreover, when verifying the corresponding PN model produced from the abstracted WSN, we introduce a strategy of component-based firing, which can reduce the state space significantly. Compared to typical approach of PN-based verification, our method enjoys an impressive improvement of performance and resource consuming, as depicted in our experimental results
On the Performance of Cognitive Underlay SIMO Networks over Equally Correlated Rayleigh Fading Channels
Get PDFThe performance of single-input multiple-output (SIMO) cognitive spectrum sharing networks with the presence of equally correlated Rayleigh fading channels is investigated. In particular, based on the truncated infinitive series of cumulative distribution function (CDF) and probability density function (PDF) of the end-to-end signal-to-noise ratios (SNRs), close-form expressions are provided for the system outage performance, bit error rate and ergodic capacity. It is shown that the system performance merely depends on the correlation coefficient between antennas. Monte-Carlo simulations are also contributed to confirm the accuracy of our analysis