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  • Investigating the Use of Email Application in Illiterate and SemiIlliterate Population
  • Abstract The use of electronic communication has been significantly increased over the last few decades. Email is one of the most well-known means of electronic communication. Traditional email applications are widely used by a large population; however, illiterate and semi-illiterate people face challenges in using them. A major population of Pakistan is illiterate that has little or no practice of computer usage. In this paper, we investigate the challenges of using email applications by illiterate and semiilliterate people. In addition, we also propose a solution by developing an application tailored to the needs of illiterate/semi-illiterate people. Research shows that illiterate people…
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  • CNN Approaches for Classification of Indian Leaf Species Using Smartphones
  • Abstract Leaf species identification leads to multitude of societal applications. There is enormous research in the lines of plant identification using pattern recognition. With the help of robust algorithms for leaf identification, rural medicine has the potential to reappear as like the previous decades. This paper discusses CNN based approaches for Indian leaf species identification from white background using smartphones. Variations of CNN models over the features like traditional shape, texture, color and venation apart from the other miniature features of uniformity of edge patterns, leaf tip, margin and other statistical features are explored for efficient leaf classification.
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  • A Novel DDoS Attack Detection Method Using Optimized Generalized Multiple Kernel Learning
  • Abstract Distributed Denial of Service (DDoS) attack has become one of the most destructive network attacks which can pose a mortal threat to Internet security. Existing detection methods cannot effectively detect early attacks. In this paper, we propose a detection method of DDoS attacks based on generalized multiple kernel learning (GMKL) combining with the constructed parameter R. The super-fusion feature value (SFV) and comprehensive degree of feature (CDF) are defined to describe the characteristic of attack flow and normal flow. A method for calculating R based on SFV and CDF is proposed to select the combination of kernel function and regularization…
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  • An Extended Approach for Generating Unitary Matrices for Quantum Circuits
  • Abstract In this paper, we do research on generating unitary matrices for quantum circuits automatically. We consider that quantum circuits are divided into six types, and the unitary operator expressions for each type are offered. Based on this, we propose an algorithm for computing the circuit unitary matrices in detail. Then, for quantum logic circuits composed of quantum logic gates, a faster method to compute unitary matrices of quantum circuits with truth table is introduced as a supplement. Finally, we apply the proposed algorithm to different reversible benchmark circuits based on NCT library (including NOT gate, Controlled-NOT gate, Toffoli gate) and…
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  • Evaluating the Topology Coverage of BGP Monitors
  • Abstract BGP monitors are currently the main data resource of AS-level topology measurement, and the integrity of measurement result is limited to the location of such BGP monitors. However, there is currently no work to conduct a comprehensive study of the range of measurement results for a single BGP monitor. In this paper, we take the first step to describe the observed topology of each BGP monitor. To that end, we first investigate the construction and theoretical up-limit of the measured topology of a BGP monitor based on the valley-free model, then we evaluate the individual parts of the measured topology…
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  • Secrecy Outage Probability Analysis Based on Cognitive Decodeand-Forward Relaying
  • Abstract Wireless communications have to face to several different security issues in practice due to the nature of broadcast. The information theory is well known to provide efficient approaches to address security issues in wireless communications, which attracts much attention in both industry and academia in recent years. In this paper, inspired by information theory, we study the outage probability of the opportunistic relay selection based on cognitive decode-and-forward relaying with the secrecy consideration. Specifically, the closed-form expression of the outage probability is proposed. Moreover, the asymptotic performance evaluation on the basis of the analytical results is investigated. The simulation results…
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  • Defend Against Adversarial Samples by Using Perceptual Hash
  • Abstract Image classifiers that based on Deep Neural Networks (DNNs) have been proved to be easily fooled by well-designed perturbations. Previous defense methods have the limitations of requiring expensive computation or reducing the accuracy of the image classifiers. In this paper, we propose a novel defense method which based on perceptual hash. Our main goal is to destroy the process of perturbations generation by comparing the similarities of images thus achieve the purpose of defense. To verify our idea, we defended against two main attack methods (a white-box attack and a black-box attack) in different DNN-based image classifiers and show that,…
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  • Service Scheduling Based on Edge Computing for Power Distribution IoT
  • Abstract With the growing amounts of multi-micro grids, electric vehicles, smart home, smart cities connected to the Power Distribution Internet of Things (PD-IoT) system, greater computing resource and communication bandwidth are required for power distribution. It probably leads to extreme service delay and data congestion when a large number of data and business occur in emergence. This paper presents a service scheduling method based on edge computing to balance the business load of PD-IoT. The architecture, components and functional requirements of the PD-IoT with edge computing platform are proposed. Then, the structure of the service scheduling system is presented. Further, a…
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  • Consensus of Multi-Agent Systems with Input Constraints Based on Distributed Predictive Control Scheme
  • Abstract Consensus control of multi-agent systems has attracted compelling attentions from various scientific communities for its promising applications. This paper presents a discrete-time consensus protocol for a class of multi-agent systems with switching topologies and input constraints based on distributed predictive control scheme. The consensus protocol is not only distributed but also depends on the errors of states between agent and its neighbors. We focus mainly on dealing with the input constraints and a distributed model predictive control scheme is developed to achieve stable consensus under the condition that both velocity and acceleration constraints are included simultaneously. The acceleration constraint is…
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