Intelligent decision support systems may be required to adapt to changes in their operating environment. FPGA-based hardware accelerators can be used to design embedded systems that are reprogrammable and reconfigurab...
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ISBN:
(纸本)9781509006274
Intelligent decision support systems may be required to adapt to changes in their operating environment. FPGA-based hardware accelerators can be used to design embedded systems that are reprogrammable and reconfigurable. A new algorithm was proposed to implement a dynamic, adaptive inference mechanism. A hardware accelerator was developed for this fuzzy automaton model. A Zynq-7000 FPGA platform was used for the hardware implementation. An application example was given in the context of eye-hand coordination problems with handicapped children. Simulations results were presented to verify the hardware implementation.
The concept of security performance emerges as the core attribute when cloud-based systems need to process data flows through different countries. To effectively address the cloud security issues through a territorial...
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The concept of security performance emerges as the core attribute when cloud-based systems need to process data flows through different countries. To effectively address the cloud security issues through a territorial perspective, it is crucial to focus on the initial objectives of the Terms of Service as issued by the cloud service operator or provider. In this paper, a cloud-based service scenario where sensitive data are transferred and managed in a cross-border manner is assessed. The threats definition process considers the adoption of mobile devices. The paper focuses on the security assessment process and on information reconnaissance which in turn leads to the cloud defence boundary's exploitation. Also, the issue of how the service level objectives (SLOs) may affect security and privacy issues in a cloud-based environment is addressed.
Students activity on social media can provide implicit knowledge and new perspectives for an educational system. Sentiment analysis is a part of text mining that can help to analyze and classify the opinion data. This...
Students activity on social media can provide implicit knowledge and new perspectives for an educational system. Sentiment analysis is a part of text mining that can help to analyze and classify the opinion data. This research uses text mining and naive Bayes method as opinion classifier, to be used as an alternative methods in the process of evaluating studentss satisfaction for educational institution. Based on test results, this system can determine the opinion classification in Bahasa Indonesia using naive Bayes as opinion classifier with accuracy level of 84% correct, and the comparison between the existing system and the proposed system to evaluate students satisfaction in learning process, there is only a difference of 16.49%.
This presentation debates over the similarities and differences between artificial neural networks (ANN) versus natural ones. The animal brain's substructures were the initial models for the synthetic neural nets,...
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ISBN:
(纸本)9781509015313
This presentation debates over the similarities and differences between artificial neural networks (ANN) versus natural ones. The animal brain's substructures were the initial models for the synthetic neural nets, but during last decades neuropsychologists also learn an important knowledge from the ANN. Currently, engineers perform research to diversify network architectures and to develop new and more efficient learning strategies while medical doctors try to better understand the way human brain process information. The authors present also some thoughts about the perspectives for the ANN development linked to the growing demand for artificial intelligence in many human fields of activity.
Aiming at the minimization of numerical dispersion effects in finite-difference time-domain (FDTD) simulations, we investigate the potential of introducing frequency-dependent coefficients in the approximations of dif...
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ISBN:
(纸本)9781509022342
Aiming at the minimization of numerical dispersion effects in finite-difference time-domain (FDTD) simulations, we investigate the potential of introducing frequency-dependent coefficients in the approximations of differential operators. The proposed methodology exploits some previous results on optimized finite-differences, but initially avoids the necessity for selecting a specific optimization point. Herein, the operators' coefficient formulae are approximated by a low-order polynomial, which is transformed into a finite-difference counterpart using the Helmholtz equation. This modifies the initial spatial stencil and improves performance over all frequencies, which can be further controlled with the least-squares method, leading to various new FDTD schemes of augmented reliability.
Quantum cryptography is arguably the fastest growing area in quantum information science. Novel theoretical protocols are designed on a regular basis, security proofs are constantly improving, and experiments are grad...
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The K-nearest neighbor (KNN) classifier is one of the simplest and most common classifiers, yet its performance competes with the most complex classifiers in the literature. The core of this classifier depends mainly ...
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The first search for the Z boson decay to ττμμ at the CERN LHC is presented, based on data collected by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV and correspond...
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The first search for the Z boson decay to ττμμ at the CERN LHC is presented, based on data collected by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV and corresponding to an integrated luminosity of 138 fb−1. The data are compatible with the predicted background. For the first time, an upper limit at the 95% confidence level of 6.9 times the standard model expectation is placed on the ratio of the Z→ττμμ to Z→4μ branching fractions. Limits are also placed on the six flavor-conserving four-lepton effective-field-theory operators involving two muons and two tau leptons, for the first time testing all such operators.
A search is presented for baryon number violating interactions in top quark production and decay. The analysis uses data from proton-proton collisions at a center-of-mass energy of 13 TeV, collected with the CMS detec...
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A search is presented for baryon number violating interactions in top quark production and decay. The analysis uses data from proton-proton collisions at a center-of-mass energy of 13 TeV, collected with the CMS detector at the LHC with an integrated luminosity of 138 fb−1. Candidate events are selected by requiring two oppositely charged leptons (electrons or muons) and exactly one jet identified as originating from a bottom quark. Multivariate discriminants are used to separate the signal from the background. No significant deviation from the standard model prediction is observed. Upper limits are placed on the strength of baryon number violating couplings. For the first time the production of single top quarks via baryon number violating interactions is studied. This allows the search to set the most stringent constraints to date on the branching fraction of the top quark decay to a lepton, an up-type quark (u or c), and a down-type quark (d, s, or b). The results improve the previous bounds by 3 to 6 orders of magnitude based on the fermion flavor combination of the baryon number violating interactions.
This paper presents a new property of maximally-flat filter prototype coefficients. The property can be used to relate the summation of all the coefficients to an elegant expression which only includes the first coeff...
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