A fog-based security framework for intelligent traffic light control system

Multimedia Tools and Applications - The world is facing many problems including that of traffic congestion. To highlight the issue of traffic congestion worldwide specially in urban areas and to...     

Algebraic properties of cryptosystem PGM

In the late 1970s Magliveras invented a private-key cryptographic system calledPermutation Group Mappings (PGM). PGM is based on the prolific existence of certain kinds of factorization sets, calledlogarithmic signatures, for finite permutation groups. PGM is an endomorphic system with message space ℤ_|G| for a given finite permutation groupG. In this paper we prove several algebraic properties of PGM. We show that the set of PGM transformations ℐ _G is not closed under functional composition and hence not a group. This set is 2-transitive on ℤ_|G| if the underlying groupG is not hamiltonian and not abelian. Moreover, if the order ofG is not a power of 2, then the set of transformations contains an odd permutation. An important consequence of these results is that the group generated by the set of transformations is nearly always the symmetric group ℒ_|G|. Thus, allowing multiple encryption, any permutation of the message space is attainable. This property is one of the strongest security conditions that can be offered by a private-key encryption system. S. S. Magliveras was supported in part by NSF/NSA Grant Number MDA904-82-H0001, by U.S. West Communications, and by the Center for Communication and Information Science of the University of Nebraska.     

Improving security of the Internet of Things via RF fingerprinting based device identification system

Neural Computing and Applications - Security is one of the primary concerns when designing wireless networks. Along detecting user identity, it is also important to detect the devices at the...     

Characterization of acoustic signals due to surface discharges on H.V. glass insulators using wavelet radial basis function neural networks

A hybrid model incorporating wavelet and radial basis function neural network is presented which is used to detect, identify and characterize the acoustic signals due to surface discharge activity and hence differentiate abnormal operating conditions from the normal ones. The tests were carried out on cleaned and polluted high voltage glass insulators by using surface tracking and erosion test procedure of international electrotechnical commission 60587. A laboratory experiment was conducted by preparing the prototypes of the discharges. This study suggests a feature extraction and classification algorithm for surface discharge classification, which when combined together reduced the dimensionality of the feature space to a manageable dimension, by “marrying” the wavelet to radial basis function neural network very high levels of classification are achieved. Wavelet signal treatment toolbox is used to recover the surface discharge acoustic signals by eliminating the noisy portion and to reduce the dimension of the feature input vector. A radial basis function neural network classifier was used to classify the surface discharge and assess the suitability of this feature vector in classification. This learning method is proved to be effective by applying the wavelet radial basis function neural network in the classification of surface discharge fault data set. The test results show that the proposed approach is efficient and reliable.     

Rheological properties of poly(vinyl chloride) / epoxidized natural rubber blends. Part II: The effect of processing variables

The effect of processing variables on the rheological properties of PVC/ENR blends was investigated. The role of crosslinking in determining the flow behavior of blends was also examined by means of dynamically cured blends. It was found that PVC/ENR blends yield melts that are power law fluids. The flow of the melts improves with an increase in temperature and shear rate. However, the introduction of crosslinks reverses this trend, although under more rigorous conditions, the influence of crosslinks is superseded, and subsequently, flow becomes shear rate and temperature dependent. PVC/ENR systems also manifested elastic phenomena. The dependence of the elastic phenomena such as die swell and melt fracture on L/D ratio of the die was demonstrated.     

Investigations on the adhesion and interfacial properties of polyurethane foam/thermoplastic materials

The adhesion and interfacial properties of polyurethane (PU) foams with thermoplastic (TP) materials were investigated using different techniques. The adhesion performance of PU foam with TP materials was evaluated using the peel test method, and the adhesion durability was checked after different climate treatments. X‐ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), and contact angle measurements were used to study the surface and interface morphology of PU foam and TP material system. Three types of PU foam samples which differ in their composition and also five commercially available TP blends systems, based on poly(carbonate), poly(styrene‐co‐maleic anhydride), poly(acrylonitrile‐butadiene‐styrene), and silicone acrylate rubber have been used. The slow reacting foam shows the best adhesion properties with all the TP materials. The climate treatments strongly effected the PU foam adhesion durability with poly(carbonate) containing TP materials (70–80% loss in adhesion), but nearly no effect with poly(styrene‐co‐maleic anhydride). The samples with lowered adhesion could be separated by peeling without visible foam residues on the TP surface. AFM, XPS, and surface tension studies have shown that the surface properties of the TP material are still governed by the PU foam. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 104: 479–488, 2007     

Fuzzy triangulation signature for detection of change in human emotion from face video image sequence

The present article proposes a geometry-based fuzzy relational technique for capturing gradual change in human emotion over time available from relevant face image sequences. As associated features, we make use of fuzzy membership arising out of five triangle signatures such as - (i) Fuzzy Isosceles Triangle Signature (FIS), (ii) Fuzzy Right Triangle Signature (FRS), (iii) Fuzzy Right Isosceles Triangle Signature (FIRS), (iv) Fuzzy Equilateral Triangle Signature (FES), and (v) Other Fuzzy Triangles Signature (OFS) to achieve the task of appropriate classification of facial transition from neutrality to one among the six expressions viz. anger (AN), disgust (DI), fear (FE), happiness (HA), sadness (SA) and surprise (SU). The effectiveness of the Multilayer Perceptron (MLP) classifier is tested and validated through 10 fold cross-validation method on three benchmark image sequence datasets namely Extended Cohn-Kanade (CK+), M&M Initiative (MMI), and Multimedia Understanding Group (MUG). Experimental outcomes are found to have achieved accuracy to the tune of 98.47%, 93.56%, and 99.25% on CK+, MMI, and MUG respectively vindicating the effectiveness by exhibiting the superiority of our proposed technique in comparison to other state-of-the-art methods in this regard.

     

Green synthesised zinc oxide nanostructures through Periploca aphylla extract shows tremendous antibacterial potential against multidrug resistant pathogens

To grapple with multidrug resistant bacterial infections, implementations of antibacterial nanomedicines have gained prime attention of the researchers across the globe. Nowadays, zinc oxide (ZnO) at nano‐scale has emerged as a promising antibacterial therapeutic agent. Keeping this in view, ZnO nanostructures (ZnO‐NS) have been synthesised through reduction by P. aphylla aqueous extract without the utilisation of any acid or base. Structural examinations via scanning electron microscopy (SEM) and X‐ray diffraction have revealed pure phase morphology with highly homogenised average particle size of 18 nm. SEM findings were further supplemented by transmission electron microscopy examinations. The characteristic Zn–O peak has been observed around 363 nm using ultra‐violet–visible spectroscopy. Fourier‐transform infrared spectroscopy examination has also confirmed the formation of ZnO‐NS through detection of Zn–O bond vibration frequencies. To check the superior antibacterial activity of ZnO‐NS, the authors'' team has performed disc diffusion assay and colony forming unit testing against multidrug resistant E. coli, S. marcescens and E. cloacae. Furthermore, protein kinase inhibition assay and cytotoxicity examinations have revealed that green fabricated ZnO‐NS are non‐hazardous, economical, environmental friendly and possess tremendous potential to treat lethal infections caused by multidrug resistant pathogens.Inspec keywords: nanomedicine, zinc compounds, II‐VI semiconductors, wide band gap semiconductors, nanoparticles, scanning electron microscopy, X‐ray diffraction, antibacterial activity, transmission electron microscopy, particle size, Fourier transform infrared spectra, ultraviolet spectra, visible spectra, enzymes, biochemistry, molecular biophysics, microorganisms, drugs, toxicology, bonds (chemical), semiconductor growth, nanofabrication, vibrational modesOther keywords: green synthesised zinc oxide nanostructures, Periploca aphylla extract, antibacterial potential, multidrug resistant pathogens, multidrug resistant bacterial infections, antibacterial nanomedicines, P. aphylla aqueous extract, structural examinations, scanning electron microscopy, X‐ray diffraction, pure phase morphology, homogenised average particle size, SEM, transmission electron microscopy, Fourier‐transform infrared spectroscopy, bond vibration frequency, antibacterial activity, disc diffusion assay, colony forming unit testing, S. marcescens, E. cloacae, E. coli, ultraviolet‐visible spectroscopy, protein kinase inhibition assay, cytotoxicity, lethal infections, ZnO     

Determination of number of kanbans in a supply chain system via Memetic algorithm

In this research multi-stage supply chain system which is controlled by kanban system, is evaluated. In kanban system, decision making is based on determination of the number of kanbans as well as batch sizes. This paper attempts to model supply chain system with regard to costs under just-in-time (JIT) production philosophy. Since adopted model is of mixed integer non-linear programming (MINLP) type and solving it by exact algorithm such as branch and bound (B&B) takes a lot of time, a heuristic method via Memetic algorithm (MA) is presented. Some problems are solved by our proposed MA to illustrate its performance.