A Lightweight and Scalable Physical Layer Attack Detection Mechanism for the Internet of Things (IoT) Using Hybrid Security Schema

Wireless Personal Communications - The Internet of Things, also known as the IoT, refers to the billions of devices around the world that are now connected to the Internet, collecting and sharing...     

A probabilistic SVM approach for hyperspectral image classification using spectral and texture features

New hyperspectral sensors can collect a large number of spectral bands, which provide a capability to distinguish various objects and materials on the earth. However, the accurate classification of these images is still a big challenge. Previous studies demonstrate the effectiveness of combination of spectral data and spatial information for better classification of hyperspectral images. In this article, this approach is followed to propose a novel three-step spectral–spatial method for classification of hyperspectral images. In the first step, Gabor filters are applied for texture feature extraction. In the second step, spectral and texture features are separately classified by a probabilistic Support Vector Machine (SVM) pixel-wise classifier to estimate per-pixel probability. Therefore, two probabilities are obtained for each pixel of the image. In the third step, the total probability is calculated by a linear combination of the previous probabilities on which a control parameter determines the efficacy of each one. As a result, one pixel is assigned to one class which has the highest total probability. This method is performed in multivariate analysis framework (MAF) on which one pixel is represented by a d-dimensional vector, d is the number of spectral or texture features, and in functional data analysis (FDA) on which one pixel is considered as a continuous function. The proposed method is evaluated with different training samples on two hyperspectral data. The combination parameter is experimentally obtained for each hyperspectral data set as well as for each training samples. This parameter adjusts the efficacy of the spectral versus texture information in various areas such as forest, agricultural or urban area to get the best classification accuracy. Experimental results show high performance of the proposed method for hyperspectral image classification. In addition, these results confirm that the proposed method achieves better results in FDA than in MAF. Comparison with some state-of-the-art spectral–spatial classification methods demonstrates that the proposed method can significantly improve classification accuracies.     

Modeling and Exploring Co‐variations in the Geometry and Configuration of Man‐made 3D Shape Families

We introduce co‐variation analysis as a tool for modeling the way part geometries and configurations co‐vary across a family of man‐made 3D shapes. While man‐made 3D objects exhibit large geometric and structural variations, the geometry, structure, and configuration of their individual components usually do not vary independently from each other but in a correlated fashion. The size of the body of an airplane, for example, constrains the range of deformations its wings can undergo to ensure that the entire object remains a functionally‐valid airplane. These co‐variation constraints, which are often non‐linear, can be either physical, and thus they can be explicitly enumerated, or implicit to the design and style of the shape family. In this article, we propose a data‐driven approach, which takes pre‐segmented 3D shapes with known component‐wise correspondences and learns how various geometric and structural properties of their components co‐vary across the set. We demonstrate, using a variety of 3D shape families, the utility of the proposed co‐variation analysis in various applications including 3D shape repositories exploration and shape editing where the propagation of deformations is guided by the co‐variation analysis. We also show that the framework can be used for context‐guided orientation of objects in 3D scenes.     

Formal analysis of seamless application execution in mobile cloud computing

Mobile cloud computing augments the resource-constrained mobile devices to run rich mobile applications by leveraging the cloud resources and services. Compute-intensive mobile apps require significant communication resources for migrating the code from mobile devices to the cloud. For such apps, distributed application execution frameworks (DAEF) have been proposed in the literature. These frameworks either migrate the mobile app code during runtime or keep the app synchronized with another remotely executed app on the cloud. Frameworks also support mobile app live migration to cater for compute node mobility. One key research question arises is how successful are these DAEFs in achieving the seamless application execution under various network conditions? The answer to this question entails formal analysis of the DAEFs to determine the realistic bounds on propagation delay, bandwidth and application interaction with mobile device for various types and sizes of apps. In this research, we apply formal analysis techniques to define the execution time of the app and the time required for code migration. We also define three conditions for seamless application execution. Given realistic values for processor speed, application executable size, possible number of executed instructions, network propagation delay and transmission delay, we show what components of the mobile app need to be migrated during execution to the cloud. Finally, we compute realistic bounds for the app size (that can be executed seamlessly) based on important features which include cloud and device resources, bandwidth and latency profile.     

Synthesis and characterization of new polyureas derived from 4‐(4′‐Methoxyphenyl)urazole

4‐(4′‐Methoxyphenyl)urazole (MPU) was prepared from 4‐methoxybenzoic acid in five steps. The reaction of monomer MPU with n‐isopropylisocyanate was performed at room temperature in N,N‐dimethylformamide solution, and the resulting bis‐urea derivative was obtained in high yield and was finally used as a model for polymerization reaction. The step‐growth polymerization reactions of monomer MPU with hexamethylene diioscyanate, isophorone diioscyanate, and toluene‐2,4‐diioscyanate were performed in N,N‐dimethylacetamide solution in the presence of pyridine as a catalyst. The resulting novel polyureas have an inherent viscosity (η_inh) in a range of 0.07–0.21 dL/g in DMF and sulfuric acid at 25°C. These polyureas were characterized by IR, ¹H‐NMR, elemental analysis, and TGA. Some physical properties and structural characterization of these novel polyureas are reported. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 85: 1141–1146, 2002     

In situ MAS NMR investigations of molecular sieves and zeolite-catalyzed reactions

Solid-state MAS NMR is a powerful technique to study heterogeneous catalysts and the way by which they operate. In situ MAS NMR has been demonstrated to be a powerful method to understand reaction mechanisms, to study the nature, dynamics and reactivity of surface intermediates and active sites, and to characterize structural modifications in the catalyst itself, in particular when using ¹³C strategically labelled substrates. In this paper, three examples selected from our own work are used to illustrate the potential of in situ MAS NMR. They are the formation of cumene and its isomerization to n-propylbenzene on zeolite H-ZSM-11, the activation of propane at low temperature and the alkylation of benzene with propane on zeolite H-ZSM-5, and the characterization of the aluminophosphate molecular sieve VPI-5 structure with temperature. Studies of the alkylation of benzene with propene confirmed that cumene was the primary reaction product. The undesired n-propylbenzene by-product results from the intermolecular reaction between cumene and benzene, enhanced by molecular shape-selective effects in medium pore size zeolites (e.g., H-ZSM-11). It explains why large pore zeolites, e.g., zeolite Beta, are used commercially today for this process. Propane can be activated at low temperature (ca. 573 K) on bifunctional medium pore size zeolites possessing intimately related acidic Brønsted sites and a dehydrogenation function provided by Ga or Zn species. In Ga/H-ZSM-5 catalysts, at 573 K, the activation of propane was shown to occur via a protonated pseudocyclopropane (PPCP) intermediate (or transition state). The latter evolves in a manner that can be formally described by the formation of CH ₃ ⁺ , C₂H ₂ ⁺ , and C₃H ₇ ⁺ carbenium ion intermediates. These species can react with olefins, alkanes, or other electron-rich molecules such as benzene. The primary reaction products of the reaction of propane with benzene are n-propylbenzene (in small amount), ethylbenzene and toluene. Their subsequent reactions lead eventually to toluene and xylenes as the final products. In the structural characterization of VPI-5, ²⁷Al, ³¹P, and ²⁷Al nutation MAS NMR spectra show that, at 294 K, fully hydrated VPI-5 contains three equally populated Al and P crystallographic sites and that one-third of Al is 6-coordinate. The VPI-5 structure then belongs to the P6₃ space group. Above 353 K, VPI-5, fully or partially hydrated, undergoes a structural transformation to a higher framework symmetry, i.e., the P6₃cm space group. The transformation occurs at nearly the same temperature in both cases, indicating that the breakdown of the hydrogen-bonded helical water structure inside the VPI-5 pores is not a factor in the process.     

Reverse micelle facilitated synthesis of nanostructured polyaniline as the counter electrode materials in dye-sensitized solar cells

ABSTRACT

We report a reverse-micelle emulsion polymerization of nanostructured PANI using a nonionic surfactant Polyglyceryl-2-Dipolyhydroxystearate (PGPH) at various concentrations from 2% to 6% (v/v). SEM images show that the obtained morphologies are irregular agglomerates at low PGPH concentration and relatively regular granules at high PGPH concentration. FTIR and Raman spectra show that the synthesized PANI is in the form of Emeraldine salt (PANI ES) with electrical conductivity around 10^?3 S cm^?1. Photovoltaic current-voltage (J-V) measurements show the highest power conversion efficiency is achieved at 1.71% at 6% (v/v) of PGPH.     

Electrocatalytic oxidation of hydrazine at overoxidized polypyrrole film modified glassy carbon electrode

Electrocatalytic oxidation of hydrazine (HZ) was studied on an overoxidized polypyrrole (OPPy) modified glassy carbon electrode using cyclic voltammetry and chronoamperometry techniques. The OPPy-modified glassy carbon electrode has very high catalytic ability for electrooxidation of HZ, which appeared as a reduced overpotential in a wide operational pH range of 5-10. The overall numbers of electrons involved in the catalytic oxidation of HZ, the number of electrons involved in the rate-determining and diffusion coefficient of HZ were estimated using cyclic voltammetry and chronoamperometry. It has been shown that using the OPPy-modified electrode, HZ can be determined by cyclic voltammetry and amperometry with limit of detection 36 and 3.7 μM, respectively. The results of the analysis suggest that the proposed method promises accurate results and could be employed for the routine determination of HZ.     

Microwave-assisted extraction kinetics of terpenes from caraway seeds

The process conditions during the extraction of carvone and limonene from caraway seed (Carum carvi L.) with microwave-assisted extraction have been studied with respect to microwave power, radiation dose and extraction time in order to obtain the secondary metabolites selectively. Using classical solid–liquid extraction, limonene, carvone and fatty oils in both the raw material and the residual matrix material were extracted. Yields of limonene, carvone and total oil (C₁₆, C₁₈) were determined by GC and GC/MS analysis for both extracts. The effects of microwaves on cell walls and cells destruction could be seen on SEM micrographs.     

Correction to: Monitoring and Predicting Saltwater Intrusion via Temporal Aquifer Vulnerability Maps and Surrogate Models

Water Resources Management -