A collaborative policy-based security scheme to enforce resource access controlling mechanism

Advances in both telecommunications and Information technology have improved the way users do business online. Android, an open-source mobile operating system, is becoming an attractive target for cyber criminals to exploit due to its predefined permission model. Without classification, the mobile operating system permits installation of mobile applications of all kinds, including Trojans, thus making its trustworthiness into question. In this paper, we present a security system called collaborative policy-based security scheme (CSS) that permits users to customize the access permissions of Android applications during runtime. The proposed CSS security scheme validates the trustworthiness of each application before being installed. The experimental results show that the proposed CSS successfully detects all malicious applications with a run-time overhead of 2.7%.

     

M-Curves path planning model for mobile anchor node and localization of sensor nodes using Dolphin Swarm Algorithm

Wireless Networks - Location information of a sensor node is the primary concern to process the sensed data in Wireless Sensor Networks (WSNs). The location of the sensor node is used in other...     

Pattern diversity of path loss compensated antennas for 5G base stations

In this article, a tapered slot antenna (TSA) operating from 27 to 29.8 GHz with an endfire gain of 9 dBi and high pattern integrity is presented. The gain specifications for path loss compensation on ground for a ceiling mounted millimeter wave base station is computed and the gain of the antenna elements with beam angled at ±45° was found to be 12 dBi. To enhance gain with minimal physical footprint, a combination of dielectric loading and electrical resonator metamaterial unit cells were integrated to the proposed TSA to achieve the expected gain enhancement of 3 dB across the band, operating in the same frequency band with aperture efficiency greater than 73% and a 1 dB gain bandwidth of 20.7%. A compact stacking topology for pattern diversity of all three antenna elements for path loss compensation is also investigated. The base station has a coverage of ±60° with uniform illumination and mutual coupling lesser than 35 dB. The detailed simulated and measured results are presented.     

Enhanced photovoltaic performance of a dye sensitized solar cell with Cu/N Co-doped TiO<Subscript>2</Subscript> nanoparticles

Pure and Copper/Nitrogen (Cu/N)-codoped TiO₂ photoanodes with various Cu concentrations are prepared via sol–gel route for the photoanode application in dye-sensitized solar cells (DSSCs). All the prepared samples are characterized by X-Ray Diffraction (XRD), X-Ray Photoelectron Spectroscopy (XPS), Scanning Electron Microscope (SEM), Transmission Electron Microscopy (TEM), UV–Vis spectroscopy (UV–VIS) and Electrochemical Impedance Spectroscopy (EIS). Addition of suitable amount of Cu and N content in TiO₂ can alter its optical and electrical properties by extending absorption in the visible region and band gap reduction. The results show that some of the Ti sites are replaced by Cu atoms while O sites are occupied by N atoms. Upon adequate addition of Cu/N could lead to smaller particle size, higher specific surface area, increased dye adsorption and retarded charge carrier recombination. A significant improvement in the power conversion efficiency is observed in case of optimized 0.3 mol% Cu/N-doped TiO₂ nanoparticles (NPs) based DSSC. This optimized 0.3 mol% Cu/N-doped photoanode accomplished a best power conversion efficiency of 11.70% with a short circuit current density of 23.41 mA cm^?2 which is 41% higher than that of the pure TiO₂ photoanode based DSSC (6.82%).     

Study of the Choice of Excitation Frequency for Sub Surface Defect Detection in Electrically Thick Conducting Specimen Using Eddy Current Testing

Understanding the scope and limitations of non-destructive testing procedure is essential for selecting the appropriate test parameters for material inspection. This paper presents the scope of material (\( \delta_{s} \)) and probe dependent (\( \delta_{t} \)) penetration depths for determining the optimal test frequency (\( f_{opt} ) \) for detection of sub surface defects in electrically thick conducting specimens. Numerical modelling is carried out for a pancake coil above an electrically thick aluminium plate, \( t/\delta_{t} \)?>?1, to study the influence of the EC probe and defect location (\( t_{df} \)) on the test frequency for near and deep sub surface defects. The study concludes that the optimal test frequency, \( f_{opt} \) for detection of deep sub surface defects (\( t_{df} /t \approx 1 \)) is determined by the probe dependent skin depth, \( \delta_{t} \), and the plate thickness is related to \( f_{opt} \) by, \( t \propto 1/\sqrt {f_{opt} } \). The numerical observations were experimentally validated for machined sub surface notches on a 10 mm thick (\( t \)) aluminium plate.     

Formation of As–As Interlayer Bonding in the cT Phase of EuFe<Subscript>2</Subscript>As<Subscript>2</Subscript> and CeFeAsO Under Pressure from First Principle

The electronic band structure and structural phase stability of EuFe₂As₂ and CeFeAsO compounds were studied using the full-potential linearized augmented plane wave (FP-LAPW) method implemented using WIEN2k. To calculate the structural stability and phase transition of these compounds, the total energies have been computed as a function of reduced volumes and fitted with the Birch–Murnaghan equation. The calculated lattice parameters are found to be in agreement with the available experimental data. The present results show that EuFe₂As₂ and CeFeAsO compounds undergo structural phase transition from body-centered tetragonal (BCT) into collapsed tetragonal (cT) and tetragonal (T) into cT phase under pressure. The calculated phase transition pressures are in agreement with recent experimental data. The calculated valence charge density of collapsed tetragonal phase reveals that As–As interactions found to be stronger under pressure.     

A review on measurement science needs for real-time control of additive manufacturing metal powder bed fusion processes

Additive manufacturing technologies are increasingly used in the development of new products. However, variations in part quality in terms of material properties, dimensional tolerances, surface roughness and defects limit its broader acceptance. Process control today based on heuristics and experimental data yields limited improvement in part quality. In an effort to identify the needed measurement science for real-time closed-loop control of additive manufacturing (AM) processes, this paper presents a literature review on the current AM control schemes, process measurements and modelling and simulation methods as it applies to the powder bed fusion process, though results from other processes are reviewed where applicable. We present our research findings to identify the correlations between process parameters, process signatures and product quality. We also present research recommendations on the key control issues to serve as a technical basis for standards development in this area. Complimentary details to this paper with summary tables, range of values, preliminary correlations and correlation figures can be accessed from a National Institute of Standards and Technology Report (http://nvlpubs.nist.gov/nistpubs/ir/2015/NIST.IR.8036.pdf). This paper is developed based on the report.     

Multiclassifier for severity-level categorization of glioma tumors using multimodal magnetic resonance imaging brain images

Brain tumor segmentation and classification is a crucial challenge in diagnosing, planning, and treating brain tumors. This article proposes an automatic method that categorizes the severity level of the tumors to render an effective diagnosis. The proposed fractional Jaya optimizer-deep convolutional neural network undergoes the severity classification based on the features obtained from the segments of the magnetic resonance imaging (MRI) images. The segments are obtained using the particle swarm optimization that ensures the optimal selection of the segments from the MRI image and yields the core tumor and the edema tumor regions. The experimentation using the BRATS database reveals that the proposed method acquired a maximal accuracy, specificity, and sensitivity of 0.9414, 0.9429, and 0.9708, respectively.