A Comparative Investigation of Optical and Structural Properties of Cu-Doped CdO-Derived Nanostructures

In this report, we studied various structural and optical properties of pure and copper-doped cadmium oxide (CdO) thin films. Nanostructured Cu-doped CdO films were deposited using sol–gel spin-coating technique. The structural and morphological changes have been observed by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), and atomic force microscopy (AFM) studies. The optical and electrical properties of the pure and Cu-doped CdO thin films were studied by UV–vis spectroscopy and four-point probe method, respectively. The XRD peaks show the formation of nanocrystalline CdO with cubic face-centered crystal structure. The band gaps of the as deposited films were found in the range of 2.32–2.73 eV, while after doping, it decreases due to structural deformation. The electrical resitivity was found to decrease approximately ～10 in Cu-doped CdO thin films.     

MESFET DC model parameter extraction using Quantum Particle Swarm Optimization

This paper presents two techniques for DC model parameter extraction for a Gallium Arsenide (GaAs) based MEtal Semiconductor Field Effect Transistor (MESFET) device. The proposed methods uses Particle Swarm Optimization (PSO) and Quantum Particle Swarm Optimization (QPSO) methods for optimizing the difference between measured data and simulated data. Simulated data are obtained by using four different popular DC models. These techniques avoid complex computational steps involved in traditional parameter extraction techniques. The performance comparison in terms of quality of solution and execution time of classical PSO and QPSO to extract the model parameters are presented. The validity of this approach is verified by comparing the simulated and measured results of a fabricated GaAs MESFET device with gate length of 0.7 μm and gate width of 600 μm (4 × 150). Simulation results indicate that both the technique based on PSO and QPSO accurately extracts the model parameters of MESFET.     

The hyperspherical acceleration effect particle swarm optimizer

This paper proposes Hyperspherical Acceleration Effect Particle Swarm Optimization (HAEPSO) for optimizing complex, multi-modal functions. The HAEPSO algorithm finds the particles that are trapped in deep local minima and accelerates them in the direction of global optima. This novel technique improves the efficiency by manipulating PSO parameters in hyperspherical coordinate system. Performance comparisons of HAEPSO are provided against different PSO variants on standard benchmark functions. Results indicate that the proposed algorithm gives robust results with good quality solution and faster convergence. The proposed algorithm is an effective technique for solving complex, higher dimensional multi-modal functions.     

Effect of Polysaccharides on the Properties of the Mucoadhesive Poly(Vinyl Alcohol) Multicore–Shell Microparticles

This study discusses about the effect of polysaccharides (agar, gum tragacanth, and guar gum) on the properties of the core (organogel)–shell [poly(vinyl alcohol)] microparticles. The size, swelling, and mucoadhesive properties of the poly(vinyl alcohol) microparticles were altered in the presence of the polysaccharides. Thermal analysis confirmed the presence of organogels within the microparticles. Fourier transform infrared spectroscopy confirmed the presence of the polysaccharides within the microparticles. The microparticles were biocompatible in nature. Drug release indicated that an alteration in the shell composition can be used for altering drug release. Ciprofloxacin-loaded microparticles showed sufficient antimicrobial efficiency.     

On designing an unaided authentication service with threat detection and leakage control for defeating opportunistic adversaries

Unaided authentication services provide the flexibility to login without being dependent on any additional device. The power of recording attack resilient unaided authentication services (RARUAS) is undeniable as, in some aspects, they are even capable of offering better security than the biometric based authentication systems. However, high login complexity of these RARUAS makes them far from usable in practice. The adopted information leakage control strategies have often been identified as the primary cause behind such high login complexities. Though recent proposals havemade some significant efforts in designing a usable RARUAS by reducing its login complexity, most of them have failed to achieve the desired usability standard. In this paper, we have introduced a new notion of controlling the information leakage rate. By maintaining a good security standard, the introduced idea helps to reduce the login complexity of our proposed mechanism − named as Textual-Graphical Password-based Mechanism or TGPM, by a significant extent. Along with resisting the recording attack, TGPM also achieves a remarkable property of threat detection. To the best of our knowledge, TGPM is the first RARUAS, which can both prevent and detect the activities of the opportunistic recording attackers who can record the complete login activity of a genuine user for a few login sessions. Our study reveals that TGPM assures much higher session resiliency compared to the existing authentication services, having the same or even higher login complexities. Moreover, TGPM stores the password information in a distributed way and thus restricts the adversaries to learn the complete secret from a single compromised server. A thorough theoretical analysis has been performed to prove the strength of our proposal from both the security and usability perspectives. We have also conducted an experimental study to support the theoretical argument made on the usability standard of TGPM.     

Design and implementation of a realtime co-processor for denoising Fiber Optic Gyroscope signal

The amount of noise present in the Fiber Optic Gyroscope (FOG) signal limits its applications and has a negative impact on navigation system. Existing algorithms such as Discrete Wavelet Transform (DWT), Kalman Filter (KF) denoise the FOG signal under static environment, however denoising fails in dynamic environment. Therefore in this paper an Adaptive Moving Average Dual Mode Kalman Filter (AMADMKF) is developed for denoising the FOG signal under both the static and dynamic environments. Performance of the proposed algorithm is compared with DWT and KF techniques. Further, a hardware Intellectual Property (IP) of the algorithm is developed for System on Chip (SoC) implementation using Xilinx Virtex-5 Field Programmable Gate Array (Virtex-5FX70T-1136). The developed IP is interfaced as a Co-processor/ Auxiliary Processing Unit (APU) with the PowerPC (PPC440) embedded processor of the FPGA. It is proved that the proposed system is an efficient solution for denoising the FOG signal in real-time environment. Hardware acceleration of developed Co-processor is 65× with respect to its equivalent software implementation of AMADMKF algorithm in the PPC440 embedded processor.     

Security analysis of GTRBAC and its variants using model checking

Security analysis is a formal verification technique to ascertain certain desirable guarantees on the access control policy specification. Given a set of access control policies, a general safety requirement in such a system is to determine whether a desirable property is satisfied in all the reachable states. Such an analysis calls for the use of formal verification techniques. While formal analysis on traditional Role Based Access Control (RBAC) has been done to some extent, recent extensions to RBAC lack such an analysis. In this paper, we consider the temporal RBAC extensions and propose a formal technique using timed automata to perform security analysis by analyzing both safety and liveness properties. Using safety properties one ensures that something bad never happens while liveness properties show that some good state is also achieved. GTRBAC is a well accepted generalized temporal RBAC model which can handle a wide range of temporal constraints while specifying different access control policies. Analysis of such a model involves a process of mapping a GTRBAC based system into a state transition system. Different reduction rules are proposed to simplify the modeling process depending upon the constraints supported by the system. The effect of different constraints on the modeling process is also studied.     

Single-molecule biophysics: at the interface of biology, physics and chemistry

Single-molecule methods have matured into powerful and popular tools to probe the complex behaviour of biological molecules, due to their unique abilities to probe molecular structure, dynamics and function, unhindered by the averaging inherent in ensemble experiments. This review presents an overview of the burgeoning field of single-molecule biophysics, discussing key highlights and selected examples from its genesis to our projections for its future. Following brief introductions to a few popular single-molecule fluorescence and manipulation methods, we discuss novel insights gained from single-molecule studies in key biological areas ranging from biological folding to experiments performed in vivo.     

Neuro fuzzy model for adaptive filtering of oscillatory signals

In this paper we have developed a neuro fuzzy model for adaptive filtering of oscillatory signals embedded with white noise. Such type of fuzzy adaptive filters are constructed from a set of fuzzy IF-THEN rules, which change adaptively to minimise the cost function until a desired information is available. Here we have used a generalised cost function for better convergence of the error. This algorithm is simulated on a digital signal processor in order to track the signal and to filter out the disturbances present in the signal at a particular instant of time. The system presented here, can measure both types of information like numerical as well as linguistic.     

Defect‐Mediated Polarization Switching in Ferroelectrics and Related Materials: From Mesoscopic Mechanisms to Atomistic Control

The plethora of lattice and electronic behaviors in ferroelectric and multiferroic materials and heterostructures opens vistas into novel physical phenomena including magnetoelectric coupling and ferroelectric tunneling. The development of new classes of electronic, energy‐storage, and information‐technology devices depends critically on understanding and controlling field‐induced polarization switching. Polarization reversal is controlled by defects that determine activation energy, critical switching bias, and the selection between thermodynamically equivalent polarization states in multiaxial ferroelectrics. Understanding and controlling defect functionality in ferroelectric materials is as critical to the future of oxide electronics and solid‐state electrochemistry as defects in semiconductors are for semiconductor electronics. Here, recent advances in understanding the defect‐mediated switching mechanisms, enabled by recent advances in electron and scanning probe microscopy, are discussed. The synergy between local probes and structural methods offers a pathway to decipher deterministic polarization switching mechanisms on the level of a single atomically defined defect.