Solution Processing Route to Multifunctional Titania Thin Films: Highly Conductive and Photcatalytically Active Nb:TiO2

This paper reports the synthesis of highly conductive niobium doped titanium dioxide (Nb:TiO₂) films from the decomposition of Ti(OEt)₄ with dopant quantities of Nb(OEt)₅ by aerosol‐assisted chemical vapor deposition (AACVD). Doping Nb into the Ti sites results in n‐type conductivity, as determined by Hall effect measurements. The doped films display significantly improved electrical properties compared to pristine TiO₂ films. For 5 at.% Nb in the films, the charge carrier concentration was 2 × 10²¹ cm^?3 with a mobility of 2 cm² V^–1 s^–1 . The corresponding sheet resistance is as low as 6.5 Ω sq^–1 making the films suitable candidates for transparent conducting oxide (TCO) materials. This is, to the best of our knowledge, the lowest reported sheet resistance for Nb:TiO₂ films synthesized by vapour deposition. The doped films are also blue in colour, with the intensity dependent on the Nb concentration in the films. A combination of synchrotron, laboratory and theoretical techniques confirmed niobium doping into the anatase TiO₂ lattice. Computational methods also confirmed experimental results of both delocalized (Ti⁴⁺) and localized polaronic states (Ti³⁺) states. Additionally, the doped films also functioned as photocatalysts. Thus, Nb:TiO₂ combines four functional properties (photocatalysis, electrical conductivity, optical transparency and blue colouration) within the same layer, making it a promising alternative to conventional TCO materials.     

An Energy Efficient Message Scheduling Algorithm Considering Node Failure in IoT Environment

Advancements in the area of computing and the networking gave birth to a new concept Internet of Things (IoT). This can be thought as “network of future” connecting diverse objects/things together. The focus is on scheduling the messages in an IoT environment where things/sensors are clustered into IoT subgroups, each subgroup has a message broker that delivers the messages originated from the group to the ultimate receiver of the sensed data. The message scheduler works at the broker level to decide which message to be transmitted first. This scheduling improves the overall IoT system efficiency. Furthermore to keep the flow of services provided by these things/sensors continuous and non-disruptive, the optimal tackling of the faulty or failed nodes has become the salient feature of the proposed scheduling algorithm. The faults or failures identified on time help to initiate recovery or replacement procedures. To find the right level of replacement nodes deployed for the sensor network, we consider the energy a scarce resource and the cost of deployment of the backup nodes as per failure of the node occurring in the underlying environment. In this work we propose an energy efficient recovery and backup node selection for IoT systems followed with energy efficient message scheduling. Simulation results show the effectiveness and efficiency of the proposed message scheduling considering the node failure with recovery and replacement technique.     

Development of Optical Code Division Multiple Access Based System Using Spectral Amplitude Coding via Fiber Bragg Gratings (FBGs)

Wireless Personal Communications - The multiple user’s based transmission systems are developed in the past using various multiple access techniques for fibre optic communications. Among...     

Correction to: Enhanced TOA Estimation Using OFDM over Wide-Band Transmission Based on a Simulated Model

Wireless Personal Communications -     

Power Control for Cognitive Radio Networks: A Game Theoretic Approach

In communication industry one of the most rapidly growing area is wireless technology and its applications. The efficient access to radio spectrum is a requirement to make this communication feasible for the users that are running multimedia applications and establishing real-time connections on an already overcrowded spectrum. In recent times cognitive radios (CR) are becoming the prime candidates for improved utilization of available spectrum. The unlicensed secondary users share the spectrum with primary licensed user in such manners that the interference at the primary user does not increase from a predefined threshold. In this paper, we propose an algorithm to address the power control problem for CR networks. The proposed solution models the wireless system with a non-cooperative game, in which each player maximize its utility in a competitive environment. The simulation results shows that the proposed algorithm improves the performance of the network in terms of high SINR and low power consumption.

     

Auto-tuning of PID controller according to fractional-order reference model approximation for DC rotor control

This paper presents a stochastic, multi-parameters, divergence optimization method for the auto-tuning of proportional–integral–derivative (PID) controllers according to a fractional-order reference model. The study aimed to approximate the step response of the real closed-loop flight control system to the response of a theoretical reference model for a smoother and more precise flight control experience. The proposed heuristic optimization method can auto-tune a PID controller without a precise plant model. This is very advantageous when dealing with model and parameter uncertainties in real control application and practice. Experimental study confirms the reference model driven auto-tuning of the DC rotor prototype.     

Optimized intrusion detection mechanism using soft computing techniques

Intrusion detection is an important technique in computer and network security. A variety of intrusion detection approaches be present to resolve this severe issue but the main problem is performance. It is important to increase the detection rates and reduce false alarm rates in the area of intrusion detection. Therefore, in this research, an optimized intrusion detection mechanism using soft computing techniques is proposed to overcome performance issues. The KDD-cup dataset is used that is a benchmark for evaluating the security detection mechanisms. The Principal Component Analysis (PCA) is applied to transform the input samples into a new feature space. The selecting of an appropriate number of principal components is a critical problem. So, Genetic Algorithm (GA) is used in the optimum selection of principal components instead of using traditional method. The Support Vector Machine (SVM) is used for classification purpose. The performance of this approach is addresses. Further, a comparative analysis is made with existing approaches. Consequently, this method provides optimal intrusion detection mechanism which is capable to minimize amount of features and maximize the detection rates.     

Performance of Object Classification Using Zernike Moment

Moments have been used in all sorts of object classification systems based on image. There are lots of moments studied by many researchers in the area of object classification and one of the most preference moments is the Zernike moment. In this paper, the performance of object classification using the Zernike moment has been explored. The classifier based on neural networks has been used in this study. The results indicate the best performance in identifying the aggregate is at 91.4% with a ten orders of the Zernike moment. This encouraging result has shown that the Zernike moment is a suitable moment to be used as a feature of object classification systems.     

Formation of Hybrid Inorganic/Organic Nanocomposites

Hybrid inorganic/organic nanocomposites were produced by the exposure of spun films of octa-(benzo-15-crown-5)-substituted phthalocyanine of Cd(II) to an environment of hydrogen sulfide gas. The formation of cadmium sulfide (CdS) quantum dots in the metal free phthalocyanine matrix was identified in the phthalocyanine matrix from atomic force microscopy images. The mean size of CdS quantum dots was estimated to be 2–3 nm, from optical absorption and Raman spectra for the nanocomposites.