Mullite for Structural, Electronic, and Optical Applications

Mullite (3Al₂O₃·2SiO₂) is becoming increasingly important in electronic, optical, and high-temperature structural applications. This paper reviews the current state of mullite-related research at a fundamental level, within the framework of phase equilibria, crystal structure, synthesis, processing, and properties. Phase equilibria are discussed in terms of the problems associated with the nucleation kinetics of mullite and the large variations observed in the solid-solution range. The incongruent melting behavior of mullite is now widely accepted. Large variations in the solid solubility from 58 to 76 mol% alumina are related to the ordering/disordering of oxygen vacancies and are strongly coupled with the method of synthesis used to form mullite. Similarly, reaction sequences which lead to the formation of mullite upon heating depend on the spatial scale at which the components are mixed. Mixing at the atomic level is useful for low-temperature (<1000°C) synthesis of mullite but not for low-temperature sintering. In contrast, precursors that are segregated are better suited for low-temperature (1250° to 1500°C) densification through viscous deformation. Flexural strength and creep resistance at elevated temperatures are significantly affected by the presence of glassy boundary inclusions; in the absence of glassy inclusions, polycrystalline mullite retains >90% of its room-temperature strength to 1500°C and displays very high creep resistance. Because of its low dielectric constant, mullite has now emerged as a substrate material in high-performance packaging applications. Interest in optical applications mainly centers on its applicability as a window material within the mid-infrared range.     

Graphite intercalated polymer coatings on stainless steel

The use of graphite modified polymer films has been investigated, on stainless steel. Polythiophene and polypyrrole films have been synthesized electrochemically on stainless steel, and then very thin graphite layers were realized on polymer films. Since the graphite layer is not applicable as a top coat, polymeric top films were also electrosynthesized on graphite layers. Following this procedure, polypyrrole-graphite-polypyrrole and polythiophene-graphite-polythiophene coatings have been obtained on stainless steel. The corrosion behaviours of coated samples have been investigated in 0.1 M H₂SO₄ solution, by means of electrochemical impedance spectroscopy (EIS) and anodic polarization curves. The intercalation of graphite layer altered the performance and properties of coatings significantly. Especially, polypyrrole coating system was found to exhibit almost an excellent coating behaviour that hindered the attack of corrosive environment within 96 h exposure time. The EIS results of polypyrrole coating system were indicating to almost a perfect capacitive behaviour that the response was reflecting capacitive behaviour in a wide frequency region. This property was also examined with successive cyclic voltammograms in a potential range between 0.10 and 0.40 V (vs. Ag/AgCl). The charge densities involved in oxidation and reduction regions were determined for successive cycles and it was shown that coated sample was able to exhibit charge-discharge (i.e. oxidation and reduction) behaviour successfully, without any degradation.     

High-capacity quantum key distribution using Chebyshev-map values corresponding to Lucas numbers coding

We propose an approach that achieves high-capacity quantum key distribution using Chebyshev-map values corresponding to Lucas numbers coding. In particular, we encode a key with the Chebyshev-map values corresponding to Lucas numbers and then use k-Chebyshev maps to achieve consecutive and flexible key expansion and apply the pre-shared classical information between Alice and Bob and fountain codes for privacy amplification to solve the security of the exchange of classical information via the classical channel. Consequently, our high-capacity protocol does not have the limitations imposed by orbital angular momentum and down-conversion bandwidths, and it meets the requirements for longer distances and lower error rates simultaneously.     

Extraction of voltage harmonics using multi-layer perceptron neural network

This paper presents a harmonic extraction algorithm using artificial neural networks for Dynamic Voltage Restorers (DVRs). The suggested algorithm employs a feed forward Multi Layer Perceptron (MLP) Neural Network with error back propagation learning to effectively track and extract the 3rd and 5th voltage harmonics. For this purpose, two different MLP neural network structures are constructed and their performances compared. The effects of hidden layer, supervisors and learning rate are also presented. The proposed MLP Neural Network algorithm is trained and tested in MATLAB program environment. The results show that MLP neural network enable to extract each harmonic effectively.     

A Polynomial Time Solution to Minimum Forwarding Set Problem in Wireless Networks under Unit Disk Coverage Model

Network-wide broadcast (simply broadcast) is a frequently used operation in wireless ad hoc networks (WANETs). One promising practical approach for energy-efficient broadcast is to use localized algorithms to minimize the number of nodes involved in the propagation of the broadcast messages. In this context, the minimum forwarding set problem (MFSP) (also known as multipoint relay (MPR) problem) has received a considerable attention in the research community. Even though the general form of the problem is shown to be NP-complete, the complexity of the problem has not been known under the practical application context of ad hoc networks. In this paper, we present a polynomial time algorithm to solve the MFSP for wireless network under unit disk coverage model. We prove the existence of some geometrical properties for the problem and then propose a polynomial time algorithm to build an optimal solution based on these properties. To the best of our knowledge, our algorithm is the first polynomial time solution to the MFSP under the unit disk coverage model. We believe that the work presented in this paper will have an impact on the design and development of new algorithms for several wireless network applications including energy-efficient multicast, broadcast, and topology control protocols for WANETs and sensor networks.     

Medical image segmentation with transform and moment based features and incremental supervised neural network

In this study, a novel incremental supervised neural network (ISNN) is proposed for the segmentation of medical images. Performance of the ISNN is investigated for tissue segmentation in medical images obtained from various imaging modalities. Two feature extraction methods based on transform and moments are comparatively investigated to segment the tissues in medical images. Two-dimensional (2D) continuous wavelet transform (CWT) and the moments of the gray-level histogram (MGH) are computed in order to form the feature vectors of ultrasound (US) bladder and phantom images, X-ray computerized tomography (CT) and magnetic resonance (MR) head images. In the 2D-CWT method, feature vectors are formed by the intensity of one pixel of each wavelet-plane of different energy bands. The MGH represents the tissues within the sub-windows by using the spatial variation of image intensities. In this study, the ISNN and Grow and Learn (GAL) network are employed for the segmentation task. It is observed that the ISNN has significantly eliminated the disadvantages of the GAL network in the segmentation of the medical images.     

ADALINE based robust control in robotics: a Riemann-Liouville fractional differintegration based learning scheme

This paper presents an approach to improve the performance of intelligent sliding model control achieved by the use of a fundamental constituent of soft computing, named Adaptive Linear Element (ADALINE). The proposed scheme is based on the fractional calculus. A previously considered tuning scheme is revised according to the rules of fractional order differintegration. After a comparison with the integer order counterpart, it is seen that the control system with the proposed adaptation scheme provides (1) better tracking performance, (2) suppression of undesired drifts in parameter evolution and (3) a very high degree of robustness and insensitivity to disturbances. The claims are justified through some simulations utilizing the dynamic model of a two degrees of freedom (DOF) direct drive robot arm and overall, the contribution of the paper is to introduce the fractional order calculus into a robust and nonlinear control problem with some outperforming features that are absent when the integer order differintegration operators are adopted.     

Metamodeling live sequence charts for code generation

This article presents a metamodeling study for Live Sequence Charts (LSCs) and Message Sequence Charts (MSCs) with an emphasis on code generation. The article discusses specifically the following points: the approach to building a metamodel for MSCs and LSCs, a metamodel extension from MSC to LSC, support for model-based code generation, and finally action model and domain-specific data model integration. The metamodel is formulated in metaGME, the metamodel language for the Generic Modeling Environment.

Semi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI

Journal of Signal Processing Systems - Segmentation of thigh tissues (muscle, fat, inter-muscular adipose tissue (IMAT), bone, and bone marrow) from magnetic resonance imaging (MRI) scans is useful...