Characterization of RF-sputtered garnet films

Noncrystalline garnet films of nominal composition Y₃Fe₅O₁₂ and Y₂GdFe₅O₁₂ were synthesized by RF sputtering. The AC and DC resistivity data have been discussed in line with the model of Mott and Davis where conduction occurs through excitation of carriers into localized states at the band edges and hopping at energies close to the band tails.     

Two‐phase flow behavior in microtube reactors during biodiesel production from waste cooking oil

Flow patterns in the course of transesterification of waste cooking oil (WCO), sunflower oil (SFO) with water and/or oleic acid as a model of WCO, and pure SFO in the presence of a KOH catalyst in microtubes were investigated. FAME yield for the transesterification of WCO reached more than 89% in the microtube reactors with a residence time of 252 s at 333 K. The flow patterns when using WCO were changed from a liquid–liquid slug flow at the inlet region to a parallel flow at the middle region, and then to a homogeneous liquid flow at the outlet region as the reaction proceeded at 333 K. Fine droplets containing glycerol and methanol generally formed in oil slugs when using pure SFO, but were almost unobservable when using WCO. The soap produced from free fatty acids was considered to be the main factor affecting the flow patterns of WCO and SFO. © 2009 American Institute of Chemical Engineers AIChE J, 2010     

Simultaneously achievement of high recoverable energy density and efficiency in sodium niobate-based ceramics

Journal of Materials Science: Materials in Electronics - Single lead-free Na0.73Bi0.09(Nb1???xTax)O3 (x?=?0, 0.10, 0.20, 0.30, and 0.40) ceramic phases were processed...     

Corrosion-resistant polypyrrole-banana carbon (PPy-BC) nanocomposites for protection against electromagnetic interference: a green approach

Journal of Materials Science: Materials in Electronics - The article focuses on the suitability of electrically characterized polypyrrole-banana carbon (PPy-BC) nanocomposites for broadband...     

Microwave bandpass filter by feedback interference topology

This paper proposes a signal feedback interference topology to control the characteristics of a coupled line bandpass filter. Control is carried out by varying the ratio of the transmission line parameters of the forward and the feedback couplers. The topology produces a compact filter that does not require a complicated design or fabrication. The results of the insertion and return losses show that the feedback‐controlled design has desirable features in terms of the design frequency, fractional bandwidth, stopband rejection level, roll‐off rate and insertion loss. The test results of the fabricated prototype achieved good agreement with the simulation results of the ideal transmission line design model. Several microwave, modern wireless and mobile/satellite communication systems may benefit from such a filter design due to its compactness and flexibility.     

基于模糊语言变量的动态目标无线网络选择技术

Even though various wireless Net-work Access Technologies (NATs) with dif-ferent specifications and applications have been developed in the recent years, no single wireless technology alone can satisfy the any-time, anywhere, and any service wire-less-access needs of mobile users. A real seamless wireless mobile environment is only realized by considering vertical and horizontal handoffs together. One of the major design issues in heterogeneous wireless networks is the support of Vertical Handoff (VHO). VHO occurs when a multi-interface enabled mobile terminal changes its Point of Attachment (PoA) from one type of wireless access technology to another, while maintaining an active session. In this paper we present a novel multi-criteria VHO algorithm, which chooses the target NAT based on several factors such as user preferences, system parameters, and traffic-types with varying Quality of Service (QoS) requirements. Two modules i.e., VHO Necessity Estimation (VHONE) module and target NAT selection module, are designed. Both modules utilize several “weighted” users’ and system’s parameters. To improve the robustness of the proposed algorithm, the weighting system is designed based on the concept of fuzzy linguistic variables.     

A robust neural network model for fault detection in the presence of mislabelled data

Several data-driven methodologies for process monitoring and detection of faults or abnormalities have been developed for the safety of processing systems. The effectiveness of data-based models, however, is impacted by the volume and quality of training data. This work presents a robust neural network model for addressing the mislabelled and low-quality data in detecting faults and process abnormalities. The approach is based on harnessing data quality features along with supervisory labels in the network training. The data quality has been computed using the Mahalanobis distances and trusted centres of each class of data such as normal and faulty data. The method has been examined for detecting abnormalities in two case studies; a continuous stirred tank heater problem for detecting leaks and the Tennessee Eastman chemical process for detecting step and sticking faults. The performance of the proposed robust artificial neural networks (ANN) model is evaluated in terms of accuracy, fault detection rate, false alarm rate, and classification index at varying extents of mislabelling, namely, 1%, 5%, and 10% mislabelled data. The proposed model demonstrates higher detection performance, especially at increased labels of mislabelled data where the performance of the conventional ANN is severely impacted. The proposed methodology can be advantageous in handling mislabelled and low-quality data issues which are crucial in the data-driven modelling of processing systems.