A methodology for development of configurable remote access measurement system

A configurable remote access measurement system (CRAMS) is designed using an object oriented methodology (OOM) and implemented using the integration of an object oriented language, JAVA, a relational database management system, MS-ACCESS, and an instrumentation software package (LabVIEW). OOM is a powerful technique that is used to manage the complexity of large systems. It allows for easy maintenance and upgrading of the developed systems. The main focus of this paper is to present a detailed procedure for the analysis, design and implementation of CRAMS. The functionality of CRAMS is demonstrated by creating a remotely accessible laboratory environment using a set of programmable and virtual instruments connected to a PC server.     

Epoxy/oil fly ash composites prepared through in situ polymerization: Enhancement of thermal and mechanical properties

The utilization of oil fly ash (OFA) as a filler in polymer composites to enhance their strength and flow properties and reduce the cost of fabrication is a promising technique. OFA filled epoxy composites, based on bisphenol‐A liquid epoxy, were prepared via in situ co‐polymerization with isophorone diamine as a curing agent. In the present work, the possibility of using residual OFA (<30 μm) as filler in epoxy composites was studied using thermal, mechanical, and morphological characterization techniques. The results showed a significant improvement in the performance of epoxy composites containing OFA. In addition, OFA filled epoxy exhibited a higher resistance to degradation in acidic and basic environments when compared to unfilled epoxy. Statistical analysis tools were used to determine the significance of the improvements. It is proposed that up to 4 wt% of OFA can be used in epoxy industrial pipes to improve their corrosive chemical resistance properties without affecting their bulk physical properties. POLYM. COMPOS., 37:512–522, 2016. © 2014 Society of Plastics Engineers     

Three-phase two-leg buck-boost DC-AC inverter with differential power processor unit

Renewable energy sources (RESs) need power-electronics-based converters to deliver the acquired power to the grid. Those converters should provide voltage-bucking/boosting capabilities to accommodate various grid modes specially for three-phase distorted commonly unbalanced distribution utility networks. Several power electronic-based converters have been elaborated to fulfill this high-demand market. Single-stage converters are the most dominant in the market where the current source inverters (CSIs), impedance source inverters (ZSIs), and boost inverters are the high-end candidates. The aspects of cost, footprint, and minimal numbers of active switches, in addition to simplified controllability, build the main challenges that face the evolution of robust renewable energy-associated grid-tied converters. This paper presents a novel three-phase differential-mode buck-boost inverter based on two bidirectional buck-boost DC/DC converters and one differential power processor (DPP) unit. The proposed topology is a single-stage DC/AC converter offering bucking/boosting capability, with reduced hardware requirements. The proposed topology features a simplified control methodology in addition to reduced size and cost of the hardware setup which makes it more suitable for grid-tied renewable energy applications. The operation principles, small-signal model, and control strategy of the proposed topology are also illustrated. Simulation and experimental results are presented in details to verify the topology-enhanced performance under various operating conditions. The deducted results elucidate the viability of the proposed configuration alongside with the claimed merits.     

Epoxy/p‐phenylenediamine functionalized graphene oxide composites and evaluation of their fracture toughness and tensile properties

In an attempt to enhance the mechanical properties of epoxy/graphene‐based composites, the interface was engineered through the functionalization of graphene oxide (GO) sheets with p‐phenylenediamine; this resulted in p‐phenylenediamine functionalized graphene oxide (GO–pPDA). The morphology and chemical structure of the GO–pPDA sheets were studied by spectroscopic methods, thermal analysis, X‐ray diffraction, and transmission electron microscopy. The characterization results show the successful covalent functionalization of GO sheets through the formation of amide bonds. In addition, p‐phenylenediamine were polymerized on graphene sheets to form crystalline nanospheres; this resulted in a GO/poly(p‐phenylenediamine) hybrid. The mechanical properties of the epoxy/GO–pPDA composite were assessed. Although the Young's modulus showed improvement, more significant improvements were observed in the strength, fracture strain, and plane‐strain fracture toughness. These improvements were attributed to the unique microstructure and strong interface between GO–pPDA and the epoxy matrix. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43821.     

Deflection Control of Concrete Beams Pretensioned by CFRP Reinforcements

Use of carbon fiber reinforced polymers (CFRP) reinforcement for prestressing concrete structures introduces a promising solution for deterioration of concrete structures due to corrosion of steel reinforcements. Due to the low elastic modulus and limited strain at failure of CFRP reinforcement, partial prestressing could be the most appropriate approach to enhance deformability and reduce the cost in comparison to fully prestressed concrete structures. For members reinforced or prestressed with fiber reinforced polymers reinforcements, serviceability requirements may be the governing criteria for the design; therefore, deflection under service loading conditions should be well defined. This paper introduces simplified methods to calculate the deflection of beams prestressed by CFRP reinforcement under short-term and repeated loading. It also examines the applicability of current approaches available to calculate the deflection. Based on an experimental program undertaken at the University of Manitoba, bond factors are introduced to account for tension stiffening of concrete beams prestressed by CFRP. A procedure to determine the location of the centroidal axis of cracked prestressed sections is also proposed. The proposed methods for deflection calculation are calibrated using the results obtained from different experimental programs. Design guidelines are proposed to predict the deflection of beams partially prestressed by CFRP reinforcement.     

Enhancing Parkinson’s Disease Diagnosis Accuracy Through Speech Signal Algorithm Modeling

Parkinson’s disease (PD), one of whose symptoms is dysphonia, is a prevalent neurodegenerative disease. The use of outdated diagnosis techniques, which yield inaccurate and unreliable results, continues to represent an obstacle in early-stage detection and diagnosis for clinical professionals in the medical field. To solve this issue, the study proposes using machine learning and deep learning models to analyze processed speech signals of patients’ voice recordings. Datasets of these processed speech signals were obtained and experimented on by random forest and logistic regression classifiers. Results were highly successful, with 90% accuracy produced by the random forest classifier and 81.5% by the logistic regression classifier. Furthermore, a deep neural network was implemented to investigate if such variation in method could add to the findings. It proved to be effective, as the neural network yielded an accuracy of nearly 92%. Such results suggest that it is possible to accurately diagnose early-stage PD through merely testing patients’ voices. This research calls for a revolutionary diagnostic approach in decision support systems, and is the first step in a market-wide implementation of healthcare software dedicated to the aid of clinicians in early diagnosis of PD.     

Nanocellulose-Graphene Hybrids:Advanced Functional Materials as Multifunctional Sensing Platform

Naturally derived nanocellulose with unique physiochem-ical properties and giant potentials as renewable smart nanomaterials opens up endless novel advanced fun...     

Preparation of magnetite and silver poly(2‐acrylamido‐2‐methyl propane sulfonic acid‐co‐acrylamide) nanocomposites for adsorption and catalytic degradation of methylene blue water pollutant

The aim of the present work was to prepare microgel nanocomposites based on silver and magnetite to apply as adsorbents and heterogeneous catalysts for removal of methylene blue (MB) cationic dye from aqueous solution. For this, 2‐acrylamido‐2‐methylpropane sulfonic acid (AMPS) and acrylamide (AAm) monomers were used to prepare AMPS/AAm microgel based on the emulsion technique. Ag and Fe₃O₄ nanoparticles were embedded into the AMPS/AAm microgel using the in situ technique. Their particle sizes, surface charges, crystalline lattice structure, morphology, magnetic properties and thermal stability were investigated. The AMPS/AAm hydrogel nanocomposites were used as an adsorbent to remove MB dye. The AMPS/AAm microgel nanocomposites were tested as catalysts to reduce MB and degrade its chemical structure with heterogeneous Fenton oxidation using Ag and Fe₃O₄ nanocomposites, respectively. This study presents promising data as the prepared materials used as adsorbents and catalysts show competitive features compared with the data presented in the literature. © 2019 Society of Chemical Industry     

Evaluating real-life performance of the state-of-the-art in facial expression recognition using a novel YouTube-based datasets

Multimedia Tools and Applications - Facial expression recognition (FER) is one of the most active areas of research in computer science, due to its importance in a large number of application...