The Effect Of Vapor Grown Carbon Nanofiber-Modified Alkyd Paint Coatings On The Corrosion Behavior Of Mild Steel

Organic coatings are extensively used as protective coatings in several industries including the automotive and aircraft industries. The last few years have witnessed an increased interest in improving not only the mechanical properties but also the corrosion protection properties of organic coatings. Among the currently investigated methods of improving the performance of organic coatings is the incorporation of additives in the organic paint matrix. Vapor grown carbon nanofibers (VGCNFs) are a class of carbon fibers that are produced by catalytic dehydrogenation of a hydrocarbon at high temperatures. Depending on the method of synthesis and the post-treatment processes, the diameter of the VGCNFs is normally in the 10-300 nm range. The small size, light weight, high aspect ratio, and unique physical, thermal, mechanical, and electrical properties of VGCNF make it an ideal reinforcing filler in polymer matrix nanocomposites to enhance the mechanical properties of the pure polymeric material in high performance applications in several industries such as the automotive, aircraft, battery, sensors, catalysis, electronics, and sports industries. The main objective of the current investigation was to study the corrosion protection offered by the incorporation of VGCNFs into a commercial alkyd paint matrix applied to the surface of mild steel coupons. The corrosion protection was investigated by immersing samples in air saturated 3% NaCl solution (artificial seawater). The samples were studied by electrochemical impedance spectroscopy (EIS) along with other measurements, including electrochemical (open circuit potential, cyclic voltammetry), chemical (salt spray test), electrical conductivity, and surface analysis (SEM, AFM, optical profilometry, and nanoindentation). The study involved the investigation of the effect of the weight percent (wt %) of the VGCNF as well as the coating film thickness on the corrosion protection performance of the coated steel samples when exposed to the corrosive electrolyte. By way of contrast, the EIS behavior of steel coupons coated with a paint coating incorporating different weight percents of powdered silicon carbide (SiC) particles was also studied. The EIS spectra were used to calculated and graph several corrosion parameters for the investigated systems. At the end, the studied coatings were ranked in order of their anticorrosive properties

Present a feature selection technique based on machine learning in order to increase the detection rate of classifiers using CHOA algorithm

In creating a pattern classifier, feature selection is often used to prune irrelevant and noisy features to producing effective features. Feature selection algorithms; try to classify an instance with lower dimension, instead of huge number of required features, with higher and acceptable accuracy. In fact an instance may contain useless features which might result to misclassification. An appropriate feature selection methods tries to increase the effect of significant features while ignores insignificant subset of features. In this paper, an efficient feature selection algorithm based on Cheetah optimization algorithm and support vector machine (CHOA-SVM) was used. First a population of cheetahs (feature subsets) were randomly generated, and then optimized by CHOA-SVM wrapper algorithms; finally the best fitness feature subset was applied to SVM classification. Experiments over a standard benchmark demonstrate that applying CHOA-SVM in the context of feature selection is a feasible approach and improves the classification results. The simulation experiment results have proved that the feature subset selection algorithm based on CHOA-SVM is very effective

Providing an efficient framework for power theft detection based on combination of Raven roosting optimization algorithm and clustering and classification techniques

One of the main concerns of power generation systems around the world is electricity theft. One of the goals of the Advanced Measurement Infrastructure (AMI) is to reduce the risk of electricity theft in the electric smart grids. However, the use of smart meters and the addition of a security layer to the measurement system paved the way for electricity theft. Nowadays, machine learning and data mining technologies are used to find abnormal patterns of consumption. The lack of a comprehensive dataset about abnormal consumption patterns, the issue of choosing effective features, the balance between consumer\u27s normal and abnormal consumption patterns, and the choice of type and number of classifiers and how to combine them are the challenges of these technologies. Therefore, a detection system for electricity theft that is capable of effectively detecting theft attacks is needed. To this end, a framework including data preparation phases, feature selection, clustering, and combined modeling have been proposed to address the aforementioned challenges. In order to balance normal and abnormal data, 6 artificial attacks have been created. Moreover, with respect to the Chief element in the Raven optimization algorithm and its two-step search feature, this algorithm has been used in feature selection and clustering phases. Stacking as a two-step combined modeler has been used to strengthen the prediction of accuracy. In the second step of this modeler, the meta-Gaussian Processes algorithm is used due to the high accuracy of detection. The Irish Social Science Data Archive (ISSDA) dataset has been used to evaluate performance. The results show that the proposed method identifies dishonest customers with higher accurac

The Effect Of Vapor Grown Carbon Nanofiber-Modified Alkyd Paint Coatings On The Corrosion Behavior Of Mild Steel

Organic coatings are extensively used as protective coatings in several industries including the automotive and aircraft industries. The last few years have witnessed an increased interest in improving not only the mechanical properties but also the corrosion protection properties of organic coatings. Among the currently investigated methods of improving the performance of organic coatings is the incorporation of additives in the organic paint matrix. Vapor grown carbon nanofibers (VGCNFs) are a class of carbon fibers that are produced by catalytic dehydrogenation of a hydrocarbon at high temperatures. Depending on the method of synthesis and the post-treatment processes, the diameter of the VGCNFs is normally in the 10-300 nm range. The small size, light weight, high aspect ratio, and unique physical, thermal, mechanical, and electrical properties of VGCNF make it an ideal reinforcing filler in polymer matrix nanocomposites to enhance the mechanical properties of the pure polymeric material in high performance applications in several industries such as the automotive, aircraft, battery, sensors, catalysis, electronics, and sports industries. The main objective of the current investigation was to study the corrosion protection offered by the incorporation of VGCNFs into a commercial alkyd paint matrix applied to the surface of mild steel coupons. The corrosion protection was investigated by immersing samples in air saturated 3% NaCl solution (artificial seawater). The samples were studied by electrochemical impedance spectroscopy (EIS) along with other measurements, including electrochemical (open circuit potential, cyclic voltammetry), chemical (salt spray test), electrical conductivity, and surface analysis (SEM, AFM, optical profilometry, and nanoindentation). The study involved the investigation of the effect of the weight percent (wt %) of the VGCNF as well as the coating film thickness on the corrosion protection performance of the coated steel samples when exposed to the corrosive electrolyte. By way of contrast, the EIS behavior of steel coupons coated with a paint coating incorporating different weight percents of powdered silicon carbide (SiC) particles was also studied. The EIS spectra were used to calculated and graph several corrosion parameters for the investigated systems. At the end, the studied coatings were ranked in order of their anticorrosive properties

Populist discourse and the remaking of political opposition in Venezuela

Artículo originalIn recent years, two main political poles have consolidated in Venezuela, those in favor of the late President Hugo Chávez or Chavistas and those in opposition. Despite their divergent propositions and deep social polarization, the two camps share similarities, and in a way each camp has reinforced the existence of the other through its discursive practices. This paper investigates the role of the opposition in consolidating a populist discourse in Venezuela. Through a qualitative content analysis of online news articles, the paper shows that the ideas and discourse of the anti-Chávez movement between 2000 and 2012 consolidated the populist discourse of the Chavista governmen

Grading zero waste design using digital and virtual methods

Doctor of PhilosophyDepartment of Apparel, Textiles, and Interior DesignSherry J. HaarTraditional practices of pattern cutting within the apparel industry result in a considerable portion of fabric waste that negatively impacts the environment. Currently, garment manufacturers make responding to fashion trends, at the lowest possible cost, the main priority, regardless of fabric waste, to ensure economic profit. Besides, one of the sustainable challenges when working with zero waste design (ZWD) is the feasibility of pattern grading under the current apparel production system. Thus, the purpose of this experimental study was to explore the feasibility of grading zero waste garments for industry production using digital and virtual methods. The main research questions in this study were: What pattern piece adjustments and marker layouts achieve both 100% marker efficiency and accurate virtual visual appearance? Can digital 3D simulation be used as an effective and sustainable sizing and fit assessment tool? Does attachment and appreciation of ZWD influence expert judges’ evaluation of visual accuracy? The first research question was answered through a functional design process that included three phases: sample development, grading and marker making, digital and virtual testing of marker adjustments, and marker refinement. The application of typical and novel marker making and design tactics for functional utilization of the cuts offs resulting in no fabric waste of the mixed marker of the graded sizes was explored. As a result, a system of four different adjustment methods were applied to reach 100% marker efficiency while maintaining visual accuracy. Multiple challenges regarding the use of 3D simulation to create virtual samples were encountered. To answer the second and third research questions, an online questionnaire was utilized to collect assessment related to the efficiency of the graded virtual samples compared to the physical based on particular design criteria. Two judge groups participated in this study, zero waste design academic researchers and industry technical designers. The judges compared the samples via video, between and across groups. The findings indicated that the use of 3D simulation was mostly challenging for grading ZWD while maintaining 100% marker efficiency and visual accuracy. Judges suggested that the 3D simulation would be a useful, sustainable tool for fit and appearance assessment to decrease the number of physical samples; however, major improvements for the software were recommended before the physical sample could be eliminated. These findings contribute to understanding the effectiveness of sizing zero waste design and use of 3D virtual simulation as an assessment method, which promotes sustainable development through pattern making within the production methods in the apparel industry. Technical judges had more agreement than ZWD judges regarding the similarity between virtual and physical samples, and the sufficiency of information provision by virtual samples that would replace physical samples. Thus, ZWD judges had higher expectations for virtual technology. This finding indicated a relationship between attachment and appreciation of sustainability in fashion with the adoption of advanced practices to develop sustainable fashion design through the functional design process