Space Vector Pulse Width Modulation Technique Applied to Two Level Voltage Source Inverter

Space vector pulse width modulation SVPWM provides a better technique compared to the other pulse width modulation techniques. This paper presents simulation and implementation of SVPWM signal generation for driving three phase two level voltage source inverter VSI, also proposes and analyzes a new switching sequence for generating an SVPWM. Simulation results are obtained using the simulation package PSIM. and the inverter performance is evaluated in terms of total harmonic distortion (THD). The model is experimentally implemented and verified on Arduino Mega Atmega2560 microcontroller

Preparation and characterisation of polyethylene-octene grafted maleic anhydride-toughened 70:30 PA6/PP/MMT nanocomposites

A series of nanocomposites consisting of a polyamide 6 (PA6) and polypropylene (PP) matrix (70:30) with a maleated polyethylene-octene elastomer (POEgMAH) and organophilic modified montmorillonite (MMT) were prepared by melt compounding in a co-rotating twin-screw extruder followed by injection moulding. The weight fraction of organoclay was adjusted from 2 - 10 wt% by increments of 2 wt% and the weight fraction of POEgMAH was fixed at 10 wt%. POEgMAH was used as an impact modifier as well as compatibiliser in the nanocomposites. Mechanical properties of the blends were investigated by tensile, flexural and impact testing. X-ray diffraction (XRD) was used to characterise the nanocomposites. The thermal properties were studied by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). Addition of 4 wt% organoclay showed the highest tensile and flexural strengths for the blends. The Young's and flexural moduli were also improved with increasing the organoclay concentration but with a corresponding reduction in impact strength and elongation at break. XRD result revealed that the organoclay was dispersed uniformly (exfoliated) although the degree of exfoliation decreased with increasing organoclay content. The DSC analysis showed that the crystallinity of the blends decreased with increasing organoclay concentration. It was shown from the TGA analysis that the thermal stability of the PA6/PP nanocomposites was significantly improved in the presence of impermeable silicate layers in the blends

An Empirical Study Towards an Automatic Phishing Attack Detection Using Ensemble Stacking Model

Phishing attacks have become one of the most attacks facing internet users, especially after the COVID-19 pandemic, as most organizations have transferred part or most of their work and communication to become online using well-known tools, like email, Zoom, WebEx, etc. Therefore, cyber phishing attacks have become progressively recent, directly and frankly reflecting the designated website, allowing the attacker to observe everything while the victim is exploring Webpages. Hence, utilizing Artificial Intelligence (AI) techniques has become a necessary approach that could be used to detect such attacks automatically. In this paper, we introduce an empirical analysis for automatic phishing detection using several well-known machine learning classification algorithms compared with an ensemble learning model for detecting phishing sites based on the uniform resource locator (URL) using two preprocessed datasets. In this empirical study, we concluded that the ensemble model grants accuracy 97.49% for dataset 1 and 98.69% for dataset 2, which gives higher accuracy than using a single machine learning classification algorithm such as Naive Bayes (NB), Decision Trees (DTs), Random Forest (RF), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA). We also compared the proposed ensemble model with one of the most recent similar model

SmoothFlood: decreasing redundant messages and increasing search quality of service in peer-to-peer networks

Flooding search is a basic searching scheme for unstructured peer-to-peer networks. This technique produces exponentially redundant messages in each hop. Subsequent growths of redundant messages will limit system scalability and will cause unnecessary traffic in network areas. To improve this searching scheme and reduce redundant messages, this paper proposed a novel algorithm (SmoothFlood) which divides flooding scheme into two stages. In first stage algorithm follows standard flooding by the limited number of hops, but in the next stage it will choose nosy nodes in each region. These nodes maintain the data index of all clients’ nodes. This proposed algorithm extends the search quality by reducing redundant messages in each hop. Simulation results show it will decrease more than 65 percentages of redundant messages and will save up to 70 percentages of searching traffic

Optimization of medium for the production of β-cyclodextrin glucanotransferase using Central Composite Design (CCD)

Production of cyclodextrin glucanotransferase (CGTase) from Bacillus G 1, a new bacterial isolate was optimized in shake-flask cultures using statistical design approach. An efficient fermentation medium producing CGTase with high activity (54.9U/ml) was determined: A 2(5) Central Composite Design (CCD; half fraction) has been chosen to elucidate the combined effect of five process variables; tapioca starch, peptone, yeast extract, magnesium sulphate and potassium phosphate concentration. Concentrations of 4% tapioca starch, 2% peptone, 0.04% magnesium sulphate and 1 % sodium carbonate have been shown to be optimum for the production of CGTase

Toughening polyamide 6 nanocomposites with maleic anhydride grafted polyethylene octene

Rubber toughened nanocomposites consisting of ternary blends of polyamide 6 (PA 6), maleic anhydride grafted polyethylene octene (POEgMAH) and organoclay montmorillonite (MMT) were prepared by melt compounding followed by injection moulding. The organoclay content was kept constant at 4 wt% while the POEgMAH content was varied between 5 to 20 wt%. The mechanical properties were studied through tensile, flexural and impact properties. The scanning electron microscope (SEM) and X-ray diffraction (XRD) were used to examine the morphology of the nanocomposties. The results showed that, the incorporation of 4 wt% organoclay significantly increased the stiffness and strength but at the expense of the toughness. Izod impact measurement indicated that the addition of POEgMAH led to a significant improvement in the impact strength of the nanocomposites. X-ray diffraction analysis (XRD) revealed that an intercalation organoclay silicate layer structure was formed in rubber-toughened PA6 nanocomposites. SEM study revealed a two-phase morphology where POE, as droplets was dispersed finely and uniformly in the PA6 matrix

Prediction of the optimum asphalt content using artificial neural networks

The performance of the asphalt mix is significantly influenced by the optimum asphalt content (OAC). The asphalt content is responsible for coating the aggregate surface and filling the voids between the aggregate particles. Thus, the aggregate gradation has a significant influence on the required asphalt content. The Marshall design process is the most common method used for estimating the OAC, and this process is called the asphalt mix design. However, this method is time consuming, labor intensive, and its results are subjected to variations. Thus, this paper employs the artificial neural network (ANN) to estimate the OAC from the aggregate gradation for the two most common gradations used in asphalt mixes in Egypt (3D, 4C). Results show that the proposed ANN can predict the OAC with a coefficient of correlation of 0.98 and an average error of 0.026%. As a result, a new approach for the Marshall test can be adopted using results of the proposed ANN, and only three specimens, instead of fifteen, are prepared and tested for estimating the remaining parameters. This approach saves the time, effort, and resources required for estimating the OAC. Additionally, the ANN was validated with previously developed models, and the ANN shows promising results

Theory and empirical evidence of the gender wage gap

Women participation in the labor force has steadily increased over the last several decades, Despite this, women still remain in lower status, less interesting and less well paid jobs. Differences in family and economic roles between men and women have resulted in wage discrimination between men and women. Attempts to explain the gender wage differential generally rely on human capital and labor market segmentation theories. The human capital theory attributes wage differentials to differences in education, training and work experience. Labor market segmentation theory on the other hand attribute wage differentials to the segmentation of the labor market into primary and secondary sectors. The human capital theory remains the dominant theory explaining wage differentials between male and females. Research evidence does suggest that differences in the level of education and experience between male and female influence wages

Pendidikan bukan formal (PBF) di Malaysia: cabaran dan hala tuju Wawasan 2020

Pendidikan Bukan Formal (PBF) adalah pelengkap kepada pendidikan formal dan tidak formal. Justeru itu, ia amat penting dan bermakna kepada pembangunan manusia secara menyeluruh; selain membantu dalam proses pembangunan sesebuah negara. Pendidikan Bukan Formal amat penting kepada sesebuah negara yang sedang pesat membangun seperti Malaysia. Oleh yang demikian, pendidikan seumpama ini secara langsung atau tidak langsung mampu membangunkan literasi masyarakat dalam pelbagai disiplin ilmu seperti teknologi maklumat, pengurusan, kemanusiaa dan kemasyarakatan, keusahawanan, kenegaraan dan sebagainya. Pengayaan dan penguasaan ilmu pengetahuan amat penting dalam membina masyarakat yang berilmu dan bertamadun. Tentu sekali, dalam konteks Malaysia ia dapat dicapai menerusi minat dan ketekunan masyarakat dan galakan yang diberikan oleh pelbagai pihak termasuk kerajaan untuk belajar terus menerus sepanjang hayat. Justeru itu, kertas kerja ini akan memerihalkan bagaimana Pendidikan Bukan Formal boleh menjadi katalis kepada Pendidikan Sepanjang Hayat di Malaysia. Secara konseptual, kertas kerja ini akan dimulai dengan definisi konsep, jenis dan bentuk Pendidikan Bukan Formal. Selanjutnya, kertas kerja ini akan menjelaskan tentang faktor penarik dan penolak yang secara tidak langsung memberi kesan terhadap penglibatan masyarakat dan peranan yang dimainkan oleh pihak kerajaan, Pertubuhan Bukan Kerajaan mahu pun swasta. Paling penting, Pendidikan Bukan Formal ini akan disorot dalam pelbagai perspektif seperti pelan perancangan dan pembangunan negara, modenisasi dan pembangunan sosioekonomi. Selain itu, kertas kerja ini turut mengupas isu permasalahan yang timbul dalam perancangan dan pelaksanaan Pendidikan Bukan Formal Di Malaysia. Akhirnya, kertas kerja ini akan merumuskan akan harapan dan cabaran Wawasan 2020 dan Pendidikan Bukan Formal di Malaysia