Optimization of Starter Motor for Automobile Applications

Normally, both brushed dc Motor and brushless dc motor are used as a starter motor in the automobile application. This paper presents the optimization methodology for brushed PM dc motors. In this brushed dc motor will be a four pole twenty-five slots based machine. This model analysis involves the more number of analytical calculations and computation for the selection of the best model, performance and excellent material characteristics. This method is considered with the existing commercial dc motors to meet the same performance after reduction of weight with change of some parameters; for cranes to lift the loads, various trucks, drill hand tool and automotive application likes car, bike. Optimised DC machine designs using Ferrite permanent magnets are proposed and provide important size and weight reductions without losing of its performance. The finalized model and the  existing model was solved using the MAGNET Software by FEA (Finite Element Analysis) to see the basic performance such as flux density, speed, torque, output power of the existing model

A Novel Hybrid Security Framework (HSF) with Vshield Based Firewall to Secure Cloud Computing Environment

Cloud Computing is an emerging technology that provides an enormous amount of computing resources which includes networks, servers and storages which are accessed through the internet. In addition it allows useful provisioning of the resources based on the user’s demands. A crucial aspect of cloud computing infrastructure is to provide secure and reliable services.  The main challenge lies in the security issues is to reduce the impact of third party attacks in the cloud computing environment. Hence a novel Hybrid Security Framework(HSF) based on Reinforcement Learning (RL) Methodology with Vshield Firewall is proposed for securing the cloud environment.  The RL method is used for deep packet inspection and VShiled based firewall is established to deny the attacks which are malicious when authenticating the signature of incoming packets. The bipartite pattern matching approach is integrated with the RL method to verify the signatures for obtaining the decisions quickly.  The simulation results shows that the hybrid security framework is effective when compared with the existing methods by considering response time, resource utilization and denial of malicious attacks.  This indicates that our proposed framework achieves not only better security but also attains better efficiency in cloud computing environment

Extraction and characterization of pectin derived from underutilized papaya seeds as a value-added product

Food processing industries generate a massive amount of biowastes, which causes major environmental issues. High-level marketable bioproducts can be extracted from these biowastes as value-added products. One such value-added product is pectin. Papaya fruit is one of the tropical fruits that is utilized the most to produce a greater number of processed foods in the food processing industries. Papaya seeds are one of the underutilized parts of papaya and have potential commercial value-added products. The present study aims to extract pectin from papaya seed waste using the hot water extraction technique. Furthermore, one factor at a time (OFAT) was used to find the optimum process conditions for the high extraction of pectin. The parameters considered were liquid–solid ratio (5-50 ml/g), sample weight (5-25 g), extraction time (15-90 min), temperature (50-100°C) and pH (1-3). A high yield of pectin (8.655%) was obtained at a liquid–solid ratio of 25 mL/g, sample weight of 20 g, extraction time of 60 min at 80°C, pH of 1.5 and precipitation with ethanol. Proximate analysis was performed for the papaya seeds that had moisture (82.10%), ash (1.76%), protein (1.52%), fat (1.42%) and carbohydrate (13.20%), and the pectin extracted from papaya seeds were found to have moisture (7.8%), ash (7.6%), protein (2.2%), fat (2.1%) and carbohydrate (80.3%). Pectin was characterized with gas chromatography for its methoxy content, which was found to be 9.216%. The current investigation found that pectin obtained from papaya seeds had low methoxy pectin, which has commercial applications in the jam and jelly industries

Genetic Variability of Human Respiratory Syncytial Virus A Strains Circulating in Ontario: A Novel Genotype with a 72 Nucleotide G Gene Duplication

Human respiratory syncytial virus (HRSV) is the main cause of acute lower respiratory infections in children under 2 years of age and causes repeated infections throughout life. We investigated the genetic variability of RSV-A circulating in Ontario during 2010–2011 winter season by sequencing and phylogenetic analysis of the G glycoprotein gene

Lung Cancer Classification Employing Proposed Real Coded Genetic Algorithm Based Radial Basis Function Neural Network Classifier

A proposed real coded genetic algorithm based radial basis function neural network classifier is employed to perform effective classification of healthy and cancer affected lung images. Real Coded Genetic Algorithm (RCGA) is proposed to overcome the Hamming Cliff problem encountered with the Binary Coded Genetic Algorithm (BCGA). Radial Basis Function Neural Network (RBFNN) classifier is chosen as a classifier model because of its Gaussian Kernel function and its effective learning process to avoid local and global minima problem and enable faster convergence. This paper specifically focused on tuning the weights and bias of RBFNN classifier employing the proposed RCGA. The operators used in RCGA enable the algorithm flow to compute weights and bias value so that minimum Mean Square Error (MSE) is obtained. With both the lung healthy and cancer images from Lung Image Database Consortium (LIDC) database and Real time database, it is noted that the proposed RCGA based RBFNN classifier has performed effective classification of the healthy lung tissues and that of the cancer affected lung nodules. The classification accuracy computed using the proposed approach is noted to be higher in comparison with that of the classifiers proposed earlier in the literatures