International Journal of Advances in Applied Sciences
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Simulation and manufacturing of modified circular monopole microstrip antenna for UWB applications
Get PDFUltra-wideband (UWB) technology is one of the most promising wireless communication solutions to be developed quickly because of the high-speed data, wide bandwidth and excellent immunity to multipath interference. In this work, the compact design of a modified circular monopole microstrip antenna is simulated and manufactured for the UWB applications. The simulation process of the proposed antenna was done based on the finite integration of the computer simulation technology (CST) microwave studio (MWS). The proposed antenna comprises a copper radiating patch, Roger’s Kappa-438 substrate, and a single stub act as a reflector. The simulation results showed a reasonable agreement with the results of the measurement and good performance was achieved in the range from 1.8 to 10 GHz with VSWR less than 2.0
Non-linear creep of polypropylene utilizing multiple integral
Get PDFMultiple integral representation (MIR) has been used to represent studying the effect of temperature on the amount of nonlinear creep on the semi-crystalline polypropylene (PP) under the influence of axial elastic stress. To complete this research, the kernel functions were selected, for the purpose of performing an analogy, and for arranging the conditions for the occurrence of the first, second and third expansion in a temperature range between 20 °C-60 °C, i.e., between the glass transition and softening temperatures, within the framework of the energy law. It was observed that the independent strain time increased non-linearly with increasing stress and non-linearly decreased with increase in temperature, although the time parameter increased non-linearly with stress and temperature directly. In general, a very satisfactory agreement between theoretical and practical results on the MIR material was observed
Enhanced model based algorithm to reinforce PV system with dynamic MPPT capability
Get PDFPhotovoltaic (PV) power has emerged as the most attractive resource in form of a clean and green energy. However, one major challenge associated with PV interfacing is its intermittent output characteristic which varies dramatically with the operating conditions. Thus designing an effective maximum power point tracking (MPPT) algorithm is a key aspect for optimizing PV system performance. Numerous MPPT algorithms have been proposed earlier having their own specific advantages. However, these are found to have two major limitations which have to be essentially addressed. Firstly, they become ineffective in the dynamic conditions where there is rapid change in environmental parameters like insolation and temperature. Secondly, they fail to discriminate between global and local peaks under partial shading conditions. Therefore, to achieve a reliable and efficient system operation, this paper presents an enhanced model-based (MB) algorithm that overcomes both these deficiencies. Based on new governing equations and precised estimation technique, it predetermines the MPP analytically. First simulated results are obtained where it is tested for dynamic variations of all the three parameters. Then the experimental validation is carried out on a 2 KW installed panel where real time data is recorded through CR1000 data logger and environmental parameters are sensed with elements like pyranometer and humidity sensor. A large number of experimental results are obtained for tracked MPP in the dynamic conditions, which are then summarized in tabular forms. These are finally plotted and compared with simulated results to illustrate the effectiveness of proposed MB algorithm
A review on the plant secondary metabolites with special context with North East India
Get PDFExtracting phytochemicals or phytocompounds for the upliftment of general health and sustainability is one of the greatest needs of the millennium. Plants have immense quality in regard to secondary metabolites although not required for general growth and development yet are very much necessary for forming a protective gear and maintaining homeostasis. With their immense diversity in curing various diseases, these plants' secondary metabolites therefore must be put forth and given much importance in generation and production from the root level to the mission worldwide. Along with the increasing cases of failure in the usage of chemotherapeutic drugs and their utilities, the implementation of secondary metabolites for their various medicinal characteristic in therapeutic cases are also increasing in demand. With the increasing demand for Ayurveda treatment and the popularity of the mass, it can be positively taken up as a means of earning capital and making self-sustaining. North-Eastern states of India in this regard are a vital source of income and also a media to generate and bring indigenous products to the world
Dashboard for analyzing SCADA data log: a case study of urban railway in Malaysia
Get PDFThe operation of maintenance in the railway industry is a high priority for safety which reflects the train services. The Kelana Jaya Line (KJL) is the leading urban metro train operator among light rail transit (LRT) categories in Malaysia. The main issue in KJL, they are facing huge historical data from the supervisory control and data acquisition (SCADA) logger when organizing the corrective maintenance work schedule. The previous conventional method leads to time constraint which causes redundancy of data reading. Hence, the SCADA dashboard was developed as a tool to structure their work prioritization for weekly planning. It was developed by using Microsoft Power Query and Power Pivot, in the advanced Excel software. The dashboard evaluation was performed based on usability and user experience studies. The evaluation test proves that the dashboard can be used effectively and it’s beneficial to the organizations as well as a contribute towards systematic maintenance
Trainable generator of educational content
Get PDFAs the main problem of the research, the possibility of creating a universal educational platform that combines the possibilities of an online generation of educational content with the interface of the training process itself was considered. The methodology of the educational platform has been developed, in which the mass generation of content is carried out at random, based on simulation models of educational objects. A matrix interface is used, which allows performing custom operations by entering a sequence of typical operators. The system forms a reference base of operators, replenishing it from user solutions, which makes it possible to train and improve the system in order to provide methodological support to student users. An active demo layout of an educational content generator was created and tested, using the example of a specific problem from school mathematics. All methodological options function in the layout. There are three interface options: administrative, training and control. It was concluded that the approach based on the simulation of educational objects makes it possible to create a unified algorithmic platform that combines the functions of content generation with educational training. The system contains a unique option to teach yourself based on its interaction with students
An application system for the design of the spindle tool clamping mechanism
Get PDFThe heart of the machining center design is the spindle design, and one of the primary functions in the spindle design is a tool clamping system mechanism. The selection of disc spring stack for a tool clamping mechanism is an iterative process that highly depends on the spindle space availability, drawbar design, tool unclamp stroke length, and standard clamping force requirements. For example, even a design space of 0.1 mm may impact one kN clamping force depending on the disc spring stack design. Hence the design of the tool clamping system for a spindle is a time-intensive process and also needed careful attention. The iterative process of disc spring stack selection may lead to an unoptimized tool clamping system, which may not be the best design. This paper explains a dynamic way to find the best spring stack selection to optimize the spindle tool clamping mechanism based on the computational application
Confirmatory factor analysis: model testing of financial ratios with decision support systems approach
Get PDFThe decision support systems approach can be developed into both computer-based and quantitative analysis tools. This research uses a model test with a confirmatory factor analysis (CFA) technique on matrix covariance against structural equation modelling (SEM) methods to measure financial ratios. Decision support system (DSS) analysis uses numerical calculations aided by mathematical models through six phases. The first three phases of a structured approach to building multivariate models and the next three phases, namely estimation, interpretation, and validation, are developing from data input that has been selected using LISREL version 8.72. The financial ratio’s testing model with a CFA approach derived into a mathematical (quantitative) model can explain the complexity of the relationship between the goodness-of-fit models (GOF) with a different approach from prior research. The goodness-of-fit test results in this study produced scores on each of the financial ratio measurement models at an accuracy level of CR of 78.49, TATO of 1.26, DER of 41.41, ROA of minus 0.033, and PBV of 540.92. This means that PBV has the highest standardized loading factors to determine the measurement of financial ratios. The CFA measurement based on SEM can be used to make appropriate decisions and combine a model comparison and redevelopment of the CFA technique and model testing with other software such as SPSS, PLS, AMOS, and others
Deep learning model for glioma, meningioma, and pituitary classification
Get PDFOne of the common causes of death is a brain tumor. Because of the above mentioned, early detection of a brain tumor is critical for faster treatment, and therefore there are many techniques used to visualize a brain tumor. One of these techniques is magnetic resonance imaging (MRI). On the other hand, machine learning, deep learning, and convolutional neural network (CNN) are the state of art technologies in recent years used in solving many medical image-related problems such as classification. In this research, three types of brain tumors were classified using magnetic resonance imaging namely glioma, meningioma, and pituitary gland on the based of CNN. The dataset used in this work includes 233 patients for a total of 3,064 contrast-enhanced T1 images. In this paper, a comparison is presented between the presented model and other models to demonstrate the superiority of our model over the others. Moreover, the difference in outcome between pre- and post-data pre-processing and augmentation was discussed. The highest accuracy metrics extracted from confusion matrices are a precision of 99.1% for the pituitary, a sensitivity of 98.7% for glioma, a specificity of 99.1%, and an accuracy of 99.1% for the pituitary. The overall accuracy obtained is 96.1%
Review of protection aspects of microgrid devices
Get PDFA microgrid is required to provide reliable, quality and efficient supply of both electricity and heat demands to its customers when operates either in autonomous or in grid-connected modes. In this context, it is most important to address a comprehensive protection scheme of the microgrid suiting both the modes of operations. This paper concentrates on the impacts of various devices, like distributed energy resources (DERs), transformers, switches, microgrid topology, communication type, grounding type, to name a few, on the microgrid protection systems. The paper reviewes previous works for the various aspects, like characteristics, construction, of these devices in the light of protection. This review-work is useful for future research in the field of microgrid protection as well as in the selection of its devices