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Comparison between Fuzzy Logic and PI Control for The Speed Of BLDC Motor
No full textIn this paper the analytical comparison of brushless DC (BLDC) motor drive with proportional integral (PI) and fuzzy logic controller (FLC) based speed controllers is estimated. Proportional integral (PI) has disadvantages like it do not operate properly when the system has a high degree of load disturbances. In recent years, the application of fuzzy logic controller (FLC) for high dynamic performance of motor drives has become an important tool. FLC is a good for load disturbances and can be easily implemented. The modeling and simulation of both the speed controllers have been made by MATLAB/SIMULINK. The dynamic characteristics of the BLDC motor (speed and torque) response, obtained under PI and Fuzzy logic based speed controller, are compared for various operating conditio
Survey On The Role Of IoT In Intelligent Transportation System
No full textPrecise and appropriate traffic related data allows travellers to choose suitable travelling modes, travelling paths, and departure time, which is crucial for the success of Intelligent Transportation System (ITS). With the growth of vehicles, the rate of pollution and consumption of fuel has increased, it also creates traffic congestions. For the recent years there has been a rapid growth in technology, which can be explored to solve traffic issues. However, depending upon the available technologies each countries ITS research area may be different. The objective of this literature review is to integrate ITS with internet of things and it also discusses the prospect of clustering, controller system, location identification and resource privacy in ITS
YouTube Spam Comment Detection Using Support Vector Machine and K–Nearest Neighbor
No full textSocial networking such as YouTube, Facebook and others are very popular nowadays. The best thing about YouTube is user can subscribe also giving opinion on the comment section. However, this attract the spammer by spamming the comments on that videos. Thus, this study develop a YouTube detection framework by using Support Vector Machine (SVM) and K-Nearest Neighbor (k-NN). There are five (5) phases involved in this research such as Data Collection, Pre-processing, Feature Selection, Classification and Detection. The experiments is done by using Weka and RapidMiner. The accuracy result of SVM and KNN by using both machine learning tools show good accuracy result. Others solution to avoid spam attack is trying not to click the link on comments to avoid any problems
Validation of S-parameter Power Cable Joint Model on Two Cable Defect Sections
No full textElectricity disruption due to power cable failure is a major challenge to power utility companies worldwide. A technique which provides quick response with accurate result is needed to detect defects along the cable to reduce the disruption time. This paper discusses the application of time domain reflectometry (TDR) technique to identify and locate the defect along a cable. A cable system is modelled in MATLAB/Simulink to replicate the cable configuration with two joints using the scattering parameter (S-parameter). This research studies the fault identification for two degraded sections in a cable by analyzing the reflected signal from the TDR technique. The characteristics of the reflected signal which indicates the defect cable section are discussed in detail in this paper. Results from MATLAB/Simulink simulations are also compared to the experimental results of the same cable configuration. This study shows that the signal reflection characteristics from MATLAB/Simulink simulations are similar to the experimental results. This indicates that the cable model system built using MATLAB/Simulink replicates the actual cable system accurately which can be used for further analysis of cable fault localization
Analysis of the Effect of an Installation of a Single Tuned Passive Filter on Harmonics and Distribution Transformers
No full textNon-linear loads on power systems cause harmonics and losses in distribution transformers. Results of the measurements on the two distribution transformers showed several phase transformer test-driven development (TDD) values above the standard SPLN D5.004-1: 2012. The values were 5.58% in the phase transformer, T 1 and 5.48% and 6.10% in S and T phases of the second transformer, respectively. In the calculations, the transformer losses due to harmonic currents were 1.64 kW in the phase transformer T 1, and 1.64 kW and 1.82 kW in the S and T phases of transformer 2, respectively. Designing a single-tuned passive filter based on the characteristics of the current, voltage, power, and power factor in the phase transformer with a value above the TDD standard can reduce the harmonics and losses. A filter with different specifications in each filtered phase transformer was obtained. The filter reduced the TDD value on the phase transformer T 1 to 3.55% and to 3.88% and 3.43% on the on phase T and S phases of transformer 2. Moreover, it reduced the losses to 0.73 kW on phase transformer T 1, and 1.02 kW and 0.92 kW on the S and T phases of transformer 2.
Hybrid Multilevel Thresholding and Improved Harmony Search Algorithm for Segmentation
No full textThis paper proposes a new method for image segmentation is hybrid multilevel thresholding and improved harmony search algorithm. Improved harmony search algorithm which is a method for finding vector solutions by increasing its accuracy. The proposed method looks for a random candidate solution, then its quality is evaluated through the Otsu objective function. Furthermore, the operator continues to evolve the solution candidate circuit until the optimal solution is found. The dataset used in this study is the retina dataset, tongue, lenna, baboon, and cameraman. The experimental results show that this method produces the high performance as seen from peak signal-to-noise ratio analysis (PNSR). The PNSR result for retinal image averaged 40.342 dB while for the average tongue image 35.340 dB. For lenna, baboon and cameramen produce an average of 33.781 dB, 33.499 dB, and 34.869 dB. Furthermore, the process of object recognition and identification is expected to use this method to produce a high degree of accuracy
Development of Guiding Cane with Voice Notification for Visually Impaired individuals
No full textNavigation in the physical environment is a challenge for those people who have very limited sense of sight or no vision at all. Assistive technologies for blind mobilization is not new and always have a room for improvement. Moreover, these assistive devices are limited in terms of its sensing and feedback abilities. This paper presents a microcontroller-based guiding stick capable of detecting several conditions of the environment such as obstacles in front, left and right positions of the user and detects ascending and descending staircases. The feedback is delivered by an audio output which dictates the direction to go or what condition the sensor detects in front of the user. Technical evaluation proves that the device was functional in terms of its accuracy, responsiveness and correctness. On the other hand, in the actual evaluation of the device with the visually impaired individuals, the device did not perform efficiently. It was also found that the device has the potential to be used effectively by the visually impaired who acquired their blindness in later stage of their life provided that they will have a proper training in using the device while navigating in the physical environmen
K-NN Classification of Brain Dominance
No full textThe brain dominance is referred to right brain and left brain. The brain dominance can be observed with an Electroencephalogram (EEG) signal to identify different types of electrical pattern in the brain and will form the foundation of one’s personality. The objective of this project is to analyze brain dominance by using Wavelet analysis. The Wavelet analysis is done in 2-D Gabor Wavelet and the result of 2-D Gabor Wavelet is validated with an establish brain dominance questionnaire. Twenty-one samples from University Malaysia Pahang (UMP) student are required to answer the establish brain dominance questionnaire has been collected in this experiment. Then, brainwave signal will record using Emotiv device. The threshold value is used to remove the artifact and noise from data collected to acquire a smoother signal. Next, the Band-pass filter is applied to the signal to extract the sub-band frequency components from Delta, Theta, Alpha, and Beta. After that, it will extract the energy of the signal from image feature extraction process. Next the features were classified by using K-Nearest Neighbor (K-NN) in two ratios which 70:30 and 80:20 that are training set and testing set (training: testing). The ratio of 70:30 gave the highest percentage of 83% accuracy while a ratio of 80:20 gave 100% accuracy. The result shows that 2-D Gabor Wavelet was able to classify brain dominance with accuracy 83% to 100%
Hexa-band MIMO CPW Bow-tie Aperture Antenna using Particle Swarm Optimization
No full textA MIMO hexa-band Bowtie Antenna for Wi-Fi is proposed. The MIMO antenna can operate at six frequency bands: 2.4, 4.4, 6.1, 8.5, 10.25 and 12.8 GHz. The MIMO antenna consists of four loaded bowtie hexa-band antennas having the same structure. Each single antenna element is loaded with six metallic strips as well as interconnected parasitic rectangular components. The presented HFSS simulations will show that the MIMO loaded antenna can operate at six frequency bands including 2.4 GHz by obtaining the return loss results, radiation patterns, and other antenna parameters. It will be shown also that the MIMO bowtie antenna has a very low mutual coupling at all the operating frequencies for the specific loaded metallic strips width which was obtained using Particle Swarm Optimization technique
Review on Security Aspects for Cloud Architecture
No full textCloud computing is one of the fastest growing and popular technology in the field of computing. As the concept of cloud computing was introduced in 2006. Since then large number of IT industries join the queue to develop many cloud services and put sensitive information over cloud. In fact cloud computing is no doubt the great innovation in the field of computing but at the same time also poses many challenges. Since a large number of organizations migrate their business to cloud and hence it appears as an attractive target for the malicious attack. The purpose of the paper is to review the available literature for security concerns and highlight a relationship between vulnerabilities, attacks and threats in SaaS model. A mapping is being presented to highlight the impact of vulnerabilities and attacks