Chittagong University of Engineering & Technology

About: Chittagong University of Engineering & Technology is a education organization based out in Chittagong, Bangladesh. It is known for research contribution in the topics: Computer science & Renewable energy. The organization has 1200 authors who have published 1444 publications receiving 10418 citations. The organization is also known as: Engineering College, Chittagong & Bangladesh Institute of Technology, Chittagong.

Traffic sign detection and recognition using fuzzy segmentation approach and artificial neural network classifier respectively

Abstract: Traffic Sign Recognition (TSR) system is a significant component of Intelligent Transport System (ITS) as traffic signs assist the drivers to drive more safely and efficiently. This paper represents a new approach for TSR system where detection of traffic sign is carried out using fuzzy rules based color segmentation method and recognition is accomplished using Speeded Up Robust Features(SURF) descriptor, trained by artificial neural network (ANN) classifier. In the detection step, the region of interest (sign area) is segmented using a set of fuzzy rules depending on the hue and saturation values of each pixel in the HSV color space, post processed to filter unwanted region. Finally the recognition of the traffic sign is implemented using ANN classifier upon the training of SURF features descriptor. The proposed system simulated on offline road scene images captured under different illumination conditions. The detection algorithm shows a high robustness and the recognition rate is quite satisfactory. The performance of the ANN model is illustrated in terms of cross entropy, confusion matrix and receiver operating characteristic (ROC) curves. Also, performances of some classifier such as Support Vector Machine (SVM), Decision Trees, Ensembles Learners (Adaboost) and K-Nearest Neighbor (KNN) classifier are assessed with ANN approach. The simulation results illustrate that recognition using ANN model is higher than classifiers stated above.

Voltage mode control of single phase boost inverter

Abstract: Boost inverter is able to generate an AC voltage whose peak value can be larger or smaller than the DC input voltage in a single stage. The boost inverter consists of two individual boost DC-DC converters. Each of the boost DC-DC converters has to be controlled in variable operating point condition. This paper proposes two voltage mode controllers. First one is conventional feedback controller based on small signal model. Second one is a simplified voltage mode controller based on feedforward pulse width modulation (FF-PWM) and simple voltage feedback loop to control the output voltage of the boost inverter. The second controller gave better result. The controller also ensures output voltage to meet IEEE Std 519 voltage harmonic limits. Unlike most previously proposed controllers, the proposed method is based only on output voltage feedback, making unnecessary the inductor current measurement. The control method is verified by means of simulations.

Modeling and performance analysis of a generalized photovoltaic array in Matlab

Abstract: A generalized photovoltaic array simulation model in Matlab/Simulink environment is developed and presented in this paper The model includes PV module and array for easy use on simulation platform The proposed model is designed with a user-friendly icon and a dialog box like Simulink block libraries This makes the generalized PV model easily simulated and analyzed even with a maximum power point tracker Considering the effect of solar irradiance and temperature change, the output current and voltage of PV modules are simulated and optimized using the proposed model The model was tested using a directly coupled dc load as well as an ac load via an inverter The test result validates the model which can be used in related research works

Design of a Miniaturized Slotted T-Shaped Microstrip Patch Antenna to Detect and Localize Brain Tumor

Abstract: This paper presents a miniaturized, single-fed, slotted T-shaped, body worn antenna mainly designed for detecting and locating brain tumor which operates in the frequency band 902-928 MHz of Industrial, Scientific, and Medical (ISM) band. The key prominences of the proposed antenna are its minuscule dimension, vast bandwidth, good parameter results to identify affected and unaffected human brain tissue. The dimension of the proposed antenna is 29.99 mm × 29.99 mm × 0.59 mm, which has been placed over a complete human head phantom model consisting of six different layers; designed in CST Microwave Studio without altering their dielectric properties to carry out the simulation. Several performance measurements have been performed for both normal condition and tumor affected conditions changing the tumor positions with respect to the antenna. Analyzing these data, the location of the tumor can be estimated. A tumor having a radius of 5 mm with conductivity and permittivity of 7 S/m and 55 respectively, has been taken into consideration for the simulation process. The maximum SAR (specific absorption rate) of the proposed model measured 0.332 W/ Kg which satisfies the required safety guidelines.