Abstract-Fractal antennas have the characteristic of radiating in multiple frequencies through the property of self similarity that fractal shapes posses. By connecting fractal shaped antennas, wideband coverage can be achieved. Microstrip patch antennas with Sierpinski fractal geometry can be tuned, by design, to work exactly at the bands of interest, through judicious choice of the fractal designs and iteration. Therefore, a broadband dualfrequency microstip patch antenna with modified Sierpienski fractal geometry is designed by using Microwave Office 2002 simulation software. The broadband and multiple frequency characteristics of fractal antennas will be demonstrated. The performance of microstrip patch antenna with the classic and modified Sierpinski fractal geometries will be presented.

Nowadays, person recognition has received significant attention due to broad applications in the security system. However, most person recognition systems are implemented based on unimodal biometrics such as face recognition or voice recognition. Biometric systems that adopted unimodal have limitations, mainly when the data contains outliers and corrupted datasets. Multimodal biometric systems grab researchers’ consideration due to their superiority, such as better security than the unimodal biometric system and outstanding recognition efficiency. Therefore, the multimodal biometric system based on face and fingerprint recognition is developed in this paper. First, the multimodal biometric person recognition system is developed based on Convolutional Neural Network (CNN) and ORB (Oriented FAST and Rotated BRIEF) algorithm. Next, two features are fused by using match score level fusion based on Weighted Sum-Rule. The verification process is matched if the fusion score is greater than the pre-set threshold. The algorithm is extensively evaluated on UCI Machine Learning Repository Database datasets, including one real dataset with state-of-the-art approaches. The proposed method achieves a promising result in the person recognition system.

Health monitoring system has been an interesting topic recently among medical practitioners, engineers as well as IT professionals [1]-[2]. However, the application of automatic temperature monitoring system where parents can monitor the temperature of their children is practically new in Malaysia and other countries. Babies are much more sensitive to high body temperature and any occurrence of fever has to be taken very seriously. Smart body temperature monitoring system for baby and infant is beneficial to the parents where such implementation will help parents to save their energy and time. The objective of this project is to design and develop smart body temperature measurement device that can be observed by the parents for monitoring children body temperature over the time especially night time in case of abnormalities or having high fever. In the proposed method, body temperature wireless sensors is developed. The target of user of this device is children under age of five. This project develops a monitoring method which benefit parents and children by lessen anxiety of parents while ensure the children body temperature is under dangerous level. The prototype showed the temperature reading was successfully receive on the android application. The temperature measurements were validated with Rossmax TG100 with a difference of plus minus 0.5 degree celcius . The temperature sensors will send the readings to one device and triggered the system alarm when the body temperature is exceed the threshold. With this device, the temperature of the children can be monitored automatically over the night and alert to the parents once the reading is triggered.

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