Ariffuddin Joret

Design and development of wireless stethoscope with data logging function

Stethoscope is a special device to hear heartbeat sound and monitor pulmonary disease. The most type of stethoscope used these days is the acoustic stethoscope. However, the problem with this acoustic stethoscope is the sound level very low. It is hard to analyze the heart sound and difficult to be diagnosed by a medical doctor. Therefore, this project was developed to monitor and display heartbeat sound using wireless digital stethoscope. The condenser microphone is used as a sensor to capture the low sensitivity of heart sound signal. ZigBee Pro Series 1 wireless module is used to send the heart beat signal wirelessly in 100 meters range. Microcontroller Arduino Nano and Arduino Mega were used as a platform to process the signal and sent the result to the computer. Graphical User Interface (GUI) was developed using MATLAB software to monitor real time electrocardiogram (ECG) waveform and for data logging purpose. The result shows that this device able to transmit and receive ECG waveform wirelessly. The ECG signal can be recorded through data logging application for further analysis by the medical personnel.

Shallow Reflection Method for Water-Filled Void Detection and Characterization

Shallow investigation is crucial in enhancing the characteristics of subsurface void commonly encountered in civil engineering, and one such technique commonly used is seismic-reflection technique. An assessment of the effectiveness of such an approach is critical to determine whether the quality of the works meets the prescribed requirements. Conventional quality testing suffers limitations including: limited coverage (both area and depth) and problems with resolution quality. Traditionally quality assurance measurements use laboratory and in-situ invasive and destructive tests. However geophysical approaches, which are typically non-invasive and non-destructive, offer a method by which improvement of detection can be measured in a cost-effective way. Of this seismic reflection have proved useful to assess void characteristic, this paper evaluates the application of shallow seismic-reflection method in characterizing the water-filled void properties at 0.34 m depth, specifically for detection and characterization of void measurement using 2-dimensional tomography.

Design and Simulation of Horn Antenna Using CST Software for GPR System

Detection of underground object can be made using a GPR system. This system is classified as a non-destructive technique (NDT) where the ground areas need not to be excavated. The technique used by the GPR system is by measuring the reflection of electromagnetic wave signal produced and detected by antenna which is known as the transmitter and the receiver antenna. In this study, a GPR system was studied by means of simulation using a Horn antenna as a transceiver antenna. The electromagnetic wave signal in this simulation is produced by current signal of an antenna which having a shape of modulation of Gaussian pulse which is having spectrum from 8 GHz until 12 GHz. CST and MATLAB Software are used in this GPR system simulation. A model of a Horn antenna has been designed using the CST software before the GPRs system simulation modeled by adding a model of background in front of the Horn antenna. The simulation results show that the output signal of the Horn antenna can be used in detecting embedded object which are made from material of wood and iron. In addition, the simulation result has successfully developed a 3D model image of the GPR system using output signal of the Horn antenna. The embedded iron object in the GPR system simulation can be seen clearly by using this 3D image.

Ashac: An alternative towards classifying the shape of aggregate

A number of image analysis applications are already available to classify the shape of aggregate. These applications were evaluated and compared with our new alternative application called aggregate shape classification system (ASHAC). This newly developed direct measurement methods have the potential to objectively classify two types of aggregate known as well-shaped (fine) aggregate and poor-shaped (coarse) aggregate. The shape properties of these aggregates used in hot-mix asphalt, hydraulic cement concrete, and unbound base and subbase layers are very important to the performance of the pavement system in which they are used in. In terms of its functionality and features, ASHAC provides more accuracy and more reliable system than others. It is an only system based on neural network using digital image processing technique. This methodology offers several advantages over current methods used in practice. Based on the overall performance, ASHAC has successfully classified the two categories of aggregate by 89.00%.