The impact of exchange rate volatility on real total export and sub-categories of real total export of Malaysia

This study aims to investigate the impact of exchange rate volatility on real export in Malaysia. The moving standard deviation with order three (MSD(3)) is used for the measurement of exchange rate volatility. The conventional and partially asymmetric autoregressive distributed lag (ARDL) models are used in the estimations. This study finds exchange rate volatility to have significant impact on real total export and some sub-categories of real total export. Moreover, this study finds that the positive or negative exchange rate volatility tends to have positive or negative impact on real export. Exchange rate volatility can be harmful to export of Malaysia

Segmentation via thresholding methodologies by using measure of fuzziness towards blind navigation

Blind navigation is specialized research directed towards the development of navigational aid for blind people to minimize assistance from sighted individuals during navigation. In this paper, two methodologies of segmentation are detailed and certain aspects of the methodologies are compared. Measure of fuzziness is applied in both the segmentation methodologies to find the threshold values. These methodologies are of an automated process resulting in the elimination of human circumvention. The segmentation methodologies have been found to work suitably for the purpose of blind navigation as shown by the results provided. The first methodology was developed for a single camera whereas the second was developed for a system of stereo cameras. A comparison in terms of results from both the methodologies is also discussed and finally, conclusions derived from the methodologies are presented

Analysis of Surface Electromyography for On-Off Control

Myogram on-and-off controller is important for improving or assisting the elderly people. One of the most important aspects of the controller development is to determine the on and off time with respect to the body movement. In this project, high accuracy signal filtering, high gain amplifier, signal converter, microcontroller and electrodes are used for circuit simulation and development to obtain muscle signal (Electromyogram). Precision rectifier is used to solve the ordinary semiconductor problem to avoid signal block. To ensurethe user-friendliness in the development of this device, non-invasive electrodes are used in this project instead of invasive electrodes

Internet of things based real-time coronavirus 2019 disease patient health monitoring system

The coronavirus disease (COVID-19) outbreak has led to many infected worldwide and has become a global crisis. COVID-19 manifests in the form of shortness of breath, coughing and fever. More people are getting infected and healthcare systems worldwide are overwhelmed as healthcare workers become exhausted and infected. Thus, remote monitoring for COVID-19 patients is required. An internet of things (IoT) based real-time health monitoring system for COVID-19 patients was proposed. It features monitoring of five physiological parameters, namely electrocardiogram (ECG), heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2) and body temperature. These vitals are processed by the main controller and transmitted to the cloud for storage. Healthcare professionals can read real-time patient vitals on the web-based dashboard which is equipped with an alert service. The proposed system was able to transmit and display all parameters in real-time accurately without any packet loss or transmission errors. The accuracy of body temperature readings, RR, SpO2 and HR, is up to 99.7%, 100%, 97.97% and 98.34%, respectively. Alerts were successfully sent when the parameters reached unsafe levels. With the proposed system, healthcare professionals can remotely monitor COVID-19 patients with greater ease, lessen their exposure to the pathogen, and improve patient monitoring

Software-based Malaysian sign language recognition

This work presents the development of a software-based Malaysian Sign Language recognition system using Hidden Markov Model. Ninety different gestures are used and tested in this system. Skin segmentation based on YCbCr colour space is implemented in the sign gesture videos to separate the face and hands from the background. The feature vector of sign gesture is represented by chain code, distance between face and hands and tilting orientation of hands. This work has achieved recognition rate of 72.22%

A study on vehicular ad hoc networks

Vehicular Ad Hoc Networks (VANETs) are special class of Mobile Ad Hoc Networks (MANETs) formed by vehicles equipped with wireless gadgets. The communication in VANET occurs between Vehicle 2 Vehicle mode and Vehicle to road side unit forming an intelligent transport system. Routing plays an important role in forwarding the required data to the nodes or vehicles. In this paper we investigate the performance evaluation of reactive routing protocols such as AODV and DSR and proactive routing protocols such as OLSR in urban city traffic scenario using SUMO and network performance using NS3 to find an appropriate protocol by using network parameters such as packet delivery ratio, throughput and delay. From the simulations we observed that AODV fared well over other routing protocols in VANET scenarios

A study of process identification, frequency response analysis and optimum proportional-integral tunings for an identified temperature control system

Single loop feedback control is commonly used in many industrial applications due to low cost. However, it still deserved an optimum control for the good performance of the controlled process to avoid failures and shutdown of the plants. A good control should have a proper process identification to imply the process dynamic behavior. This paper presents the process identification, frequency response analysis and an optimal PI tuning of a single loop controlled system without involving the complicated stage in determining the best PI tunings for both the servo and regulatory control problems at a nominal point. In realizing the objective, a temperature control function of the Process Control Simulator is chosen. Process identification of the First Order Plus Dead Time is obtained through the developed algorithm. Meanwhile, frequency analysis and the optimal PI tunings are studied by using MATLAB simulation tools. It is found that the produced responses are varied by adjusting the compensator ratio where the optimal PI tunings for a stable and aggressive control is eventually determined

Block Matching Algorithm (BMA) of the Hybrid Adaptive Rood Pattern Search (ARPS) Based on Its Motion Speed

There are several numbers famous proposed Block Matching Algorithm (BMA) in video coding technique and among it, the ARPS is a well known BMA technique that produce lower computational complexity and higher quality of the encoded video at the same time. In general, a video will has a lot of temporal redundancy among its neighborhood frames especially for a low motion video which make encoding a low motion video with smaller MB and bigger p size seemed impractical and vice versa. In this paper, the hybrid version of ARPS technique is used depending on its motion video type either low, medium, or high motion video. Basically this hybrid model works by setting the Macro Block (MB) and Search Range Size, p according to the motion type. Low motion video will be use higher size of MB and smaller size of p, medium motion has medium size of MB and p, and high or fast motion video will use smaller MB and bigger p size. The experimental result shows that by using the hybrid BMA technique, it can produce a better quality of the constructed frame and also it achieve less computational complexity at the same time

Internet of things based real-time coronavirus 2019 disease patient health monitoring system

The coronavirus disease (COVID-19) outbreak has led to many infected worldwide and has become a global crisis. COVID-19 manifests in the form of shortness of breath, coughing and fever. More people are getting infected and healthcare systems worldwide are overwhelmed as healthcare workers become exhausted and infected. Thus, remote monitoring for COVID-19 patients is required. An internet of things (IoT) based real-time health monitoring system for COVID-19 patients was proposed. It features monitoring of five physiological parameters, namely electrocardiogram (ECG), heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2) and body temperature. These vitals are processed by the main controller and transmitted to the cloud for storage. Healthcare professionals can read real-time patient vitals on the web-based dashboard which is equipped with an alert service. The proposed system was able to transmit and display all parameters in real-time accurately without any packet loss or transmission errors. The accuracy of body temperature readings, RR, SpO2 and HR, is up to 99.7%, 100%, 97.97% and 98.34%, respectively. Alerts were successfully sent when the parameters reached unsafe levels. With the proposed system, healthcare professionals can remotely monitor COVID-19 patients with greater ease, lessen their exposure to the pathogen, and improve patient monitoring