ABSTRACT
Collaboration competency in engineering education is receiving more attention and it shall be developed outside the traditional classroom or pedagogy. It is getting challenging to evaluate the effectiveness of the mentioned skills in the COVID-19 pandemic when online distant learning become one of the main approaches regardless the education course. Computer-Support Collaboration Learning (CSCL) method allow educator to evaluate the skills by using creative and innovation ICT tools and platform to conduct cooperative activities even without face-to-face classroom environments. The feature Insight of Microsoft Team and Private Channel enable student and educator to conduct group work and monitoring work respectively in a private and confidential virtual environment. Through the analysis data, it showed a significant outcome when group utilizing ICT tools during the group work. The result also showed the important of leaderships in an engineering group project and formative feedback and consultation of the instructor. © School of Engineering, Taylor's University.
ABSTRACT
The smart IoT scanner for covid-19 contact tracing project was proposed and developed to help increasing the efficiency of the contact tracing process during the covid-19 virus pandemic. As of 15th January 2021, Malaysia has recoded 151066 cases and 586 deaths [1]. The aim of this project is to develop a smart IoT scanner for covid-19 contact tracing by scanning telecommunication signal to break the chain of covid-19 virus transmission. This project digitalized the conventional contact tracing by scanning BLE beacons transmitted by any proximity devices. A custom hardware is developed in this project with the ability to advertise an anonymous ID and scanning other devices for the contact tracing purpose. BLE has been choose as the medium of communication between devices as it consumes low power. All the recorded data can be analysed by the software for the data matching and contact tracing purpose. This method reduces the time to interview covid-19 patient and find the contact by simplifying into a single click method. As the results, this project achieved 72.62% of detection rate between the devices and the average response time between each scan was recorded for 4 seconds. The distance accuracy test between the device shows that the accuracy up to 98.08% can be achieved from this system. © School of Engineering, Taylor's University.
ABSTRACT
Presently, the coronavirus (COVID-19) epidemic presents a major threat to global communal fitness also socio-financial development. Ignoring worldwide isolation as well as shutdown attempts, the occurrence of COVID-19 infected patients continues to be extremely large. Nonetheless, COVID-19's final course, combined with the prevalence of emerging contaminants (antibiotics, pharmaceuticals, nanoplastics, pesticides, and so forth) in wastewater treatment plants (WWTPs), presents a major problem in wastewater situations. The research, therefore, intends near examine an interdisciplinary as well as technical greet to succor COVID-19 with subsequent COVID cycles of an epidemic as a framework for wastewater treatment settings. This research investigated the potential for wastewater-based epidemiology to detect SARS-CoV-2 also the enzymes happening in wastewater conditions. In addition, a chance for the incorporation into the WWTPs of emerging and robust technologies such as mesmeric nanobiotechnology, electrochemical oxidation, microscopy, and membrane processes to enhance the overall likelihood of environmental consequences of COVID-19 also strengthen such quality of water is resolved.
ABSTRACT
A reinforced learning experience (Lx) framework (through a) developed, executed, and evaluated against preCOVID19 and COVID19 operational semesters. This framework is designed through the unlearning approach of the inhouse design thinking tool and lateral executive of curricular delivery, assessments, and evaluations. © 2023 American Institute of Physics Inc.. All rights reserved.
ABSTRACT
Presently, the coronavirus (COVID‐19) epidemic presents a major threat to global communal fitness also socio‐financial development. Ignoring worldwide isolation as well as shutdown attempts, the occurrence of COVID‐19 infected patients continues to be extremely large. Nonetheless, COVID‐19's final course, combined with the prevalence of emerging contaminants (antibiotics, pharmaceuticals, nanoplastics, pesticides, and so forth) in wastewater treatment plants (WWTPs), presents a major problem in wastewater situations. The research, therefore, intends near examine an interdisciplinary as well as technical greet to succor COVID‐19 with subsequent COVID cycles of an epidemic as a framework for wastewater treatment settings. This research investigated the potential for wastewater‐based epidemiology to detect SARS‐CoV‐2 also the enzymes happening in wastewater conditions. In addition, a chance for the incorporation into the WWTPs of emerging and robust technologies such as mesmeric nanobiotechnology, electrochemical oxidation, microscopy, and membrane processes to enhance the overall likelihood of environmental consequences of COVID‐19 also strengthen such quality of water is resolved.