Conference Publications
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PublicationA review paper on face recognition techniques(IEEE, 2023)The study of computer vision and pattern recognition is growing because of the various commercial and practical applications of these disciplines. Identification of individuals in a multitude, access control, forensics, and human-computer interactions are only among the topics studied by these areas. However, analyzing unconstrained face recognition poses ethical issues and privacy concerns. Many recent proposals employ Holistic Methods, Geometric Approach and Local-Texture Approach, methods and databases like ORL, FERET and AR Dataset to study constrained face recognition. At least some understanding of 2D perspective was achieved. This occurred in highly controlled environments where parameters such as camera angles, lighting and distance were strictly regulated. However, significant degradation in recognition performance occurred if the environment changed or the subject smiled or frowned. This critique discusses the technology utilized in face recognition, as well as the databases of methods that utilize this technology. To help guide future research, this article discusses current knowledge and suggests future directions for study in the field of facial recognition.
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PublicationShort-time fourier transform with optimum window type and length: an application for sag, swell and transient(Springer, 2023)The characteristics of power quality signals are non-stationary, where the behaviour confirms the negative consequence in sensitive equipment. Modern cross-term time-frequency distributions (TFDs) are able to characterize the power quality accurately but suffer from a delay in measurement since the power quality signals, in this case, sag, swell and transient, need to be analyzed in real-time. It is shown that one window shift (OWS) properties of linear time-frequency representation (TFR) results from short-time Fourier transform (STFT) satisfies accuracy, complexity and memory. By optimally selecting the window length of 512, the TFR is able to provide optimal time, and frequency localization, as well as the spectral leakage, can be reduced by the Hanning window. The proposed technique can accurately characterize the power quality signals averagely by 95%, as well as the complexity and memory usage is low. Finally, the paper is concluded by the recommendation of pre-setting for optimum window type and length for real-time power quality measurement.
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PublicationAn emerging detection design adopting two-keying technique in SAC-OCDMA-based MDW code(IEEE, 2023)This paper aims to enable the two-keying approach in spectral-amplitude coding optical code-division multiple-access (SAC-OCDMA) system that employs modified double weight (MDW) code. To achieve this goal, two-keying subtraction detection (TKSD) is suggested, which also declines the impact of multiuser interference (MUI) and phase-induced intensity noise (PIIN). The results of simulation test demonstrate that the TKSD is efficient in realizing the two-keying detection feature in SAC-OCDMA system with superior bit-error rate (BER) performance, security, and transmission rate.
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PublicationThe design of photovoltaic based mobile dental healthcare system(IEEE, 2023)Renewable energy has been growing in the medical field for the past decades. The technological development in the dental healthcare system brings lots of benefits to people, especially those who live in rural areas. This is because rural areas lack efficient transportation and power supply systems. Hence, this work focuses on the design of a mobile dental truck that uses renewable energy, particularly solar energy. In this paper, three different types of photovoltaic systems have been presented from which the optimum design is integrated into a mobile dental truck. In addition, energy management and the amount of energy usage in a mobile dental truck system are determined accordingly. The analysis of the system performance is then carried out, which aims to design and simulate energy demand in the dental system. This work demonstrates that renewable energy technology, particularly photovoltaic systems, can be implemented into mobile trucks for dental healthcare system applications.
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PublicationIoT-based laboratory safety monitoring camera using deep-learning algorithm(Springer, 2023)The monitoring system available in the market currently does not come with detection of clothing that abide to the safety standard. The purpose of this project is to develop, analyze, and evaluate IoT-based laboratory safety monitoring camera using deep learning algorithm. This project is developed base on the System Development Life Cycle (SDLC) model. In which there are five steps to be taken which is analyze, design, develop, implement, and evaluate. The OpenCV library for Python is used to develop the programming of the PPE detection algorithm and the system also integrates the element of IoT which is developed using the platform Telegram to send notification. Technical analysis was conducted for the circuit, detection algorithm, and notification system before the project was handed over to expert for evaluation purposes. The project was evaluated by three experts that have expertise in the field of electric and electronic using the checklist instrument from the aspect of design, necessity, and functionality. The findings of the response by the expert show that it was very positive towards the project objective and it can be more optimized by expertly trained algorithms. This can increase the amount of individuals being monitored and further modify the project so that it could be used on any environment to control the door remotely.