Journal of Advanced Research in Applied Sciences and Engineering Technology

SIRS (Student Involvement Report System) Case Study – Studies on QOS (Quality of Service) Perimeters, Daily Error Types and Activities Within the Server

2024-06-11T15:18:37+07:00

Relational Database Management System (RDBMS) is commonly applied in Small, Medium, and Enterprise businesses. In this research, we investigated Quality of Service (QoS) perimeters over day-to-day operations in RDBMS and how the running process able to be expedited with the adaptation and combination of autonomic computing approach using MAPE-K (Monitor, Analyse, Plan, Execute, and Knowledge Base) and Fuzzy rules. The core function of the system is to monitor student attendance, assessment, and lastly escalation of identified student issues to the department of academic. In a nutshell, it is called the Student Involvement Report (Sir). Two segments have been analysed and focused on errors in request time out, bandwidth, hits, and user activities. The outcomes of this are significant on activities that related to the peak of academic activity, due to the submission of student reports and escalation among departments. The MAPE-K and Fuzzy rules can capture the scenarios and identify rules that are significantly important to reduce and enhance the Request Time Out and Hits activities.

A Comparative Analysis of Machine Learning Models for Prediction of Autism Spectrum Disorder Using Screening Data

2023-11-03T10:10:02+07:00

Autism spectrum disorder (ASD) is a neurological and developmental disorder that affects how people interact with others, communicate, learn, and behave. ASD prediction is difficult because the diagnostic factors may not be based solely on observation. In this research paper, an in-depth comparative analysis of various machine learning models applied to the task of classifying autism traits was presented. Our study aimed to assess the performance of these models within the context of identifying individuals with autism based on relevant features and data. The machine learning models investigated in this study encompassed Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), k-Nearest Neighbours (KNN), Naive Bayes (NB), and Neural Network (NN). The models were evaluated using six essential classification metrics: accuracy, precision, recall, specificity, F1 score, and AUC score. On the training dataset, our results reveal nuanced performance characteristics. SVM and RF excel in precision and recall, showing promise for accurate autism trait classification. KNN exhibits remarkable specificity, suggesting its potential for minimizing false positives. LR and NB demonstrate balanced performance across multiple metrics, while NN exhibits high precision and recall, albeit with higher computational demands. It was concluded that SVM was the best classification model for autism trait classification.

A DEA-Based Malmquist Productivity Approach for Assessing Total Factor Productivity Change in Malaysian Public Universities

2024-01-27T06:04:34+07:00

This study uses the non-parametric frontier method to examine the productivity growth of Malaysian public universities from 2017 to 2021. It examines changes in productivity at university groups and individual institutions, using three inputs (academic staff, undergraduate student enrolment, and postgraduate student enrolment) and three outputs (undergraduate and postgraduate qualifications awarded and publications). This study analyses productivity changes and breaks them down into technical efficiency and technological change using the Data Envelopment Analysis (DEA)-based Malmquist productivity index (MPI). The analysis reveals that public universities in Malaysia have seen an average annual increase in MPI of 0.5% over the period of the study. However, when the components of this productivity change are examined, it becomes evident that Malaysian public universities have had an annual average 1.3% increase in technology along with a 0.8% decline in technical efficiency. Further evaluation of the indexes reveals disparities between Malaysian university groups. Technical, comprehensive, and research universities make up the group that performs the best to the worst. Although Malaysian public universities’ productivity is increasing, it is mostly due to technology, which comes at the expense of decreased technical efficiency.

Technology Trends and Augmented Reality: A Systematics Literature Review

2023-11-02T10:22:05+07:00

The real environment is combined with artificial virtual things to create a dynamic, context-based and interactive augmented reality. Therefore, with the latest advances in augmented reality technology and using diverse displays in mobile computing system, augmented reality is affordable for the public. However, its use, as well as the variety of concepts have not yet been fully explored. Therefore, on this page, we describe the variety of industries that have used augmented reality in a variety of uses as well as a variety of displays. Therefore, in order to find relevant data about various industries using augmented reality, a review study involving filtering information from two databases was done. The results of the analysis found a total of 2,929 primary research articles that had been published between 2020 and 2024. While the literature review found that the authors paid attention to the sample size, methodology, devices used, field and results. We conclude that augmented reality design technology is able to thrive by incorporating more fields and capabilities.

Electrical Tree Image De-Noising using Threshold Wavelet Transform and Wiener Filter

2023-12-08T02:43:17+07:00

Electrical treeing occurred in solid dielectric materials, especially in electrical application with high voltage. The occurrence of electrical tree happens when high electric fields applied, causing tiny channels or paths to form. The main issue during the data collection process is the changes of lighting, making it difficult to study the tree's propagation length, fractal dimension, and growth rate due to corrupted images. This research aims to analyse electrical tree structure images in XLPE material using a CCD camera and develop image de-noising techniques to suppress noise on the electrical tree image. The performance was then analysed using the Otsu thresholding algorithm for accurate segmentation. The methodology was divided into four phases: sample preparation, experimental setup, image pre-processing in MATLAB, and testing four de-noising filters: Wiener, median, NLM, and Gaussian. The Wiener filter with higher PSNR, SNR, and RMSE was selected and using superimposed method, both threshold wavelet transforms and wiener was combined to eliminate the noise. Finally, the proposed method of superimposed was tested with the Otsu thresholding method to evaluate accuracy, sensitivity, and specificity of the combination filter. Based on the analysis of PSNR, SNR, and RMSE, the performance of the threshold wavelet and Wiener filter (TWWF) de-noising technique improves the image quality of the electrical tree structure. Thus, for the Otsu thresholding segmentation algorithm analysis, it also had the highest values in terms of accuracy, sensitivity, and specificity.

Hyperparameter Optimization for Convolutional Neural Network-Based Sentiment Analysis

2024-01-05T07:32:12+07:00

The rapid development of digital technology brings about the importance of product or service opinions as a data source in business intelligence. Sentiment analysis is a business intelligence tool that can help gauge market trends by analysing the available opinions. Various studies have been developed to solve sentiment analysis problems, from selecting feature engineering techniques to selecting sentiment classification models based on classical or deep learning methods. However, these studies still select hyperparameters on a trial basis, which poses problems in terms of time and not optimal performance. Therefore, this research proposes the implementation of Bayesian Optimization to automate the selection of hyperparameters in sentiment analysis based on a Convolutional Neural Network (CNN). The results show that implementing the Bayesian Optimization method has the lowest computation time compared to Random and Grid Searches, which is only 175.746765 seconds, in the fifth trial. In addition, it made a reasonably large cut in terms of times compared to manual trial-based hyperparameter tuning that needs 540 trials. In the model assessment process, implementing Bayesian Optimization gives the highest values on Precision and Specificity, which are 0.8168 and 0.7176, respectively. Thus, implementing Bayesian Optimization is the right choice for sentiment analysis tasks since the precision of predicting negative sentiment classes is vital in hospitality business intelligence, especially the use of related information for product improvement or hotel service improvement. The implementation of Bayesian Optimization not only applied as a reliable hyperparameter selection technique for classification tasks but also regression prediction tasks.

Robo-Advisor Can Play a Role in Promoting Financial Knowledge Within Society

2023-11-22T09:54:19+07:00

This research investigates the role of artificial intelligence, specifically Robo advisors, in society's financial knowledge. Previous studies have mainly focused on the role of Robo advisors in investment decision-making aspects. However, this study focuses on how Robo advisors can facilitate learning in six critical areas of financial planning, both Islamic and conventional. These areas include retirement planning, investment planning, tax and zakat planning, risk management planning, retirement planning, and estate planning. The study interviewed various stakeholders, including bankers, financial education trainers, financial advisors, and members of society. The goal was to gain a comprehensive understanding of the digitization of financial knowledge and the implementation of robo-advisors. The findings reveal that Robo-advisors have the potential to stimulate interest in financial knowledge, particularly if they serve as gateways to a range of financial advisory services and act as tools for providing basic-level financial advice and information sharing. The convenience factor allows individuals to access initial insights into financial knowledge at their preferred time and location. Overall, this study significantly contributes to the advancement of financial education.

Analysis of the Use of Polypad-Based Educational Media on Mathematics Teacher Competencies in Indonesia: A Structural Equation Modelling (SEM) Approach

2024-07-21T15:32:38+07:00

This research focuses on use of Polypad-based educational media to improve the competence of mathematics teachers using the Structural Equation Modelling (SEM) approach. The background to this research includes the challenges in mathematics education in Indonesia, especially in terms of the lack of interactive and relevant educational media, resulting in students' low literacy and numeracy abilities. The problem statement identified is the limitations of media that can affect the effectiveness of mathematics teaching. The main aim of this research is to evaluate the effectiveness of Polypad-based educational media in the context of mathematics learning on the competence of mathematics teachers. The research method used is a quasi-experimental method. Data collection was carried out through questionnaires to measure the effectiveness of Polypad-based educational media in the context of mathematics learning on the competence of mathematics teachers. The quantitative data was analysed using structural equation modelling (SEM) to identify relationships between the variables studied. The research results show that Polypad-based educational media has a significant influence in improving teachers' mathematical competence. SEM analysis revealed a positive relationship between the use of this media and increased competence of mathematics teachers. In conclusion, Polypad-based educational media can increase the effectiveness of mathematics learning and is recommended for application in mathematics education to improve the quality of learning in the future.

Evaluating the Sabah Pay Mobile Application (e-Wallet) using the Technology Acceptance Model

2023-12-05T07:01:41+07:00

The Sabah Pay e-wallet has been introduced as a digital payment solution in the state of Sabah, Malaysia, as part of a digital transformation initiative. However, there is a lack of comprehensive understanding regarding its user acceptance and the factors influencing it. Specifically, there is a need to investigate whether users perceive Sabah Pay as useful and easy to use. This research problem arises due to the importance of user acceptance in the success and sustainability of the e-wallet. Hence, we used the technology acceptance model (TAM) to analyse the perceived usefulness (PU) and customer satisfaction in using the Sabah Pay mobile application and the relationship between perceived ease of use (PEOU) and customer satisfaction using the Sabah Pay mobile application. The Cronbach's Alpha and composite reliability values are higher than 0.7, and the average variance extracted (AVE) is higher than 0.5, which supports the TAM constructs' convergence validity. The square root of AVE for each construct is higher than the corresponding correlations between constructs, which suggests the discriminant validity of the constructs. We used the Partial least squares structural equation modelling (PLS-SEM) to assess the data from the 173 respondents who reported using the Sabah Pay mobile application. We found that PU did not significantly affect customer satisfaction (CS), with a p-value of 0.207, although the path coefficient is 0.109, thus disproving the null hypothesis (H1). However, we supported the second hypothesis (H2) by observing that PEOU substantially impacted CS, with a p-value of 0.000 and a path coefficient of 0.614. The correlation indices demonstrated a satisfactory relationship between the data and the model. This research adds to the body of knowledge on mobile payment platforms by shedding light on perceived usefulness and ease of use factors that most affect users' happiness with Sabah Pay. The study suggests and identifies extensive research into potential customer satisfaction aspects like safety, trust, and value. This study's findings have real-world applications for practitioners and regulators looking to improve the mobile payment platform user experience and, by extension, boost customer happiness and adoption rates.

An MPPT Controller with a Modified Four-Leg Interleaved DC/DC Boost Converter for Fuel Cell Applications

2024-05-20T02:11:17+07:00

A fuel cell system can produce electricity and water more efficiently while emitting near-zero emissions. Internal constraints and operating parameters such as hydrogen, temperature, humidity levels, and oxygen gas partial pressures trigger a nonlinear power characteristic in a typical fuel cell stack, resulting in reduced overall system efficiency. Consequently, it's critical to get the most power out of the fuel cell stack while minimizing fuel use. This study examines and proposes a radial basis function network (RBFN) based maximum power point tracking technique (MPPT) for a 6-kW proton exchange membrane fuel cell (PEMFC) system. The proposed MPPT algorithm modulates the duty cycle of the modified four-leg interleaved DC/DC boost converter (MFLIBC) to extricate the maximum power from the fuel cell system. To validate the execution of the proposed controller, the outcome is related to the various MPPT control strategies such as PID & Mamdani fuzzy inference systems. Finally, it was observed that the proposed RBFN controller has achieved an enhanced efficiency of 83.2 % relative to the PID and fuzzy logic controllers of 75.5 % and 77.4 % respectively. The efficiency of the proposed configuration is analysed using the MATLAB/Simulink platform.

User Acceptance: Quranic Verses Inspire Motivation Used into the Creation of Augmented Reality Board Games

2023-11-03T04:26:20+07:00

Numerous studies have revealed that Malaysian students are developing spiritually and intellectually every year. Mental health illnesses may endanger students' wellbeing and academic progress. Students with mental health illnesses may find it difficult to handle a task or communicate with others due to their inability to control their emotions and lack of desire, which may have an effect on their ability to study. The key to personal behaviour, zeal, and reinforcement for exceptional academic success is motivation. In light of technological improvements, particularly Augmented Reality Board Games (ARBG), a learning tool that can be connected to cell phones has been developed in order to increase motivation. It was found that there is still little research on motivation, particularly when Quranic verses are used in augmented reality. The research method was carried out using a quantitative approach. This study investigates users' approval of employing Qur'anic verses to boost motivation, notably in ARBG technology. It looks at works that were published in six journals over the relevant five-year span (2019-2023). Users acknowledged the Quran's inspirational passages, on the results of the survey, which was carried out as part of the research approach used in this study, which used descriptive statistics of user perception. Students at Malaysia's Sultan Zainal Abidin University (UniSZA) made up the study's subjects (n=100). The survey results show that adding motivational translations of Quranic verses to ARBGs is consistently and favourably viewed by users as having an impact. The study not only produces remarkable findings, but it also paves the way for further investigation into the use of Al-Quran verses and ARBGs.

Solution of Volterra Integral Equations of the Second Kind with Weakly Singular Kernels Using Legendre Polynomials

2024-01-07T09:27:53+07:00

The shifted Legendre polynomials of the first kind are employed to solve second kind Volterra integral equations with weakly singular kernels. In this method the unknown function and the data function are approximated through three matrices, while the kernel function is approximated through five matrices. Regarding the kernel's two variables, it will be approximated twice, first with respect to variable x and second with respect to variable t. The singularity of the kernel is removed analytically. It is proved that the solution is equivalent to an algebraic linear system without applying the collocation method. Two numerical experiments are solved to illustrate the efficiency of the proposed method.

Fostering Innovation in K-12 Education: A Systematic Review of the Integration of Design Thinking within Educational Technology

2023-11-01T10:30:46+07:00

Design Thinking has surfaced as a skill set as well as mindset phenomenon renowned for its problem-solving efficacy in the realms of business, engineering, and corporate endeavors. Nevertheless, the degree to which these skills and mindsets can be harnessed to benefit the field of Education, particularly within the domain of Educational Technology (edtech) at the K-12 educational level, warrants examination. In order to meet this inquiry, the present study conducts a Systematic Literature Review aimed at identifying potential gaps in applying Design Thinking principles within the sphere of Educational Technology, with the objective of making these principles accessible to all stakeholders involved in K-12 education. A comprehensive analysis encompassed 133 articles retrieved from SCOPUS as well as Web of Science (WoS) databases. Moreover, these articles underwent a thorough filtering process following the PRISMA Framework, including 32 articles for final-stage analysis. These 32 articles explored three overarching themes: (1) Design Thinking in education, (2) Student-Centered Learning Environments, and (3) Innovative Educational Technologies. In summation, Design Thinking possesses the potential to enhance the field of Educational Technology, equipping it with the requisite knowledge, skills, values, and mindset necessary to fortify 21st-century-oriented pedagogical practices for K-12 students. Furthermore, this research encourages subsequent investigations by fellow scholars to adapt and refine Design Thinking methodologies in facilitating creative and innovative approaches to Educational Technology and Science, Technology, Engineering, and Mathematics (STEM)-based instruction as well as learning within K-12 educational settings.

Image De-noising Based on WMF Technique for Electrical Trees Structure in High Voltage Cable Insulation

2023-12-08T02:42:18+07:00

Electrical treeing is a common problem during the pre-breakdown phenomenon in solid insulations due to the damage caused by Partial Discharge (PD) that progresses through stressed insulation via chemical degradation, which resembles the shape of a tree root. This resulted in a decrease in performance through degrading the insulation, which became a serious problem while dealing with electrical equipment. Hence, a deep understanding of electrical tree structure is vital to improving the quality of solid insulations. Ergo, optical microscopy is primarily used to examine tree structures, shapes, and fractal dimensions to reconstruct electrical tree structures for morphological study. However, optical microscopy images are frequently degraded by noise from readout procedures or image data acquisition systems, noise caused by occlusion, illumination, non-uniform intensity, destroying potential tree pixels, and a critical loss of information about the electrical tree structures. Therefore, this research proposed the Wiener Median Fusion (WMF) filter for electrical tree study. The performance of the WMF de-noising technique improves the image quality for the precise portrayal of the electrical tree structure based on thresholding segmentation algorithm analysis in terms of accuracy, sensitivity, and false positive rate. Based on the analysis of the thresholding segmentation algorithm, Otsu's thresholding exhibits the highest result compared to Niblack. The Otsu's overall percentage in terms of accuracy is 80.2934%, the sensitivity is 99.1513%, and the false positive rate is 82.6265%.

Temperature Analysis of Single Busbar with Variation of Total Harmonic Distortion in Current

2023-05-10T08:21:43+07:00

Typically, busbars are used to transmit and distribute currents in a bus duct system. The alarming use of nonlinear loads in the industrial sector or at residentials, such as arc welding, computers, ballast lighting, variable speed drives, and so on, has resulted in the generation of harmonics in current distortion, which are uncontrolled and thus increase heat generation within the system. The research conducted in this paper focuses on the prediction of the heat distribution as well as the analysis on operating temperature of a single busbar with compliance to the British National and International Standard (BS 159: 2014) using the Finite Element Method (FEM) in COMSOL Multiphysics software. The copper busbar dimension used for this research was 20mm x 6mm x 300mm, and the fundamental Root Mean Square (RMS) current was 419.1 A. The size of this busbars can withstand the maximum current of 430 A at a maximum operating temperature of 90°C, which complies with the standard requirement. The fundamental current is injected with variation of total harmonic distortion in current up to 55% with an interval of 5%. According to the findings, the operating temperature increases in direct proportion to the increase in total harmonic distortion with the current injections. With the presence of 55% of total harmonics in the current, the current was increased up to 57.73 A from the fundamental current, while the operating temperature was increased up to 140C from the fundamental temperature. The total harmonics in current produced by the nonlinear loads could affect the operating temperature of the busbars, and this continuous operation of current flow will affect the busbars' lifespan due to the occurrence of overheating.

Experimental Investigation of Energy Harvesting by Employing Piezoelectric Element and Metallic Cantilever Beam

2023-11-11T11:18:16+07:00

In this paper, in response to the worldwide energy crisis, a piezoelectric element (0.2*35*50) mounted on a host metallic cantilever beam (0.8*37*220) will be presented as a unique contribution to power generation via the micro-electrical mechanical system. It's made out of aluminium and low carbon steel, both of which have a Young modulus of elasticity of 6.8 and 196 GPa, respectively. In order to take advantage of the engine's vibration as an exciting external force to collect energy in the aforementioned piezoelectric device, the whole rig has been coupled to a diesel engine 5kw 3000 rpm (50 Hz). The average power generated by the aluminium beam was 943 microWatts, while the power generated by the low carbon steel beam was 335 microWatts, an increase of 256%. In addition, for both scenarios, (45) mm from the cantilever beam's fixed point was where the engaged piezoelectric element performed best. The used two metals have different stiffnesses, and this accounts for the obtained difference between the induced powers; increasing the stiffness will result in relatively more power created, and vice versa.