Journal of Advanced Research in Applied Sciences and Engineering Technology

Using Analytical Hierarchy Process for Medical Equipment Maintenance and Replacement Decision in Malaysia Private Hospitals

2023-08-18T02:34:35+00:00

Medical equipment is any instrument, appliance, software, or material intended by the manufacturer to be used, alone or in combination for medical purpose. Further, medical equipment maintenance and replacement is a challenging procedure, especially for high-end equipment. This topic has been a long debate as the equipment will increase undesirable failure; where an early maintenance or replacement will result in high investment costs and premature disposal and late maintenance or replacement will lead to malfunctions that can pose serious risks to patient safety and healthcare operations. However, hospitals are unable to decide whether to maintain or replace the equipment especially when the equipment reaches its life and has a high repair cost. A few studies were conducted on the same research topic, but most of the findings emphasized maintenance and replacement methods rather than the criteria contributing to the decision. The criteria to maintain or replace medical equipment play an essential role to ensure the equipment is operating cost-effectively. Hence, the objective of this research is to apply Analytical Hierarchy Process (AHP) approach to prioritize important criteria that influence decision-makers to decide whether to maintain or replace medical equipment. Some of potential criteria for the decision-making include maintenance cost, support, and regulatory compliance. This research utilized a mixed method approach to gather preliminary data from medical equipment experts and surveys to prioritize the criteria. Findings suggested a list of criteria that are influenced in decision-making to maintain or replace the medical equipment. The prioritization of the criteria reveals the downtime, life cycle cost and beyond economical repair (BER) to be the most important criteria.

Analyzing the Impact of Loss Functions on Dehazing Effectiveness and Unveiling the Discrepancy between Quantitative and Qualitative Results

2024-01-10T14:45:46+00:00

The work focuses on the analysis of the impact of loss functions on the effectiveness of a model for dehazing images. Dehazing, the process of removing haze or atmospheric scattering from images, plays a crucial role in various computer vision applications. To enhance the performance of dehazing models, it is essential to examine different loss functions and their variations. In this study, we employ a Generative Adversarial Network (GAN) as our model and evaluate the performance of various loss functions. The primary objective is to assess how well each loss function is capable of dehazing an image, while specifically investigating the influence of various structural similarity index (SSIM) loss variations on the dehazing effectiveness. Our experimental results reveal a notable discrepancy between qualitative and quantitative outcomes. Contradicting the traditional interpretation in literature, our qualitative analysis reveals that the SSIM IQA metric may not be a fully reliable indicator of dehazing effectiveness despite it being viewed to be correlated to human visual perception unlike Mean Square Error and Peak Signal to Noise Ratio Metrics. Moreover, we demonstrate that relying solely on quantitative results may lead to the selection of an inappropriate loss function. This finding emphasizes the significance of qualitative analysis in evaluating the performance of dehazing models. The disparity between quantitative and qualitative results emphasizes the need for newer image assessment metrics in the domain that can effectively bridge this gap. Such metrics should be able to be better correlated with human perception. This research contributes to the field of image dehazing by shedding light on the importance of qualitative analysis in addition to quantitative evaluation. By comprehensively analysing the impact of variations of SSIM loss functions and their combination with Mean Absolute Error (MAE) loss, we provide valuable insights into enhancing the effectiveness of dehazing models.

The Numerical Solutions of weakly singular Fredholm integral equations of the Second kind Using Chebyshev Polynomials of the Second Kind

2024-01-07T09:37:49+00:00

In this study, the second kind Chebyshev Polynomials were utilized to acquire interpolated solutions for the second kind Fredholm integral equations with weakly singular kernel. To accomplish this, the data, unknown, and kernel functions were converted into matrix form, and consequently we completely isolated the singularity of the kernel. The primary benefit of this method is the ability to change the form of integral equation to an equivalent algebraic system, which is easier to solve. The effectiveness of our technique was evaluated by applying it to three illustrated examples, and it was observed that the solutions obtained exhibit strong convergence towards the exact solutions.

A Light Review on Cyber Security Awareness Models for the Elderly

2023-06-22T15:25:13+00:00

Millions of people use the internet daily, including the elderly, who are among the most at-risk groups for cybercrime, such as fraud, hacking, and cyberbullying. However, there has been a lack of cybercrime studies focusing on them. Additionally, various cybersecurity models deployed by governments and organizations are found to be inconvenient and too technical for the elderly, especially those with impairments or conditions that require special attention. This subsequently leads to an increasing number of cybercrimes. Therefore, this paper presents a light review of existing cybersecurity models suitable for the elderly. Three methods were used to review existing cybersecurity awareness models. First, a feasibility study was conducted following several works of literature related to cybersecurity, types of cybercrimes involving the elderly, characteristics of the elderly commonly targeted by cybercriminals, cybersecurity awareness models, and the elderly's learning styles. Second, based on the literature review, the elderly's learning styles were analyzed. Finally, the cybersecurity awareness model suitable for the elderly was chosen and analyzed with respect to their phases, validity, and technicality. In conclusion, the SCSAM-Elderly was selected as the most suitable model for the elderly to learn and spread awareness of cybersecurity. This study could increase cybersecurity awareness and encourage educating the elderly to maximize their knowledge of cybersecurity. The findings from this study can guide organizations, agencies, governments, and educational institutions in their endeavours to educate the elderly about cybercrime and cyberattacks.

Wavelet Transform-based Methods for Forensic Analysis of Digital Images

2023-12-21T08:13:32+00:00

In recent years, Generative Adversarial Networks (GANs) have been utilized in many applications of our daily lives to create digital media that was previously impossible. This paper utilizes GANs in multimedia forensics, where the precision and accuracy of image classification are crucial. The objective of the study is to detect sophisticated manipulated images generated by advanced deep learning methods using classical transformation methods. The method combines the classical wavelet transform for feature extraction with a classifier model to distinguish between real and fake images. The proposed method extracts unique features that differentiate between fake and real images, which are then fed to several gradient-boosting-based classifiers. The proposed method was tested using the FaceForensics++ dataset, which contains low-resolution video sequences of faces. The proposed model achieves an accuracy of 95% in detecting manipulated videos compared with 87% accuracy of other classical techniques.

Design and Development Research (DDR) Approach in Designing Design Thinking Chemistry Module to Empower Students' Innovation Competencies

2023-06-23T03:33:55+00:00

Design and evaluation processes to provide an empirical basis for producing instructional and non-instructional products, tools, and new or improved development models. This method uses various methods, including qualitative and quantitative techniques, and thoroughly examines the literature. The design and development of this chemistry module using design thinking to empower students' innovation competencies are described in this article. The main challenge for the teaching implementation process that is capable of mastering the skills of generating new ideas and solving problems in the real world is preparing teaching materials, consuming time, and putting pressure on the teacher. Teachers need more support resources to translate the expected teaching practices. This effort aims to generate a new perspective in education, especially chemistry education, in developing student innovation competence in secondary schools in Malaysia. Therefore, this study aims to discuss the design and development research (DDR) approach used to develop a design thinking chemistry module using a DDR approach. The researcher will go through three study phases and use several different research approaches in each phase. In the first phase, the researcher investigated the teachers' needs in their pedagogy used in teaching and students' innovation competencies. The second phase is the design and development phase, involving the consensus of twelve experts in various fields, such as chemistry/science, technology, engineering, and mathematics (STEM), curriculum development, module construction experts, and research and innovation planning experts. Consequently, the final phase is implementation and evaluation, focusing on determining the module's effectiveness in teaching and learning. Expert consensus is the primary input in developing modules in Malaysian chemistry education. Malaysian education needs to bring a different educational paradigm and teaching strategy, which includes the impact of teacher pedagogy through design thinking in the future. The conclusion of this article proposes a conceptual framework for the research to contribute to the advancement of design thinking and chemistry education.

Breaking Language Barriers: How E-Learning Enhances Metacognitive Awareness and Self-Efficacy in Foreign Language Acquisition

2023-06-22T09:40:46+00:00

With its plethora of advantages, learning foreign language brings out a lot of benefits to students. Acquiring the foreign language has the potential to attract students to uplift the educational environment to be more productive and more strategised. Unfortunately, acquiring the foreign language can be troublesome since students were unaware of the skills and strategies needed. This paper explains the pilot test approach to a proposed framework model based on metacognitive awareness and self-efficacy before embarking on the extensive research necessary to develop best practices in foreign language learning. The content validity index and a pilot study were used to determine the usability and reliability of a survey questionnaire. Based on a simple random sampling plan, an online survey method was used to gather data from 163 respondents at the Universiti Malaya, Malaysia. The results indicate that the instrument's content validity index value is 0.9. The Cronbach alpha values for most of the constructs in the proposed framework model ranged between 0.9 and 0.7, indicating that the constructs are highly reliable. To contribute to the body of knowledge, the researchers provide an overview of the pilot test procedures as well as the methodology that was utilized. Based on the integration of the unified theory of acceptance and use of technology and the strategies needed to acquiring foreign language, a proposed framework model is presented to provide a more comprehensive framework model. It is concluded that the questionnaire items are deemed suitable and acceptable for further examination on a larger scale. As a result, the instrument can be investigated further in other contexts.

Robust Segmentation of COVID-19 Chest X-Ray Images: Analysis of Variant k-Means Based Clustering Algorithms

2023-05-09T06:24:09+00:00

Computer aided diagnosis (CADx) become one the most famous method in diagnostic medical field due to the high reliability and efficiency. Recently, the coronavirus disease (COVID-19) has become severe global pandemic. Particularly, the Chest X-ray (CXR) imaging has become an essentiality in COVID-19 detection. As a result, the convergence of CADx technology with Chest X-ray analysis has achieved great efficiency in COVID-19 diagnosis. Therefore, the research value of CADx in COVID-19 diagnosis is exceptionally high. This study aims to evaluate different k-means based clustering algorithms and identifying the one with the highest overall accuracy. First of all, 150 COVID-19 CXR open-source images are acquired from Kaggle and Github. All the images will be unified into a same image size with 1000*1000 pixels and quality during the image pre-processing. Next, the resized images are enhanced by the Modified Global Contrast Stretching (MGCS) enhancement method to increase the quality of images. Then, the traditional k-means, k-medians, k-medoids and fast k-means clustering methods have been implemented in the image segmentation. At the same time, five different numbers <2, 4, 6, 8, 10> of clusters also tested out in this study. Lastly, all the segmented is proceeded to the segmentation performance based on sensitivity, specificity, accuracy, precision, recall and F-score. The result proves that the k-medoids clustering algorithm with 2 clusters archived the best overall segmentation performance as it obtained the highest sensitivity, accuracy, recall and F-score with 66.14%, 87.98%, 0.6614 and 0.7327.

Numerical Scheme by Legendre-Galerkin for Characterization of Micropolar-Maxwell Unsteady Fluid Model

2023-12-22T08:53:46+00:00

In this dissertation, Micropolar-Maxwell unsteady fluid flow prior an expanding sheet is asymptotically investigated using an efficient Legendre-Galerkin technique in the existence of magnetic field. By employing fitting similarity mapping to the controlling partial differential equations, a system of nonlinear ordinary differential equations is obtained. In comparison to the prior studies, the suggested asymptotic outcomes are guaranteed. The impacts of elasticity/material parameters on velocity/micro-rotation profiles are shown and explored with the help of tables and figures to enhance the mechanical properties of the sheet.

An Artificial Intelligence Approach to Monitor and Predict Student Academic Performance

2023-05-05T07:25:26+00:00

Recent progress in technology has altered the learning behaviours of students. It can easily be said that the improvements in technologies especially from the area of artificial intelligence and data mining can empower students to learn more efficiently, effectively, and contentedly. The purpose of this paper is aimed at developing a prediction model that gives a guide to the stakeholders likes university, student’s sponsor and parents that can monitor and interpret the on-going student’s performance. The proposed system will help the user to identify students who have a high risk or low risk to ending the semester with unsatisfactory results through discovering the essential features that can influence student’s academic performance. The methodology used were mixed method approach which is qualitative and quantitative. For the part of quantitative technique, the data set for this research will be collected from the academic records section. Meanwhile, the part of qualitative will go through a few main stages which are focused on developmental phase. The prediction model used in this research are RepTree, k-NN and Naïve Bayes. The finding states that RepTree had the highest accuracy compared to k-NN and Naïve Bayes techniques. It also suggests that the RepTree algorithm would be the best prediction model which has focused the research in term of developing the system of monitoring students’ academic performance at UPTM.

Hand Joint Position Analysis System for the Care of Patients with Rheumatoid Arthritis

2023-06-30T15:09:04+00:00

According to the studies carried out in advance, the medical area has analysed the patient's condition visually by applying a common methodology to all patients based on their knowledge of the disease, making a mistaken assessment due to the complexity of the disease, which varies according to the length of time the patient has been suffering from it. The problem posed by this disease rheumatoid arthritis is the bad evaluation by means of radiographs of the hands, relying on the criteria of the doctor when treating the disease with his experience, making serious mistakes when the quality of the image is not correct when interpreting a first stage disease with an advanced one, therefore, it is important to evaluate rheumatoid arthritis by means of an image treatment in a safe way for a better diagnosis of the patient. The aim of this research is to develop a hand joint position analysis system for the care of patients with rheumatoid arthritis to help doctors detect tuberculosis earlier and more accurately and to avoid prolonged infections that could be fatal for patients. The methodology used for this research is based on taking a computerized X-ray of both hands and applying image processing using a computer, the image processing is carried out using MATLAB by applying the various processing tools to detect these conditions. According to the tests performed, it was observed that the system detects the state of the patient with rheumatoid arthritis with an efficiency of 96.14% in its operation, standing out satisfactorily with respect to other systems for its high efficiency of image analysis of patients with the MATLAB tool. It concludes that this system can be used in different circumstances of the patient's condition, from the initial stage of arthritis to an advanced stage of the patient's disease.

Time Aware Long Short-Term Memory and Kronecker Gated Intelligent Transportation for Smart Car Parking

2023-09-28T18:26:28+00:00

Technology desires to improve quality of life and impart citizen’s health as well as happiness. The concept of Internet of Things (IoT) refers to smart world where prevailing objects are said to be embedded and hence interact with each other (i.e., between objects and human beings) to achieve an objective. In the period of IoT as well as smart city, there is requirement for Intelligent Transport System-based (ITS) ingenious smart parking or car parking space prediction (CPSP) for more feasible cities. With the increase in population and mushroom growth in vehicles are bringing about several distinct economic as well as environmental issues. One of pivotal ones is optimal parking space identification. To address on this problem, in this work, Time-aware Long Short-Term Memory and Kronecker product Gated Recurrent Unit (TLSTM-KGRU) for smart parking in internet of transportation things is proposed. The TLSTM-KGRU method is split into two sections. In the first section, smart parking occupancy is derived using Time-aware Long Short-Term Memory (Time-aware LSTM) for Kuala Lumpur Convention Centre car parking sensor dataset. Following which the resultant smart car occupancy results are subjected to Linear Interpolations and Kronecker product Gated Recurrent Unit for predicting smart parking. When compared against other predictive methods such as SGRU-LSTM and CPSP using DELM, our experimental outcomes denote that TLSTM-KGRU method has improved performance for smart parking occupancy forecast as it not only enhances sensitivity and specificity but also reduces prediction time with minimum delay.

Beam Steering using Space-Time Modulated Coding Metasurface Based on Reconfigurable Plasma Ionization

2024-01-11T11:50:30+00:00

This paper explores the use of space-time coding in beam steering, using 1-bit, 2-bit, and 3-bit reconfigurable coded meta-surfaces. By periodically changing the code arrangement in the time domain, a metasurface with code order in space and time is achieved. Selected codes are used to steer the beam in different directions for radar sensing systems applications. The phase of the harmonic signal is changed by controlling the position of different bits in each code sequence. The construction of 8×8 unit-cell elements (120×120×3.2 mm3) involves the use of a grounded dielectric container filled with inert-argon gas. The metasurface logic-state is controlled via the ionization degree of inert-gas with time-switching controlling the harmonic frequencies. Different time-switching sequences are investigated for beam steering. The proposed coding metasurface is analysed using CST Microwave Studio and the results are compared with the analytical solution using MATLAB.

Understanding the Role of Digital Identity: A Conceptual Framework and Proposed Methodology for Measuring Malaysia's National Digital Identity Initiative

2023-06-22T02:34:06+00:00

Malaysia is in the process of developing a National Digital Identity (NDI) system to provide citizens and residents with secure and efficient access to digital services. However, the success of the initiative depends on public awareness, perception and acceptance of the system. This paper proposes a preliminary framework for measuring public awareness, perception and acceptance of the NDI initiative in Malaysia. The framework was developed based on an extensive literature review and includes several important variables, including public awareness, perception and acceptance, as well as perceived usefulness, perceived ease of use, user experience, social influence and facilitating conditions. The proposed research design is based on a quantitative methodology using a questionnaire to collect data from a diverse sample of respondents. The proposed framework and methodology are a valuable contribution to the literature on the NDI initiative and can provide a foundation for future empirical research in this area. By using a rigorous research design, this study can provide valuable insights into the public's attitudes and perceptions towards this initiative, which can inform policy decisions and contribute to the successful implementation of the NDI initiative in Malaysia. The study contributes to the ongoing discussions on digital identity (DI) and provides valuable insights for policy makers, practitioners and researchers seeking to promote the adoption of DI systems in Malaysia and beyond.

Risk Classes of Cloud Computing Project in Healthcare: A Review of Technical Report and Standards

2024-01-01T12:34:39+00:00

Cloud computing has been shown to have positive impacts on the organization such as “cost savings”, “enhanced efficiency”, etc. Cloud computing has been implemented in multiple sectors around the world including the healthcare sector. The rise of chronic illnesses requires the assistance of new technologies such as cloud computing to bring flexibility and convenience to treat these illnesses. However, as with all IT architecture projects, there are risks and challenges to adopting cloud computing. As such this study aims to find the prevailing risk classes of cloud computing projects in healthcare through risk classes discussed in technical reports and standards. This study will employ TLR as a method for this study. Through this study, we found five technical reports and standards that discuss the risk management of cloud computing. The result shows that there are 13 prevalent risk classes of cloud computing. We hope that the results discovered through this study can help academics, researchers, and practitioners to recognize what are the prevalent risk classes currently discussed regarding cloud computing and whether the discussion has matured or not.

Exploring Students’ Creativity Using STEAM-Based Reading Texts

2023-03-23T07:35:17+00:00

Creative thinking is one of the important skills required to face the 21st century challenges. However, students’ creativity assessment is challenging. Grounded on the paradigm that creativity is a tangible parameter, this study aims to explore students’ creative thinking skill via a reading-based creativity test. The test was developed by considering the creativity indicators defined by Paul Torrance, i.e., fluency, flexibility, originality, and elaboration. In this creativity test, the reading and the questions were designed to make students integrate their science, technology, engineering, arts, and mathematics (STEAM) knowledge. Based on the empirical validation, the creativity test had a reliability of 0.897, indicating that the test was reliable to measure students’ creativity. Due to the Covid-19 pandemic, the test was conducted online to 108 junior high school students in East Java, Indonesia. In general, the students achieved the highest level of creativity in terms of originality that gained average score of 3.63 (with scale 4.00). Meanwhile, they underperformed on the aspects of elaboration having average score of 2.40. There were 93 and 79 students who responded very well on the originality and fluency aspects, respectively. In contrast, respectively over 30% and 50% of students showed a lack of creativity on the aspect of flexibility and elaboration. These creativity assessment data are beneficial for educational stakeholders especially to increase the quality of teaching and learning related to STEAM education.

A Comparative Review on Acoustic and Inductive Power Transfer

2023-06-20T07:05:57+00:00

Wireless Power Transmission (WPT) has emerged as a prominent player in numerous industries recently. It is already established in wireless charging for electric cars and electronic gadgets. However, it has promising applications in medical implants and imaging as well. Among several proposals, Inductive Power Transfer (IPT) and Acoustic Power Transfer (APT) have shown a major impact on this area of interest. This paper presents a comparison between IPT and APT for wireless power transmission (WPT). Most recent proposals are reported, and several key parameters are considered to evaluate the proposals. That includes operating frequencies, separations gaps, powers and power transmission efficiencies and experimental validity. It is found from the review that; a maximum 818 kW of power is transmitted using IPT for electric vehicles. However, APT can transmit 1.068 kW and 5.4 W through wall and in-body medium (implants). Over 90% efficiencies are found for both APT and IPT. In fact, power transfer with 95.66% efficiency over a 6 cm distance of 23.4 W is achieved for APT and 95.6% with 20 cm separation gaps is achieved for IPT for 20 kW power. A wide range of frequencies are applied for both APT and IPT. However, lower frequencies are mostly suitable for high power, more specifically less than MHz ranges. Naturally, lower frequencies are preferable for low power high efficiencies.

An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA

2024-01-15T03:32:49+00:00

Network intrusion detection is an essential component of contemporary cybersecurity strategies, and the development of efficient techniques to accurately identify malicious activities has become a priority. This study investigates the performance of various conventional machine learning algorithms, including decision trees, naive Bayes, naive Bayes trees, random forest, random trees, MLP, and SVM, in detecting network intrusions using binary and multi-classification approaches. Furthermore, the study proposes a deep learning method, CNN-LSTM-SA, which consistently outperforms conventional machine learning techniques in terms of precision, recall, F1 score, and overall accuracy for network intrusion detection. Specifically, the proposed method combines CNN and LSTM with SA in machine learning theory to extract more optimized, strongly correlated features. The proposed method is evaluated using the benchmark NSL-KDD database. The results indicate that the CNN-LSTM-SA method holds great potential in enhancing the efficacy of network intrusion detection systems.

Novel Orthogonal Time Frequency Space Based on Universal Filter Multi Carrier for 6G Wireless Networks

2024-02-14T13:40:46+00:00

Obtaining an efficient multicarrier signalling technique is an essential part in signal processing of the (6G) wireless networks. In order to achieve their intended objectives, the 6G mobile networks needs the utilization of a multicarrier scheme that possesses the ability to withstand multipath fading and inter-symbol interference (ISI), as well as exhibit resilience against inter-carrier interference (ICI) and Doppler spread. In recent research, several filter-based methods have been suggested, including Filter Bank Multicarrier (FBMC), as well as various Orthogonal Frequency Division Multiplexing (OFDM) based techniques such as Universal Filtered Multicarrier (UFMC). Orthogonal Time-Frequency Space (OTFS) technique has been identified as a promising candidate waveform for 6G, particularly in high-mobility scenarios, where it has demonstrated superior performance compared to traditional OFDM-based techniques. The OTFS method offers an advantage in that it can be considered the pre-and post-processing stages for techniques based on OFDM. This papaer presents the design (OTFS) using (UFMC) technique. Additionally, a novel structure is proposed for coded/uncoded UFMC-based OTFS technique, which combines the advantages of both strategies while mitigating their limitations. The results of our analysis demonstrate that the UFMC-based OTFS system exhibits superior performance in terms of error probability and time-spectral efficiency compared to the OFDM-based OTFS system.