International Journal of Advances in Applied Sciences
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The study of requirements for the workforce of the digital industries using web scraping techniques
Get PDFThis study investigates workforce requirements in Thailand's digital industries, focusing on qualification requirements across five industry groups: hardware and smart devices, software and software services, digital service, digital content, and telecommunication. Employing Python-based web scraping from selected job websites during 2022–2023, the data undergoes natural language processing (NLP) for analysis. Within Group 1 (hardware and smart devices), electrical engineers dominate with 92 positions, emphasizing a demand for engineering expertise. Group 2 (software and software services) sees a surge in programmer roles, totaling 244 positions, showcasing a need for robust programming skills. Group 3 (digital service) prioritizes information technology (IT) support, claiming 354 positions, indicating high demand for IT support qualifications. Graphic design leads Group 4 (digital content) with 587 positions, highlighting the need for a workforce in digital content production. In Group 5 (telecommunication), network engineers dominate with 37 positions, signaling a demand for top-tier network engineering skills. Most positions across groups specify a bachelor's degree and often require prior experience, highlighting the industry's preference for both academic and practical qualifications. This study underscores the digital industry's rapid growth and the sustained demand for a qualified workforce, emphasizing the importance of academic credentials and specialized skills for future employment in these sectors
Healthy building phytoarchitecture requires essential criteria for sustainable phylloremediation of contaminated indoor air
Get PDFVarious ambient air contaminants can spread into the indoor building through air transport. With the additional generation of contaminants from indoor activities, indoor air quality (IAQ) has the potential to be polluted. Indoor air pollution incidents can occur anytime, which is difficult to predict. Therefore, it is necessary to take action to improve IAQ as early as possible and sustainably. The solution to sustainable remediation is using plants to apply phylloremediation, which functions as leaves and leaf-associated microbial communities to reduce air contaminants. This study aims to provide new practical yet essential criteria for the sustainable operation of phylloremediation. This review is based on the latest results of a literature-based study. An analysis of the fundamental processes of plant life forms the basis for obtaining these criteria. The study emphasizes key criteria for phylloremediation encompassing the selecting plants with high transpiration and leaf-microbe synergy, and conducting maintenance by spraying water on leaves. These measures optimize efficiency and sustain the process for indoor air pollutant reduction. The final result summarises the new criteria for sustainable phylloremediation to maintain plant life. These essential criteria can be used for conducting experiments in empirical research, indoor design, and education for the community
A novel fuzzy-logic controller-MDsUPQC topology for power quality improvement in multi-feeder distribution system
Get PDFIn the current situation, the significant usage of massive non-linear functioned power electronic loads has been increased in domestic and industrial applications. The main problem of power-quality (PQ) deterioration in both voltage quality and current quality from nominal values and also damaging the single/multi feeder distribution systems. The major contribution is to alleviate the PQ issues by employing novel multi-devices unified power-quality conditioner (MDsUPQC) topology in a multi-feeder distribution system. This MDsUPQC comprises multiple voltage source inverter (VSI) devices connected with a common direct current-link (DC-link) capacitor which is controlled by a proportional-integral (PI) controller. However, this controller has some technical issues that are not suited for the regulation of common DC voltage at the desired level because of improper selection of gain values. The contribution of this work is proposing an intelligent fuzzy-logic (FL) DC-link controller-driven MDsUPQC device which evidences the intelligent knowledge base for better regulation of PQ issues. The technique and performance of the suggested strategy for PQ improvement, load sharing between feeders, and simulation results are presented with comparative analysis utilizing the MATLAB/Simulink software tool
User interface design of a sengkedan concept-based digital test
Get PDFThis study’s purpose was to demonstrate the design of a digital test for the “educational evaluation” course based on the sengkedan (swales) concept that has good quality. This research approach was a development that used the Borg and Gall model with more focus on the design development stage, initial design trials, and revisions. Subjects involved in the initial testing of the digital test user interface design were 42 respondents. The tool used to conduct initial testing of the digital test user interface design is a questionnaire. The data analysis technique used in this research was descriptive quantitative. The results showed user interface design of a sengkedan concept-based digital test for the “educational evaluation” course was quite good. The impact of this research on evaluators in the education field was a positive thing that added to their insights in developing a digital test. The evaluators will finally understand the importance of designing the user interface before finalizing the physical application to minimize errors
Disturbance detection due to lightning at ionospheric D-region over Malaysia
Get PDFPrevious research on the interference of very low frequency (VLF) signals in the equator region was inadequate and largely concentrated in the middle and high latitude regions. Therefore, this research aims to determine the disruption of VLF waves in the ionospheric D-region above Malaysia, which is in the equator area. This paper presents observations of early/fast, early/slow, and lightning-induced electron precipitation (LEP) events in January 2010. Broadband and narrowband data are monitored and investigated using Japan’s JJI Ebino transmitter (32°40' N, 130°81' E) to the receiver at the Universiti Kebangsaan Malaysia (2°55' N, 101°46' E). Broadband and narrowband data are analyzed with theoretical considerations and linked to events from interference in the ionospheric D-region. Many early/fast, early/slow, and LEP events are found to originate from the lightning release activity emitted and may alter the amplitude and VLF signal phase in the lower layer ionosphere over Malaysia
Early detection of coronary heart disease based on risk factors using interpretable machine learning
Get PDFCoronary heart disease (CHD) is the leading cause of death in the world. The risk of coronary heart disease can be reduced or even prevented by early detection. Early detection of CHD has been widely developed using machine learning, but the machine learning algorithms used sometimes have low interpretability. Low interpretability makes it difficult for users to understand the cause of the decision. Referring to this, this research aims to propose an early detection model using machine learning interpretability, which is implemented using the C5.0 algorithm and interpreted using Shapley additive explanations (SHAP). This research method is divided into 3 stages, namely preprocessing, interpretable machine learning, and performance evaluation. This study used 215 patient data from Dr. Moewardi Surakarta Hospital. Testing the resulting model using the k-folds cross-validation method. The test results show that the risk factors that make a high contribution to the output of the coronary heart disease detection model are systolic blood pressure, diastolic blood pressure, and employment level, with the resulting accuracy performance of 84.64%. The proposed model can be an alternative for early prediction of coronary heart disease which can explain the influence of each selected risk factor on the model output
An improved golden jackal optimization algorithm for combined economic emission dispatch problems
Get PDFIn this research paper, a new improved golden jackal optimization (IGJO) algorithm is applied to address the combined economic emission dispatch (CEED) problem, along with various thermal generator constraints such as valve point loading (VPL) effect, generator limits (GL) in power system. The hunting behavior of the golden jackals is mimicked in the golden jackal optimization (GJO) algorithm. The main aim of the CEED problem is to find the best optimal generation scheduling while minimizing both fuel cost and emission besides meeting the different power system constraints. The original GJO algorithm faces challenges when dealing with high-dimensional optimization problems, as it tends to get trapped in local optima. To address this issue the opposition-based learning (OBL) method was adopted in this GJO algorithm to obtain the global optimal solution and ensure enhanced performance in finding the solution for the CEED problems. To assess the competitiveness of the IGJO algorithm, it is used for various CEED test problems available in the literature, and results are contrasted with other recent heuristic optimization algorithms. Simulation results show that the proposed IGJO performs more effectively than the other compared algorithms in terms of solution quality, and robustness
Image enhancement optimization on bright and dark spots of retinal fundus image
Get PDFDiagnosing diabetic retinopathy (DR) based on features that appear on fundus images is currently conducted through an eye exam by an ophthalmologist. Tracking DR progression manually is time-consuming and keen for a high-skill person. As the technology offered in industrial revolution (IR) 4.0, namely artificial intelligence, is shown to help in the medical diagnosis process, this study proposes an image enhancement algorithm based on a hybrid of contrast enhancement (CE) and particle swarm optimization (PSO). The proposed method incorporates contrast adjustment on the bright and dark region of LAB color space where the bright and dark region is initially segmented using K-mean PSO. 100 retinal fundus images are used for training and testing purposes. The proposed method undergoes qualitative and quantitative evaluation with a comparison between the two methods. The result indicates that the performance of the proposed method is more acceptable as compared to another two methods
Application of K-means clustering and B-value algorithms for analysis of earthquake-dangerous zones in Java Island
Get PDFJava Island is an island with a high earthquake vulnerability. Therefore, earthquake mitigation measures are needed to reduce the impact of earthquakes. Earthquake mitigation is done by knowing the zones with a high risk of earthquakes and high levels of rock stress. The methods used to map earthquake-prone zones are K-means clustering and B-value. The K-means clustering method can provide earthquake clusters based on their characteristics and the B-value can produce rock stress conditions in the area. The results of this study are that the K-means clustering method produces 7 earthquake clusters with 5 classifications of very low, low, medium, high, and very high. In contrast, the B-value process has a high B-value with a value of 1.2-1.5 in West Java and a low B-value with a value of 0.9-1.2 in the central to the eastern part of Java
Google Play review analysis of digital mobile applications of Islamic microfinance institutions
Get PDFThe study aims to analyze user reviews of Islamic microfinance mobile applications to evaluate their effectiveness for micro, small, and medium-sized enterprises (MSMEs). Using the netnography method, this study collected and analyzed 4,131 reviews from the Google Play Store, focusing on applications with ratings above 4.5. The data was categorized into positive and negative reviews. Key findings indicate that users appreciate 50.42% of positive reviews expressed satisfaction and motivation to advance, 28.90% praised the ease of transactions via the application, and 20.68% appreciated the practical benefits in any payment, while with frequent errors (25.53%), issues with activation codes (21.28%), and transaction failures (17.02%) being the most common complaints. The study recommends improving technical reliability to enhance user satisfaction. Future research should explore user experiences in more diverse digital environments. This research contributes to understanding user perceptions and strengthening the development of Islamic microfinance applications