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IJAAS Journal

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International Journal of Advances in Applied Sciences (IJAAS), p-ISSN 2252-8814, e-ISSN 2722-2594, is a peer-reviewed and open access journal dedicated to publish significant research findings in the field of Applied Sciences, Engineering and Information Technology. The journal is designed to serve researchers, developers, professionals, graduate students and others interested in state-of-the art research activities in applied science, engineering and information technology areas, which cover topics including: applied physics; applied chemistry; applied biology; environmental and earth sciences; electrical & electronic engineering; instrumentation & control; telecommunications & computer science; industrial engineering; materials & manufacturing; mechanical, mechatronics & civil engineering; food, chemical & agricultural engineering; and acoustic & music engineering.
Supervisors: Dr. Qing Wang. Email: ijaas.iaes@gmail.com
Address: - D6 JEC Residence, Plumbon, Banguntapan, Bantul, Yogyakarta, Indonesia 55198
- D2 Griya Ngoto Asri, Bangunharjo, Sewon, Bantul, Yogyakarta, Indonesia 55187

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Claudio Sassanelli

Politecnico di Milano

University of Karachi

Dr.Asghar Ali Alias Daahar Hakro

University of sindh jamshoro

Qadeer Khan Panhwar

faizan ul Hasan

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Papers by IJAAS Journal

Water quality assessment of groundwater resources in rural areas of Karachi, Pakistan

International Journal of Advances in Applied Sciences (IJAAS), 2024

The quality of drinking water directly controls many diseases and affects the growth of the human... more The quality of drinking water directly controls many diseases and affects the growth of the human body. The provision of quality water is a major concern around the world, especially for developing countries that have poor environmental rules, insufficient water supply, and poor drainage systems. Considering these issues, this research was undertaken to assess drinking water quality in the rural areas surrounding Karachi, Pakistan. Samples were collected in the monitoring of the Pakistan Council of Research in Water Resources (PCRWR) and tested for physicochemical and bacteriological parameters (PCB) using geographical information system (GIS). Further, the results were compared with World Health Organization (WHO) standards for human consumption. An analysis of 35 drinking water samples revealed that 14% exceeded the permissible ranges for physical parameters. Moreover, 60% of the samples were deemed unsafe for consumption as the levels of inorganic substances surpassed permissible ranges outlined by WHO. All water samples contained coliform bacteria, making them unsafe, and 46% were contaminated with E. coli, highlighting the urgent need for improved sanitation and water treatment infrastructure in the area.

Abrief on artificial intelligence in medicine

International Journal of Advances in Applied Sciences (IJAAS), 2024

This review explores the transformative impact of artificial intelligence (AI) in medicine. It di... more This review explores the transformative impact of artificial intelligence (AI) in medicine. It discusses the benefits of AI, its core technologies, integration processes, and diverse applications. AI enhances diagnostics, personalizes treatments, and optimizes healthcare operations. Machine learning and deep learning are key AI technologies, while explainable AI ensures transparency. The review emphasizes the integration journey and highlights AI applications, from image diagnosis to telemedicine. Ethical concerns, data privacy, regulations, and algorithmic bias are challenges. The future promises continued innovation, global health equity, and responsible AI application in medicine.

A review of the literature on “determinants of insurers' capital structure”

International Journal of Advances in Applied Sciences (IJAAS), 2024

Capital structure plays an essential role in the financial decision-making of a company by streng... more Capital structure plays an essential role in the financial decision-making of a company by strengthening financial performance and worth. This research aims to provide a literature review to identify the factors that affect insurance companies’ capital structure. The paper focuses on articles published from 2010 to 2021 on insurance companies’ capital structure in developing countries were reviewed. Three theories were identified as having common determinants: trade-off, pecking order, and agency cost. These independent determinants include seven firm-specific determinants: company size, age, profitability, growth, liquidity, tangibility, and risk along with two macroeconomic determinants: economic growth and inflation rate. The research found that the leverage ratio is the primary measurement of capital structure used as a dependent variable. Furthermore, previous studies have shown that the static data model was the most appropriate framework in most research. This research provides future researchers with information on understanding the determinants of capital structure in the insurance field.

Enhancing flexural resistance in hot mix asphalt: a study of effects of wire mesh on load-bearing capacity

International Journal of Advances in Applied Sciences (IJAAS), 2024

In transportation engineering, road pavement is commonly categorized as either flexible pavement ... more In transportation engineering, road pavement is commonly categorized as either flexible pavement or rigid pavement. The pavement demonstrates a distinct capacity to endure a variety of loads, including compressive and tensile loads. The capacity to endure compressive and tensile forces is extremely important, especially in the field of pavement construction, as it ensures both the longevity and the safety of the pavement. The objective of this study was to evaluate the capacity of hot mix asphalt to endure compressive and tensile pressures. The experimental methodology employed four different wire mesh deployment configurations on hot asphalt mixtures, utilizing three-point flexural test equipment. The data indicates the most effective method for mimicking hot mix asphalt involves adding a wire mesh layer at a depth of 30 mm below the surface of the experimental specimen. The particular modeling method showed a measurement of flexural resistance up to 291.85 kN. The study's findings indicate that the hot asphalt mixture exhibits a state of balance in its capacity to endure both compressive and tensile pressures. Incorporating a wire mesh layer within the middle section of the hot asphalt mixture has been perceived to enhance its ability to withstand tensile loads, hence improving its overall performance.

Performance analysis of solar electric scooters with different charger controllers

International Journal of Advances in Applied Sciences (IJAAS), 2024

This study investigates the impact of solar charge controller (SCC) type on battery charging in s... more This study investigates the impact of solar charge controller (SCC) type on battery charging in solar-powered electric scooters (e-scooters). The research compared maximum power point tracking (MPPT) and pulse width modulation (PWM) controllers by monitoring average output power, current, and voltage every 10 minutes. Results showed that under stationary conditions, MPPT controllers delivered higher efficiency, generating 5.87 W of power compared to PWM's 5.05 W. This advantage persisted even during scooter operation, with MPPT controllers producing 4.91 W versus PWM's 4.31 W. Overall, the findings demonstrate that MPPT SCCs offer a more efficient solution for charging e-scooter batteries.

Evaluating metaverse platforms for educational purposes: a heuristic evaluation study

International Journal of Advances in Applied Sciences (IJAAS), 2024

This research's primary objective is to investigate the educational potential by investigating th... more This research's primary objective is to investigate the educational potential by investigating the metaverse website, emphasizing from users' perspectives. It is critical to examine the functionality to identify any potential faults in the learning experience because of the complexities of metaverse apps, which include 3D virtual environments and complex interactions. This study uses heuristic evaluation, which is a useful method for analyzing application success by utilizing well-established design principles and best practices in user interface and user experience design. To conduct this study, a panel of five experts, each with outstanding competence in the topic, was assembled to test the metaverse website in an educational setting. The evaluation was built on the ten heuristic evaluation standards, which served as a solid framework for measuring its usability and functionality. According to the findings of this examination, the average severity number of heuristic issues is one. This result indicates that the website is under "cosmetic problems only." While this implies that specific areas need to be addressed to improve overall quality, it also means that these difficulties do not take precedence over other vital ones. As a result, the website has significant promise as a metaverse instructional platform, and changes can be made to further improve its efficiency.

Enhanced U-Net models with encoder and augmentation for phytoplankton segmentation

International Journal of Advances in Applied Sciences (IJAAS), 2024

This study comprehensively analyzes U-Net models for semantic segmentation in phytoplankton image... more This study comprehensively analyzes U-Net models for semantic segmentation in phytoplankton image recognition, leveraging encoders such as EfficientNet-B5, MobileNetV2, ResNet50, and ResNeXt50 and employing the Adam optimizer. The research highlights the U-Net MobileNetV2 model with optical distortion, which achieves notable test scores with 93.69% Dice, 88.14% intersection over union (IoU), 99.89% Precision, and 100% Recall, underscoring the efficacy of the applied augmentation strategies, including geometric and distortion transforms, and color and blur techniques. The U-Net ResNet50 model with mix transform consistently demonstrates high accuracy in critical metrics, outperforming others, while EfficientNet-B5 with blur suggests increased model sensitivity with improved recall. These results underscore the crucial role of encoder augmentation synergy in model performance. Training and testing times across models have remained under 250 seconds, reflecting methodological efficiency. Overall, these results demonstrate the model's excellent performance for the semantic segmentation task.

Pyrolysis of biomass mixture of coconut fiber and rice husk waste with polypropylene plastic

International Journal of Advances in Applied Sciences (IJAAS), 2024

This research aims to evaluate the effect of the composition ratio of oil from coconut fiber wast... more This research aims to evaluate the effect of the composition ratio of oil from coconut fiber waste biomass and rice husks as well as polypropylene (PP) plastic which is not optimally utilized and can be used as an alternative fuel processed through the pyrolysis process. This research was conducted by mixing biomass of coconut fiber and rice husk with PP plastic in the form of refuse-derived fuel (RDF)-3 with compositional variations of 100:0%, 75:25%, 50:50%, 75:25%, and 0:100% for 60 minutes. The pyrolysis product in the form of oil was then distilled to separate the compounds contained in it and produce pure oil. Next, quantity (volume of pyrolysis oil and distilled oil) and quality (yield, density, viscosity, visual, and color) tests were carried out. The results of the study showed that there is an influence of the variation in the composition ratio of the mixture of biomass of coconut fiber and rice husk and PP plastic on its quantity and quality. The highest quantity was obtained from the 100% PP ratio and the best quality was obtained from the 100% PP ratio, which leads to the specifications of solar fuel oil.

Real-time smoke and fire detection using you only look once v8 based advanced computer vision and deep learning

International Journal of Advances in Applied Sciences (IJAAS), 2024

Fire and smoke pose severe threats, causing damage to property and the environment and endangerin... more Fire and smoke pose severe threats, causing damage to property and the environment and endangering lives. Traditional fire detection methods struggle with accuracy and speed, hindering real-time detection. Thus, this study introduces an improved fire and smoke detection approach utilizing the you only look once (YOLO)v8-based deep learning model. This work aims to enhance accuracy and speed, which are crucial for early fire detection. The methodology involves preprocessing a large dataset containing 5,700 images depicting fire and smoke scenarios. YOLOv8 has been trained and validated, outperforming some baseline models- YOLOv7, YOLOv5, ResNet-32, and MobileNet-v2 in the precision, recall, and mean average precision (mAP) metrics. The proposed method achieves 68.3% precision, 54.6% recall, 60.7% F1 score, and 57.3% mAP. Integrating YOLOv8 in fire and smoke detection systems can significantly improve response times, enhance the ability to mitigate fire outbreaks, and potentially save lives and property. This research advances fire detection systems and establishes a precedent for applying deep learning techniques to critical safety applications, pushing the boundaries of innovation in public safety.

Development of a primary reference material for the analysis of BTEX and chlorobenzenes in environmental samples

International Journal of Advances in Applied Sciences (IJAAS), 2024

Benzene, toluene, ethylbenzene, and xylene (BTEX) and chlorobenzenes are measured in all environm... more Benzene, toluene, ethylbenzene, and xylene (BTEX) and chlorobenzenes are measured in all environments as part of world official pollution control programs. The health impact of these analytes increased the relevance of the validity and comparability of the measurement results. Therefore, equipment performance, implementation of test methods, and accuracy of results need to be verified through internal and external quality control programs. Herein, a new certified reference material (CRM) for benzene, toluene, chlorobenzene, ethylbenzene, o-xylene, 1,2-dichlorobenzene, 1,3 dichlorobenzene and 1,4-dichlorobenzene, and m, p-xylene has been produced and characterized by an approach that is metrologically valid and complies with ISO 17034:2016 and ISO 33405:2024 standards. The reference material was prepared gravimetrically and certified values were calculated based on masses of pure components. Homogeneity results proved that the between-ampule heterogeneity was negligible in comparison with the method precision. The stability of the material was evaluated for both long-term storage and dispatch and no measurable loss of analytes was observed within one year period. The developed certified reference material with small uncertainties values will support regulatory bodies, environmental protection agencies, and testing laboratories in their efforts to improve the quality of motoring results and compliance with regulations.

Enhancing energy efficiency with poncebloc and hemp wool: a Moroccan case study

International Journal of Advances in Applied Sciences (IJAAS), 2024

In recent years, the building sector's energy consumption in Morocco has been steadily increasing... more In recent years, the building sector's energy consumption in Morocco has been steadily increasing, highlighting the urgent need for sustainable building practices. Optimizing building parameters and the development of new insulation materials have become critical areas of research due to the significant energy losses associated with traditional insulation materials. Insulation materials can be a simple and cost-effective way to improve building energy efficiency and reduce environmental impact. Unfortunately, not all of these materials exhibit favorable thermal characteristics such as conductivity or heat capacity. Some involve complex production processes, while others are prohibitively expensive or toxic. At this juncture, the strategy of integrating ecological materials with insulation materials to enhance thermal performance holds considerable promise. This paper investigates the impact of the integration of poncebloc and hemp wool in inside temperature and annual consumption of a building construction numerically under a transient simulation program (TRNSYS). The results show that by using these two materials along with double-glazed windows, energy savings ranging from 50-55% can be achieved.

Factors influencing the intention to use m-commerce in Malaysian: an extended IS success model

International Journal of Advances in Applied Sciences (IJAAS), 2024

The progress of mobile technology has undergone substantial development in recent years, leading ... more The progress of mobile technology has undergone substantial development in recent years, leading to the emergence of new and creative ideas. This paper investigates the factors influencing consumers' intentions to use mobile commerce in Malaysia. The DeLone and McLean updated information system success model served as the basis for this study's proposed model. A convenience sampling method was employed to collect 310 surveys from smartphone owners who conduct mobile commerce activities in Malaysia. A “two-stage structural equation modeling” (SEM) technique assessed the research model and the study's assumptions. The findings revealed that “information quality”, “service quality”, “system quality”, and “trust” significantly influence consumers' “intention to use mobile commerce in Malaysia”. The findings further reveal that “system quality” is the strongest factor influencing the “intention to use mobile commerce in Malaysia”. Therefore, the research outcomes will benefit academicians, researchers, policymakers, and practitioners in the mobile commerce industry in Malaysia. To the best of the authors’ knowledge, this is the first empirical study that expanded the “information system success model” by including “trust” in the context of Malaysian mobile commerce users’ “intentions”. However, further research is recommended to explore the factors influencing consumers' “intention to use mobile commerce in Malaysia”.

Early detection of coronary heart disease based on risk factors using interpretable machine learning

International Journal of Advances in Applied Sciences (IJAAS), 2024

Coronary heart disease (CHD) is the leading cause of death in the world. The risk of coronary hea... more Coronary 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.

Review on electrical submersible pump failures detection and monitoring system

International Journal of Advances in Applied Sciences (IJAAS), 2024

An artificial lift is a technique for pumping fluids in the petroleum industry today. Most artifi... more An artificial lift is a technique for pumping fluids in the petroleum industry today. Most artificial lift that is used nowadays is an electrical submersible pump (ESP). ESP is very convenient and reliable for lifting production. It applies under offshore and onshore industries, where it has high displacement capacity and flexibility to handle various sizes and flow rates under different well conditions. Due to severe operating conditions, ESP may experience fatigue failure, an undesirable malfunction resulting in a shortened service life. Early failure detection on ESP is imperative to prevent a major failure in the pump and reduce the cost of the damage. This study provides an in-depth examination of condition monitoring and early failure detection, with a focus on mechanical and electrical failures. This paper begins with a description of the ESP working principle followed by an analysis of ESP fault and numerous ESP performance monitoring techniques, including the application of early detection. Finally, the authors summarize ESP’s failures, including detection methods for each failure. Besides, recommendations for future research to increase ESP’s lifetime are also discussed. This review revealed that the lifetime of existing ESP can be extended if extensive monitoring of ESP conditions and advanced fault detection methods are applied.

Insights into pour point depressants: a brief review of their impact on the behavior of waxy crude oil

International Journal of Advances in Applied Sciences (IJAAS), 2024

A persistent challenge in the petroleum industry involves paraffin wax deposition from crude oils... more A persistent challenge in the petroleum industry involves paraffin wax deposition from crude oils during low-temperature conditions, complicating pipeline flow assurance due to the intricate rheological behaviors exhibited by waxy crude oil gels. These behaviors include viscoelasticity, yield stress, and thixotropy, contributing to issues like flow reduction and pipeline obstruction, adversely affecting overall pipeline performance. Mitigating this problem requires a combination of mechanical and chemical processes, with pour point depressants (PPDs) emerging as an effective chemical solution. PPDs operate by interacting with wax crystals in the oil, disrupting their formation into a continuous network and preventing flow blockage at lower temperatures. The performance of PPDs depends on factors such as base oil type, PPD concentration, and application temperature. Recent advancements in PPDs focus on developing new polymers with enhanced performance and reduced environmental impact, including those derived from renewable resources, biodegradable PPDs, nano-structured PPDs, or hybrid PPDs. Polymeric additives, such as crystalline-amorphous copolymers, ethylene vinyl acetate copolymers, comb polymers, and nanohybrids, are employed to modify wax crystallization behavior. Understanding the molecular structure of these additives, fluid composition, and pipeline conditions is crucial for optimizing formulations tailored to specific petroleum fluid compositions and transport conditions, ensuring effective wax deposition mitigation.

Application of K-means clustering and B-value algorithms for analysis of earthquake-dangerous zones in Java Island

International Journal of Advances in Applied Sciences (IJAAS), 2024

Java Island is an island with a high earthquake vulnerability. Therefore, earthquake mitigation m... more Java 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.

The production-inventory model with imperfect, rework, and scrap items under stochastic demand

International Journal of Advances in Applied Sciences (IJAAS), 2024

Inventory is crucial in maintaining a smooth production process and meeting consumer demand for m... more Inventory is crucial in maintaining a smooth production process and meeting consumer demand for manufacturing companies. This research focuses on production problems involving defects, rework, and scrap items in stochastic demand. This research aims to develop a production-availability model by minimizing the expectation of total cost (ETC). The model includes four main decision variables, namely production quantity (Q), safety factor (k), production rate (P), and rework rate (P1). This research uses the Aquila optimizer algorithm to optimize the objective function. It compares with the heuristic procedure and Harris Hawk optimization algorithm. The results showed that the Aquila optimizer algorithm successfully optimized the production-availability problem. A comparison between algorithms indicates that the Aquila optimizer algorithm performs equivalently to the Harris Hawk optimization algorithm and outperforms the heuristic procedure. Sensitivity analysis shows that increasing demand uncertainty increases ETC and k. At the same time, it can decrease Q.

Preparation and characterization of cellulose acetate propionate membrane

International Journal of Advances in Applied Sciences (IJAAS), 2024

Membrane technology is a technique in water and wastewater treatment that has many advantages. Th... more Membrane technology is a technique in water and wastewater treatment that has many advantages. This study focuses on the manufacture and characterization of cellulose acetate propionate (CAP) membranes using the phase inversion method. The CAP is preferable since it is a biopolymer that is environmentally friendly and cheap. The production of CAP membrane was carried out using phase inversion method, and varied in 3 different concentrations of CAP i.e., 13, 14, and 15% wt., with additional material of polyethylene glycol (PEG). The characterization was conducted using scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) analysis to determine its morphology, pores, and functional groups. The results show that the membrane containing 13% wt. CAP exhibits higher porosity with more macropores than a membrane with 14 and 15% wt. CAP. However, membranes with higher concentrations of CAP show more uniform pores and fewer macropores. FTIR analysis confirmed the presence of functional groups in the membrane such as C-O, -CH3, C=O, C-H, and OH. It is also found that there is a shift in Wavenumber due to the increase in the concentration of CAP in each membrane.

User perceptions of artificial intelligence powered phishing attacks on Facebook's resilient infrastructure

International Journal of Advances in Applied Sciences (IJAAS), 2024

This study focuses on examining the user perceptions of a cybersecurity certificate transparency ... more This study focuses on examining the user perceptions of a cybersecurity certificate transparency (CT) monitoring tool in the context of artificial intelligence (AI) powered phishing attacks on the Facebook platform. Implementing CT monitoring tools is one strategy for preventing these attacks. It reveals a significant level of concern among respondents regarding the potential risks associated with phishing attacks, indicating a growing awareness of the severity of such threats for future resilient infrastructure development. Users' knowledge and understanding of AI driven phishing threats were found to vary, emphasizing the need for awareness campaigns towards sustainable development education. The study also highlights varying levels of confidence among users in effectively identifying and thwarting phishing efforts, suggesting the importance of user empowerment through improved training, tools, and technologies as responsive institutions. These findings underscore the significance of addressing user concerns, enhancing security awareness, and providing users with the necessary resources to protect themselves against sophisticated phishing attacks. The research contributes to the understanding of user perceptions and lays the groundwork for further improvements in security measures and user education in the fight against phishing threats on Facebook's inclusive growth.

The study of requirements for the workforce of the digital industries using web scraping techniques

International Journal of Advances in Applied Sciences (IJAAS), 2024

This study investigates workforce requirements in Thailand's digital industries, focusing on qual... more This 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.

Water quality assessment of groundwater resources in rural areas of Karachi, Pakistan

International Journal of Advances in Applied Sciences (IJAAS), 2024

The quality of drinking water directly controls many diseases and affects the growth of the human... more The quality of drinking water directly controls many diseases and affects the growth of the human body. The provision of quality water is a major concern around the world, especially for developing countries that have poor environmental rules, insufficient water supply, and poor drainage systems. Considering these issues, this research was undertaken to assess drinking water quality in the rural areas surrounding Karachi, Pakistan. Samples were collected in the monitoring of the Pakistan Council of Research in Water Resources (PCRWR) and tested for physicochemical and bacteriological parameters (PCB) using geographical information system (GIS). Further, the results were compared with World Health Organization (WHO) standards for human consumption. An analysis of 35 drinking water samples revealed that 14% exceeded the permissible ranges for physical parameters. Moreover, 60% of the samples were deemed unsafe for consumption as the levels of inorganic substances surpassed permissible ranges outlined by WHO. All water samples contained coliform bacteria, making them unsafe, and 46% were contaminated with E. coli, highlighting the urgent need for improved sanitation and water treatment infrastructure in the area.

Abrief on artificial intelligence in medicine

International Journal of Advances in Applied Sciences (IJAAS), 2024

This review explores the transformative impact of artificial intelligence (AI) in medicine. It di... more This review explores the transformative impact of artificial intelligence (AI) in medicine. It discusses the benefits of AI, its core technologies, integration processes, and diverse applications. AI enhances diagnostics, personalizes treatments, and optimizes healthcare operations. Machine learning and deep learning are key AI technologies, while explainable AI ensures transparency. The review emphasizes the integration journey and highlights AI applications, from image diagnosis to telemedicine. Ethical concerns, data privacy, regulations, and algorithmic bias are challenges. The future promises continued innovation, global health equity, and responsible AI application in medicine.

A review of the literature on “determinants of insurers' capital structure”

International Journal of Advances in Applied Sciences (IJAAS), 2024

Capital structure plays an essential role in the financial decision-making of a company by streng... more Capital structure plays an essential role in the financial decision-making of a company by strengthening financial performance and worth. This research aims to provide a literature review to identify the factors that affect insurance companies’ capital structure. The paper focuses on articles published from 2010 to 2021 on insurance companies’ capital structure in developing countries were reviewed. Three theories were identified as having common determinants: trade-off, pecking order, and agency cost. These independent determinants include seven firm-specific determinants: company size, age, profitability, growth, liquidity, tangibility, and risk along with two macroeconomic determinants: economic growth and inflation rate. The research found that the leverage ratio is the primary measurement of capital structure used as a dependent variable. Furthermore, previous studies have shown that the static data model was the most appropriate framework in most research. This research provides future researchers with information on understanding the determinants of capital structure in the insurance field.

Enhancing flexural resistance in hot mix asphalt: a study of effects of wire mesh on load-bearing capacity

International Journal of Advances in Applied Sciences (IJAAS), 2024

In transportation engineering, road pavement is commonly categorized as either flexible pavement ... more In transportation engineering, road pavement is commonly categorized as either flexible pavement or rigid pavement. The pavement demonstrates a distinct capacity to endure a variety of loads, including compressive and tensile loads. The capacity to endure compressive and tensile forces is extremely important, especially in the field of pavement construction, as it ensures both the longevity and the safety of the pavement. The objective of this study was to evaluate the capacity of hot mix asphalt to endure compressive and tensile pressures. The experimental methodology employed four different wire mesh deployment configurations on hot asphalt mixtures, utilizing three-point flexural test equipment. The data indicates the most effective method for mimicking hot mix asphalt involves adding a wire mesh layer at a depth of 30 mm below the surface of the experimental specimen. The particular modeling method showed a measurement of flexural resistance up to 291.85 kN. The study's findings indicate that the hot asphalt mixture exhibits a state of balance in its capacity to endure both compressive and tensile pressures. Incorporating a wire mesh layer within the middle section of the hot asphalt mixture has been perceived to enhance its ability to withstand tensile loads, hence improving its overall performance.

Performance analysis of solar electric scooters with different charger controllers

International Journal of Advances in Applied Sciences (IJAAS), 2024

This study investigates the impact of solar charge controller (SCC) type on battery charging in s... more This study investigates the impact of solar charge controller (SCC) type on battery charging in solar-powered electric scooters (e-scooters). The research compared maximum power point tracking (MPPT) and pulse width modulation (PWM) controllers by monitoring average output power, current, and voltage every 10 minutes. Results showed that under stationary conditions, MPPT controllers delivered higher efficiency, generating 5.87 W of power compared to PWM's 5.05 W. This advantage persisted even during scooter operation, with MPPT controllers producing 4.91 W versus PWM's 4.31 W. Overall, the findings demonstrate that MPPT SCCs offer a more efficient solution for charging e-scooter batteries.

Evaluating metaverse platforms for educational purposes: a heuristic evaluation study

International Journal of Advances in Applied Sciences (IJAAS), 2024

This research's primary objective is to investigate the educational potential by investigating th... more This research's primary objective is to investigate the educational potential by investigating the metaverse website, emphasizing from users' perspectives. It is critical to examine the functionality to identify any potential faults in the learning experience because of the complexities of metaverse apps, which include 3D virtual environments and complex interactions. This study uses heuristic evaluation, which is a useful method for analyzing application success by utilizing well-established design principles and best practices in user interface and user experience design. To conduct this study, a panel of five experts, each with outstanding competence in the topic, was assembled to test the metaverse website in an educational setting. The evaluation was built on the ten heuristic evaluation standards, which served as a solid framework for measuring its usability and functionality. According to the findings of this examination, the average severity number of heuristic issues is one. This result indicates that the website is under "cosmetic problems only." While this implies that specific areas need to be addressed to improve overall quality, it also means that these difficulties do not take precedence over other vital ones. As a result, the website has significant promise as a metaverse instructional platform, and changes can be made to further improve its efficiency.

Enhanced U-Net models with encoder and augmentation for phytoplankton segmentation

International Journal of Advances in Applied Sciences (IJAAS), 2024

This study comprehensively analyzes U-Net models for semantic segmentation in phytoplankton image... more This study comprehensively analyzes U-Net models for semantic segmentation in phytoplankton image recognition, leveraging encoders such as EfficientNet-B5, MobileNetV2, ResNet50, and ResNeXt50 and employing the Adam optimizer. The research highlights the U-Net MobileNetV2 model with optical distortion, which achieves notable test scores with 93.69% Dice, 88.14% intersection over union (IoU), 99.89% Precision, and 100% Recall, underscoring the efficacy of the applied augmentation strategies, including geometric and distortion transforms, and color and blur techniques. The U-Net ResNet50 model with mix transform consistently demonstrates high accuracy in critical metrics, outperforming others, while EfficientNet-B5 with blur suggests increased model sensitivity with improved recall. These results underscore the crucial role of encoder augmentation synergy in model performance. Training and testing times across models have remained under 250 seconds, reflecting methodological efficiency. Overall, these results demonstrate the model's excellent performance for the semantic segmentation task.

Pyrolysis of biomass mixture of coconut fiber and rice husk waste with polypropylene plastic

International Journal of Advances in Applied Sciences (IJAAS), 2024

This research aims to evaluate the effect of the composition ratio of oil from coconut fiber wast... more This research aims to evaluate the effect of the composition ratio of oil from coconut fiber waste biomass and rice husks as well as polypropylene (PP) plastic which is not optimally utilized and can be used as an alternative fuel processed through the pyrolysis process. This research was conducted by mixing biomass of coconut fiber and rice husk with PP plastic in the form of refuse-derived fuel (RDF)-3 with compositional variations of 100:0%, 75:25%, 50:50%, 75:25%, and 0:100% for 60 minutes. The pyrolysis product in the form of oil was then distilled to separate the compounds contained in it and produce pure oil. Next, quantity (volume of pyrolysis oil and distilled oil) and quality (yield, density, viscosity, visual, and color) tests were carried out. The results of the study showed that there is an influence of the variation in the composition ratio of the mixture of biomass of coconut fiber and rice husk and PP plastic on its quantity and quality. The highest quantity was obtained from the 100% PP ratio and the best quality was obtained from the 100% PP ratio, which leads to the specifications of solar fuel oil.

Real-time smoke and fire detection using you only look once v8 based advanced computer vision and deep learning

International Journal of Advances in Applied Sciences (IJAAS), 2024

Fire and smoke pose severe threats, causing damage to property and the environment and endangerin... more Fire and smoke pose severe threats, causing damage to property and the environment and endangering lives. Traditional fire detection methods struggle with accuracy and speed, hindering real-time detection. Thus, this study introduces an improved fire and smoke detection approach utilizing the you only look once (YOLO)v8-based deep learning model. This work aims to enhance accuracy and speed, which are crucial for early fire detection. The methodology involves preprocessing a large dataset containing 5,700 images depicting fire and smoke scenarios. YOLOv8 has been trained and validated, outperforming some baseline models- YOLOv7, YOLOv5, ResNet-32, and MobileNet-v2 in the precision, recall, and mean average precision (mAP) metrics. The proposed method achieves 68.3% precision, 54.6% recall, 60.7% F1 score, and 57.3% mAP. Integrating YOLOv8 in fire and smoke detection systems can significantly improve response times, enhance the ability to mitigate fire outbreaks, and potentially save lives and property. This research advances fire detection systems and establishes a precedent for applying deep learning techniques to critical safety applications, pushing the boundaries of innovation in public safety.

Development of a primary reference material for the analysis of BTEX and chlorobenzenes in environmental samples

International Journal of Advances in Applied Sciences (IJAAS), 2024

Benzene, toluene, ethylbenzene, and xylene (BTEX) and chlorobenzenes are measured in all environm... more Benzene, toluene, ethylbenzene, and xylene (BTEX) and chlorobenzenes are measured in all environments as part of world official pollution control programs. The health impact of these analytes increased the relevance of the validity and comparability of the measurement results. Therefore, equipment performance, implementation of test methods, and accuracy of results need to be verified through internal and external quality control programs. Herein, a new certified reference material (CRM) for benzene, toluene, chlorobenzene, ethylbenzene, o-xylene, 1,2-dichlorobenzene, 1,3 dichlorobenzene and 1,4-dichlorobenzene, and m, p-xylene has been produced and characterized by an approach that is metrologically valid and complies with ISO 17034:2016 and ISO 33405:2024 standards. The reference material was prepared gravimetrically and certified values were calculated based on masses of pure components. Homogeneity results proved that the between-ampule heterogeneity was negligible in comparison with the method precision. The stability of the material was evaluated for both long-term storage and dispatch and no measurable loss of analytes was observed within one year period. The developed certified reference material with small uncertainties values will support regulatory bodies, environmental protection agencies, and testing laboratories in their efforts to improve the quality of motoring results and compliance with regulations.

Enhancing energy efficiency with poncebloc and hemp wool: a Moroccan case study

International Journal of Advances in Applied Sciences (IJAAS), 2024

In recent years, the building sector's energy consumption in Morocco has been steadily increasing... more In recent years, the building sector's energy consumption in Morocco has been steadily increasing, highlighting the urgent need for sustainable building practices. Optimizing building parameters and the development of new insulation materials have become critical areas of research due to the significant energy losses associated with traditional insulation materials. Insulation materials can be a simple and cost-effective way to improve building energy efficiency and reduce environmental impact. Unfortunately, not all of these materials exhibit favorable thermal characteristics such as conductivity or heat capacity. Some involve complex production processes, while others are prohibitively expensive or toxic. At this juncture, the strategy of integrating ecological materials with insulation materials to enhance thermal performance holds considerable promise. This paper investigates the impact of the integration of poncebloc and hemp wool in inside temperature and annual consumption of a building construction numerically under a transient simulation program (TRNSYS). The results show that by using these two materials along with double-glazed windows, energy savings ranging from 50-55% can be achieved.

Factors influencing the intention to use m-commerce in Malaysian: an extended IS success model

International Journal of Advances in Applied Sciences (IJAAS), 2024

The progress of mobile technology has undergone substantial development in recent years, leading ... more The progress of mobile technology has undergone substantial development in recent years, leading to the emergence of new and creative ideas. This paper investigates the factors influencing consumers' intentions to use mobile commerce in Malaysia. The DeLone and McLean updated information system success model served as the basis for this study's proposed model. A convenience sampling method was employed to collect 310 surveys from smartphone owners who conduct mobile commerce activities in Malaysia. A “two-stage structural equation modeling” (SEM) technique assessed the research model and the study's assumptions. The findings revealed that “information quality”, “service quality”, “system quality”, and “trust” significantly influence consumers' “intention to use mobile commerce in Malaysia”. The findings further reveal that “system quality” is the strongest factor influencing the “intention to use mobile commerce in Malaysia”. Therefore, the research outcomes will benefit academicians, researchers, policymakers, and practitioners in the mobile commerce industry in Malaysia. To the best of the authors’ knowledge, this is the first empirical study that expanded the “information system success model” by including “trust” in the context of Malaysian mobile commerce users’ “intentions”. However, further research is recommended to explore the factors influencing consumers' “intention to use mobile commerce in Malaysia”.

Early detection of coronary heart disease based on risk factors using interpretable machine learning

International Journal of Advances in Applied Sciences (IJAAS), 2024

Coronary heart disease (CHD) is the leading cause of death in the world. The risk of coronary hea... more Coronary 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.

Review on electrical submersible pump failures detection and monitoring system

International Journal of Advances in Applied Sciences (IJAAS), 2024

An artificial lift is a technique for pumping fluids in the petroleum industry today. Most artifi... more An artificial lift is a technique for pumping fluids in the petroleum industry today. Most artificial lift that is used nowadays is an electrical submersible pump (ESP). ESP is very convenient and reliable for lifting production. It applies under offshore and onshore industries, where it has high displacement capacity and flexibility to handle various sizes and flow rates under different well conditions. Due to severe operating conditions, ESP may experience fatigue failure, an undesirable malfunction resulting in a shortened service life. Early failure detection on ESP is imperative to prevent a major failure in the pump and reduce the cost of the damage. This study provides an in-depth examination of condition monitoring and early failure detection, with a focus on mechanical and electrical failures. This paper begins with a description of the ESP working principle followed by an analysis of ESP fault and numerous ESP performance monitoring techniques, including the application of early detection. Finally, the authors summarize ESP’s failures, including detection methods for each failure. Besides, recommendations for future research to increase ESP’s lifetime are also discussed. This review revealed that the lifetime of existing ESP can be extended if extensive monitoring of ESP conditions and advanced fault detection methods are applied.

Insights into pour point depressants: a brief review of their impact on the behavior of waxy crude oil

International Journal of Advances in Applied Sciences (IJAAS), 2024

A persistent challenge in the petroleum industry involves paraffin wax deposition from crude oils... more A persistent challenge in the petroleum industry involves paraffin wax deposition from crude oils during low-temperature conditions, complicating pipeline flow assurance due to the intricate rheological behaviors exhibited by waxy crude oil gels. These behaviors include viscoelasticity, yield stress, and thixotropy, contributing to issues like flow reduction and pipeline obstruction, adversely affecting overall pipeline performance. Mitigating this problem requires a combination of mechanical and chemical processes, with pour point depressants (PPDs) emerging as an effective chemical solution. PPDs operate by interacting with wax crystals in the oil, disrupting their formation into a continuous network and preventing flow blockage at lower temperatures. The performance of PPDs depends on factors such as base oil type, PPD concentration, and application temperature. Recent advancements in PPDs focus on developing new polymers with enhanced performance and reduced environmental impact, including those derived from renewable resources, biodegradable PPDs, nano-structured PPDs, or hybrid PPDs. Polymeric additives, such as crystalline-amorphous copolymers, ethylene vinyl acetate copolymers, comb polymers, and nanohybrids, are employed to modify wax crystallization behavior. Understanding the molecular structure of these additives, fluid composition, and pipeline conditions is crucial for optimizing formulations tailored to specific petroleum fluid compositions and transport conditions, ensuring effective wax deposition mitigation.

Application of K-means clustering and B-value algorithms for analysis of earthquake-dangerous zones in Java Island

International Journal of Advances in Applied Sciences (IJAAS), 2024

Java Island is an island with a high earthquake vulnerability. Therefore, earthquake mitigation m... more Java 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.

The production-inventory model with imperfect, rework, and scrap items under stochastic demand

International Journal of Advances in Applied Sciences (IJAAS), 2024

Inventory is crucial in maintaining a smooth production process and meeting consumer demand for m... more Inventory is crucial in maintaining a smooth production process and meeting consumer demand for manufacturing companies. This research focuses on production problems involving defects, rework, and scrap items in stochastic demand. This research aims to develop a production-availability model by minimizing the expectation of total cost (ETC). The model includes four main decision variables, namely production quantity (Q), safety factor (k), production rate (P), and rework rate (P1). This research uses the Aquila optimizer algorithm to optimize the objective function. It compares with the heuristic procedure and Harris Hawk optimization algorithm. The results showed that the Aquila optimizer algorithm successfully optimized the production-availability problem. A comparison between algorithms indicates that the Aquila optimizer algorithm performs equivalently to the Harris Hawk optimization algorithm and outperforms the heuristic procedure. Sensitivity analysis shows that increasing demand uncertainty increases ETC and k. At the same time, it can decrease Q.

Preparation and characterization of cellulose acetate propionate membrane

International Journal of Advances in Applied Sciences (IJAAS), 2024

Membrane technology is a technique in water and wastewater treatment that has many advantages. Th... more Membrane technology is a technique in water and wastewater treatment that has many advantages. This study focuses on the manufacture and characterization of cellulose acetate propionate (CAP) membranes using the phase inversion method. The CAP is preferable since it is a biopolymer that is environmentally friendly and cheap. The production of CAP membrane was carried out using phase inversion method, and varied in 3 different concentrations of CAP i.e., 13, 14, and 15% wt., with additional material of polyethylene glycol (PEG). The characterization was conducted using scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) analysis to determine its morphology, pores, and functional groups. The results show that the membrane containing 13% wt. CAP exhibits higher porosity with more macropores than a membrane with 14 and 15% wt. CAP. However, membranes with higher concentrations of CAP show more uniform pores and fewer macropores. FTIR analysis confirmed the presence of functional groups in the membrane such as C-O, -CH3, C=O, C-H, and OH. It is also found that there is a shift in Wavenumber due to the increase in the concentration of CAP in each membrane.

User perceptions of artificial intelligence powered phishing attacks on Facebook's resilient infrastructure

International Journal of Advances in Applied Sciences (IJAAS), 2024

This study focuses on examining the user perceptions of a cybersecurity certificate transparency ... more This study focuses on examining the user perceptions of a cybersecurity certificate transparency (CT) monitoring tool in the context of artificial intelligence (AI) powered phishing attacks on the Facebook platform. Implementing CT monitoring tools is one strategy for preventing these attacks. It reveals a significant level of concern among respondents regarding the potential risks associated with phishing attacks, indicating a growing awareness of the severity of such threats for future resilient infrastructure development. Users' knowledge and understanding of AI driven phishing threats were found to vary, emphasizing the need for awareness campaigns towards sustainable development education. The study also highlights varying levels of confidence among users in effectively identifying and thwarting phishing efforts, suggesting the importance of user empowerment through improved training, tools, and technologies as responsive institutions. These findings underscore the significance of addressing user concerns, enhancing security awareness, and providing users with the necessary resources to protect themselves against sophisticated phishing attacks. The research contributes to the understanding of user perceptions and lays the groundwork for further improvements in security measures and user education in the fight against phishing threats on Facebook's inclusive growth.

The study of requirements for the workforce of the digital industries using web scraping techniques

International Journal of Advances in Applied Sciences (IJAAS), 2024

This study investigates workforce requirements in Thailand's digital industries, focusing on qual... more This 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.