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International Journal of Advances in Applied Sciences
Published by Institute of Advanced Engineering and Science
ISSN : 22528814     EISSN : 27222594     DOI : http://doi.org/10.11591/ijaas
Core Subject : Science, Education, Social,
Earth & Planetary Sciences Environmental Science Materials Science & Nanotechnology Mathematics Physics
International Journal of Advances in Applied Sciences (IJAAS) is a peer-reviewed and open access journal dedicated to publish significant research findings in the field of applied and theoretical sciences. The journal is designed to serve researchers, developers, professionals, graduate students and others interested in state-of-the art research activities in applied science areas, which cover topics including: chemistry, physics, materials, nanoscience and nanotechnology, mathematics, statistics, geology and earth sciences.
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Articles 31 Documents
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Search results for , issue "Vol 13, No 4: December 2024" : 31 Documents clear
Hybrid load forecasting considering energy efficiency and renewable energy using neural network Aizam, Adriana Haziqah Mohd; Dahlan, Nofri Yenita; Asman, Saidatul Habsah; Yusoff, Siti Hajar
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp759-768

Abstract

In recent years, the relationship between a country's gross domestic product (GDP) and its electricity consumption has changed significantly due to increased energy efficiency (EE) and renewable energy (RE) adoption. This decoupling disrupts conventional load forecasting models, affecting utility companies. This study has developed an innovative solution using an artificial neural network (ANN) Hybrid method for load forecasting, resulting in a remarkably accurate model with 99.68% precision. Applying this model to Malaysia's electricity consumption from 2020 to 2040 reveals a significant 13% reduction when accounting for EE and RE trends. This method aids risk management, contingency planning, and decision-making by accurately reflecting changing energy usage dynamics influenced by EE and RE sources.
A brief on artificial intelligence in medicine Ounasser, Nabila; Rhanoui, Maryem; Mikram, Mounia; El Asri, Bouchra
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp1055-1064

Abstract

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.
Potentiometric field-effect transistor pH sensing in a low-power wide-area network Zulhakim, Akmal Mustaffa; Abdullah, Wan Fazlida Hanim; Bakar, Ahmad Zaki Abu; Mamat, Robaiah; Halim, Ili Shairah Abdul; Muslan, Muhammad Izzat Alif; Herman, Sukreen Hana
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp777-786

Abstract

This research paper explores the application of extended-gate field-effect transistors (EGFET) as a potentiometric sensing method for pH detection within an internet of things (IoT) system. The pH EGFET sensor is integrated with a long-range (LoRa) microcontroller, enabling data transmission via a low-power, long-range wide-area network (LoRaWAN) IoT framework to a dedicated IoT application server. The framework utilizes a message queuing telemetry transport (MQTT) broker, employing a publish/subscribe message architecture for efficient data transmission. The study focuses on addressing the problem of determining whether EGFET technology can provide precise and dependable measurements in various settings. To achieve this, the data from the IoT framework is compared with data signals from a semiconductor parametric analyzer and a readout interfacing circuit serial data acquisition (DAQ). From the study, EGFET sensors provide a sensitivity of 61.1 mV/pH with a linearity of 0.9968 through the IoT method. Meanwhile, non-IoT methods yield slightly different sensitivities of 53.1 and 50.5 mV/pH with comparable linearity of 0.9984 and 0.9979. Overall, the research demonstrates the versatility of EGFET technology, highlighting its effective use in various sensing instruments, while ensuring reliable data transfer through the LoRaWAN framework.
Insights into pour point depressants: a brief review of their impact on the behavior of waxy crude oil Khaklari, Gaurav Himanta; Talukdar, Prasenjit
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp916-931

Abstract

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.
Characteristic of black soy miso with crude bromelain and Lactobacillus plantarum Setiani, Bhakti Etza; Pramono, Yoyok Budi; Nurwantoro, Nurwantoro; Dwiloka, Bambang; Arini, Annisa Shafa Putri; Ramadhaningrum, Ilma Muliasari; Sudjono, Elisabeth Febriane Lovita
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp814-820

Abstract

This research aims to improve the diversity of functional foods rich in bioactive peptide components and have a unique flavor for black soybean miso through the addition of crude bromelain and Lactobacillus plantarum. This research uses a completely randomized design with 5 treatments and 4 repetitions to obtain a total of 20 experimental units. The treatments are the different concentrations of crude bromelain addition, namely the control treatment or 0% (T0), 3% (T1), 6% (T2), 9% (T3), and 12 % (T4). The parameters observed are water content, water activity, pH value, and lactic acid bacteria (LAB) viability. The result showed that an increase in the crude bromelain concentration may increase the water content and water activity of the black soybean miso, while the pH value decreases. Based on the viability of the LAB showed a wavering result. Miso with the 9% concentration of crude bromelain is the best result among the others.
Development of a primary reference material for the analysis of BTEX and chlorobenzenes in environmental samples Tahoun, Ibrahim F; Gab-Allah, Mohamed Adly
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp981-986

Abstract

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.
A review of the literature on "determinants of insurers' capital structure" Alsofiani, Ashwag; Md Husin, Maizaitulaidawati
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp1046-1054

Abstract

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.
Information system architecture for healthcare company based on TOGAF Christy, Vania; Andry, Johanes Fernandes; Kamila, Ahya Radiatul; Lee, Francka Sakti
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp806-813

Abstract

In 2020 COVID-19 cases have entered Indonesia causing public health problems and millions of deaths. To prevent transmission of COVID-19, an air purifier is needed whose function is to remove small droplets that can carry the virus. One of them is a medical device company located in Jakarta. The purpose of this research is to produce a design that can improve business processes in the health sector and achieve company goals. The current business process is not very optimal because it is still done conventionally and the existing system has not been integrated with other divisions. To achieve business goals, it is necessary to integrate business processes with information technology (IT) and technology development that will be proposed based on the design of information system architecture that will produce a blueprint and assisted by the open group architecture framework (TOGAF) framework which is very helpful in the process of analyzing company needs. In this research, data collection through interviews with directors and direct observation of health service companies. The results of this study are recommendations given to help health.
Modelling soil deposition predictions on solar photovoltaic panels using ANN under Malaysia’s meteorological condition Suhaimi, Muhammad Aiman Amin Muhammad; Dahlan, Nofri Yenita; Asman, Saidatul Habsah; Rajasekar, Natarajan; Mohamed, Hassan
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp796-805

Abstract

Solar photovoltaic (PV) panels performance is influenced by various external factors such as precipitation, wind angle, ambient temperature, wind speed, transient irradiation, and soil deposition. Soiling accumulation on panels poses a significant challenge to PV power generation. This paper presents the development of an artificial neural network (ANN)-based soil deposition prediction model for PV systems. Conducted at a Malaysian solar farm over three months, the research utilized power output data from the inverter as model output and meteorological data as input variables. The model employed the Levenberg-Marquardt backpropagation method with Tansig and Purline activation functions. Performance assessment via statistical comparison of experimental and simulated results revealed a coefficient of determination (R2) value of 0.68073 for the ANN architecture of 5 input layers, 30 hidden layers, and 1 output layer (5-30-1). Sensitivity analysis highlighted relative humidity and wind direction as the most influential parameters affecting PV soiling rate. The developed ANN model, combined with sensitivity analysis, serves as a robust foundation for enhancing the efficiency of smart sensors in PV module cleaning systems.
Water quality assessment of groundwater resources in rural areas of Karachi, Pakistan Panjwani, Suresh Kumar; Khuhawar, Muhammad Yar; Murtaza, Ghulam; Kumar, Vinod; Bughio, Zohaib ur Rehman; Devi, Paryanka; Sewani, Indra Devi
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp1065-1074

Abstract

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.

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