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31,456 Article Results

Theoretical and experimental analysis of unbalanced doubly fed induction generators

10.11591/ijra.v13i4.pp476-484
Yaakoub Diboune , Redouane Hachelaf , Djilali Kouchih
In this paper, a novel approach has been developed for the modeling and analysis of doubly fed induction generators operating under unbalanced load conditions. This comprehensive approach considers the derivation of the doubly fed induction generator’s neutral voltage during unbalanced conditions. Using this innovative approach, important and extremely precise signatures on stator currents and voltages have been extracted during a rational simulation time. It has been shown that for unbalanced conditions, an abnormal operation is produced. It is characterized by unbalanced stator voltages, currents, and specific harmonics through the stator variables. These harmonics have been proposed to detect unbalanced conditions. The consistency and reliability of this approach for the analysis and modeling of unbalanced doubly fed induction generators are validated by the coherence and good correlation between experimental and simulation results.
Volume: 13
Issue: 4
Page: 476-484
Publish at: 2024-12-01

Evaluation of the time-of-use tariff responsiveness for plug-in electric vehicle home charging in Malaysia

10.11591/ijaas.v13.i4.pp773-780
Nurliyana Baharin , Mohamad Fani Sulaima , Nofri Yenita Dahlan , Hazlie Mokhlis
Plug-in electric vehicles (PEVS) have become increasingly popular as a viable transportation option as owners can charge them at home. This will add much energy to the house if the users charge their PEVs at home. The PEV charging load will lead to extra energy demand on the distribution network, and the users will need to pay more for electricity if they use the current domestic tariff in Malaysia. This research aims to analyze the PEV charging costs using time-of-use (ToU) tariffs with different time segmentations and price elasticity. The effect of four residential load profile patterns has also been investigated in Malaysia as a case study. Four PEV charging scenarios were created, and the charging times were set according to Malaysian driving styles, with charging times starting at 6 PM, 10 PM, and 9 AM. The PEV and electric vehicle supply equipment (EVSE) are set to be homogeneous, and the EV was assumed to have a minimum state-of-charge of 20%. The main contribution of this paper is the selection of the ToU tariff segmentation, where the structure of the smallest time segmentation gave the lowest electricity bill per month compared to the Tenaga Malaysia Berhad (TNB) domestic tariff.
Volume: 13
Issue: 4
Page: 773-780
Publish at: 2024-12-01

Design system and performance analysis of fish storage box by utilizing solar energy

10.11591/ijpeds.v15.i4.pp2591-2602
Rizal Justian Setiawan , Khakam Ma'ruf , Darmono Darmono , Indra Dwi Suryanto , Andi Tri Hermawan
Indonesia is a maritime country and many people work as traditional fishermen. Traditional fishermen generally use thermos filled with wet ice, ice boxes, or ice blocks to maintain the freshness of fish. The temperature obtained is still insufficient to maintain the fish’s quality and freshness. Furthermore, some existing technologies are expensive and use fossil fuels. Researchers designed and manufactured a cool box that utilizes solar energy to store fish. The experimental research method was conducted by testing the performance of the cool box device at four different locations. The results showed that the solar panel produced an average of 2,527.2 W of energy in a day, which can power the cool box device for 10 hours. To maintain the fish’s freshness with the reference temperature of 0 °C-5 °C, the device uses temperature control to prevent the fish from freezing, which damages its structure. The temperature control also helps the tool save energy, allowing it to last 170 minutes longer than without using the temperature control feature.
Volume: 15
Issue: 4
Page: 2591-2602
Publish at: 2024-12-01

Low-cost multi-sensing fire-fighting robot with obstacle avoidance mechanism

10.11591/ijra.v13i4.pp373-379
Adekunle Taofeek Oyelami , Joshua Ayomide Oyadokun , Olusola A. Akintunlaji , George C. Ihenacho
Robots are mostly optimized for tasks that require strength exceeding that of humans or for operations in hazardous environments. The fire-fighting robot developed has multiple sensing capabilities with obstacle avoidance mechanisms and is divided into two units: the robot and the static unit. The robot is equipped with three flame sensors to detect flames (infrared radiation) in three directions, an ultrasonic sensor to avoid obstacles, a wireless receiver to receive data from the static unit, a magnetometer giving the robot a sense of direction, and a unit of Arduino Mega microcontroller serving as the central controlling platform. The static unit has four flame sensors and a transmitter that transmits signals to the robot unit, which an Arduino Uno directly controls. A prototype was developed, which helps prevent the escalation of fires in the home as it can detect, navigate and extinguish flames while avoiding obstacles autonomously.
Volume: 13
Issue: 4
Page: 373-379
Publish at: 2024-12-01

Risk factors and trends analysis of unwanted pregnancy in Indonesia

10.11591/ijphs.v13i4.23702
Supriyadi supriyadi , Tris Eryando , Purnawan Junadi
Unwanted pregnancy has serious and adverse health, social, and economic impacts, as well as the risk of maternal and child mortality. In Indonesia, unwanted pregnancy is one of the most troubling public health problems and a major reproductive health problem. The sample consisted of 2002 (12,612), 2007 (14,471), 2012 (14,212), and 2017 (8,838), so the total sample was 50,233 couples of childbearing age by random sample method. This study was analyzed using logistic regression analysis. Unintended pregnancies were associated with maternal age, age at first marriage, number of children, maternal education, contraceptive use, contraceptive failure, residence, and the interval between pregnancies. Unwanted pregnancies at the mother's vulnerable age have increased over the past 10 years and decreased after entering the last 5 years, tend to be stable and constant at the age of first marriage. About one and a half women in Indonesia encounter unwanted pregnancies. Unwanted pregnancies fluctuate over 20 years. Women, especially the most vulnerable should be empowered to avoid unwanted pregnancies for their awareness and independence. Programs to expand access and quality of information and counseling centers, access and quality of women's health services, and specific reproductive health services as needed.
Volume: 13
Issue: 4
Page: 1864-1871
Publish at: 2024-12-01

Information system architecture for healthcare company based on TOGAF

10.11591/ijaas.v13.i4.pp810-817
Vania Christy , Johanes Fernandes Andry , Ahya Radiatul Kamila , Francka Sakti Lee
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.
Volume: 13
Issue: 4
Page: 810-817
Publish at: 2024-12-01

A multi-core makespan model for parallel scientific workflow execution in cloud computational framework

10.11591/ijai.v13.i4.pp3849-3857
Farha Naaz , Sameena Banu
Researchers have shown a lot of potential in optimizing cloud-based workload-scheduling over the past few years. However, executing scientific workloads inside the cloud is time-consuming and costly, making it inefficient from both a financial and productivity standpoint. As a result, there are many investigations conducted, with the general trend being to speed up the rate of processing and establish a cost-effective system, whereby customers are billed according to their actual use. In addition, energy-consumption is capable of being reduced, especially if the available resources are heterogeneous; however, few investigations have optimized multi-core with analyzing makespan parameters collectively to fulfill the quality of service (QoS) and service level agreement (SLA) of the workload task. In this research, we introduce an optimal scheduling for a heterogeneous distributed cloud computing environment called task aware makespan optimized scheduler (TAMOS) that guarantees requirements across the task levels of scientific workflows. The energy and time required to carry out specific workflows are significantly reduced by using this TAMOS strategy. The TAMOS framework was studied using the scientific workflows namely, inspiral and sipht. When compared to the conventional method of scheduling work, our methodology used less energy and makespan.
Volume: 13
Issue: 4
Page: 3849-3857
Publish at: 2024-12-01

A neural machine translation system for Kreol Repiblik Moris and English

10.11591/ijai.v13.i4.pp4976-4987
Sameerchand Pudaruth , Sheeba Armoogum , Nirmal Kumar Betchoo , Aneerav Sukhoo , Vandanah Gooria , Abdallah Peerally , Mohammad Zafar Khodabocus
Although Google Translate is a widely used machine translation service that supports 133 languages, it does not incorporate support for the Kreol Repiblik Moris (KRM) language. Addressing this limitation, the current research focuses on enhancing the accuracy and fluency of machine translation between KRM and English through natural language processing and deep neural machine translation techniques. In this study, a machine translation system using a transformer model trained with a dataset of 50,000 parallel corpora has been developed. The model was evaluated using manual translations and the bilingual evaluation understudy (BLEU) score. A score of 31.46 for translating from KRM to English and 28.15 for translating from English to KRM was achieved. To our knowledge, these are the highest BLEU scores for translation between these two languages. This is due to utilising the largest dataset and extensive atomic words from the KRM dictionary. This successful interdisciplinary funded project led to the setting up of a free online translation service and a smartphone app for Mauritian citizens and tourists.
Volume: 13
Issue: 4
Page: 4976-4987
Publish at: 2024-12-01

Modelling soil deposition predictions on solar photovoltaic panels using ANN under Malaysia’s meteorological condition

10.11591/ijaas.v13.i4.pp800-809
Muhammad Aiman Amin Muhammad Suhaimi , Nofri Yenita Dahlan , Saidatul Habsah Asman , Natarajan Rajasekar , Hassan Mohamed
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.
Volume: 13
Issue: 4
Page: 800-809
Publish at: 2024-12-01

Text encryption using secure and expeditious multiprocessing SerpentCTR using logistic map

10.11591/ijece.v14i6.pp6753-6772
Huwaida T. Elshoush , Duaa M. Ahmed , Abdalmajid A. Ishag , Muawia A. Elsadig , Abdelrahman Altigani
Unarguably performance is a critical factor to the success of any cipher. Al-Beit Serpent is more secure than advanced encryption standard (AES), it faces limitations such as speed and memory requirement. Hence, this paper proffers a text encryption method S  that ameliorates the performance by running Serpent in parallel using the counter (CTR) encryption mode and further enhances the security by generating sub-keys for each block using logistic map. The intricate logistic map generated keys adds robustness to the proposed algorithm. Comprehensive experiments using Python 3.9 on commonly used metrics verify the efficacy of the proposed method in terms of execution time, central processing unit (CPU) usage, security analysis including key space, strict avalanche effect and its randomness. The encryption/decryption reduction rate reached up to 80.81%. It is worthy of note that it is effectually resistant to brute force attacks having a large key space in addition to its dependency on the number of blocks besides the randomly generated keys. The enhanced Serpent was examined using the statistical test suite (STS) recommended by the National Institute of Standards and Technology (NIST) and verified its randomness by passing all tests. Furthermore, it efficaciously resisted statistical analysis, particularly histogram and correlation coefficient analysis. Moreover, it prevails over current methods when juxtaposed with them in terms of performance, key space, key sensitivity, avalanche effect, histogram analysis and correlation coefficient, ergo affirming its efficiency.
Volume: 14
Issue: 6
Page: 6753-6772
Publish at: 2024-12-01

Study of roundwood sorting on the simulation model of longitudinal chain conveyor

10.11591/ijpeds.v15.i4.pp2068-2079
Nurbanu Sarbassova , Anara Umurzakova , Sergey Kladiev
When sorting roundwood on chain longitudinal conveyors of considerable length, there is an error in moving the selected roundwood assortment to the place of discharge into the accumulator, which increases in proportion to the length of the sorting line. Currently, conveyors of limited length are used. The accumulators are located on both sides of the conveyor. This reduces the transportation error. Sometimes the sorting yard does not allow placing a short conveyor on it or there is a considerable amount of assortments. In this case, it is necessary to use a conveyor of considerable length. The paper proposes a new method of sorting roundwood on longitudinal chain conveyors of considerable length. This reduces the tracking error of the assortment movement. Angular displacement sensors of the leading and driven sprockets of the closed plate chain of the sorting conveyor are used as sensors of angular displacements. The shafts of both sensors are mechanically connected to the shafts of the driving and driven sprockets, respectively. The results of simulation modeling of the sorting control system with complex mechanical system confirmed the possibility of practical application of the proposed method to reduce the tracking error of the sorted cargo. The results of the study confirm the possibility of practical application of the device for operation on longitudinal conveyors.
Volume: 15
Issue: 4
Page: 2068-2079
Publish at: 2024-12-01

A brief on artificial intelligence in medicine

10.11591/ijaas.v13.i4.pp1059-1068
Nabila Ounasser , Maryem Rhanoui , Mounia Mikram , Bouchra El Asri
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.
Volume: 13
Issue: 4
Page: 1059-1068
Publish at: 2024-12-01

Load forecasting using fuzzy logic, artificial neural network, and adaptive neuro-fuzzy inference system approaches: application to South-Western Morocco

10.11591/ijece.v14i6.pp7067-7079
Hicham Stitou , Mohamed amine Atillah , Abdelghani Boudaoud , Mounaim Aqil
The demand for energy on a global scale is continuously rising due to the expansion of energy infrastructure and the increasing number of new appliances. To address this growing need, an efficient energy management system (EMS) has become indispensable. By implementing EMS, both residential and commercial buildings can significantly improve their energy efficiency and consumption. One crucial aspect of enabling EMS to operate efficiently is load forecasting. The accuracy of load forecasting depends on numerous factors. A reliable load forecast model should consider the region’s weather forecast, as it plays a crucial role in developing an accurate prediction. This study is about the medium-term load forecasting (MTLF) for the Province of Taroudant, Morocco, using historical monthly load and weather data for five years (2018 to 2022). To forecast consumed energy three methods are used namely artificial neural network (ANN), fuzzy logic (FL) and adaptive neuro-fuzzy inference system (ANFIS). This paper selects absolute percentage error (APE), mean absolute percentage error (MAPE), correlation coefficient (R) and root mean square error (RMSE) to compare and evaluate the prediction accuracy of models. It has been observed through results analysis that the ANFIS model produces very accurate forecasting prediction with MAPE of 4.75% while ANN and FL models give respectively MAPE of 7.36% and 8.42%.
Volume: 14
Issue: 6
Page: 7067-7079
Publish at: 2024-12-01

A review of the literature on "determinants of insurers' capital structure"

10.11591/ijaas.v13.i4.pp1050-1058
Ashwag Alsofiani , Maizaitulaidawati Md Husin
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.
Volume: 13
Issue: 4
Page: 1050-1058
Publish at: 2024-12-01

Disturbance detection due to lightning at ionospheric D-region over Malaysia

10.11591/ijaas.v13.i4.pp825-833
Suryadi Suryadi , Mariyam Jamilah Homam , Rohaida Mat Akir , Mardina Abdullah
Previous 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.
Volume: 13
Issue: 4
Page: 825-833
Publish at: 2024-12-01
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