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23,598 Article Results

Optimal control design of the COVID-19 model based on Lyapunov function and genetic algorithm

10.11591/ijece.v14i5.pp5117-5130
Aminatus Sa'adah , Roberd Saragih , Dewi Handayani
Millions of people died worldwide as a result of the coronavirus disease 2019 (COVID-19) pandemic that started in early 2020. Examining the COVID-19 susceptible-exposed-infected-recovery (SEIR) mathematical model is one approach to developing the best control scenario for this disease. The study utilized two control variables, vaccination, and therapy, to construct a control function that relied on the quadratic Lyapunov function. The control objective was to lower the number of COVID-19 infections while maintaining system stability. A genetic algorithm (GA) is used as a novel method to estimate controller parameter value to replace the previously used parameter tuning procedure. Then, a numerical simulation was carried out implementing three control scenarios, namely vaccination control only, treatment control only, and vaccination and treatment control simultaneously. Based on the results, scenario 3 (vaccination and treatment simultaneously) showed the most significant decrease: the average decrease in the exposed human population was 98.29%, and the infected human population was 98.18%.
Volume: 14
Issue: 5
Page: 5117-5130
Publish at: 2024-10-01

13-level modular multilevel inverter application for the exhaust fan drive control of Thu Thiem Road tunnel

10.11591/ijece.v14i5.pp5008-5017
An Thi Hoai Thu Anh , Tran Hung Cuong
The ventilation system plays a vital role in ensuring the safety of people and means of transportation. Fresh air is created in the tunnel mainly thanks to the exhaust fans arranged at the top of the tunnels. The drive motor for the exhaust fan in the Thu Thiem Road tunnel has a power of 560 kW and operates at a voltage of 6 kV. The paper proposes a 13-level modular multilevel inverter (MMC) with the improved nearest level modulation (NLM) method to ensure the quality of voltage output from the voltage source inverter-fed exhaust fan drive motor. This is a novel combination aimed at transforming electrical power at high voltage levels, high power, and enhancing operational efficiency and the lifespan of semiconductor components within the inverter when operating continuously and over extended durations. The theoretical research results verified through MATLAB/Simulink software with simulation parameters collected from the exhaust fan motor of Thu Thiem Road tunnel, Vietnam show total harmonic distortion of the current in operation with 13 levels is 1.23%, while that of the current in operation with 7 levels is 10.1%; total harmonic distortion (THD) of the voltage with 13 levels is 5.33%, while that of the voltage with 7 levels is 11.37%.
Volume: 14
Issue: 5
Page: 5008-5017
Publish at: 2024-10-01

The feasibility of processing waste from religious ceremonies in Bali as clean energy

10.11591/ijece.v14i5.pp4921-4928
I Made Aditya Nugraha , I Gusti Made Ngurah Desnanjaya
Bali is one of the islands with the largest Hindu religion in Indonesia. This is of course an attraction for tourists to see the culture and natural beauty that the island of Bali has to offer. However, apart from that, there are many religious activities that occur on the island of Bali and the waste produced is something that needs special attention. If this waste is not handled properly, it will threaten environmental sustainability in Bali and indirectly the tourism offered. Therefore, there is a need for a solution to overcome the waste problem. By conducting observations, interviews and literature studies, a way to overcome this problem was found, namely by converting the waste into aromatherapy incense, vermicomposting, briquettes and biofuel. The results of this processing have been studied and of course have the potential to be carried out on the island of Bali. The application of this method also indirectly plays an important role in preserving the environment and economy on the island of Bali.
Volume: 14
Issue: 5
Page: 4921-4928
Publish at: 2024-10-01

Pedestrian flow prediction in commercial avenue

10.11591/ijece.v14i5.pp5848-5857
Marwane Benhadou , Amina El Gonnouni , Abdelouahid Lyhyaoui
Mobility plans are one of the most important management tools for city development and an important factor for society and economic growth, where pedestrians are the end goal of any mobility plan. Human behavior is generally unpredictable, and many attempts have been interested at pedestrians' mobility in urban environments, both microscopic and macroscopic (flow, density, and speed) levels. The objective of pedestrian traffic flow prediction is to predict the number of pedestrians at the next moment. Assisting operators and city managers in making decisions in urban environments such as emergency support systems, and quality-of-service evaluation. This study aims to model and predict bi-directional pedestrian flow in a commercial avenue, based on two essential stages, data collection through video recording over two months (pedestrian flow) and data analysis using machine learning algorithms that provide a lower error and a higher accuracy rate. Two metrics were selected as basic measures to evaluate the model performances, root mean square error (RMSE) and coefficient of determination R2. Artificial neural network (ANN) gives a little better performance and fitness.
Volume: 14
Issue: 5
Page: 5848-5857
Publish at: 2024-10-01

Enhanced accuracy estimation model energy import in on-grid rooftop solar photovoltaic

10.11591/ijece.v14i5.pp5970-5983
Alfin Sahrin , Imam Abadi , Ali Musyafa
Installing rooftop solar photovoltaic (PV) with an on-grid system benefits consumers because it can reduce imports of electrical energy from the grid. This study aims to model the estimation of energy imports generated from on-grid rooftop solar PV systems. This estimation model was carried out in 20 provincial capitals in Indonesia. The parameters used are weather conditions, orientation angle, and energy generated from the on-grid rooftop solar PV system. The value of imported energy is divided into three combinations based on the azimuth angle direction, which describes the type and shape of the roof of the building (one-direction, two-directions, and three-directions). Modeling was done using machine learning with neural network (NN), linear regression, and support vector machine. A comparison of the machine learning algorithm results is NN produces the smallest root mean square error (RMSE) value of the three. Model enhancement uses a grid search cross-validation (GSCV) to become the GSCV-NN model. The RMSE results were enhanced from 53.184 to 44.389 in the one-direction combination, 145.562 to 141.286 in the two-direction combination, and 81.442 to 76.313 in the three-direction combination. The imported energy estimation model on the on-grid rooftop solar PV system with GSCV-NN produces a more optimal and accurate model.
Volume: 14
Issue: 5
Page: 5970-5983
Publish at: 2024-10-01

Dual soft decoding of linear block codes using memetic algorithm

10.11591/ijece.v14i5.pp5263-5273
Rajaa Sliman , Ahmed Azouaoui
In this article we will approach the soft-decision decoding for the linear block codes, is a kind of decoding algorithms used to decode data to form better original estimated received message, it is considered as a NP-hard problem. In this article we present a new decoder using memetic algorithm such metaheuristic technic operates on the dual code rather than the code itself that aims to find the error caused when sending a codeword calculated from a message of k bits of information, the resulting codeword contains n bits, including the redundancy bits, the efficiency of an error-correcting code is equivalent to the ratio k/n, the rate is belong the interval [0,1]. Hence a good code is the one that ensures a certain error correcting capability at minimum ratio. The results proved that this approach using a combination of genetic algorithm and local search algorithm provides a sufficiently good solution to an optimization problem; the new decoder is applied on linear codes where the structure is given by a parity check matrix.
Volume: 14
Issue: 5
Page: 5263-5273
Publish at: 2024-10-01

Assessing power quality in individual circuits of industrial electrical system

10.11591/ijece.v14i5.pp4888-4896
Eliana Noriega Angarita , Vladimir Sousa Santos , Pablo Daniel Donolo , Enrique Ciro Quispe
This article evaluates energy quality in individual circuits within an industrial electrical system and its impact on common connection point parameters. The research is crucial due to rising challenges in power quality arising from increased nonlinear electrical loads in industrial processes. The study involves sequential steps, covering the industrial electrical system´s description, power quality parameters analysis, and issue identification. A comprehensive assessment was conducted on a 3,000 kVA, 13.8 kV/460 V point of common coupling (PCC) transformer, and 10 transformers (10 to 250 kVA) supplying individual circuits. Findings indicated load factors below 70% in all transformers and a power factor below 0.9 in eight. Issues like voltage variation, current imbalance, and harmonic distortion were identified in nine transformers supplying individual circuits, while the PCC exhibited no power quality problems. The research emphasizes the importance of including individual circuits in power quality assessments, as compliance with regulatory limits at the PCC may not guarantee the absence of power quality issues in individual circuits, affecting equipment lifespan and increasing energy losses.
Volume: 14
Issue: 5
Page: 4888-4896
Publish at: 2024-10-01

Geographic information system-based spatio-temporal detection and mapping of COVID–19 hot/cold spots in Oman

10.11591/ijece.v14i5.pp5779-5801
Yaseen Al-Mulla , Mohammed Al–Muqaimi , Ahsan Ali , Taif Al-Badi , Krishna Parimi , Anusha Chowdary
Infected COVID-19 patients, especially after March 11, 2020, grew drastically in Oman. Hence, a variety of measures were issued to restrict all social gatherings, commercial activities, and mandating preventative health practices. This study aimed to i) understand distribution patterns and impact of decisions and responses at the spread of confirmed cases; ii) highlight and verify most concentrated regions with infections; and iii) overview spatial changes of cases overtime. The analysis was carried out using inverse–distance-weighted interpolation and hotspot (Getis–Ord GI*) techniques. Results showed a substantial relationship between spatial structure of COVID–19 and population distribution and density. COVID–19 has increased by 11.5% weekly in the capital, which were locked down since April 2020. However, after health quarantine was lifted on May 29, 2020, weekly cases surged in the capital. Al-Batinah-North and Dhofar recorded an increase of 32.1% and 30.5%, respectively, after restrictions had eased. The analysis illustrated that spread of COVID–19 was shifting from Northeast to Southeast and later shifted back to the Northeast of the country at the end of year 2022. This study is beneficial for pertinent organizations to perform detailed studies for developing and monitoring disease systems and dominating relevant factors.
Volume: 14
Issue: 5
Page: 5779-5801
Publish at: 2024-10-01

Real-time business intelligence development using machine learning to increase the potential of the dairy goat milk business

10.11591/ijece.v14i5.pp5612-5625
Alusyanti Primawati , Imas Sukaesih Sitanggang , Annisa Annisa , Dewi Apri Astuti
The development of big data and real-time data warehouse (RTDW) technologies has transformed traditional business intelligence (BI) into real-time business intelligence (RTBI). The RTBI framework is developed in this study by incorporating machine learning-based real-time prediction features. The complexity of layer integration in the RTBI framework is a challenge in building RTBI. The development of RTBI was carried out in business areas that did not have RTBI from the beginning, such as the dairy goat milk business in Probolinggo, East Java. Another main reason is that the dairy goat milk business is a food alternative to cow's milk in Indonesia. The results of this study can contribute to increasing the potential value of the goat milk business. The research method was developed by adapting to the Kimball method and unified modeling language (UML). The real-time prediction feature with the long short-term memory (LSTM) algorithm is the main feature in the RTBI framework developed in the research. The calculation results of real-time predictive analysis latency successfully approached 0 milliseconds (ms), namely 9.35×10-5 ms. The application of RTBI in the dairy goat milk business was successfully built but the real data is very limited, so RTBI is less able to describe the movement of the business.
Volume: 14
Issue: 5
Page: 5612-5625
Publish at: 2024-10-01

Detection of fungal diseases of plants from leaf images based on neural network technologies

10.11591/ijece.v14i5.pp5866-5873
Ievgen Fedorchenko , Mohd Faizal Yusof , Andrii Oliinyk , Maksym Chornobuk , Mykola Khokhlov , Jamil Abedalrahim Jamil Alsayaydeh
The paper addresses the issue of automating the detection of fungal diseases in plants using digital images of their leaves. The spread of diseases among agricultural and horticultural crops causes significant economic losses worldwide, making the development of an effective and affordable solution to this problem highly valuable. Literature analysis suggests the viability of employing a convolutional neural network (CNN) to tackle this issue. The 'Fungus recognition' model was developed based on a custom CNN architecture using the TensorFlow library. The model underwent training and testing on a publicly available dataset. Test results show that 'Fungus recognition' achieves a classification accuracy level of 90%, surpassing similar models considered. The developed model can be adapted for deployment on mobile computing devices, paving the way for its practical implementation in agriculture and horticulture.
Volume: 14
Issue: 5
Page: 5866-5873
Publish at: 2024-10-01

Single phase robustness variable structure load frequency controller for multi-region interconnected power systems with communication delays

10.11591/ijece.v14i5.pp5064-5071
Phan-Thanh Nguyen , Cong-Trang Nguyen
This paper proposes an estimator-based single phase robustness variable structure load frequency controller (SPRVSLFC) for the multi-region interconnected power systems (MRIPS) with communication delays. The key attainments of this research consist of two missions: i) a global stability of the power systems is guaranteed by removing the reaching phase in traditional variable structure control (TVSC) technique; and ii) a novel output feedback load frequency controller is established based on the estimator tool and output information only. Initially, a single-phase switching function is constructed to disregard the reaching phase in TVSC. Then, an unmeasurable state variable of the MRIPS is estimated by using the proposed estimator tool. Next, a new SPRVSLFC for the MRIPS is suggested based on the support of the estimator tool and output data only. Furthermore, a sufficient constraint is constructed by retaining the linear matrix inequality (LMI) procedure for ensuring the robust stability of motion dynamics in sliding mode. Finally, the performance of interconnected power plant under changed multi-constraints is imitated with the novel control technique to validate the practicability of the plant.
Volume: 14
Issue: 5
Page: 5064-5071
Publish at: 2024-10-01

A novel AI-AVO approach for maximum power generation of PMSG

10.11591/ijeecs.v36.i1.pp99-114
Prashant Kumar S. Chinamalli , Mungamuri Sasikala
Permanent magnet synchronous generators (PMSGs) are necessary for producing wind energy that is both highly reliable and reasonably priced. An inventive control technique for the driven interior PMSG (IPMSG) is presented here to maximize wind energy output and decrease losses. This research established an innovative optimization strategy for the highest wind power generation with reduced overall loss in PMSG-based Wind power generation systems. Considering, that the tip speed ratio (TPR), rotor speed 𝜔𝑟 , and quadrature axis current 𝐼𝑞 are optimized in the proposed work in such a way to enhance wind power generation. Further, the direct axis current 𝐼𝑑 is calculated from the optimized rotor speed 𝜔𝑟. The minimization of core loss is considered as the fitness function, which is a function of the direct current axis 𝐼𝑑and quadrature current axis 𝐼𝑞. The optimization is carried out using the explored aquila with African vulture optimization (EA-AVO) technique, which is the conceptual incorporation of prevailing techniques, like the aquila optimization algorithm (AOA) and the AVO algorithm. The performance of the proposed method is validated over the conventional methods, in terms of power output, losses, efficiency, and convergence analysis. According, the findings show that the proposed method attains less overall loss of 149.62 at the starting stage of 50 rotor speed, and it was 36.46% higher than AQO, 36.17% higher than AVOA, 36.59% higher than GOA methods 36.42%, and higher than WHO+PI approaches.
Volume: 36
Issue: 1
Page: 99-114
Publish at: 2024-10-01

Integrating hetero-core fiber optics sensor in intelligent technological textiles

10.11591/ijece.v14i5.pp4987-4995
Noor Azie Azura Mohd Arif , Chong Chee Jiun , Yong Wei Sen , Abang Annuar Ehsan
In the context of the emerging Industry 4.0 paradigm, smart fabric sensors have been representing a novel addition to the textile industry. The proposed sensors utilize macro-bending techniques with varying fiber optic core sizes. The study involved the construction and testing of macro-bending sensors using single-mode (9 μm) and hetero-core (50–9–50 μm) fibers, configured into seven sinusoidal loops. The experiment was further extended to different types of elastic textiles. Spandex demonstrated superior linearity compared with jersey and rubber bands. The integration with the DOIT ESP32 DevKit facilitated real-time monitoring of respiratory rates. The results from the experiment indicated that the macro-bending sensor, fabricated using hetero-core optical fiber, exhibited superior sensitivity in comparison to the sensor assembled from single-mode optical fiber, with respective sensitivity values of 1.72 and 1.30 dB/cm. The designed sensors displayed closely aligned behavior during forward and reverse loading, indicating the reversibility of the fiber optic sensor. Given its simplistic design and low fabrication cost, the proposed sensor holds significant potential for practical applications.
Volume: 14
Issue: 5
Page: 4987-4995
Publish at: 2024-10-01

The comparison of several cryptosystems using the elliptic curve: a report

10.11591/ijece.v14i5.pp5319-5329
Mai Manh Trung , Le Phe Do , Do Trung Tuan , Thu Thuy Trieu , Nguyen Van Tanh , Ngo Quang Tri , Bui Van Cong
The elliptic curve cryptosystem (ECC) has several applications in Information Security, especially in cryptography with two main activities including encrypting and decrypting. There were several solutions of different research teams which propose various forms of the elliptic curve cryptosystem on cryptographic sector. In the paper, we proposed a solution for applying the elliptic curve on cryptography which is based on these proposals as well as basic idea about the elliptic curve cryptosystem. We also make comparison between our proposal and other listed solution in the same application of the elliptic curve for designing encryption and decryption algorithms. The comparison results are based on parameters such as time consumption (t), RAM consumption (MB), source code size (Bytes), and computational complexity.
Volume: 14
Issue: 5
Page: 5319-5329
Publish at: 2024-10-01

Sliding mode control for the speed loop combined with adaptive coefficients for urban trains’ load variations of Nhon – Hanoi Station Metro line

10.11591/ijece.v14i5.pp5030-5037
An Thi Hoai Thu Anh , Tran Hung Cuong , Ha Van Dinh
Electric trains are becoming increasingly popular due to their environmental protection and ability to transport a large number of passengers. Alongside this trend, traction motors for electric trains have become diverse thanks to the rapid development of power electronics. Among them, the permanent magnet synchronous motor (PMSM) stands out with advantages such as high efficiency, high torque-to-current ratio, and compactness compared to other motors of the same power, making it the top choice. However, PMSM motors are nonlinear objects, so the nonlinear control technique of sliding mode control has been applied to the speed loop in this paper. Additionally, electric trains' inertial torque and load torque vary due to changes in the number of passengers during peak and off-peak hours and weather conditions. Therefore, this paper introduces two adaptive coefficients to account for these variations. Simulation results show that the sliding mode control technique for the speed loop circuit provides a faster and more accurate speed response. Meanwhile, the two parameters also adapt to the inertial and load torque variations. This ensures the safety and efficiency of the electric train system, contributing to the advantages of this mode of transportation.
Volume: 14
Issue: 5
Page: 5030-5037
Publish at: 2024-10-01
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