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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

Faults-as-address simulation

10.11591/ijra.v13i4.pp452-468
Vladimir Hahanov , Svetlana Chumachenko , Eugenia Litvinova , Ivan Hahanov , Veronika Ponomarova , Hanna Khakhanova , Georgiy Kulak
Fault-as-address-simulation (FAAS) is a simulation mechanism for testing combinations of circuit line faults, represented by the bit addresses of element logical vectors. The XOR relationship between the test set T and the truth table L of the element forms a deductive vector for fault simulation, using truth table addresses or the logic vector bits. Addresses are used in the simulation matrix to mark those n-combinations of input faults detected at the element's output. The columns of the simulation matrix are treated as n-row addresses to generate an element output row via a deductive vector. There is no transport of input faults to the element output, Only the 1-signals written in the non-input row coordinates of the circuit simulation matrix. The simulation matrix is initially filled with 1-signals along the main diagonal. The line faults detected on the test set of circuits are determined by the inverse of lines good values, which have 1-values in the matrix row corresponding to the output circuit element. The deductive vector is obtained by the XOR-relations between the test set and logical vector in three table operations. The advantage of the proposed FAAS mechanism is the predictable complexity of the algorithm and memory consumption for storing data structures when simulating a test set.
Volume: 13
Issue: 4
Page: 452-468
Publish at: 2024-12-01

Design and implementation of high voltage DC generation system based on push-pull inverter integrated with Cockcroft-Walton

10.11591/ijpeds.v15.i4.pp2388-2396
Luthfiyyatun Mardiyah , Abdul Syakur , Iwan Setiawan
High-voltage DC generation is essential for industrial, medical, and scientific applications, such as X-ray machines, particle accelerators, and electrostatic precipitators. Existing high-voltage DC generators face challenges such as high cost, complexity, and inefficiency. A simplified and cost-effective solution that can reliably generate high-voltage DC from a low DC power supply is needed. This paper discusses the design and implementation of a high-voltage DC generator with a low-voltage DC power supply input. The generator employs a push-pull inverter to transform the DC 12 V voltage into AC 400 V at a frequency of 20 kHz. A Cockcroft-Walton circuit, comprising a positive and a negative Cockcroft-Walton circuit, then steps up this voltage. The Arduino Nano microcontroller uses pulse width modulation (PWM) signals to control the system. This research aims to provide a reliable and economical high-voltage DC voltage generation system for various applications. We discuss the design process and hardware implementation in detail. We set the target output voltage of this hardware at 10 kV DC. MATLAB/Simulink simulation software verifies the performance of the proposed high-voltage generator, and hardware implementation validates its effectiveness. The proposed high-voltage DC generator's hardware tests successfully produced an output voltage of 14.12 kV DC.
Volume: 15
Issue: 4
Page: 2388-2396
Publish at: 2024-12-01

Stochastic assessment of voltage sags and techno-economic optimization

10.11591/ijpeds.v15.i4.pp2501-2516
Jeyagopi Raman , Choon Kit Chan , Munish Kumar Gupta , Yuli Panca Asmara , Sudesh Nair Baskara , Chaloemphol Kaewthep , Yuzhen Gao
Power quality has become an essential concern for industries and domestic energy consumption with the development of sophisticated equipment like micro-electronic devices. When a power quality event happens, such as voltage sag, financial losses for industries increase tremendously. Therefore, voltage sag evaluation becomes crucial for predicting the number of events and severity of voltage sag events of the electrical network. Industries can determine the mitigation investment needed for optimal operation using the knowledge obtained through voltage sag analysis method. Thus, the first part of the study addressed the development of a stochastic assessment method for voltage sag at an interested bus in the power system network, which was an initial objective of the study. The second part of the research investigates dynamic voltage restorer (DVR) control techniques, as well as the necessary capacitance and energy storage dimensions. The studies also recommend a technique for economic evaluation that emphasizes the expense of voltage sag events as well as the cost of investment in DVR with and without voltage sag events. The size of DVR and economic assessment model established in these studies enables industries to rate the cost of voltage sag and the total investment in mitigation devices.
Volume: 15
Issue: 4
Page: 2501-2516
Publish at: 2024-12-01

Construction of fuzzy systems based on fuzzy c-means clustering and singular value decomposition for predicting rate of penetration in geothermal drilling

10.11591/ijpeds.v15.i4.pp2190-2198
Agus Maman Abadi , Akhid Khirohmah Mansyaroh , Allen Haryanto Lukmana , Lusi Harini , Aditya Wisnugraha Sugiyarto
The potential for geothermal energy is very abundant, but its utilization is still minimal. Therefore, the utilization of geothermal energy facility that has been installed must be optimized. This study aims to predict drilling rate of penetration using the first-order Sugeno’s fuzzy system. Fuzzy c-mean and singular value decomposition were used to form the rules and determined the parameters respectively. This study used in total of 6738 data of geothermal wells drilling in Indonesia. The results show that the rate of penetration prediction has accuracy 85.76% for data training and 87.72% for data testing, and it is better than the radial basis function neural networks (RBFNN) and RBFNN-singular value decomposition (SVD) methods.
Volume: 15
Issue: 4
Page: 2190-2198
Publish at: 2024-12-01

An introduction to using QR codes in web portals for synchronizing calendar events over phones

10.11591/ijra.v13i4.pp469-475
Inder Pal Singh Sethi , Om Pradyumana Gupta , Sulbha Bhaisare , Ritesh Kumar Dwivedi , Misha Kapoor
An optical label with machine-readable information about the object it is attached to is called a quick response (QR) code. QR codes frequently hold information for a tracker, locator, or identifier that directs users to a website or application. To efficiently store data, a QR code has four standardized encoding modes: kanji, byte or binary, alphanumeric, and numeric. As a means of identifying a wide range of commercial goods, including transactions, ads, and other public notices, the QR code gained popularity. In our web portal, the proposed QR code model synchronizes all the event details synchronously in the mobile calendar. QR code is used for web-to-mobile data transfer, saving events or meeting details in the mobile calendar. Anyone with a smartphone can view the data encoded in a QR code by scanning it. Although it makes it easier for end users to decode QR codes, verifying access to the encoded data is a cause for worry. Our proposed model validates access to data through the QR code, allowing only authorized personnel to access data. To ensure accessibility control, the proposed model has the functionality of a one-time password (OTP) that enhances application security. The model achieved an average decoding speed of 157 milliseconds with an error rate of 0.38%.
Volume: 13
Issue: 4
Page: 469-475
Publish at: 2024-12-01

Integrating artificial immune systems and multi-layer perceptron-biogeography-based optimization for enhanced inverse kinematics in robotic arm

10.11591/ijra.v13i4.pp401-409
Amel Serat , Bachir Djebbar
Determining required joint angles to achieve a desired position in a manipulator’s arm is a complicated problem without simple analytical solutions. This paper researches several computational methods based on artificial intelligence (AI) for calculating the joint positions of the 6-DOF robotic arm. We can extrapolate relevance, for example, to the crucial role that robotic manipulator arms play in industrial and medical applications, where enhanced precision and movement efficiency may sharply boost performance and expand applicability. Here, we investigate the effectiveness of methods, such as the artificial immune system (AIS) and multi-layer perceptron-biogeography-based optimization (MLP-BBO). Those AI-driven methods have been applied to determine joint angles for reaching desired positions through simulations for the robotic arm. The results show that the AIS and MLP-BBO approach can handle the intrinsic complexities of the task, thus testifying to the practicability and dependability of these two methods in this application. From the findings in the study, it was indicated that AI-driven techniques can effectively answer the complex problem of the robotic manipulator arm in finding joint angles.
Volume: 13
Issue: 4
Page: 401-409
Publish at: 2024-12-01

LCL filter based high power density AC/DC converter for fast charging applications

10.11591/ijpeds.v15.i4.pp2308-2322
Nguyen Dinh Tuyen , Nguyen Van Minh Tam , Truong Phuoc Hoa
This paper introduces a LCL filter design tailored for a 40 kW three-phase grid-connected converter utilized in electric vehicle onboard fast chargers. In contrast to conventional filters, the LCL filter finds extensive application in AC/DC converters for power factor correction, thanks to its enhanced harmonic reduction and improved stability of the system. The parameters of LCL filter are devised based on considerations such as the system’s power, the frequency of the alternating current (AC) input, and the PWM frequency, determined through simulation and comprehensive theoretical analysis. By implementing a dual-current closed-loop control strategy, the system ensures a robust response for both the current on the AC side of the converter and the voltage on the direct current (DC) side. The analysis of the system’s performance includes rapid dynamic response, system efficiency, AC current harmonic, and DC ripple voltage. Both simulation and experimental results are presented to validate the proposed design for the LCL filter.
Volume: 15
Issue: 4
Page: 2308-2322
Publish at: 2024-12-01

Maternal hair lead and cytokine pro-inflammatory effects in preterm birth

10.11591/ijphs.v13i4.24146
Qonita Nur Qolby , Julian Dewantiningrum , Besari Adi Pramono , Nani Maharani , Eka Djatnika Nugraha , Muflihatul Muniroh
This case-control study analyzed the lead (Pb), interleukin 6 (IL-6), and tumor necrosis factor alpha (TNF-α) levels in pregnant women with preterm birth (PTB) in Central Java, Indonesia. Hair samples from 72 pregnant women were collected non-invasively. The prenatal exposure to Pb was determined with the total reflection X-ray fluorescence (TXRF) method. Serum IL-6 and TNF-α were examined using enzyme-linked immunosorbent assays (ELISA). The Pb concentration in hair was slightly higher in women with PTB than those without PTB; however, this difference was not statistically significant. An elevated hair Pb level was not associated with increased PTB risk (OR 24.69, 95% CI 0.93–653.82, p>0.05). A serum TNF-α level ≥27 pg/ml, a serum IL-6 level ≥9 pg/ml, and the spouse’s smoking frequency were significantly associated with increased PTB risk (TNF-α OR 42.25, 95% CI 5.26–339.61; IL-6 OR 22.33, 95% CI 3.12–158.54; spouse’s smoking frequency OR 1.28, 95% CI 1.09–1.5), while the maternal hemoglobin concentration significantly decreased PTB risk (OR 0.43, 95% CI 0.2–0.927). This study demonstrates that maternal hair Pb concentration has no significant relationship with PTB. Serum TNF-α, IL-6, and the spouse’s smoking frequency potentially increased PTB risk, while the maternal hemoglobin level is a protective factor.
Volume: 13
Issue: 4
Page: 1826-1833
Publish at: 2024-12-01

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

10.11591/ijaas.v13.i4.pp920-935
Gaurav Himanta Khaklari , Prasenjit Talukdar
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.
Volume: 13
Issue: 4
Page: 920-935
Publish at: 2024-12-01

Factors of susceptibility to online romance scam in Malaysia: unraveling the complex pathways

10.11591/ijphs.v13i4.23669
Evi Kurniasari Purwaningrum , Yi Ming Ho , Diana Imawati , Kususanto Ditto Prihadi , Mansor Abu Talib
In this cross-sectional study, we delve into the multifaceted realm of online scam victimization by investigating a diverse array of individual factors that may predispose adults to fall prey to online scams. The central objective of this research is to ascertain the strongest predictor among the following variables: loneliness and the sense of mattering and to elucidate the moderating effect of social media engagement (SME) on the relationship between these predictors and online romantic scam (ORS) susceptibility (OSS). A sample of 380 adults aged 18 to 65 years (M=33.4) participated in this study to respond to demographic questionnaires and scales of the respective variable. The results suggested that the direct effect of relationship satisfaction on ORS susceptibility is not significant without the serial mediation roles of loneliness and mattering at a high level of SME. Further implications, limitations, and suggestions are discussed.
Volume: 13
Issue: 4
Page: 2053-2060
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

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

Fuzzy logic assessment of X-ray tube risks in robotic C-arm angiography: a failure mode and effect analysis study

10.11591/ijra.v13i4.pp506-514
Ade Firdaus , Andi Adriansyah , Nanda Ferdana , Rahmalisa Suhartina , Rino Ferdian Surakusumah , Jakfat Haekal , Zulhamidi Zulhamidi , Abu Ubaidillah Shamsudin
This research examines the integration of robotic C-arm technology in angiography, a critical tool for treating cardiac conditions. The robotic C-arm, which includes an X-ray tube, is essential for scanning patients during procedures. The study also investigates the associated risks, specifically in Indonesian hospitals with cardiac facilities. Angiography is used to diagnose and treat heart disease by visualizing blood vessels and facilitating catheterization procedures. However, its mobility poses hazards and can impact the process. To address potential risks, failure mode and effect analysis (FMEA) is utilized. Traditionally, risk assessment using risk priority numbers (RPN) is conducted, but these may not accurately reflect failures due to complex evaluating processes. To overcome this limitation, fuzzy logic is employed, enhancing risk assessment accuracy. Through this approach, twenty-seven failure modes are identified across two brands, with ten major ones prioritized using fuzzy logic. These findings facilitate the development of preventive measures to mitigate future failures and enhance patient safety during angiography in hospitals. In conclusion, the study underscores the importance of robust risk management in medical equipment, particularly in dynamic environments. By integrating fuzzy logic into risk assessment, the study improves prioritization accuracy, enabling effective allocation of resources for preventive actions.
Volume: 13
Issue: 4
Page: 506-514
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
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