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Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world. The journal publishes original papers in the field of electrical, computer and informatics engineering.
Arjuna Subject : -
Articles 66 Documents
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Search results for , issue "Vol 11, No 6: December 2022" : 66 Documents clear
In-line measurement of multiphase flow viscosity Taisiia Ushkova; Alexandra Kopteva; Vadim Shpenst; Tole Sutikno; Mohd Hatta Jopri
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4856

Abstract

The transportation modes depend entirely on the viscosity of the oil. To date, none of the viscometric methods are able to provide measurements to meet all the requirements of oil flow, features of main oil pipelines, and trends in the oil industry, such as decarbonization and digitalization. The method of inline viscosity measurement of multiphase flow through a metal pipeline can be based on direct gamma ray measurement. It is stipulated by the ability of gamma-radiation to penetrate through the pipeline material without destroying it, as well as by the ability to work with flows containing free gas and the high capability to be introduced into automatic control systems. The authors consider the physical forces acting on the gas inclusions in the oil flow. They determine the physical dependence between the parameters determined by the radioisotope method and the viscosity of oil in the three-phase flow. These studies show good agreement with the work of other scientists. The prospect of further research will be to clarify the mathematical model of gas-oil flow, to increase the accuracy by reducing the number of assumptions made.
An maximum power point tracking interface circuit for low-voltage DC-type energy harvesting sources Eun Jeong Yun; Jong Tae Park; Chong Gun Yu
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4124

Abstract

This paper presents a maximum power point tracking (MPPT) interface circuit for low-voltage DC-type energy harvesting sources such as light and thermal energy. Most energy harvesting systems used in miniature-sized sensor systems require start-up circuits because the output voltages of small-sized energy transducers are very low and not enough to directly power electronic systems. The proposed interface circuit is driven directly by the low output voltages of small size energy transducers, eliminating the need for complex start-up circuitry. A simple MPPT controller with the fractional open-circuit voltage (FOCV) method is designed and fabricated in a 65-nm complementary metal oxide semiconductor (CMOS) process. Measurement results show that the designed circuit can track the MPP voltage even in the presence of the open-circuit voltage fluctuations and can operate properly at operating voltages as low as 0.3 V. The interface circuit achieves a peak power efficiency of 97.1% and an MPPT accuracy of over 98.3%.
Physical layer security of reconfigurable intelligent surface empowered wireless network with cooperative jammer Kehinde Oluwasesan Odeyemi; Pius Adewale Owolawi; Olakanmi Oladayo Olufemi
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4070

Abstract

This paper evaluates the physical layer security performance of a reconfigurable intelligent surface (RIS) enabled wireless network in the presence of a passive eavesdropper. To secure the information transmission, a cooperative jammer is proposed to generate interference signal that degrade the performance of the eavesdropper. The source-to-RIS and RIS-to-destination links are subjected to Rician and Rayliegh fading distributions with phase errors, respectively, while other transmission links in the network follow the Nakagami-m fading distributions. The system phase error of the RIS is estimated by the von Mises distribution. To quantify the secrecy performance of the concerned system, the exact closed-form expressions in terms of connection outage probability (COP), security outage probability (SOP), and secrecy throughput (ST) are derived. In addition, the asymptotic expression of the system COP is obtained at high signal-to-noise ratio (SNR), providing more insight about the system performance. The accuracy of the derived expression is justified by Monte Carlo simulation. Also, the results clarify the analysis of the security performance, taking into account the impact of system and channel parameters on the system.
Hybrid load-balancing algorithm for distributed fog computing in internet of things environment Abrar Saad Kadhim; Mehdi Ebady Manaa
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4127

Abstract

Fog computing is a novel idea created by Cisco that provides the same capabilities as cloud computing but close to objects to improve performance, such as by minimizing latency and reaction time. Packet failure can happen on a single fog server across a large number of messages from internet of things (IoT) sensors due to several variables, including inadequate bandwidth and server queue capacity. In this paper, a fog-to-server architecture based on the IoT is proposed to solve the problem of packet loss in fog and servers using hybrid load balancing and a distributed environment. The proposed methodology is based on hybrid load balancing with least connection and weighted round robin algorithms combined together in fog nodes to take into consideration the load and time to distribute requests to the active servers. The results show the proposed system improved network evaluation parameters such as total response time of 131.48 ms, total packet loss rate of 15.670%, average total channel idle of 99.55%, total channel utilization of 77.44%, average file transfer protocol (FTP) file transfer speed (256 KB to 15 MB files) of 260.77 KB/sec, and average time (256 KB to 15 MB) of 19.27 sec.
An IoT-fuzzy based password checker system for wireless video surveillance system Mohammed Ahmed Jasim; Tayseer Salman Atia
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4375

Abstract

Wireless video surveillance systems (WVSS) are deployed in large environments for use in strategic places such as town centers, public streets, and airports and play an essential role in protecting critical infrastructure. However, WVSSs are vulnerable to unauthorized access due to weak login credentials, which leads to their exploitation to launch cyberattacks on other systems, such as distributed denial-of-service attacks. Hence, it is essential to secure these systems from unauthorized access. This paper proposes the Mamdani fuzzy inference system (FIS)-based password checker algorithm to estimate the password strength ratio (PSR) of internet protocol (IP) cameras and internet of things (IoT) devices. This algorithm composes three stages, the password extraction stage, which evaluates the input parameters of FIS from the real-time streaming protocol (RTSP) protocol using a counter of password characters. Then, the processing stage uses Mamdani FIS to optimize the input parameters to calculate the PSR. Finally, the alarm stage will notify the system administrator about weak IoT nodes. Unlike the existing approaches, this algorithm improves detection accuracy by informing the system administrator about threatened nodes. Extensive experiments are carried out to determine the efficiency of the proposed algorithm. The results confirm the efficiency of the proposed algorithm with high accuracy, which outperforms existing schemes.
Power system contingency classification using machine learning technique Sandhya Rani Gongada; Muktevi Chakravarthy; Bhukya Mangu
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4031

Abstract

One of the most effective ways for estimating the impact and severity of line failures on the static security of the power system is contingency analysis. The contingency categorization approach uses the overall performance index to measure the system's severity (OPI). The newton raphson (NR) load flow technique is used to extract network variables in a contingency situation for each transmission line failure. Static security is categorised into five categories in this paper: secure (S), critically secure (CS), insecure (IS), highly insecure (HIS), and most insecure (MIS). The K closest neighbor machine learning strategy is presented to categorize these patterns. The proposed machine learning classifiers are trained on the IEEE 30 bus system before being evaluated on the IEEE 14, IEEE 57, and IEEE 118 bus systems. The suggested k-nearest neighbor (KNN) classifier increases the accuracy of power system security assessments categorization. A fuzzy logic approach was also investigated and implemented for the IEEE 14 bus test system to forecast the aforementioned five classifications.
Packet loss compensation over wireless networked using an optimized FOPI-FOPD controller for nonlinear system Muhannad Ali Hasan; Ahmed A. Oglah; Mehdi J. Marie
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4345

Abstract

Wireless networked control systems (WNCS) consist of an actuator, sensor, and controller communicating over wireless networks in place of traditional point-to-point wired connection. Due to their main advantages, a decrease in maintenance costs, more flexibility, and safety could be achieved. As a result, it attracted a great deal of interest, but packet losses and time delays in the wireless network through transmitting and receiving the data are considered very challenging issues, which impair the output accuracy of the WNCS and can affect the entire system stability. In this study, integer-order proportional integral-proportional derivative (PI-PD) and fractional-order PI-PD (FOPI-FOPD) controllers are proposed to reduce the effect of expected packet loss in a WNCS to improve system performance. At high packet loss percent, the PI controller is introduced to act as a compensator in the feed-forward loop to keep the system stable. MATLAB/Simulink and Truetime simulator are used to simulate the WNCS. The rotary inverted pendulum (RIP) is utilized as the object of the controllers. Grey wolf optimization (GWO) algorithm is used to find the optimal controllers and compensator parameters. The simulation results showed that the FOPI-FOPD is superior to PI-PD in the packet loss compensation.
A self-startup DC-DC boost converter for thermal energy harvesting in a 0.35 μm CMOS process Eun Jeong Yun; Chong Gun Yu
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4133

Abstract

In this paper a self-startup DC-DC boost converter for thermal energy harvesting applications is presented. A startup circuit boosts an internal supply voltage using a low voltage generated from a thermoelectric generator to operate the internal circuitry of the converter. To reduce power dissipation, the startup circuit is disabled after the startup operation is finished. A boosted output voltage is obtained by alternating an auxiliary converter for the internal supply voltage and a main converter for the output voltage. The converter has been implemented in a 0.35 μm complementary metal–oxide–semiconductor (CMOS) process. Measurement results shows that the designed converter is capable of generating an output voltage close to 3V from an input voltage of 200 mV, and can provide a maximum output power of 278 μW with an end-to-end power efficiency of 46.5%. It occupies an active area of 0.36 mm2.
Classifications of signatures by radial basis neural network Musab Tahseen Salahaldeen Al-Kaltakchi; Saadoon Awad Mohammed Al-Sumaidaee; Raid Rafi Omar Al-Nima
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.3931

Abstract

The personal signature can be considered one of the most common behavioral biometrics. In this study, signatures are classified according to their specifications. The statistical calculation is considered for the specifications of each signature. Then, a radial basis neural network (RBNN) is adapted to apply multiple classifications for the employed signatures. A big number of signatures are utilized; they are obtained from the database called biometric ideal test (BIT). The total number of collected signatures is equally divided between the testing and training phases, where it is partitioned into 50% for the training and 50% for the testing. The proposed technique could achieve attractive performance, where each of the mean square error (MSE) and mean absolute error (MAE) attained a small value of 0.028. In addition, the proposed approach using the RBNN is compared with the different neural networks of the state-of-the-art techniques in order to demonstrate that the outcomes are acceptable and successful.
Design and analysis of microstrip patch antenna for 5G wireless communication systems Md. Sohel Rana; Md. Mostafizur Rahman Smieee
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.3955

Abstract

Due to lower latency, greater transmission speed, wider bandwidth, and the possibility to connect with greater multiple devices, fifth-generation (5G) networks are far better than 4G. In this study, a microstrip patch antenna operating at 28 GHz is investigated and modeled for future 5G communication technologies. The substrate used in this work for the antenna is Rogers RT/Duroid5880. Dielectric of the substrate is 2.2 and thickness is 0.3451 mm. CST software is used to simulate the antenna as it is convenient to use. From the simulation, the return loss, gain, radiation efficiency, side-lobe level was found to be -38.348 dB, 8.198dB, 77%, and -18.3 dB respectively. The result found from this simulation is better than the works took place in the past. As a result, it can be utilized as a capable candidate for 5G wireless technology. The results of this proposed antenna are superior to those of existing antennas published in recent scientific journals. As a result, it's likely that this antenna will meet the needs of 5G wireless communication systems.

Page 5 of 7 | Total Record : 66

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