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International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal 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.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 6,393 Documents
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Automation conditions of mobile base station shelter via cloud and IoT computing applications Ahmed Hussein Shatti; Haider Ali Hasson; Laith Ali Abdul-Rahaim
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4550-4557

Abstract

In this paper, a monitoring and controlling process of the mobile base station shelter has been implemented. We have proposed a model that is based on a firebase cloud service and the principle of the internet of things (IoT) to carry out the process of automation. In this model, we have used Raspberry Pi 4 as the main microcontroller of our system that has interacted with a DHT11 Humidity-Temperature sensor and a PIR motion sensor. It's found that the Pi4 module provides efficient analysis, low consumption of power, and effective control of the operation. It turns ON/OFF the electrical appliances automatically inside the shelter. The main advantage of our proposed model is to maintain the temperature and humidity degrees inside the shelter within the required range of operation. Another important advantage is to diminish the tall human exertion level behind the monitoring process throughout the day. The model has been tested through a localhost server via an HTML page. The last one was created with the assistance of HTML and CSS languages to be used as a local user interface. Moreover, the Raspberry Pi 4 was programmed by Python Language to catch up on the reading of the sensors, processes the data, and sends it to the cloud service. Finally, those data will be shown in real-time to the authenticated user on the database of the firebase cloud service.
Time series activity classification using gated recurrent units Yi-Fei Tan; Xiaoning Guo; Soon-Chang Poh
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp3551-3558

Abstract

The population of elderly is growing and is projected to outnumber the youth in the future. Many researches on elderly assisted living technology were carried out. One of the focus areas is activity monitoring of the elderly. AReM dataset is a time series activity recognition dataset for seven different types of activities, which are bending 1, bending 2, cycling, lying, sitting, standing and walking. In the original paper, the author used a many-to-many Recurrent Neural Network for activity recognition. Here, we introduced a time series classification method where Gated Recurrent Units with many-to-one architecture were used for activity classification. The experimental results obtained showed an excellent accuracy of 97.14%.
Word-based encryption algorithm using dictionary indexing with variable encryption key length Ahmad Al-Jarrah; Amer Albsharat; Mohammad Al-Jarrah
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp669-683

Abstract

This paper proposes a new algorithm for text encryption utilizing English words as a unit of encoding. The algorithm vanishes any feature that could be used to reveal the encrypted text through adopting variable code lengths for the English words, utilizing a variable-length encryption key, applying two-dimensional binary shuffling techniques at the bit level, and utilizing four binary logical operations with randomized shuffling inputs. English words that alphabetically sorted are divided into four lookup tables where each word has assigned an index. The strength of the proposed algorithm concluded from having two major components. Firstly, each lookup table utilizes different index sizes, and all index sizes are not multiples of bytes. Secondly, the shuffling operations are conducted on a two-dimensional binary matrix with variable length. Lastly, the parameters of the shuffling operation are randomized based on a randomly selected encryption key with varying size. Thus, the shuffling operations move adjacent bits away in a randomized fashion. Definitively, the proposed algorithm vanishes any signature or any statistical features of the original message. Moreover, the proposed algorithm reduces the size of the encrypted message as an additive advantage which is achieved through utilizing the smallest possible index size for each lookup table.
Cassini-Huygens mission images classification framework by deep learning advanced approach Ashraf AlDabbas; Zoltan Gal
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2457-2466

Abstract

Developing a deep learning (DL) model for image classification commonly demands a crucial architecture organization. Planetary expeditions produce a massive quantity of data and images. However, manually analyzing and classifying flight missions image databases with hundreds of thousands of images is ungainly and yield weak accuracy. In this paper, we speculate an essential topic related to the classification of remotely sensed images, in which the process of feature coding and extraction are decisive procedures. Diverse feature extraction techniques are intended to stimulate a discriminative image classifier. Features extraction is the primary engagement in raw data processing with the purpose of data classification; when it comes across the task of analysis of vast and varied data, these kinds of tasks are considered as time-consuming and hard to be treated with. Most of these classifiers are either, in principle, quite intricate or virtually unattainable to calculate for massive datasets. Stimulated by this perception, we put forward a straightforward, efficient classifier based on feature extraction by analyzing the cell of tensors via layered MapReduce framework beside meta-learning LSTM followed by a SoftMax classifier. Experiment results show that the provided model attains a classification accuracy of 96.7%, which makes the provided model quite valid for diverse image databases with varying sizes.
Evaluation of exponential moving average application to smooth the power output of wind turbine with different control modes Dinh Chung Phan; Ngọc An Luu
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4708-4717

Abstract

This paper focused on evaluating the application of exponential moving average method into wind turbine to smooth its power output without an energy storage system or an anemometer. Wind turbine control modes including active power control mode and rotor speed control mode are considered. For each control mode, two positions of the Exponential Moving Average method in controller were compared to choose the best position. Additionally, the impact of smoothing factor on wind turbine performance was also considered to determine a reasonable value of the smoothing factor for each control mode. Simulation results in MATLAB/Simulink indicated that, for wind turbine using rotor speed control mode, the Exponential Moving Average method should be applied to reduce the variation of actual rotor speed signal while for wind turbine with the power control mode, it should be used to smooth reference power signal. From the performance of wind turbine with different smoothing factor values, we can suggest that the smoothing factor value should be set at 0.5 and 0.4 for the power control mode and the rotor speed control mode, respectively.
High-performance AES-128 algorithm implementation by FPGA-based SoC for 5G communications Paolo Visconti; Ramiro Velazquez; Stefano Capoccia; Roberto de Fazio
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4221-4232

Abstract

In this research work, a fast and lightweight AES-128 cypher based on the Xilinx ZCU102 FPGA board is presented, suitable for 5G communications. In particular, both encryption and decryption algorithms have been developed using a pipelined approach, so enabling the simultaneous processing of the rounds on multiple data packets at each clock cycle. Both the encryption and decryption systems support an operative frequency up to 220 MHz, reaching 28.16 Gbit/s maximum data throughput; besides, the encryption and decryption phases last both only ten clock periods. To guarantee the interoperability of the developed encryption/decryption system with the other sections of the 5G communication apparatus, synchronization and control signals have been integrated. The encryption system uses only 1631 CLBs, whereas the decryption one only 3464 CLBs, ascribable, mainly, to the Inverse Mix Columns step. The developed cypher shows higher efficiency (8.63 Mbps/slice) than similar solutions present in literature.
A smart fire detection system using iot technology with automatic water sprinkler Hamood Alqourabah; Amgad Muneer; Suliman Mohamed Fati
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp2994-3002

Abstract

House combustion is one of the main concerns for builders, designers, and property residents. Singular sensors were used for a long time in the event of detection of a fire, but these sensors can not measure the amount of fire to alert the emergency response units. To address this problem, this study aims to implement a smart fire detection system that would not only detect the fire using integrated sensors but also alert property owners, emergency services, and local police stations to protect lives and valuable assets simultaneously. The proposed model in this paper employs different integrated detectors, such as heat, smoke, and flame. The signals from those detectors go through the system algorithm to check the fire's potentiality and then broadcast the predicted result to various parties using GSM modem associated with the system. To get real-life data without putting human lives in danger, an IoT technology has been implemented to provide the fire department with the necessary data. Finally, the main feature of the proposed system is to minimize false alarms, which, in turn, makes this system more reliable. The experimental results showed the superiority of our model in terms of affordability, effectiveness, and responsiveness as the system uses the Ubidots platform, which makes the data exchange faster and reliable.
Broadband microstrip patch antenna at 28 GHz for 5G wireless applications Kinde Anlay Fante; Mulugeta Tegegn Gemeda
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2238-2244

Abstract

In this paper, a 28 GHz broadband microstrip patch antenna (MSPA) for 5G wireless applications is presented. The Rogers RT/Duroid5880 substrate material, with a dielectric constant of 2.2, the thickness of 0.3451 mm, and loss tangent of 0.0009, is used for the studied antenna to operate at 28 GHz center frequency. The proposed design of antenna is simulated by using CST studio suite. The simulation results highlight that the studied antenna has a return loss of -54.49 dB, a bandwidth of 1.062 GHz, a gain of 7.554 dBi. Besides, radiation efficiency and the sidelobe level of the proposed MSPA are 98% and 18.4 dB, respectively. As compared to previous MSPA designs reported in the recent scientific literature, the proposed rectangular MSPA has achieved significantly improved performance in terms of the bandwidth, beam-gain, return loss, sidelobe level, and radiation efficiency. Hence, it is a potential contender antenna type for emerging 5G wireless communication applications.
Development of cost-effective phasor measurement unit for wide area monitoring system applications V. Vijaya Rama Raju; K. H. Phani Shree; S. V. Jayarama Kumar
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4731-4739

Abstract

Sustained growth in the demand with unprecedented investments in the transmission infrastructure resulted in narrow operational margins for power system operators across the globe. As a result, power networks are operating near to stability limits. This has demanded the electrical utilities to explore new avenues for control and protection of wide area systems. Present supervisory control and data acquisition/energy management systems (SCADA/EMS) can only facilitate steady state model of the network, whereas synchrophasor measurements with GPS time stamp from wide area can provide dynamic view of power grid that enables supervision, and protection of power network and allow the operator to take necessary control/remedial measures in the new regime of grid operations. Construction of phasor measurement unit (PMU) that provide synchrophasors for the assessment of system state is widely accepted as an essential component for the successful execution of wide area monitoring system (WAMS) applications. Commercial PMUs comes with many constraints such as cost, proprietary hardware designs and software. All these constraints have limited the deployment of PMUs at high voltage transmission systems alone. This paper addresses the issues by developing a cost-effective PMU with open-source hardware, which can be easily modified as per the requirements of the applications. The proposed device is tested with IEEE standards.
A hybrid method of genetic algorithm and support vector machine for intrusion detection Tally, Mushtaq Talb; Amintoosi, Haleh
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i1.pp900-908

Abstract

With the development of web applications nowadays, intrusions represent a crucial aspect in terms of violating the security policies. Intrusions can be defined as a specific change in the normal behavior of the network operations that intended to violate the security policies of a particular network and affect its performance. Recently, several researchers have examined the capabilities of machine learning techniques in terms of detecting intrusions. One of the important issues behind using the machine learning techniques lies on employing proper set of features. Since the literature has shown diversity of feature types, there is a vital demand to apply a feature selection approach in order to identify the most appropriate features for intrusion detection. This study aims to propose a hybrid method of Genetic Algorithm and Support Vector Machine. GA has been as a feature selection in order to select the best features, while SVM has been used as a classification method to categorize the behavior into normal and intrusion based on the selected features from GA. A benchmark dataset of intrusions (NSS-KDD) has been in the experiment. In addition, the proposed method has been compared with the traditional SVM. Results showed that GA has significantly improved the SVM classification by achieving 0.927 of f-measure.

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