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Coplanar waveguide-fed ultra-wideband antenna with WLAN band
Chaiyong Soemphol;
Niwat Angkawisittpan
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v21.i3.pp1523-1529
A coplanar waveguidefed ultra-wideband antenna with extended transmission band to WLAN frequency is investigated. The proposed antenna consists of a modified semi-circular patch and staircase of ground plane. The prototype is fabricated on a low cost FR4 substrate with dielectric constant of 4.4 with thicknes of 0.8 mm. The overall dimensions of proposed UWB antenna are 34 mm x 40 mm. The simulation and experimental results have been shown that the proposed antenna archives low VSWR over transmission bandwidth from 2.10 - 12.7 GHz to cover both WLAN and UWB bands. The average gain is 3.87 dBi. It depicts nearly omni-directional radiation pattern like dipole antenna. Moreover, the fabricated prototype antenna shows a good agreement between the simulated and measured results
Fault diagnosis of a squirrel cage induction motor fed by an inverter using lissajous curve of an auxiliary winding voltage
Yakout Khadouj Jelbaoui;
El Menzhi Lamiaà;
Abdallah Saad
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v21.i3.pp1299-1308
The development of electronic power components has allowed the increase of the induction machine performance. Indeed, monitoring squirrel cage induction motors driven through rectifiers and inverters has been a major concern. This paper presents a new method to diagnose the combination inverter-machine faults. This technic considers an auxiliary winding which is a small coil inserted between two stator phases. It is based on Lissajous curve of this auxiliary winding voltage Park components. For this purpose, modeling the electromechanical conversion chain is necessary. The focus will particularly be on modeling both the squirrel cage induction machine and the inverter in a non-defected case which is a reference. Moreover, the explicit expressions developed for the inserted winding voltage and its Park components will be presented. The simulation results show the effectiveness of the proposed method.
Haar wavelet method for solving coupled system of fractional order partial differential equations
Abbas AL-Shimmary;
Sajeda Kareem Radhi;
Amina Kassim Hussain
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v21.i3.pp1444-1454
This paper deal with the numerical method, based on the operational matrices of the Haar wavelet orthonormal functions approach to approximate solutions to a class of coupled systems of time-fractional order partial differential equations (FPDEs.). By introducing the fractional derivative of the Caputo sense, to avoid the tedious calculations and to promote the study of wavelets to beginners, we use the integration property of this method with the aid of the aforesaid orthogonal matrices which convert the coupled system under some consideration into an easily algebraic system of Lyapunov or Sylvester equation type. The advantage of the present method, including the simple computation, computer-oriented, which requires less space to store, time-efficient, and it can be applied for solving integer (fractional) order partial differential equations. Some specific and illustrating examples have been given; figures are used to show the efficiency, as well as the accuracy of the, achieved approximated results. All numerical calculations in this paper have been carried out with MATLAB.
An automatic system for detecting voltage leaks in houses to save people's lives
Hussein M. Haglan;
Hussam Jasim Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v21.i3.pp1485-1492
Many people are exposed to many dangers, such as electrical leakage into parts of the home that lead to death, injury, or loss of material resources. With the great developments that happen daily in the field of technology, one of the most important examples of these developments is the Arduino. The Arduino is a company that produces a software and electronic parts that are open source for companies and students in order to design and build digital devices, design and implement projects and systems that can be linked together or linked with the Internet to facilitate their use to serve society and humanity. It became easier to deploy this technology to solve problems that put people at risk. Many systems that detect leakage of gas, liquids and fires were built using these modern technologies to protect the lives of people and their resources, but no one has actually used these technologies to detect unexpected electrical voltage leaks into the home's water network or walls that resulting from damage in some parts of electrical devices. Therefore, in this paper, we have proposed and designed a system that can detect an unexpected voltage leak from some electric devices to the water network or walls in houses, alarm of house owners by sound, and cut off the electrical current to the house in order to save people's lives and resources.
Combining feature selection and hybrid approach redefinition in handling class imbalance and overlapping for multi-class imbalanced
Hartono Hartono;
Erianto Ongko;
Yeni Risyani
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v21.i3.pp1513-1522
In the classification process that contains class imbalance problems. In addition to the uneven distribution of instances which causes poor performance, overlapping problems also cause performance degradation. This paper proposes a method that combining feature selection and hybrid approach redefinition (HAR) method in handling class imbalance and overlapping for multi-class imbalanced. HAR was a hybrid ensembles method in handling class imbalance problem. The main contribution of this work is to produce a new method that can overcome the problem of class imbalance and overlapping in the multi-class imbalance problem. This method must be able to give better results in terms of classifier performance and overlap degrees in multi-class problems. This is achieved by improving an ensemble learning algorithm and a preprocessing technique in HAR using minimizing overlapping selection under SMOTE (MOSS). MOSS was known as a very popular feature selection method in handling overlapping. To validate the accuracy of the proposed method, this research use augmented R-Value, Mean AUC, Mean F-Measure, Mean G-Mean, and Mean Precision. The performance of the model is evaluated against the hybrid method (MBP+CGE) as a popular method in handling class imbalance and overlapping for multi-class imbalanced. It is found that the proposed method is superior when subjected to classifier performance as indicate with better Mean AUC, F-Measure, G-Mean, and precision.
Bidirectional gated recurrent unit for improving classification in credit card fraud detection
Imane Sadgali;
Nawal Sael;
Fouazia Benabbou
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v21.i3.pp1704-1712
In recent years, the use of credit cards around the world has grown enormously. Thus, the number of fraud cases have also increased, resulting in losses of thousands of dollars worldwide. Therefore, it is mandatory to use techniques that are able to assist in the detection of credit card fraud. For this purpose, we have proposed a multi-level architecture, composed of four levels: authentication level, behavioral level, smart level and background processing level. In this paper, we focus on the implementation of the smart level. The aim of this level is to develop a classifier for the detection of credit card fraud, using bidirectional gated recurrent units (BGRU). The experiments, applied on well-known credit card fraud dataset from Kaggle, show that this model has peak performance compared to other proposed models, with 97.16% for accuracy rate and 99.66% for the area under the ROC curve.
Development of an inventory management system using association rule
Tinuke Omolewa Oladele;
Roseline Oluwaseun Ogundokun;
Adekanmi Adeyinka Adegun;
Emmanuel Abidemi Adeniyi;
Ayobami Tayo Ajanaku
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v21.i3.pp1868-1876
Stores today still make use of manual approaches to keeping inventory which could be cumbersome. Having a computerized inventory system would make inventory management more efficient and effective. In this chapter, an Inventory Management System using Association Rule was developed which will ensure proper record keeping and keep items in stocks updated. ANGULARJS, a JavaScript framework, was used for the implementation of the system, PHP (hypertext pre-processor) was used for the backend of the system development as well as the database management, HTML was used alongside CSS for the system interface design and NoSQL database was the database used for this research. In conclusion, a computerized inventory system that had been improved using the Association Rule method was the resulting product useful for creating transactions, updating items in stock, record keeping, generating reports for decision making, and lastly, the system will make the stores more effective.
New text steganography method using the arabic letters dots
Ahlam R. Khekan;
Hiba Mohammed Wajeh Majeed;
Omer F. Ahmed Adeeb
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v21.i3.pp1784-1793
With the increasing technological and electronic development, methods have been developed to hide important information using text steganography as a new technology, since it is not noticeable and easy to send and receive. The use of the Arabic language is one of the new methods used to hide data. In this work, we preview our method that depends to use the part of Arabic language properties to embed the secret English message in to cover text to create text steganography. More than half of the Arabic characters contain dots. Several characters have upper dots and others have lower dots. Some have one dot others have two dots. Few have even three dots. In this new idea, we will use the dots of charters to embed the English secret message. First, we will compress the secret message by using the 5-Bit Encoding (T-5BE) to make the cover text able to embed more bits of the secret message by 37.5%. Then we start using the Arabic semantic dictionary to correct the hiding path and enhancement the stego-cover text to eliminate errors caused by switching words. In this research, we were able to extract experimental results that show that the proposed model achieves high masking accuracy in addition to the storage capacity of the cover text.
A novel image encryption scheme based on DCT transform and DNA sequence
Ali A. Yassin;
Abdullah Mohammed Rashid;
Abdulla J. Yassin;
Hamid Alasadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v21.i3.pp1455-1464
Recently, the concept of DNA has been invested in computing technology in different ways which linking information technology and biological sciences. There are several encryption algorithms based on DNA encoding that has been proposed, which leads to generating a new direction in image encryption. However, the DNA encryption scheme has drawbacks such as expensive experimental equipment, difficult operations, and hard to hold its biotechnology. Additionally, during careful cryptanalysis that applied to most of these image encryption schemes, we notice that DNA operators can only influence one DNA base, which causes poor diffusion. Our proposed scheme is not applied complex biological operation but just is given to improve the diffusion ability of image encryption scheme by using DNA sequence and DCT transform. Our works overcome above-aforementioned issues. Furthermore, empirical results on real images and security analysis demonstrate that our proposed scheme not only has flexibility and efficiency encryption scheme but also has the ability to resist well-known attacks such as entropy attack, differential attack, statistical attack, chosen/known plain image attack. Additionally, our work enjoys several strong characteristics as follows: (1) the decryption error is very low to recover the original image; (2) Once key for each encryption process and if the user wants to use the same key in many times, our proposed scheme supports secret key sensitivity; (3) the value of correlation of the encrypted image is null; (4) the scrambling process is good and generate high disorder at the output. As a result, our proposed scheme achieves a good balance between strong security and high performance.
Accident vehicle types classification: a comparative study between different deep learning models
Mardin A. Anwer;
Shareef M. Shareef;
Abbas M. Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 3: March 2021
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v21.i3.pp1474-1484
Classifying and finding type of individual vehicles within an accident image are considered difficult problems. This research concentrates on accurately classifying and recognizing vehicle accidents in question. The aim to provide a comparative analysis of vehicle accidents. A number of network topologies are tested to arrive at convincing results and a variety of matrices are used in the evaluation process to identify the best networks. The best two networks are used with faster recurrent convolution neural network (Faster RCNN) and you only look once (YOLO) to determine which network will identifiably detect the location and type of the vehicle. In addition, two datasets are used in this research. In consequence, experiment results show that MobileNetV2 and ResNet50 have accomplished higher accuracy compared to the rest of the models, with 89.11% and 88.45% for the GAI dataset as well as 88.72% and 89.69% for KAI dataset, respectively. The findings reveal that the ResNet50 base network for YOLO achieved higher accuracy than MobileNetV2 for YOLO, ResNet50 for Faster RCNN with 83%, 81%, and 79% for GAI dataset and 79%, 78% and 74% for KAI dataset.