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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 66 Documents
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Search results for , issue "Vol 23, No 3: September 2021" : 66 Documents clear
Efficient hardware implementation for lightweight mCrypton algorithm using FPGA Yasir Amer Abbas; Ahmed Salah Hameed; Safa Hazim Alwan; Maryam Adnan Fadel
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1674-1680

Abstract

The lightweight cryptography is used for low available resources devices such as radio frequency identification (RFID) tags, internet of things (IoTs) and wireless sensor networks. In such case, the lightweight cryptographic algorithms should consider power consumption, design area, speed, and throughput. This paper presents a new architecture of mCrypton lightweight cryptographic algorithm which considers the above-mentioned conditions. Resource-shared structure is used to reduce the area of the new architecture. The proposed architecture is implemented using ISE Xilinx V14,5 and Spartan 3 FPGA platform. The simulation results introduced that the proposed design area is 375 of slices, up to 302 MHz operating frequency, a throughput of 646 Mbps, efficiency of 1.7 Mbps/slice and 0.089 Watt power consumption. Thus, the proposed architecture outperforms similar architectures in terms of area, speed, efficiency and throughput.
Design of a portable radio-frequency-identification reader capable to reading a user memory bank for smart-building energy management Ajib Setyo Arifin; M. B. Fathinah Hanun; Eka Maulana; I Wayan Mustika; Fitri Yuli Zulkifli
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1538-1549

Abstract

Communication is an important factor in smart-building energy management (SBEM). Many communications technologies have been applied to SBEM, including radio-frequency identification (RFID). RFID has been used not only for identification but also for carrying information, which is stored in a user memory bank attached to the tag. To access the user memory bank, an RFID reader should comply with ISO 18000-6C standards. The greatest challenge of RFID-reader technology is its short communication range, which limits the sensing area. To overcome this problem, this paper proposes a portable RFID reader built to an ISO 18000-6C standard to extend the sensing area due to its moveability. The reader is designed using low-cost devices widely available on the market for ease of duplication and assembly by researchers, educators, and startups. The proposed RFID reader can read passive tags with distances up to 12 and 5.5 m for line-of-sight (LOS) and non-line-of-sight (NLOS) communication, respectively. The minimum received-signal-strength indicators (RSSIs) for LOS and NLOS are found to be −63.75 and −59.66 dBm, respectively. These results are comparable with those of non-portable RFID readers on the market.
Enhancement of WiMAX networks using OPNET modeler platform Noor Nateq Alfaisaly; Suhad Qasim Naeem; Azhar Hussein Neama
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1510-1519

Abstract

Worldwide interoperability microwave access (WiMAX) is an 802.16 wireless standard that delivers high speed, provides a data rate of 100 Mbps and a coverage area of 50 km. Voice over internet protocol (VoIP) is flexible and offers low-cost telephony for clients over IP. However, there are still many challenges that must be addressed to provide a stable and good quality voice connection over the internet. The performance of various parameters such as multipath channel model and bandwidth over the Star trajectoryWiMAX network were evaluated under a scenario consisting of four cells. Each cell contains one mobile and one base station. Network performance metrics such as throughput and MOS were used to evaluate the best performance of VoIP codecs. Performance was analyzed via OPNET program14.5. The result use of multipath channel model (disable) was better than using the model (ITU pedestrian A). The value of the throughput at 15 dB was approximately 1600 packet/sec, and at -1 dB was its value 1300 packet/se. According to data, the Multipath channel model of the disable type the value of the MOS was better than the ITU Pedestrian A type.
Some results on χ-single valued neutrosophic subgroups M. Shazib Hameed; Zaheer Ahmad; Salman Mukhtar; Asad Ullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1583-1589

Abstract

In this study, we develop a novel structure χ-single valued neutrosophic set, which is a generalization of the intuitionistic set, inconsistent intuitionistic fuzzy set, Pythagorean fuzzy set, spherical fuzzy set, paraconsistent set, etc. Fuzzy subgroups play a vital role in vagueness structure, it differ from regular subgroups in that it is impossible to determine which group elements belong and which do not. In this paper, we investigate the concept of a χ-single valued neutrosophic set and χ-single valued neutrosophic subgroups. We explore the idea of χ-single valued neutrosophic set on fuzzy subgroups and several characterizations related to χ-single valued neutrosophic subgroups are suggested.
Enhancement of medical images using fuzzy logic Yousra Ahmed Fadil; Baidaa Al-Bander; Hussein Y. Radhi
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1478-1484

Abstract

Image enhancement is one of the most critical subjects in computer vision and image processing fields. It can be considered as means to enrich the perception of images for human viewers. All kinds of images typically suffer from different problems such as weak contrast and noise. The primary purpose of image enhancement is to change an image's visual appearance. Many algorithms have recently been proposed for enhancing medical images. Image enhancement is still deemed a challenging task. In this paper, the fuzzy c-means clustering (FCM) technique is utilized to enhance the medical images. The method of enhancement consists of two stages. The proposed algorithm conducts a cluster test on the image pixels. It then increases the difference of gray level between the diverse objects to accomplish the enhancement purpose of the medical images. The experimental results have been tested using various images. The algorithm enhanced the small target of the image to a reasonable limit and revealed favorable performance. The results of image enhancement techniques were evaluated by using terms of different criteria such as peak signal to noise ratio (PSNR), mean square error (MSE) and average information contents (AIC), showing promising performance.
Design and simulation of cascaded H-bridge multilevel inverter with energy storage Tan Chee Ting; Zulhani Rasin; Chan Sia Ching
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1289-1298

Abstract

Stand-alone power system provides a solution for the user in rural areas that are disconnected from the utility grid which requires power electronics device for the power conversion. This work proposes a design of 5-level cascaded H-bridge inverter with energy storage to realize DC-AC power conversion for such system. The DC-DC bidirectional converter is designed to control the charging and discharging of current into/from the battery during the buck and boost mode of operation. At the DC side, dual-loop control strategy using PI controllers is designed to control the current and voltage. The inner loop current controller controls the recharging/discharging of current for the battery, while the outer voltage controller controls the DC link voltage at 200 V for each of the H-bridge unit. At the AC side, multiple feedback loop control strategy regulates the inverter output voltage at 240 Vrms under various load change. The modelling and design of the system is implemented under Matlab Simulink environment. From the results, the battery storage unit works well with the DC link voltage to achieve a balance power transfer within the system between the PV source, load and battery storage under variation of PV power and loading condition.
Big transfer learning for automated skin cancer classification Zinah Mohsin Arkah; Dalya S. Al-Dulaimi; Ahlam R. Khekan
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1611-1619

Abstract

Skin cancer is an example of the most dangerous disease. Early diagnosis of skin cancer can save many people’s lives. Manual classification methods are time-consuming and costly. Deep learning has been proposed for the automated classification of skin cancer. Although deep learning showed impressive performance in several medical imaging tasks, it requires a big number of images to achieve a good performance. The skin cancer classification task suffers from providing deep learning with sufficient data due to the expensive annotation process and required experts. One of the most used solutions is transfer learning of pre-trained models of the ImageNet dataset. However, the learned features of pre-trained models are different from skin cancer image features. To end this, we introduce a novel approach of transfer learning by training the pre-trained models of the ImageNet (VGG, GoogleNet, and ResNet50) on a large number of unlabelled skin cancer images, first. We then train them on a small number of labeled skin images. Our experimental results proved that the proposed method is efficient by achieving an accuracy of 84% with ResNet50 when directly trained with a small number of labeled skin and 93.7% when trained with the proposed approach.
Analyzing the BER and optical fiber length performances in OFDM RoF links Marwa M. Kareem; Sameer A. S. Lafta; Hadi Fakhir Hashim; Raed Khalid Al-Azzawi; Adnan Hussein Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1501-1509

Abstract

Radio over fiber (RoF) can be assessed as a system of most convenient combination of optical fiber and radio signals. The technique of orthogonal frequency division multiplexing (OFDM) considers as a data distribution over a huge number of carriers having spaced from each other with specific frequencies at overlap bands. Hence incorporates OFDM with the optical fiber, OFDM-RoF system can be increased the modulation RF access capacity besides high-speed data transmission, it considers a broadband communication trend of the current and future applications specifically for 5G mobile. The optical network scenarios of various RF can be model with optisystem software, and OFDM in addition to use a section of the orthogonal multiplex frequency of 16-quadrature amplitude modulation (QAM) RF modulating signal. In the optical domain, Mach-Zehnder modulator (MZM) optical modulators are used to carry out different results with different fiber lengths. An OFDM-RoF wireless communication system considers as advanced data rate transmission achievement by minimum delays. The essential goal of this paper is for identifying the minimum bit error rate (BER) for the 16-QAM modulation with varying fiber length. The OFDM-RoF system can be able for realizing a fiber length 100 km with a restricted decreasing in the received power so that the constellation noise is became greater despite of applying electrical amplification and optical amplification.
An effective face recognition method using guided image filter and convolutional neural network Yallamandaiah S.; Purnachand N.
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1699-1707

Abstract

In the area of computer vision, face recognition is a challenging task because of the pose, facial expression, and illumination variations. The performance of face recognition systems reduces in an unconstrained environment. In this work, a new face recognition approach is proposed using a guided image filter, and a convolutional neural network (CNN). The guided image filter is a smoothing operator and performs well near the edges. Initially, the ViolaJones algorithm is used to detect the face region and then smoothened by a guided image filter. Later the proposed CNN is used to extract the features and recognize the faces. The experiments were performed on face databases like ORL, JAFFE, and YALE and attained a recognition rate of 98.33%, 99.53%, and 98.65% respectively. The experimental results show that the suggested face recognition method attains good results than some of the state-of-the-art techniques.
A comparative and comprehensive study of prediction of Parkinson’s disease N. Prasath; Vigneshwaran Pandi; Sindhuja Manickavasagam; Prabu Ramadoss
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i3.pp1748-1760

Abstract

Objectives: Parkinson's Disease (PD) is a form of neurodegenerative disease that is caused the progressive weakening of dopaminergic nerve cells that affects a large number of people around the world.  The event of recent treatment methods principally depends upon the experimental data resulting from assessment balances and patients’ journals that take varied boundaries with reference to legitimacy, inter-rater inconsistency, and incessant monitoring. Methods: Nowadays various techniques and algorithms are utilized in predicting the accuracy in PD. A range of those techniques, including SVM, Artificial Neural Network, Naive Bayes, Kernel based extreme learning through subtractive clustering landscapes, Random Forest, The Multi-Layer Perceptron with Back-Propagation Learning Algorithm are widely applied to form the acceptable decision accurately. During this work, and in-depth review was administered on various techniques proposed by numerous researchers. a replacement system must be proposed which uses DL techniques and considers other attributes of paralysis agitans which can improve the prediction and be an advancement within the medical field. Result: It has been observed that many researches have been done in identifying the PD yet there is a need of suitable method or algorithm to improve the prediction of PD which will help in the clinical management. Conclusion and Future work: Most of the methods have used speech as a major attribute for their research and have produced substantial accuracy. In order to increase the precision approaches involving movements, facial expression and other attributes also be considered for evaluation

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