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International Journal of Electrical and Computer Engineering
ISSN : 20888708     EISSN : 27222578     DOI : -
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.
Articles 115 Documents
Search results for , issue "Vol 10, No 3: June 2020" : 115 Documents clear
Efficient two-stage cryptography scheme for secure distributed data storage in cloud computing Rabab F. Abdel-Kader; Samar H. El-sherif; Rawya Y. Rizk
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (972.339 KB) | DOI: 10.11591/ijece.v10i3.pp3295-3306

Abstract

Cloud computing environment requires secure access for data from the cloud server, small execution time, and low time complexity. Existing traditional cryptography algorithms are not suitable for cloud storage. In this paper, an efficient two-stage cryptography scheme is proposed to access and store data into cloud safely. It comprises both user authentication and encryption processes. First, a two-factor authentication scheme one-time password is proposed. It overcomes the weaknesses in the existing authentication schemes. The proposed authentication method does not require specific extra hardware or additional processing time to identity the user. Second, the plaintext is divided into two parts which are encrypted separately using a unique key for each. This division increases the security of the proposed scheme and in addition decreases the encryption time. The keys are generated using logistic chaos model theory. Chaos equation generates different values of keys which are very sensitive to initial condition and control parameter values entered by the user. This scheme achieves high-security level by introducing different security processes with different stages. The simulation results demonstrate that the proposed scheme reduces the size of the ciphertext and both encryption and decryption times than competing schemes without adding any complexity.
Thermal response of skin diseased tissue treated by plasmonic nanoantenna Rasha H. Mahdi; Hussein A. Jawad
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (844.471 KB) | DOI: 10.11591/ijece.v10i3.pp2969-2977

Abstract

The thermal distribution in the diseased tissue treated by different methods faces the problem of an uncontrollable defused heat. In the present article, we use a plasmonic bowtie nanoantenna working in the near infrared region to enhance the temperature confinement in the tissue. The Computer Simulation Technology Studio Suite package version 2019 was used to execute the design of both plasmonic nanoantenna and the tissue. Gold nanostructure and silicon carbide dioxide are the components the plasmonic nanoantenna in the bowtie shape. The results showed that the distance between the tumor tissue and the antenna is important to determine the intensity field where the maximum field is 5.9*107 V/m at a distance of 100 nm. The maximum specific absorption rate is 1.92*1011 W/kg at a similar distance which gives a higher temperature in the tissue of 580 Co. It is concluded that from the obtained results that the near infrared (1064 nm) resonance wavelength is recommended in the treatment of cancer cell by plasmonic bowtie nanoantenna because higher intensity field is generated. The closer distance to the nanoantenna gives higher temperature in the tissue while the temperature gradually decreases in the tissue till 400 nm where no valuable temperature was detected.
Performance evaluation of interference aware topology power and flow control channel assignment algorithm Jatinder Singh Saini; Balwinder Singh Sohi
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (760.595 KB) | DOI: 10.11591/ijece.v10i3.pp2503-2512

Abstract

Multi-Radio Multi-Channel Wireless Mesh Network (MRMC-WMN) has been considered as one of the key technology for the enhancement of network performance. It is used in a number of real-time applications such as disaster management system, transportation system and health care system. MRMC-WMN is a multi-hop network and allows simultaneous data transfer by using multiple radio interfaces. All the radio interfaces are typically assigned with different channels to reduce the effect of co-channel interference. In MRMC-WMN, when two nodes transmit at the same channel in the range of each other, generates co-channel interference and degrades the network throughput. Co-channel interference badly affects the capacity of each link that reduces the overall network performance. Thus, the important task of channel assignment algorithm is to reduce the co-channel interference and enhance the network performance. In this paper, the problem of channel assignment has been addressed for MRMC-WMN. We have proposed an Interference Aware, Topology, Power and Flow Control (ITPFC) Channel Assignment algorithm for MRMC-WMN. This algorithm assignes the suitable channels to nodes, which provides better link capacity and reduces the co-channel interference. In the previous work performance of the proposed algorithm has been evaluated for a network of 30 nodes. The aim of this paper is to further evaluate the performance of proposed channel assignment algorithm for 40 and 50 nodes network. The results obtained from these networks show the consistent performance in terms of throughput, delay, packet loss and number of channels used per node as compared to LACA, FCPRA and IATC Channel Assignment algorithms.
Binary operation based hard exudate detection and fuzzy based classification in diabetic retinal fundus images for real time diagnosis applications Arun Pradeep; X Felix Joseph
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (647.903 KB) | DOI: 10.11591/ijece.v10i3.pp2305-2312

Abstract

Diabetic retinopathy (DR) is one of the most considerable reasons for visual impairment. The main objective of this paper is to automatically detect and recognize DR lesions like hard exudates, as it helps in diagnosing and screening of the disease. Here, binary operation based image processing for detecting lesions and fuzzy logic based extraction of hard exudates on diabetic retinal images are discused. In the initial stage, the binary operations are used to identify the exudates. Similarly, the RGB channel space of the DR image is used to create fuzzy sets and membership functions for extracting the exudates. The membership directives obtained from the fuzzy rule set are used to detect the grade of exudates. In order to evaluate the proposed approach, experiment tests are carriedout on various set of images and the results are verified. From the experiment results, the sensitivity obtained is 98.10%, specificity is 96.96% and accuracy is 98.2%.  These results suggest that the proposed method could be a diagnostic aid for ophthalmologists in the screening for DR.
Comprehensive investigation of coherent optical OFDM-RoF employing 16QAM external modulation for long-haul optical communication system Anas Ali Hussien; Adnan Hussein Ali
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (860.219 KB) | DOI: 10.11591/ijece.v10i3.pp2607-2616

Abstract

Given the growing need for long haul transmission that requires a high rate of data, the orthogonal frequency division multiplexing scheme (OFDM), is regarded as a technique with high potentials for high-capacity optical networks. OFDM transmits over both optical and wireless channels, with the data distributed over a huge amount of the subcarrier, and the data is distributed over a huge number of subcarriers. OFDM achieves RF signal for a long-haul transmitting by utilizing Radio over Fiber (RoF) system, which is known to produce higher orthogonality of the OFDM modulated signal designed for the wireless network. RoF systems comprise of heterogeneous networks designed through the use of wireless and optical links. The aim of this paper is to carry out an investigation of the performance of the external modulation in RoF links, while analyzing the shortcomings caused by the various elements of the optical system. The Mach–Zehnder modulator (MZM) can be applied in external modulation, and exhibits a more robust performance when implemented with the OFDM modulation technique.
Classification of instagram fake users using supervised machine learning algorithms Kristo Radion Purba; David Asirvatham; Raja Kumar Murugesan
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (644.165 KB) | DOI: 10.11591/ijece.v10i3.pp2763-2772

Abstract

On Instagram, the number of followers is a common success indicator. Hence, followers selling services become a huge part of the market. Influencers become bombarded with fake followers and this causes a business owner to pay more than they should for a brand endorsement. Identifying fake followers becomes important to determine the authenticity of an influencer. This research aims to identify fake users' behavior, and proposes supervised machine learning models to classify authentic and fake users. The dataset contains fake users bought from various sources, and authentic users. There are 17 features used, based on these sources: 6 metadata, 3 media info, 2 engagement, 2 media tags, 4 media similarity. Five machine learning algorithms will be tested. Three different approaches of classification are proposed, i.e. classification to 2-classes and 4-classes, and classification with metadata. Random forest algorithm produces the highest accuracy for the 2-classes (authentic, fake) and 4-classes (authentic, active fake user, inactive fake user, spammer) classification, with accuracy up to 91.76%. The result also shows that the five metadata variables, i.e. number of posts, followers, biography length, following, and link availability are the biggest predictors for the users class. Additionally, descriptive statistics results reveal noticeable differences between fake and authentic users.
Human gait recognition using preprocessing and classification techniques Samer Kais Jameel; Jihad Anwar Qadir; Mohammed Hussein Ahmed
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (417.798 KB) | DOI: 10.11591/ijece.v10i3.pp2978-2985

Abstract

Biometric recognition systems have been attracted numerous researchers since they attempt to overcome the problems and factors weakening these systems including problems of obtaining images indeed not appearing the resolution or the object completely. In this work, the object movement reliance was considered to distinguish the human through his/her gait. Some losing features probably weaken the system’s capability in recognizing the people, hence, we propose using all data recorded by the Kinect sensor with no employing the feature extraction methods based on the literature. In these studies, coordinates of 20 points are recorded for each person in various genders and ages, walking with various directions and speeds, creating 8404 constraints. Moreover, pre-processing methods are utilized to measure its influences on the system efficiency through testing on six types of classifiers. Within the proposed approach, a noteworthy recognition rate was obtained reaching 91% without examining the descriptors.
An exploratory research on grammar checking of Bangla sentences using statistical language models M. D. Riazur Rahman; M. D. Tarek Habib; M. D. Sadekur Rahman; Gazi Zahirul Islam; M. D. Abbas Ali Khan
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (845.526 KB) | DOI: 10.11591/ijece.v10i3.pp3244-3252

Abstract

N-gram based language models are very popular and extensively used statistical methods for solving various natural language processing problems including grammar checking. Smoothing is one of the most effective techniques used in building a language model to deal with data sparsity problem. Kneser-Ney is one of the most prominently used and successful smoothing technique for language modelling. In our previous work, we presented a Witten-Bell smoothing based language modelling technique for checking grammatical correctness of Bangla sentences which showed promising results outperforming previous methods. In this work, we proposed an improved method using Kneser-Ney smoothing based n-gram language model for grammar checking and performed a comparative performance analysis between Kneser-Ney and Witten-Bell smoothing techniques for the same purpose. We also provided an improved technique for calculating the optimum threshold which further enhanced the the results. Our experimental results show that, Kneser-Ney outperforms Witten-Bell as a smoothing technique when used with n-gram LMs for checking grammatical correctness of Bangla sentences.
Performance analysis of bio-signal processing in ocean environment using soft computing techniques N. R. Krishnamoorthy; Immanuel Rajkumar; Jerry Alexander; D. Marshiana
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (8.212 KB) | DOI: 10.11591/ijece.v10i3.pp2944-2950

Abstract

Wireless communication has become an essential technology in our day-to-day life both in air and water medium. To monitor the health parameter of human begins, advancement techniques like internet of things is evolved. But to analyze underwater living organisms health parameters, researchers finding difficulties to do so. The reason behind is underwater channels has drawbacks like signal degradation due to multipath propagation, severe ambient noise and Attenuation by bottom and surface loss. In this paper Artificial Neural Networks (ANN) is used to perform data transfer in water medium. A sample EEG signal is generated and trained with 2 and 20 hidden layers. Simulation result showed that error free communication is achieved with 20 hidden layers at 10th iteration. The proposed algorithm is validated using a real time watermark toolbox. Two different modulation scheme was applied along with ANN. In the first scenario, the EEG signal is modulated using convolution code and decoded by Viterbi Algorithm. Multiplexing technique is applied in the second scenario. It is observed that energy level in the order of 40 dB is required for least error rate. It is also evident from simulation result that maximum of 5% CP can be maintained to attain the least Mean Square Error.
Hybrid energy storage system optimal sizing for urban electrical bus regarding battery thermal behavior Si Mohamed Faresse; Mohamed Assini; Abdallah Saad
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1383.274 KB) | DOI: 10.11591/ijece.v10i3.pp2894-2911

Abstract

This paper proposes an algorithm for sizing the hybrid energy storage system of an urban electrical bus regarding battery thermal behavior. The aim of this study is to get the supercapacitors optimal contribution part in the hybrid energy storage system to keep the battery temperature within its allowable limit. A semi-active parallel topology that uses supercapacitors as a main source of energy is considered. According to the bus mechanical parameters and the ARTEMIS driving cycle, the power and energy demand are calculated. Using mathematical models for the battery, supercapacitors and DC-DC converter, several simulations are performed for different hybridization percentages. While observing the evolution of battery temperature, the most favorable hybridization percentage is defined.

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