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29,922 Article Results

Application of particle swarm optimization with ANFIS model for double scroll chaotic system

10.11591/ijece.v11i1.pp328-335
W. A. Wali
The predictions for the original chaos patterns can be used to correct the distorted chaos pattern which has changed due to any changes whether from undesired disturbance or additional information which can hide under chaos pattern. This information can be recovered when the original chaos pattern is predicted. But unpredictability is most features of chaos, and time series prediction can be used based on the collection of past observations of a variable and analysis it to obtain the underlying relationships and then extrapolate future time series. The additional information often prunes away by several techniques. This paper shows how the chaotic time series prediction is difficult and distort even if Neuro-Fuzzy such as Adaptive Neural Fuzzy Inference System (ANFIS) is used under any disturbance. The paper combined particle swarm (PSO) and (ANFIS) to exam the prediction model and predict the original chaos patterns which comes from the double scroll circuit. Changes in the bias of the nonlinear resistor were used as a disturbance. The predicted chaotic data is compared with data from the chaotic circuit.
Volume: 11
Issue: 1
Page: 328-335
Publish at: 2021-02-01

Reduction of common mode voltage for cascaded multilevel inverters using phase shift keying technique

10.11591/ijeecs.v21.i2.pp691-706
Vinh-Quan Nguyen , QuangTho Tran
Demand of cascaded multilevel inverters in industries of electric drives and renewable energy is increasing due to their large-scale capacity and high voltage. The modulation technique of inverters significantly affects the power quality of the inverter output voltage. This paper proposes a new method of carrier wave modulation using the phase shift keying technique for cascaded multilevel inverters. The phase of a constant frequency carrier wave is changed at an accurate time by an input sinusoidal control signal. This modulation technique is simply implemented and only needs a small memory. It also helps reduce the common mode voltage of inverters in order to suppress the output voltage harmonics. Moreover, the ability to reduce switching count also helps the inverters decrease switching loss. The simulated and experienced results on a cascaded 9-level 3-phase inverter and an F28379D DSP kit have validated the performance of the proposed technique compared with that of the APOD and POD methods.
Volume: 21
Issue: 2
Page: 691-706
Publish at: 2021-02-01

High speed pulse generators with electro-optic modulators based on different bit sequence for the digital fiber optic communication links

10.11591/ijeecs.v21.i2.pp957-967
Mahmoud M. A. Eid , Ashraf S. Seliem , Ahmed Nabih Zaki Rashed , Abd El-Naser A. Mohammed , Mohamed Yassin Ali , Shaimaa S. Abaza
The paper outlines the simulation of various pulse generators for the enhancement of optical fiber access transmission networks within flow rate of 10 Gbps and transmission range of 100 km. The pulse generators are gaussian, hyperbolic secant, triangle, sine, raised cosine in the transmission stage. Proposed pulse generators are mixed with both electro-absorption modulator (EAM) and mach-zehnder modulator (MZM) for efficient transmission. We have compared the max.  the quality factor with using proposed pulse generators against nonreturn to zero (NRZ) return to zero (RZ) pulse generators in the previous research works for different bit sequences. The signal power amplitude is tested for both optical fiber and PIN photodetector optical time-domain visualizer and RF spectrum analyzer by using in the optimum cases for different bit sequence. It is observed that proposed pulse generators/EAM have presented an efficient increase in Q-factor value compared with proposed pulse generators/MZM for different bit sequences.
Volume: 21
Issue: 2
Page: 957-967
Publish at: 2021-02-01

Maximum power point tracking techniques for photovoltaic systems: a comparative study

10.11591/ijece.v11i1.pp57-73
M. A. Abo-Sennah , M. A. El-Dabah , Ahmed El-Biomey Mansour
Photovoltaic systems (PV) are one of the most important renewable energy resources (RER). It has limited energy efficiency leading to increasing the number of PV units required for certain input power i.e. to higher initial cost. To overcome this problem, maximum power point tracking (MPPT) controllers are used. This work introduces a comparative study of seven MPPT classical, artificial intelligence (AI), and bio-inspired (BI) techniques: perturb and observe (P&O), modified perturb and observe (M-P&O), incremental conductance (INC), fuzzy logic controller (FLC), artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and cuckoo search (CS). Under the same climatic conditions, a comparison between these techniques in view of some criteria’s: efficiencies, tracking response, implementation cost, and others, will be performed. Simulation results, obtained using MATLAB/SIMULINK program, show that the MPPT techniques improve the lowest efficiency resulted without control. ANFIS is the highest efficiency, but it requires more sensors. CS and ANN produce the best performance, but CS provided significant advantages over others in view of low implementation cost, and fast computing time. P&O has the highest oscillation, but this drawback is eliminated using M-P&O. FLC has the longest computing time due to software complexity, but INC has the longest tracking time.
Volume: 11
Issue: 1
Page: 57-73
Publish at: 2021-02-01

Simulation of a microgrid for a non-interconnected zone that integrates renewable energies

10.11591/ijece.v11i1.pp201-216
German Reina , Mauricio Mauledoux , Oscar A. Aviles
This paper develops a simulation of a small electrical network (Microgid) that integrates renewable energies, the model of the micro network is made up of a solar energy source, a wind energy source, an energy storage element, a non-renewable source such as a diesel generator. The model of the microgrid represent a non-interconnected area from the electrical network in Colombia. The non-interconnected areas sometimes depend on unreliable connections to the grid integration of renewable energies could be the best option to guarantee energy in these sectors and allow generating projects with social impact. A possible solution to this deficit of energy is to supplement the production of energy with renewable energy plants from resources as sun or wind. The simulated model allowed to study the effects of the network in island mode and in interconnected mode, showing the imbalances that can be obtained by integrating renewable energies and storage systems. It is verified that with an inclusion of more than 30% of power in renewable energies there is the possibility of having load imbalances, which affect the frequency and cause instability in the network. It also verifies how a control system can regulate the load balance but must interact with the other energy sources.
Volume: 11
Issue: 1
Page: 201-216
Publish at: 2021-02-01

Measuring memetic algorithm performance on image fingerprints dataset

10.12928/telkomnika.v19i1.16418
Priati; Universitas Bina Nusantara Jakarta Assiroj , H. L. H. S.; Universitas Bina Nusantara Jakarta Warnars , E.; Universitas Bina Nusantara Jakarta Abdurrachman , A. I.; Institut Teknologi Bandung Kistijantoro , A.; La Rochelle Universite Doucet
Personal identification has become one of the most important terms in our society regarding access control, crime and forensic identification, banking and also computer system. The fingerprint is the most used biometric feature caused by its unique, universality and stability. The fingerprint is widely used as a security feature for forensic recognition, building access, automatic teller machine (ATM) authentication or payment. Fingerprint recognition could be grouped in two various forms, verification and identification. Verification compares one on one fingerprint data. Identification is matching input fingerprint with data that saved in the database. In this paper, we measure the performance of the memetic algorithm to process the image fingerprints dataset. Before we run this algorithm, we divide our fingerprints into four groups according to its characteristics and make 15 specimens of data, do four partial tests and at the last of work we measure all computation time.
Volume: 19
Issue: 1
Page: 96-104
Publish at: 2021-02-01

Optimized architecture for SNOW 3G

10.11591/ijece.v11i1.pp545-557
N. B. Hulle , Prathiba B. , Sarika R. Khope , K. Anuradha , Yogini Borole , D. Kotambkar
SNOW 3G is a synchronous, word-oriented stream cipher used by the 3GPP standards as a confidentiality and integrity algorithms. It is used as first set in long term evolution (LTE) and as a second set in universal mobile telecommunications system (UMTS) networks. The cipher uses 128-bit key and 128 bit IV to produce 32-bit ciphertext. The paper presents two techniques for performance enhancement. The first technique uses novel CLA architecture to minimize the propagation delay of the 232 modulo adders. The second technique uses novel architecture for S-box to minimize the chip area. The presented work uses VHDL language for coding. The same is implemented on the FPGA device Virtex xc5vfx100e manufactured by Xilinx. The presented architecture achieved a maximum frequency of 254.9 MHz and throughput of 7.2235 Gbps.
Volume: 11
Issue: 1
Page: 545-557
Publish at: 2021-02-01

Improved feature exctraction process to detect seizure using CHBMIT-dataset

10.11591/ijece.v11i1.pp827-843
Raveendra Kumar T. H. , C. K. Narayanappa
One of the most dangerous neurological disease, which is occupying worldwide, is epilepsy. Fraction of second nerves in the brain starts impulsion i.e. electrical discharge, which is higher than the normal pulsing. So many researches have done the investigation and proposed the numerous methodology. However, our methodology will give effective result in feature extraction. Moreover, we used numerous number of statistical moments features. Existing approaches are implemented on few statistical moments with respect to time and frequency. Our proposed system will give the way to find out the seizure-effected part of the brain very easily using TDS, FDS, Correlation and Graph presentation. The resultant value will give the huge difference between normal and seizure effected brain. It also explore the hidden features of the brain.
Volume: 11
Issue: 1
Page: 827-843
Publish at: 2021-02-01

Secured node detection technique based on artificial neural network for wireless sensor network

10.11591/ijece.v11i1.pp536-544
Bassam Hasan , Sameer Alani , Mohammed Ayad Saad
The wireless sensor network is becoming the most popular network in the last recent years as it can measure the environmental conditions and send them to process purposes. Many vital challenges face the deployment of WSNs such as energy consumption and security issues. Various attacks could be subjects against WSNs and cause damage either in the stability of communication or in the destruction of the sensitive data. Thus, the demands of intrusion detection-based energy-efficient techniques rise dramatically as the network deployment becomes vast and complicated. Qualnet simulation is used to measure the performance of the networks. This paper aims to optimize the energy-based intrusion detection technique using the artificial neural network by using MATLAB Simulink. The results show how the optimized method based on the biological nervous systems improves intrusion detection in WSN. In addition to that, the unsecured nodes are affected the network performance negatively and trouble its behavior. The regress analysis for both methods detects the variations when all nodes are secured and when some are unsecured. Thus, Node detection based on packet delivery ratio and energy consumption could efficiently be implemented in an artificial neural network.
Volume: 11
Issue: 1
Page: 536-544
Publish at: 2021-02-01

Multi-user media streaming service for e-learning based web real-time communication technology

10.11591/ijece.v11i1.pp567-574
Naktal Edan , Sanabil A. Mahmood
Web real-time communication (WebRTC) standards do not define precisely how two browsers establish and control their communication. Therefore, a signalling mechanism/protocol has not specified in WebRTC. The essential goal of this research is to create and apply a WebRTC bi-directional video conferencing based on mesh topology (many-to-many) using Google Chrome, Firefox, Opera, and Explorer. This experiment involved through Ethernet and Wireless of the Internet and 4G networks in e-learning. The signalling mechanism of this experiment has been created and implemented using JavaScript language along with MultiConnection libraries. In addition, an evaluation of quality of experience (QoE), resources, such as bandwidth consumption, and CPU performance was done. In this paper, a novel implementation was accomplished over e-learning using different networks, different browsers, many peers, opening one or many rooms concurrently, defining room initiator, sharing the information of the new user with participants, using user identification (user-id), and so on. Moreover, the paper also highlights the advantages and disadvantages of using WebRTC video conferencing.
Volume: 11
Issue: 1
Page: 567-574
Publish at: 2021-02-01

Fine-grained or coarse-grained? Strategies for implementing parallel genetic algorithms in a programmable neuromorphic platform

10.12928/telkomnika.v19i1.15026
Indar; Petra Christian University Sugiarto , Steve; University of Manchester Furber
Genetic Algorithm (GA) is one of popular heuristic-based optimization methods that attracts engineers and scientists for many years. With the advancement of multi- and many-core technologies, GAs are transformed into more powerful tools by parallelising their core processes. This paper describes a feasibility study of implementing parallel GAs (pGAs) on a SpiNNaker. As a many-core neuromorphic platform, SpiNNaker offers a possibility to scale-up a parallelised algorithm, such as a pGA, whilst offering low power consumption on its processing and communication overhead. However, due to its small packets distribution mechanism and constrained processing resources, parallelising processes of a GA in SpiNNaker is challenging. In this paper we show how a pGA can be implemented on SpiNNaker and analyse its performance. Due to inherently numerous parameter and classification of pGAs, we evaluate only the most common aspects of a pGA and use some artificial benchmarking test functions. The experiments produced some promising results that may lead to further developments of massively parallel GAs on SpiNNaker.
Volume: 19
Issue: 1
Page: 182-191
Publish at: 2021-02-01

Comparison of data recovery techniques on master file table between Aho-Corasick and logical data recovery based on efficiency

10.12928/telkomnika.v19i1.16276
Hussein Ismael; University Tun Hussein Malaysia (UTHM) Sahib , Nurul Hidayah Ab; University Tun Hussein Malaysia (UTHM) Rahman , Ali Kazem; University Essex Al-Qaysi , Mothana L.; Middle Technical University Attiah
Data recovery is one of the tools used to obtain digital forensics from various storage media that rely entirely on the file system used to organize files in these media. In this paper, two of the latest techniques of file recovery from file system (new technology file system (NTFS)) logical data recovery, Aho-Corasick data recovery were studied, examined and a practical comparison was made between these two techniques according to the speed and accuracy factors using three global datasets. It was noted that all previous studies in this field completely ignored the time criterion despite the importance of this standard. On the other hand, algorithms developed with other algorithms were not compared. The proposed comparison of this paper aims to detect the weaknesses and strength of both algorithms to develop a new algorithm that is more accurate and faster than both algorithms. The paper concluded that the logical algorithm was superior to the Aho-Corasick algorithm according to the speed criterion, whereas the algorithms gave the same results according to the accuracy criterion. The paper leads to a set of suggestions for future research aimed at achieving a highly efficient and high-speed data recovery algorithm such as the file-carving algorithm.
Volume: 19
Issue: 1
Page: 73-78
Publish at: 2021-02-01

Predicting the notch band frequency of an ultra-wideband antenna using artificial neural networks

10.12928/telkomnika.v19i1.15912
Lahcen; Cadi Ayyad University Aguni , Samira; Ibn Zohr University Chabaa , Saida; Cadi Ayyad University Ibnyaich , Abdelouhab; Cadi Ayyad University Zeroual
In this paper we propose to predict the notch frequency of an ultra-wideband (UWB) antenna which operates in the frequency band from 3.85 GHz to 12.38 GHz. The prediction of the notch frequency in order to avoid interferences between (WLAN) IEEE802.11a and HIPERLAN/2 WLAN applications and UWB technology is achieved using the artificial neural networks (ANN) technique. The developed ANN is optimized with the help of K-fold cross validation method which allows us to divide the datasets into 10 subsets in the training phase. The simulated datasets are generated by controlling high frequency structural simulator (HFSS) from MATLAB using a VB script. The performance of the ANN technique is assessed using some statistical criteria. During the training process, the mean absolute percentage error (MAPE) between the simulated and the predicted ANN notch frequencies is 0,125. A comparison between simulated, theoretical, and ANN results has been achieved during the test and validation process, good accuracy is obtained between the simulated and the ANN predictions. The proposed UWB antenna exhibits a notch band from 5.1 GHz to 6.0 GHz with a notch frequency of approximately 5.51 GHz.
Volume: 19
Issue: 1
Page: 1-8
Publish at: 2021-02-01

GPON and V-band mmWave in green backhaul solution for 5G ultra-dense network

10.11591/ijece.v11i1.pp390-401
Ayodeji Akeem Ajani , Vitalice Kalecha Oduol , Zachaeus Kayode Adeyemo
Ultra-dense network (UDN) is characterized by massive deployment of small cells which resulted into complex backhauling of the cells. This implies that for 5G UDN to be energy efficient, appropriate backhauling solutions must be provided. In this paper, we have evaluated the performance of giga passive optical network (GPON) and V-band millimetre wave (mmWave) in serving as green backhaul solution for 5G UDN. The approach was to first reproduce existing backhaul solutions in Very Dense Network (VDN) scenario which served as benchmark for the performance evaluation for the UDN scenario. The best two solutions, GPON and V-band solutions from the VDN were then deployed in 5G UDN scenario. The research was done by simulation in MATLAB. The performance metrics used were power consumption and energy efficiency against the normalized hourly traffic profile. The result revealed that GPON and V-band mmWave outperformed other solutions in VDN scenario. However, this performance significantly dropped in the UDN scenariodue to higher data traffic requirement of UDN compared to VDN. Thus, it can be concluded that GPON and V-band mmWave are not best suited to serve as green backhaul solution for 5G UDN necessitating further investigation of other available backhaul technologies.
Volume: 11
Issue: 1
Page: 390-401
Publish at: 2021-02-01

Smart fire monitoring system with remote control usingZigBee network

10.11591/ijeecs.v21.i2.pp1132-1139
Jung kyu Park , Jaeho Kim
There are several differences between the two types of alarm systems, conventionalsystems and addressable systems.  It is important to carefully determine the introduc-tion of a fire alarm system according to the installation environment.  Talking aboutthe main difference relates to how the connected device communicates with the maincontrol panel by sending a signal.  Cost is another factor that can be a determinant ofyour chosen fire alarm system. In this paper, we proposed smart addressable fire detec-tion system.  In the proposed system, IoT was used and the network was constructedusing ZigBee module.  In the configured network, it consists of a local server and acontrol server. The local server controls the addressing sensor and sends the informa-tion obtained from the sensor to the control server.  The control server receives datatransmitted from the local server and enables quick fire action.  In the actual imple-mentation, the local server used the Lycra controller and ZigBee module. In addition,the control server used the Raspberry Pi and ZigBee modules and connected to theEthernet so that the administrator could monitor or control the local server.
Volume: 21
Issue: 2
Page: 1132-1139
Publish at: 2021-02-01
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