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International Journal of Electrical and Computer Engineering

IJECE
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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 6,301 Documents

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Frequent itemset mining: technique to improve eclat based algorithm Mahadi Man; Masita Abdul Jalil
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

In frequent itemset mining, the main challenge is to discover relationships between data in a transactional database or relational database. Various algorithms have been introduced to process frequent itemset. Eclat based algorithms are one of the prominent algorithm used for frequent itemset mining. Various researches have been conducted based on Eclat based algorithm such as Tidset, dEclat, Sortdiffset and Postdiffset. The algorithm has been improvised along the time. However, the utilization of physical memory and processing time become the main problem in this process. This paper reviews and presents a comparison of various Eclat based algorithms for frequent itemset mining and propose an enhancement technique of Eclat based algorithm to reduce processing time and memory usage. The experimental result shows some improvement in processing time and memory utilization in frequent itemset mining.

MICCS: A Novel Framework for Medical Image Compression Using Compressive Sensing Lakshminarayana M; Mrinal Sarvagya
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

The vision of some particular applications such as robot-guided remote surgery where the image of a patient body will need to be captured by the smart visual sensor and to be sent on a real-time basis through a network of high bandwidth but yet limited. The particular problem considered for the study is to develop a mechanism of a hybrid approach of compression where the Region-of-Interest (ROI) should be compressed with lossless compression techniques and Non-ROI should be compressed with Compressive Sensing (CS) techniques. So the challenge is gaining equal image quality for both ROI and Non-ROI while overcoming optimized dimension reduction by sparsity into Non-ROI. It is essential to retain acceptable visual quality to Non-ROI compressed region to obtain a better reconstructed image. This step could bridge the trade-off between image quality and traffic load. The study outcomes were compared with traditional hybrid compression methods to find that proposed method achieves better compression performance as compared to conventional hybrid compression techniques on the performances parameters e.g. PSNR, MSE, and Compression Ratio.

Design and implementation of secured agent based NoC using shortest path routing algorithm Kendaganna Swamy S; Anand Jatti; Uma B. V.
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science

Network on chip (NoC) is a scalable interconnection architecture for every increasing communication demand between many processing cores in system on chip design. Reliability aspects are becoming an important issue in fault tolerant architecture. Hence there is a demand for fault tolerant Agent architecture with suitable routing algorithm which plays a vital role in order to enhance the NoC performance. The proposed fault tolerant Agent based NoC method is used to enhance the reliability and performance of the Multiprocessor System on Chip (MPSoC) design against faulty links and nodes. These agents are placed in hierarchical manner to collect, process, classify and distribute different fault information related to the faulty links and nodes of the network. This fault information is used for further packet routing in the network with the help of shortest path routing algorithm. In addition to this the agent will provide the security for the node by setting firewall, which then decides whether the packet has to be processed or not. This intern provides high performance, low latency NoC by avoiding deadlock and live lock with low area overhead.

Identity-Based Blind Signature Scheme with Message Recovery Salome James; T. Gowri; G.V. Ramesh Babu; P. Vasudeva Reddy
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Blind signature allows a user to obtain a signature on a message without revealing anything about the message to the signer. Blind signatures play an important role in many real world applications such as e-voting, e-cash system where anonymity is of great concern. Due to the rapid growth in popularity of both wireless communications and mobile devices, the design of secure schemes with low-bandwidth capability is an important research issue. In this paper, we present a new blind signature scheme with message recovery in the ID-based setting using bilinear pairings over elliptic curves. The proposed scheme is unforgeable with the assumption that the Computational Diffie-Hellman problem is hard. We compare our scheme with the related schemes in terms of computational and communicational point of view.

Blockchain outlook for deployment of IoT in distribution networks and smart homes Heliasadat Hosseinian; Hossein Shahinzadeh; Gevork B. Gharehpetian; Zohreh Azani; Mahdi Shaneh
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Nowadays, unlike depleting fossil fuel resources, the integration of different types of renewable energy, as distributed generation sources, into power systems is accelerated and the technological development in this area is evolving at a frantic pace. Thus, inappropriate use of them will be irrecoverably detrimental. The power industry will reach a turning point in the pervasiveness of these infinite energy sources by three factors. Climate changes due to greenhouse gas accumulation in the atmosphere; increased demand for energy consumption all over the world, especially after the genesis of Bitcoin and base cryptocurrencies; and establishing a comprehensive perspective for the future of renewable energy. The increase in the pervasiveness of renewable energy sources in small-scale brings up new challenges for the power system operators to manage an abundant number of small-scale generation sources, called microsources. The current structure of banking systems is unable to handle such massive and high-frequency transactions. Thus the incorporation of cryptocurrencies is inevitable. In addition, by utilization of IoT-enabled devices, a large body of data will be produced must be securely transferred, stored, processed, and managed in order to boost the observability, controllability, and the level of autonomy of the smart power systems. Then the appropriate controlling measures must be performed through control signals in order to serve the loads in a stable, uninterruptible, reliable, and secure way. The data acquires from IoT devices must be analyzed using artificial intelligence methods such as big data techniques, data mining, machine learning, etc. with a scant delay or almost real-time. These measures are the controversial issues of modern power systems, which are yet a matter of debate. This study delves into the aforementioned challenges and opportunities, and the corresponding solutions for the incorporation of IoT and blockchain in power systems, particularly in the distribution level and residential section, are addressed. In the last section, the role of IoT in smart buildings and smart homes, especially for energy hubs schemes and the management of residential electric vehicle supply equipment is concisely discussed.

Adaptive Neuro-fuzzy Inference System Based Control of puma 600 Robot Manipulator Ouamri Bachir; Ahmed-Foitih Zoubir
International Journal of Electrical and Computer Engineering (IJECE) Vol 2, No 1: February 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (241.431 KB)

The strong dependence of the computed torque control of dynamic model of the robot manipulator makes this one very sensitive to uncertainties of modelling and to the external disturbances. In general, the vector of Coriolis torque, centrifugal and gravity is very complicated, consequently, very difficult to modelled. Fuzzy Logic Controller can very well describe the desired system behavior with simple “if-then” relations owing the designer to derive “if-then” rules manually by trial and error. On the other hand, Neural Networks perform function approximation of a system but cannot interpret the solution obtained neither check if its solution is plausible. The two approaches are complementary. Combining them, Neural Networks will allow learning capability while Fuzzy-Logic will bring knowledge representation (Neuro-Fuzzy). This paper presents the control of puma 600 robot arm using Adaptive Neuro Fuzzy Inference System (ANFIS) based computed torque controller (type PD). Numerical simulation using the dynamic model of puma 600 robot arm shows the effectiveness of the approach in improving the computed torque method. Comparative evaluation with Fuzzy computed torque (type PD) control is presented to validate the controller design. The results presented emphasize that a satisfactory trajectory tracking precision and stabilility could be achieved using ANFIS controller than Fuzzy controller. Keywords: Fuzzy computed torque control, Robot control, Adaptive neuro-fuzzy inference system (ANFIS).DOI:http://dx.doi.org/10.11591/ijece.v2i1.116

Optimization of Modified Sliding Mode Controller for an Electro-hydraulic Actuator System with Mismatched Disturbance Siti Marhainis Othman; M. F. Rahmat; S. M. Rozali; Zulfatman Has; A. F. Z. Abidin
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

This paper presents the design of the modified sliding mode controller (MSMC) for the purpose of tracking the nonlinear system with mismatched disturbance. Provided that the performance of the designed controller depends on the value of control parameters, gravitational search algorithm (GSA), and particle swarm optimization (PSO) techniques are used to optimize these parameters in order to achieve a predefined system’s performance. In respect of system’s performance, it is evaluated based on the tracking error present between reference inputs transferred to the system and the system output. This is followed by verification of the efficiency of the designed controller in simulation environment under various values, with and without the inclusion of external disturbance. It can be seen from the simulation results that the MSMC with PSO exhibits a better performance in comparison to the performance of the similar controller with GSA in terms of output response and tracking error.

New Method to Optimize Initial Point Values of Spatial Fuzzy c-means Algorithm Iman Omidvar Tehrani; Subariah Ibrahim; Habib Haron
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 5: October 2015
Publisher : Institute of Advanced Engineering and Science

Fuzzy based segmentation algorithms are known to be performing well on medical images. Spatial fuzzy C-means (SFCM) is broadly used for medical image segmentation but it suffers from optimum selection of seed point initialization which is done either manually or randomly. In this paper, an enhanced SFCM algorithm is proposed by optimizing the SFCM initial point values. In this method in order to increasing the algorithm speed first the approximate initial values are determined by calculating the histogram of the original image. Then by utilizing the GWO algorithm the optimum initial values could be achieved. Finally By using the achieved initial values, the proposed method shows the significant improvement in segmentation results. Also the proposed method performs faster than previous algorithm i.e. SFCM and has better convergence. Moreover, it has noticeably improved the clustering effect.

Real-time online fingerprint image classification using adaptive hybrid techniques Annapurna Mishra; Satchidananda Dehuri
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

This paper presents three different hybrid classification techniques applied for the first time in real-time online fingerprint classification. Classification of online real time fingerprints is a complex task as it involves adaptation and tuning of classifier parameters for better classification accuracy. To accomplish the optimal adaptation of parameters of functional link artificial neural network (FLANN) for real-time online fingerprint classification, proven and established optimizers, such as Biogeography based optimizer (BBO), Genetic algorithm (GA), and Particle swarm optimizer (PSO) are intelligently infused with it to form hybrid classifiers. The global features of the real-time fingerprints are extracted using a Gabor filter-bank and then passed into adaptive hybrid classifiers for the desired classification as per the Henry system. Three hybrid classifiers, the optimized weight adapted Biogeography based optimized functional link artificial neural network (BBO-FLANN), Genetic algorithm based functional link artificial neural network (GA-FLANN) and Particle swarm optimized functional link artificial neural network (PSO-FLANN), are explored for real-time online fingerprint classification, where the PSO-FLANN technique is showing superior performance as compared to GA-FLANN and BBO-FLANN techniques. The best accuracy observed by the application of PSO-FLANN, is 98% for real-time online fingerprint classification.

FPGA Implementation of Higher Order FIR Filter Gurpadam Singh; Neelam R. Prakash
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 4: August 2017
Publisher : Institute of Advanced Engineering and Science

The digital Finite-Impulse-Response (FIR) filters are mainly employed in digital signal processing applications. The main components of digital FIR filters designed on FPGAs are the register bank to save the samples of signals, adder to implement sum operations and multiplier for multiplication of filter coefficients to signal samples. Although, design and implementation of digital FIR filters seem simple but the design bottleneck is multiplier block for speed, power consumption and FPGA chip area occupation. The multipliers are an integral part in FIR structures and these use a large part of the chip area. This limits the number of processing elements (PE) available on the chip to realize a higher order of filter. A model is developed in the Matlab/Simulink environment to investigate the performance of the desired higher order FIR filter. An equivalent FIR filter representation is designed by the Xilinx FIR Compiler by using the exported FIR filter coefficients. The Xilinx implementation flow is completed with the help of Xilinx ISE 14.5. It is observed how the use of higher order FIR filter impacts the resource utilization of the FPGA and it’s the maximum operating frequency.

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Home Page

OAI Link

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Contact Name Tole Sutikno

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Journal Mail Official ijece@iaesjournal.com

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Abstract

Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

Phone
-

Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA