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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

107 108 109 110 111

Impact of big data congestion in IT: an adaptive knowledge-based bayesian network Soheli Farhana; Adidah Lajis; Zalizah Awang Long; Haidawati Nasir
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

Recent progress on real-time systems are growing high in information technology which is showing importance in every single innovative field. Different applications in IT simultaneously produce the enormous measure of information that should be taken care of. In this paper, a novel algorithm of adaptive knowledge-based Bayesian network is proposed to deal with the impact of big data congestion in decision processing. A Bayesian system show is utilized to oversee learning arrangement toward all path for the basic leadership process. Information of Bayesian systems is routinely discharged as an ideal arrangement, where the examination work is to find a development that misuses a measurably inspired score. By and large, available information apparatuses manage this ideal arrangement by methods for normal hunt strategies. As it required enormous measure of information space, along these lines it is a tedious method that ought to be stayed away from. The circumstance ends up unequivocal once huge information include in hunting down ideal arrangement. A calculation is acquainted with achieve quicker preparing of ideal arrangement by constraining the pursuit information space. The proposed algorithm consists of recursive calculation intthe inquiry space. The outcome demonstrates that the ideal component of the proposed algorithm can deal with enormous information by processing time, and a higher level of expectation rates.

Coordinated Control of Interconnected Microgrid and Energy Storage System Md. Asaduz-Zaman; Md. Habibur Rahaman; Md. Selim Reza; Md. Mafizul Islam
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Several microgrids can be interconnected together to enhance the grid reliability and reduce the cost of supplying power to an island area where conventional power grid cannot be connected. Source and load demand do not properly balance always. Besides that, sometimes power and frequency fluctuation has occurred in MG at island mode. Need to design a special control for maintaining the state of charge (SoC) of energy storage system. This paper proposes a new power supply system for an island area that interconnects two microgrids with a single energy storage system (ESS). An algorithm has been proposed that control the microgrids energy storage system for spinning reserve and load power/frequency regulation purpose. The minimum loading constraints of diesel engine generator (DEG) is considered and the SOC of the ESS is properly maintained.

Novel ROADM modelling with WSS and OBS to Improve Routing Performance in Optical Network Kavitha G.R G.R.; Indumathi T.S.
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 2: April 2016
Publisher : Institute of Advanced Engineering and Science

The area of optical network is on constant point of focus among the research communities owing to potential advantage of long distance communication as well as the routing issues associated with it. Majority of the implemented techniques calls for using expensive hardware or adopting narrowed technical assumptions, for which reason the routing performance couldn’t be optimized to a large extent. The present manuscript proposes a novel technique called as Optimized Routing for Peak Traffic under the scenario of uncertainties in the existing traffic scenario. The proposed solution presents some potential principle that is incorporated in the ROADM design for enhancing the capabilities of the proposed system. The system is evaluated under multiple scenarios of analysis using blocking probabilities, OSNR, bit error rate, iteration etc. The outcome of the proposed system is compared with the one of the existing significant study to benchmark it.

Robustness Study of Fractional Order PID Controller Optimized by Particle Swarm Optimization in AVR System N. Ramesh Raju; P. Linga Reddy
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 5: October 2016
Publisher : Institute of Advanced Engineering and Science

In this paper a novel design method for determining fractional order PID (PIλDµ) controller parameters of an AVR system using particle swarm optimization algorithm is presented. This paper presents how to employ the particle swarm optimization to seek efficiently the optimal parameters of PIλDµ controller. The robustness study is made for this controller against parameter variation of AVR system. This work has been simulated in MATLAB environment with FOMCON (Fractional Order Modeling and Control) tool box.The proposed PSOPIλDµ controller has superior performance and robust compared to GA tuned PIλDµ controller. The results are also compared with PSO tuned PID controller.

A Novel Semantic Statistical Model for Automatic Image Annotation Using the Relationship between the Regions Based on Multi-Criteria Decision Making Hengame Deljooi; Ahmad Reza Eskandari
International Journal of Electrical and Computer Engineering (IJECE) Vol 4, No 1: February 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (520.572 KB)

Automatic image annotation has emerged as an important research topic due to the existence of the semantic gap and in addition to its potential application on image retrieval and management. In this paper we present an approach which combines regional contexts and visual topics to automatic image annotation. Regional contexts model the relationship between the regions, whereas visual topics provide the global distribution of topics over an image. Conventional image annotation methods neglected the relationship between the regions in an image, while these regions are exactly explanation of the image semantics, therefore considering the relationship between them are helpful to annotate the images. The proposed model extracts regional contexts and visual topics from the image, and incorporates them by MCDM (Multi Criteria Decision Making) approach based on TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution) method. Regional contexts and visual topics are learned by PLSA (Probability Latent Semantic Analysis) from the training data. The experiments on 5k Corel images show that integrating these two kinds of information is beneficial to image annotation.DOI:http://dx.doi.org/10.11591/ijece.v4i1.4598

Bayesian distance metric learning and its application in automatic speaker recognition systems Satyanand Singh
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

This paper proposes state-of the-art Automatic Speaker Recognition System (ASR) based on Bayesian Distance Learning Metric as a feature extractor. In this modeling, I explored the constraints of the distance between modified and simplified i-vector pairs by the same speaker and different speakers. An approximation of the distance metric is used as a weighted covariance matrix from the higher eigenvectors of the covariance matrix, which is used to estimate the posterior distribution of the metric distance. Given a speaker tag, I select the data pair of the different speakers with the highest cosine score to form a set of speaker constraints. This collection captures the most discriminating variability between the speakers in the training data. This Bayesian distance learning approach achieves better performance than the most advanced methods. Furthermore, this method is insensitive to normalization compared to cosine scores. This method is very effective in the case of limited training data. The modified supervised i-vector based ASR system is evaluated on the NIST SRE 2008 database. The best performance of the combined cosine score EER 1.767% obtained using LDA200 + NCA200 + LDA200, and the best performance of Bayes_dml EER 1.775% obtained using LDA200 + NCA200 + LDA100. Bayesian_dml overcomes the combined norm of cosine scores and is the best result of the short2-short3 condition report for NIST SRE 2008 data.

Balancing Trade-off between Data Security and Energy Model for Wireless Sensor Network Manjunath B. E.; P. V. Rao
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

An extensive effort to evolve various routing protocol to ensure optimal data delivery in energy efficient way is beneficial only if there is additional means of security process is synchronized. However, the security process consideration introduces additional overhead thus a security mechanism is needed to accomplish an optimal trade-off that exists in-between security as well as resource utilization especially energy. The prime purpose of this paper is to develop a process of security in the context of wireless sensor networks (WSN) by introducing two types of sensor node deployed with different capabilities. The proposed algorithm Novel Model of Secure Paradigm (N-MSP) which is further integrated with WSN. However, this algorithm uses a Hash-based Message Authentication Code (HMAC) authentication followed by pairwise key establishment during data aggregation process in a WSN. The extensive simulation carried out in a numerical platform called MATLAB that depicts that the proposed N-MSP achieves optimal processing time along with energy efficient pairwise key establishment during data aggregation process

RMEER: Reliable Multi-path Energy Efficient Routing Protocol for Underwater Wireless Sensor Network Mukhtiar Ahmed; Mazleena Salleh; M. Ibrahim Channa; Mohd Foad Rohani
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Underwater Wireless Sensor Networks (UWSNs) is interesting area for researchers.To extract the information from seabed to water surface the the majority numbers of routing protocols has been introduced. The design of routing protocols faces many challenges like deployment of sensor nodes, controlling of node mobility, development of efficient route for data forwarding, prolong the battery power of the sensor nodes, and removal of void nodes from active data forwarding paths. This research article focuses the design of the Reliable Multipath Energy Efficient Routing (RMEER) which develops the efficient route between sensor nodes, and prolongs the battery life of the nodes. RMEER is a scalable and robust protocol which utilizes the powerful fixed courier nodes in order to enhance the network throughput, data delivery ratio, network lifetime and reduces the end-to-end delay. RMEER is also an energy efficient routing protocol for saving the energy level of the nodes. We have used the NS2.30 simulator with AquaSim package for performance analysis of RMEER.We observed that the simulation performance of RMEER is better than D-DBR protocol.

A Vertical Handover Algorithm in Integrated Macrocell Femtocell Networks Suman Deswal; Anita Singhrova
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 1: February 2017
Publisher : Institute of Advanced Engineering and Science

The explosion in wireless telecommunication technologies has lead to a huge increase in the number of mobile users. The greater dependency on the mobile devices has raised the user’s expectations to always remain best connected. In the process, the user is always desiring good signal strength even at certain black spots and indoors. Moreover, the exponential growth of the number of mobile devices has overloaded macrocells. Femtocells have emerged out as a good promising solution for complete coverage indoors and for offloading macrocell. Therefore, a new handover strategy between femtocells and macrocell is proposed in this paper. The proposed handover algorithm is mainly based on calculating equivalent received signal strength along with dynamic margin for performing handover. The simulation results of proposed algorithm are compared with the traditional algorithm. The proposed strategy shows improvement in two major performance parameters namely reduction in unnecessary handovers and Packet Loss Ratio. The quantitative analysis further shows 55.27% and 23.03% reduction in packet loss ratio and 61.85% and 36.78% reduction in unnecessary handovers at a speed of 120kmph and 30kmph respectively. Moreover, the proposed algorithm proves to be an efficient solution for both slow and fast moving vehicles.

A hybrid non-dominated sorting genetic algorithm for a multi-objective demand-side management problem in a smart building Zineb Garroussi; Rachid Ellaia; El-Ghazali Talbi; Jean-Yves Lucas
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

One of the most significant challenges facing optimization models for the demand-side management (DSM) is obtaining feasible solutions in a shorter time. In this paper, the DSM is formulated in a smart building as a linear constrained multi-objective optimization model to schedule both electrical and thermal loads over one day. Two objectives are considered, energy cost and discomfort caused by allowing flexibility of loads within an acceptable comfort range. To solve this problem, an integrative matheuristic is proposed by combining a multi-objective evolutionary algorithm as a master level with an exact solver as a slave level. To cope with the non-triviality of feasible solutions representation and NP-hardness of our optimization model, in this approach discrete decision variables are encoded as partial chromosomes and the continuous decision variables are determined optimally by an exact solver. This matheuristic is relevant for dealing with the constraints of our optimization model. To validate the performance of our approach, a number of simulations are performed and compared with the goal programming under various scenarios of cold and hot weather conditions. It turns out that our approach outperforms the goal programming with respect to some comparison metrics including the hypervolume difference, epsilon indicator, number of the Pareto solutions found, and computational time metrics.

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

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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