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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

283 284 285 286 287

Torque improvement of PM motor with semi-cycle stator design using 2D-finite element analysis Kwang T. C.; Mohd Luqman Mohd Jamil; Auzani Jidin
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

This paper presents sizing approaches to improve output torque performance in PM motor when partial stator body is removed. As the output torque performance is directly proportional to the electric loading, Q, modification on stator geometry affects the output torque performance and special procedures have to be taken to restore the desired output torque capability. Influences of split ratio, tooth body width, airgap and magnet thickness of magnet in PM motor with asymmetry stator design are carried out and the performance verification are referred to the back-emf, average output torque, torque ripple as well as cogging torque. From the investigation using 2D-Finite Element Analysis, optimum size of tooth body width and optimum number of coil turns result better output torque while other sizing approaches result no significant change as quick saturation took place.

An Enhancement Role and Attribute Based Access Control Mechanism in Big Data M Meneka; K. Meenakshisundaram
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

To be able to leverage big data to achieve enhanced strategic insight and make informed decision, an efficient access control mechanism is needed for ensuring end to end security of such information asset. Attribute Based Access Control (ABAC), Role Based Access Control (RBAC) and Event Based Access Control (EBAC) are widely used access control mechanisms. The ABAC system is much more complex in terms of policy reviews, hence analyzing the policy and reviewing or changing user permission are quite complex task. RBAC system is labor intensive and time consuming to build a model instance and it lacks flexibility to efficiently adapt to changing user’s, objects and security policies. EBAC model considered only the events to allocate access controls. Yet these mechanisms have limitations and offer feature complimentary to each other. So in this paper, Event-Role-Attribute based fine grained Access Control mechanism is proposed, it provide a flexible boundary which effectively adapt to changing user’s, objects and security policies based on the event. The flexible boundary is achieved by using temporal and environment state of an event. It improves the big data security and overcomes the disadvantages of the ABAC and RBAC mechanisms. The experiments are conducted to prove the effectiveness of the proposed Event-Role-Attribute based Access Control mechanism over ABAC and RBAC in terms of computational overhead.

Blended intelligence of FCA with FLC for knowledge representation from clustered data in medical analysis Ch. Neelima; S. S.V.N. Sarma
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 1: February 2019
Publisher : Institute of Advanced Engineering and Science

Formal concept analysis is the process of data analysis mechanism with emergent attractiveness across various fields such as data mining, robotics, medical, big data and so on. FCA is helpful to generate the new learning ontology based techniques. In medical field, some growing kids are facing the problem of representing their knowledge from their gathered prior data which is in the form of unordered and insufficient clustered data which is not supporting them to take the right decision on right time for solving the uncertainty based questionnaires. In the approach of decision theory, many mathematical replicas such as probability-allocation, crisp set, and fuzzy based set theory were designed to deals with knowledge representation based difficulties along with their characteristic. This paper is proposing new ideological blended approach of FCA with FLC and described with major objectives: primarily the FCA analyzes the data based on relationships between the set of objects of prior-attributes and the set of attributes based prior-data, which the data is framed with data-units implicated composition which are formal statements of idea of human thinking with conversion of significant intelligible explanation. Suitable rules are generated to explore the relationship among the attributes and used the formal concept analysis from these suitable rules to explore better knowledge and most important factors affecting the decision making. Secondly how the FLC derive the fuzzification, rule-construction and defuzzification methods implicated for representing the accurate knowledge for uncertainty based questionnaires. Here the FCA is projected to expand the FCA based conception with help of the objective based item set notions considered as the target which is implicated with the expanded cardinalities along with its weights which is associated through the fuzzy based inference decision rules. This approach is more helpful for medical experts for knowing the range of patient’s memory deficiency also for people whose are facing knowledge explorer deficiency.

Performance Evaluation of Energy Detector Based Spectrum Sensing for Cognitive Radio using NI USRP-2930 Fatima Zahra El Bahi; Hicham Ghennioui; Mohcine Zouak
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 4: August 2017
Publisher : Institute of Advanced Engineering and Science

This paper presents the performance evaluation of the Energy Detector technique, which is one of the most popular Spectrum Sensing (SS) technique for Cognitive Radio (CR). SS is the ability to detect the presence of a Primary User (PU) (i.e. licensed user) in order to allow a Secondary User (SU) (i.e unlicensed user) to access PU's frequency band using CR, so that the available frequency bands can be used efficiently. We used for implementation an Universal Software Radio Peripheral (USRP), which is the most used Software Defined Radio (SDR) device for research in wireless communications. Experimental measurements show that the Energy Detector can obtain good performances in low Signal to Noise Ratio (SNR) values. Furthermore, computer simulations using MATLAB are closer to those of USRP measurements.

Optimized BER for channel equalizer using cuckoo search and neural network Swati Katwal; Vinay Bhatia
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

The digital data transfer faces issues regarding Inter-Symbol Interference (ISI); therefore, the error rate becomes dependent upon channel estimation and its equalization. This paper focuses on the development of a method for optimizing the channel data to improve ISI by utilizing a swarm intelligence series algorithm termed as Cuckoo Search (CS). The adjusted data through CS is cross-validated using Artificial Neural Network (ANN). The data acceptance rate is considered with 0-10% marginal error which varies in the given range with different bit streams. The performance evaluation of the proposed algorithm using the Average Bit Error Rate (A-BER) and Logarithmic Bit Error Rate (L-BER) had shown an overall improvement of 30-50% when compared with the Kalman filter based algorithm.

An Optimizing Approach for Multi Constraints Reassignment Problem of Human Resources Tkatek Said; Abdoun Otman; Abouchabaka Jaafar; Rafalia Najat
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 4: August 2016
Publisher : Institute of Advanced Engineering and Science

This paper presents an effective approach to optimize the reassignment of Human Resources in the enterprise that is formed by several units of productions to take into consideration the human characteristics. This approach consists of two steps; the first step is to formalize the studied problem that is practically take the form of the generalized assignment problem (GAP) known as NP-hard problem. Additionally, the variables in the formulation of our problem are interlinked by certain constraints. These two proprieties can to justify the important complexity of this problem. The second step is focused to solve this complex problem by using the genetic algorithm. We present the experimentally result for justifying the validity of the proposed approach. So, the solution obtained allowed us to get an optimal assignment of personnel that can lead to improve the average productivity or ratability or at least ensure its equilibration within sites of enterprise.

Modal Coupling Coefficients and Frequency/Bias Planes for Gyromagnetic Boundary Value Problems Junaid Zafar; Tasneem Zafar; Haroon Zafar
International Journal of Electrical and Computer Engineering (IJECE) Vol 2, No 5: October 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (112.612 KB)

In this paper, electromagnetic and uniform precession magnetostatic mode interaction theory is reformulated to include comprehensive electromagnetic modal impact in the determination of modal coupling calculations. For this purpose orthogonal electromagnetic and normal magnetostatic modes character is solved with coupled field Maxwell’s equations and vectorized magnetization expression to model the interactions between electromagnetic modes and magnetostatic uniform precession mode. Calculations for modal coupling factors are presented here for the first time and frequency/ bias planes are constructed using the developed modal interaction formulation with an ameliorated accuracy. The proposed formulation is validated and tested against closed form frequency/ bias solutions concerning these gyromagnetic boundary value problems.DOI:http://dx.doi.org/10.11591/ijece.v2i5.222

Scientific Documents clustering based on Text Summarization Pedram Vahdani Amoli; Omid Sojoodi Sh.
International Journal of Electrical and Computer Engineering (IJECE) Vol 5, No 4: August 2015
Publisher : Institute of Advanced Engineering and Science

In this paper a novel method is proposed for scientific document clustering. The proposed method is a summarization-based hybrid algorithm which comprises a preprocessing phase. In the preprocessing phase unimportant words which are frequently used in the text are removed. This process reduces the amount of data for the clustering purpose. Furthermore frequent items cause overlapping between the clusters which leads to inefficiency of the cluster separation. After the preprocessing phase, Term Frequency/Inverse Document Frequency (TFIDF) is calculated for all words and stems over the document to score them in the document. Text summarization is performed then in the sentence level. Document clustering is finally done according to the scores of calculated TFIDF. The hybrid progress of the proposed scheme, from preprocessing phase to document clustering, gains a rapid and efficient clustering method which is evaluated by 400 English texts extracted from scientific databases of 11 different topics. The proposed method is compared with CSSA, SMTC and Max-Capture methods. The results demonstrate the proficiency of the proposed scheme in terms of computation time and efficiency using F-measure criterion.

Firefly Algorithm to Opmimal Distribution of Reactive Power Compensation Units Vadim Z. Manusov; Pavel V. Matrenin; Lola S. Atabaeva
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science

The issue of electric power grid mode of optimization is one of the basic directions in power engineering research. Currently, methods other than classical optimization methods based on various bio-heuristic algorithms are applied. The problems of reactive power optimization in a power grid using bio-heuristic algorithms are considered. These algorithms allow obtaining more efficient solutions as well as taking into account several criteria. The Firefly algorithm is adapted to optimize the placement of reactive power sources as well as to select their values. A key feature of the proposed modification of the Firefly algorithm is the solution for the multi-objective optimization problem. Algorithms based on a bio-heuristic process can find a neighborhood of global extreme, so a local gradient descent in the neighborhood is applied for a more accurate solution of the problem. Comparison of gradient descent, Firefly algorithm and Firefly algorithm with gradient descent is carried out.

Identification of individualization techniques for criminal records in sanction lists Gonzalo M Arias; Pablo Peláez; Fredy E Hoyos
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

Using efficient searching techniques on sanctions list and press articles allows a better filtering on individuals and entities to establish a commercial relationship with, including those who are going to have access to confidential information belonging to the company, in order to minimize the risk of leakage or information mismanagement. That process of filtering on individuals or entities could be automated by using individualization algorithms, searching techniques based on string comparisons, artificial intelligence, and facial recognition. Diverse methods were examined to be applied on each mentioned technique in order to identify which ones are ideal to its application on individualization due to their characteristics, in order to obtain agile and reliable results; taking into account that different methods are complementary and not exclusive, and that their combination allows to minimize human interaction in the classification of information, avoiding analysis of data irrelevant for that particular search.

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Home Page

OAI Link

Editorial Team

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Reviewer

Google Scholar

Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

Phone -

Journal Mail Official ijece@iaesjournal.com

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

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Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

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