cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
,
INDONESIA
Bulletin of Electrical Engineering and Informatics
Published by IAES Indonesia Section and Partners
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Arjuna Subject : -
Articles 3 Documents
 1 
Search results for , issue " Vol 7, No 3: September 2018" : 3 Documents clear
Distributed Scheme To Authenticate Data Storage Security In Cloud Computing Bandarupalli, Rakesh; Rajitha, O.; Parveen Sultana, H.
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v7i3.715

Abstract

Cloud Computing is the revolution in current generation IT enterprise. Cloud computing displaces database and application software to the large data centers, where the management of services and data may not be predictable, where as the conventional solutions, for IT services are under proper logical, physical and personal controls. This aspect attribute, however comprises different security challenges which have not been well understood. It concentrates on cloud data storage security which has always been an important aspect of quality of service (QOS). In this paper, we designed and simulated an adaptable and efficient scheme to guarantee the correctness of user data stored in the cloud and also with some prominent features.  Homomorphic token is used for distributed verification of erasure – coded data. By using this scheme, we can identify misbehaving servers.  In spite of past works, our scheme supports effective and secure dynamic operations on data blocks such as data insertion, deletion and modification. In contrast to traditional solutions, where the IT services are under proper physical, logical and personnel controls, cloud computing moves the application software and databases to the large data centers, where the data management and services may not be absolutely truthful.  This effective security and performance analysis describes that the proposed scheme is extremely flexible against malicious data modification, convoluted failures and server clouding attacks.
Signal-to-Noise Ratio Study on Pipelined Fast Fourier Transform Processor Hassan, L. M.; S. Shariffudin, S.; N. T. Yaakub, T.; L. M. Hassan, S.
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v7i3.1271

Abstract

Fast Fourier transform (FFT) processor is a prevailing tool in converting signal in time domain to frequency domain.  This paper provides signal-to-noise ratio (SNR) study on 16-point pipelined FFT processor implemented on field-programable gate array (FPGA). This processor can be used in vast digital signal applications such as wireless sensor network, digital video broadcasting and many more. These applications require accuracy in their data communication part, that is why SNR is an important analysis. SNR is a measure of signal strength relative to noise. The measurement is usually in decibles (dB). Previously, SNR studies have been carried out in software simulation, for example in Matlab. However, in this paper, pipelined FFT and SNR modules are developed in hardware form. SNR module is designed in Modelsim using Verilog code before implemented on FPGA board. The SNR module is connected directly to the output of the pipelined FFT module. Three different pipelined FFT with different architectures were studied. The result shows that SNR for radix-8 and R4SDC FFT architecture design are above 40dB, which represent a very excellent signal. SNR module on the FPGA and the SNR results of different pipelined FFT architecture can be consider as the novelty of this paper.
Oscillatory Stability Prediction using PSO Based Synchronizing and Damping Torque Coefficients A. M. Kamari, N.; Musirin, I.; A. Hamid, Z.; H. M. Zaman, M.
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v7i3.1288

Abstract

This paper presents the assessment of stability domains for the angle stability condition of the power system using particle swarm optimization (PSO) technique. An efficient optimization method using PSO for synchronizing torque coefficients Ks and damping torque coefficients Kd to identify the angle stability condition on multi-machine system. In order to accelerate the determination of angle stability, particle swarm optimization (PSO) is proposed to be implemented in this study. The application of the proposed algorithm has been justified as the most accurate with lower computation time as compared to other optimization techniques such as evolutionary programming (EP) and artificial immune system (AIS). Validation with respect to eigenvalues determination, Least Square (LS) method and minimum damping ratio ξmin confirmed that the proposed technique is feasible to solve the angle stability problems.

Page 1 of 1 | Total Record : 3

 1 

Filter by Year

2018 2018


Reset
Filter By Issues
All Issue Vol 8, No 4: December 2019 Vol 8, No 3: September 2019 Vol 8, No 3: September 2019 Vol 8, No 2: June 2019 Vol 8, No 2: June 2019 Vol 8, No 1: March 2019 Vol 8, No 1: March 2019 Vol 7, No 4: December 2018 Vol 7, No 3: September 2018 Vol 7, No 3: September 2018 Vol 7, No 2: June 2018 Vol 7, No 1: March 2018 Vol 6, No 4: December 2017 Vol 6, No 3: September 2017 Vol 6, No 2: June 2017 Vol 6, No 1: March 2017 Vol 5, No 4: December 2016 Vol 5, No 4: December 2016 Vol 5, No 3: September 2016 Vol 5, No 2: June 2016 Vol 5, No 2: June 2016 Vol 5, No 1: March 2016 Vol 5, No 1: March 2016 Vol 4, No 4: December 2015 Vol 4, No 4: December 2015 Vol 4, No 3: September 2015 Vol 4, No 3: September 2015 Vol 4, No 2: June 2015 Vol 4, No 1: March 2015 Vol 4, No 1: March 2015 Vol 3, No 4: December 2014 Vol 3, No 4: December 2014 Vol 3, No 3: September 2014 Vol 3, No 2: June 2014 Vol 3, No 1: March 2014 Vol 2, No 4: December 2013 Vol 2, No 3: September 2013 Vol 2, No 2: June 2013 Vol 2, No 1: March 2013 Vol 1, No 4: December 2012 Vol 1, No 3: September 2012 Vol 1, No 2: June 2012 Vol 1, No 1: March 2012 More Issue