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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 66 Documents
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Search results for , issue "Vol 18, No 2: May 2020" : 66 Documents clear
DES encryption and decryption algorithm implementation based on FPGA Subhi R. M. Zeebaree
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 2: May 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i2.pp774-781

Abstract

Nowadays there is a lot of importance given to data security on the internet. The DES is one of the most preferred block cipher encryption/decryption procedures used at present. This paper presents a high throughput reconfigurable hardware implementation of DES Encryption algorithm. This achieved by using a new proposed implementation of the DES algorithm using pipelined concept.  The implementation of the proposed design is presented by using Spartan-3E (XC3S500E) family FPGAs and is one of the fastest hardware implementations with much greater security. At a clock frequency of 167.448MHz for encryption and 167.870MHz for decryption, it can encrypt or decrypt data blocks at a rate of 10688Mbps.
Systematic mapping study of economic and business models of cloud services Isaac Odun-Ayo; Toro-Abasi Williams; Olusola Abayomi-Alli; Jamaiah Yahaya
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 2: May 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i2.pp987-994

Abstract

Cloud computing is a business paradigm wherein computers and computing related services are provided by Cloud Service Providers to consumers either as software, development platform, or infrastructure. From an economic and business perspective, Cloud services involve cost, ownership quality of service and service level agreements. There are studies on economic and business models of cloud services on the cloud landscape especially in the area of pricing. Despite this, there is still a dearth of papers in this area of study. The objective of this study is to conduct a systematic mapping study to collect all relevant research on economic and business models of Cloud services. A systematic map provides a structured overview in a particular research area. The representation of the mapping process offers unique course-grained overview of the results. The results are presented in terms of research such as evaluation and solution, and contribution such as tools and method utilized. The results showed that there are more publications on pricing models in relation to tools with 6.87% and model with 14.5%, more publications on economic and business implications in terms of method with 11.45%, more publications on Cloud market in term of processes with 6.87%, more papers on security in the area of evaluation with 8.55% and validation research with 6.58%, and more papers on Cloud markets with respect to experience with 4.61% and validation with 5.92%. The research gaps identified in this study should motivate researchers to carry out more mapping studies in the field.
Double stages of feature extarction-based GFPMI for colored finger vein identification Dawlat Mustafa Sulaiman; Adnan Mohsin Abdulazeez; Habibollah Haron
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 2: May 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i2.pp927-937

Abstract

Today, finger vein recognition has a lot of attention as a promising approach of biometric identification framework and still does not meet the challenges of the researchers on this filed. To solve this problem, we propose s double stage of feature extraction schemes based localized finger fine image detection. We propose Globalized Features Pattern Map Indication (GFPMI) to extract the globalized finger vein line features basede on using two generated vein image datasets: original gray level color, globalized finger vein line feature, original localized gray level image, and the colored localized finger vein images. Then, two kinds of features (gray scale and texture features) are extracted, which tell the structure information of the whole finger vein pattern in the whole dataset. The recurrent based residual neural network (RNN) is used to identify the finger vein images. The experimental show that the localized colored finger vein images based globalized feature extraction has achieved the higher accuracy (93.49%) while the original image dataset achieved less accuracy by (69.86%).
Two-level hiding an encrypted image Faten H. MohammedSediq Al-Kadei
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 2: May 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i2.pp961-969

Abstract

Encryption and hiding images are becoming a hot research area and a broad prospect for application. This article uses a secure algorithm with Low Significant Bit method to hide an encrypted high-resolution color bitmap image in two selectively color images (i.e., two cover images). The paper introduces a two-level hiding encrypted image using MATLAB-GUI programming language. In the beginning, with a key image using XOR bit operation, the original RGB image is encrypted. After that, the encrypted image is hidden into the first cover image. The cover image is then hidden into another cover to make the secret image safer without changing the perceptual quality for both covers. Then, the algorithm is tested on many bitmap images, which can be an important image, fingerprint image, samples of secret medicine, or bank account pattern. The correlation histograms demonstrate a high correlation for all encrypted images. The PSNR is used to find steganography quality for the two cover images after hiding the secret image showing a high quality for the two levels of hiding operation
Extraction of cause-effect-concept pair series from web documents Chaveevan Pechsiri; Titirut Mekbunditkul
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 2: May 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i2.pp970-978

Abstract

This research aims to extract a cause-effect-concept pair series of consequent event occurrences in health information of hospital web-boards. The extracted cause-effect-concept pair series representing a disease causation pathway benefits for the automatic diagnosis and solving system. Where each causative/effect event concept is expressed by an elementary discourse unit (EDU which is a simple sentence). The research has three problems; how to determine causative/effect concept EDUs from the documents containing some EDU occurrences with both causative concepts and effect concepts, how to determine the cause-effect relation between two adjacent EDUs having the discourse cue ambiguity, and how to extract cause-effect-concept pair series mingled with either a stimulation relation EDU or other non-cause-effect relation EDUs from the documents. Therefore, we apply annotated NWordCo pairs with causative-effect concepts to represent EDU pairs with causative-effect concept where the NWordCo size solved by Naïve Bayes. We also apply Naïve Bayes to solve NWordCo-concept pairs having the cause-effect relation from the adjacent EDU pairs. We then propose using cue words and the collected NWordCo-concept pairs with the cause-effect relation to extract the cause-effect-concept pair series. The research results provide the high precision of the cause-effect-concept pair series determination from the documents. 
An ensemble technique for speech recognition in noisy environments Imad Qasim Habeeb; Tamara Z. Fadhil; Yaseen Naser Jurn; Zeyad Qasim Habeeb; Hanan Najm Abdulkhudhur
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 2: May 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i2.pp835-842

Abstract

Automatic speech recognition (ASR) is a technology that allows a computer and mobile device to recognize and translate spoken language into text. ASR systems often produce poor accuracy for the noisy speech signal. Therefore, this research proposed an ensemble technique that does not rely on a single filter for perfect noise reduction but incorporates information from multiple noise reduction filters to improve the final ASR accuracy. The main factor of this technique is the generation of K-copies of the speech signal using three noise reduction filters. The speech features of these copies differ slightly in order to extract different texts from them when processed by the ASR system. Thus, the best among these texts can be elected as final ASR output. The ensemble technique was compared with three related current noise reduction techniques in terms of CER and WER. The test results were encouraging and showed a relatively decreased by 16.61% and 11.54% on CER and WER compared with the best current technique. ASR field will benefit from the contribution of this research to increase the recognition accuracy of a human speech in the presence of background noise.

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