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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 9,174 Documents
 634   635   636   637   638 
Elliptical curve cryptography image encryption scheme with aid of optimization technique using gravitational search algorithm Ramireddy Navatejareddy; Muthukuru Jayabhaskar; Bachala Sathyanarayana
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 1: January 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i1.pp247-255

Abstract

Image encryption enables users to safely transmit digital photographs via a wireless medium while maintaining enhanced anonymity and validity. Numerous studies are being conducted to strengthen picture encryption systems. Elliptical curve cryptography (ECC) is an effective tool for safely transferring images and recovering them at the receiver end in asymmetric cryptosystems. This method's key generation generates a public and private key pair that is used to encrypt and decrypt a picture. They use a public key to encrypt the picture before sending it to the intended user. When the receiver receives the image, they use their private key to decrypt it. This paper proposes an ECC-dependent image encryption scheme utilizing an enhancement strategy based on the gravitational search algorithm (GSA) algorithm. The private key generation step of the ECC system uses a GSA-based optimization process to boost the efficiency of picture encryption. The image's output is used as a health attribute in the optimization phase, such as the peak signal to noise ratio (PSNR) value, which demonstrates the efficacy of the proposed approach. As comparison to the ECC method, it has been discovered that the suggested encryption scheme offers better optimal PSNR values.
Performance comparison of channel coding schemes for 5G massive machine type communications Salima Belhadj; Abdelmounaim Moulay Lakhdar; Ridha Ilyas Bendjillali
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp902-908

Abstract

Channel coding for the fifth generation (5G) mobile communication is currently facing new challenges as it needs to uphold diverse emerging applications and scenarios. Massive machine-type communication (mMTC) constitute one of the main usage scenarios in 5G systems, which promise to provide low data rate services to a large number of low power and low complexity devices. Research on efficient coding schemes for such use case is still ongoing and no decision has been made yet. Therefore, This paper compares the performance of different coding schemes, namely: tail-biting convolutional code (TBCC), low density parity check codes (LDPC), Turbo code and Polar codes, in order to select the appropriate channel coding technique for 5G-mMTC scenario. The considered codes are evaluated in terms of bit error rate (BER) and block error rate (BLER) for short information block lengths (K ≤ 256). We further investigate their Algorithmic complexity in terms of the number of basic operations. The Simulation results indicate that polar code with CRC-aided successive cancelation list decoder has better performance compared with other coding schemes for 5G-mMTC scenario.
Automated handwriting analysis based on pattern recognition: a survey Samsuryadi Samsuryadi; Rudi Kurniawan; Fatma Susilawati Mohamad
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp196-206

Abstract

Handwriting analysis has wide scopes include recruitment, medical diagnosis, forensic, psychology, and human-computer interaction. Computerized handwriting analysis makes it easy to recognize human personality and can help graphologists to understand and identify it. The features of handwriting use as input to classify a person’s personality traits. This paper discusses a pattern recognition point of view, in which different stages are described. The stages of study are data collection and pre-processing technique, feature extraction with associated personality characteristics, and the classification model. Therefore, the purpose of this paper is to present a review of the methods and their achievements used in various stages of a pattern recognition system. 
Privacy preserving association rule hiding using border based approach Suma B.; Shobha G.
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 2: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i2.pp1137-1145

Abstract

Association rule mining is a well-known data mining technique used for extracting hidden correlations between data items in large databases. In the majority of the situations, data mining results contain sensitive information about individuals and publishing such data will violate individual secrecy. The challenge of association rule mining is to preserve the confidentiality of sensitive rules when releasing the database to external parties. The association rule hiding technique conceals the knowledge extracted by the sensitive association rules by modifying the database. In this paper, we introduce a border-based algorithm for hiding sensitive association rules. The main purpose of this approach is to conceal the sensitive rule set while maintaining the utility of the database and association rule mining results at the highest level. The performance of the algorithm in terms of the side effects is demonstrated using experiments conducted on two real datasets. The results show that the information loss is minimized without sacrificing the accuracy. 
An intelligent indian stock market forecasting system using LSTM deep learning K Kumar; Dattatray P. Gandhmal
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp1082-1089

Abstract

Stock market data is considered to be one of the chaotic data in nature. Analyzing the stock market and predicting the stock market has been the area of interest among the researchers for a long time. In this paper, we have stepped forward and used a deep learning algorithm with classification to predict the behavior of the stock market. LSTM deep learning algorithm is used with an optimization algorithm to formulate the hyperparameters. To further improve the accuracy of prediction the stock data is first given to a classification algorithm to reduce the number of input parameters. In this research Technical indicators are subjected to classification and deep LSTM algorithm which are both integrated to improve the accuracy of prediction. Deep LSTM hyperparameters are trained using the optimization algorithm. In this paper infosys and zensar stocks data is collected from the Indian stock market data i.e. both national stock exchange (NSE) and bombay stock exchange (BSE). The proposed approach is applied on infosys and zensar share values, the prediction accuracy obtained by employing this integrated approach of classification and LSTM has given a prominent value of MSE and RMSE as 1.034 and 1.002 respectively. 
An efficient and robust parallel scheduler for bioinformatics applications in a public cloud: A bigdata approach Leena Ammanna; Jagadeeshgowda Jagadeeshgowda; Jagadeesh Pujari
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 2: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i2.pp1078-1086

Abstract

In bioinformatics, genomic sequence alignment is a simple method for handling and analysing data, and it is one of the most important applications in determining the structure and function of protein sequences and nucleic acids. The basic local alignment search tool (BLAST) algorithm, which is one of the most frequently used local sequence alignment algorithms, is covered in detail here. Currently, the NCBI's BLAST algorithm (standalone) is unable to handle biological data in the terabytes. To address this problem, a variety of schedulers have been proposed. Existing sequencing approaches are based on the Hadoop MapReduce (MR) framework, which enables a diverse set of applications and employs a serial execution strategy that takes a long time and consumes a lot of computing resources. The author, improves the BLAST algorithm based on the BLAST-BSPMR algorithm to achieve the BLAST algorithm. To address the issue with Hadoop's MapReduce framework, a customised MapReduce framework is developed on the Azure cloud platform. The experiment findings indicate that the suggested bulk synchronous parallel MapReduce-basic local alignment search tool (BSPMR-BLAST) algorithm matches bioinformatics genomic sequences more quickly than the existing Hadoop-BLAST method, and that the proposed customised scheduler is extremely stable and scalable.
Speed control of DC motor using fractional order PID controller based on particle swarm optimization Ghassan A. Sultan; Amer F. Sheet; Satar M. Ibrahim; Ziyad K. Farej
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i3.pp1345-1353

Abstract

Due to the required different speeds and important role of direct current (DC) motors in laboratories, production factories and industrial application, speed controlling of these motors becomes an essential matter for proper operation with high efficiency and performance accuracy. This paper presents a new speed controlling technique that is based on particle swarm optimization (PSO) algorithm in the optimization process of the parameters for the fractional order proportional–integral–derivative (FOPID) controller. The FOPID is an advanced and modern controlling system in which the two more added parameters (the derivative μ and integral λ orders) are fractional rather than integer. Through the process of minimizing the fitness functions, the obtained results show that the designed controller system can excellently set the best controller parameters due to the fractions of these additional parameters. With respect to the PSO-PID controller, the simulation results for the proposed PSO-FOPID controller show performance improvements of 14%, 21%, 24.5%, 78%, and 19.3% in the values of the parameters Kp, Ki, Kd, Tr, and Ts respectively.
Design and simulation of video monitoring structure over TCP/IP system using MATLAB Amany Mohammad Abood; Maysam Sameer Hussein; Zainab G. Faisal; Zainab H. Tawfiq
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i3.pp1840-1845

Abstract

Video monitoring systems are undergoing an evolution from conventional analog to digital clarification to provide better rate and security over internet protocols. In addition, analog surveillance becomes insufficient to face enormous demand of security of system contains more than hundreds of camera often deployed in hotels environments far away from room control. This paper presents the design and simulation of a video monitoring scheme in excess of a transmission control protocol/internet protocol (TCP/IP) system using MATLAB. Sophisticated cameras could record directly high-definition digital videos based on digital technology which simply communicate the control room relaying on ordinary internet protocol infrastructure networks. This technology provides a flexible network interface over a wide variety of heterogeneous technology networks. Though, the acceptance of IP designed for video monitoring pretense severe difficulties in terms of power processing, system dependability, required bandwidth, and security of networks. The advantage of IP based video monitoring system has been investigated over conventional analog systems and the challenges of the method are described. The open research issues are still requiring a final solution to permits complete abandon against conventional technology of analog methods. In conclusion, the method to tackle the purpose of video monitoring in actual operation is proposed and verified properly by means of model simulation.
A robust watermark algorithm for copyright protection by using 5-level DWT and two logos Alaa Rishek Hoshi; Nasharuddin Zainal; Mahamod Ismail; Abd Al-Razak T. Rahem; Salim Muhsin Wadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 2: May 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i2.pp842-856

Abstract

Recent growth and development of internet and multimedia technologies have made it significant to upload data; however, in this situation, the protection of intellectual property rights has become a critical issue. Digital media, including videos, audios, and images are readily distributed, reproduced, and manipulated over these networks that will be lost copyright. Also, the development of various data manipulation tools like PDF converter and Photoshop Editor has resulted in digital data copyright issues. So, a digital watermarking technique has emerged as an efficient technique of protecting intellectual property rights by providing digital data copyright authentication and protection. In this technique, a watermarked document was integrated into electronic data to prevent unauthorized access. In this paper, A robust watermark algorithm based on a 5-level DWT and Two Log was proposed to enhance the copyright protection of images in unsecured media. Our lab results validate that our algorithm scheme is robust and forceful against several sets of attacks, and high quality watermarked image was achieved, where the algorithm was assessed by computation of many evaluation metrics such as PSNR, SNR, MAE, and RMSE.
IoT and transparent solar cell based automated green house monitoring system for tomato plant cultivation Yus Rama Denny; Endi Permata; Adhitya Trenggono; Vaka Gustiono
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 1: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i1.pp18-27

Abstract

This study aimed to develop and test the feasibility of a smart greenhouse prototype media that is used as a planting medium with an automatic watering system. The method in this study was research and development using the waterfall model. In order to test the feasibility, the prototype was validated with material expert validators, media expert, and farmers. The questionnaire instrument was compiled based on Walker and Hess instrument. The results of the research found are as follows: the results of feasibility research by media experts has an average score of 4.35 with the category "very feasible", assessment by experts the material has an average score of 4.4 with the category "very feasible", and the assessment of the user has an average score of 4.06 with "feasible". The purposed controlled system of smart greenhouse and as a media for farmers was validated. Our results demonstrated that the smart greenhouse is suitable media to help farmers cultivating the tomatoes plant.

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