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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 64 Documents
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Search results for , issue "Vol 29, No 3: March 2023" : 64 Documents clear
Proficient matrix codes for error detection and correctionin 8-port network on chip routers Neelima Koppala; Nagarajan Ashok Kumar; Satyam Satyam; Neeruganti Vikram Teja
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1336-1344

Abstract

This paper verifies the applicability of the proposed code to dynamic Network on Chips that have variable faulty blocks with runtime suggesting an online error detection mechanism with adaptive routing algorithm that bypasses faulty components dynamically and the router architecture uses additional diagonal state indications for the reliable network on chip (NoC) operation. In NoC, the permanently faulty routers are disconnected to enable high runtime throughput as data packets are not lost due to self-loopback mechanism. The proposed proficient matrix codes use the capabilities of decimal matrix code technique with minimum check bits for maximum error correction capability. The proposed code is compared with existing codes such as decimal matrix codes, modified decimal matrix codes and parity matrix codes. The codes are developed in verilog hardware description language and simulated in the Xilinx ISE 14.5 tool. This proficient matrix code proves to be efficient for multiple adjacent error detection and correction with trade off in delay. Also 65% code rate is achieved with 22.73% less redundant bits that occupy less area by atleast 11.78%. The codes when used for increased data sizes like 8, 16, 32, and 64 bits, the power delay product decreased by atleast 1.74%.
Linear precoder optimization of spectral efficiency of time division duplex hyper MIMO system with pilot contamination Zanga Mvodo Martin Paulin; Koko Same Louis Christian; Essiben Dikoundou Jean-François
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1520-1528

Abstract

Our work is developed in context of studing Massive MIMO in a 5G context. The aim is to optimize spectral efficiency of several users hyper MIMO system during Uplink communication in a multi-cell contaminated pilot environment, using a new type of precoders called single cell-minimum mean square eroor (S-MMSE) and multicell-minimum mean square eroor (MMMSE). Indeed, we address two key and well-known issues of massive multiuser MIMO (MU-MIMO) environments in a test-driven development (TDD) operation scheme, namely acquisition of uplink channel state information (UL) and optimisation of the bit stream per unit frequency, the spectral efficiency (SE). From a practical point of view, these two notions are inclusively linked. Indeed, a very good channel estimation leads to a better spectral efficiency. In our approcah, we derive from the minimum mean square error estimator (MMSE) to two new types of precoders that can operate in a multicell environment with a contaminated pilot sequence, namely the SMMSE and the M-MMSE. A comparative study performance of these classical precoders such as regulated zero forcing (RZF), ZF (Zero Forcing) and MR (Minimum Ratio) encountered in multi-antenna processing shows an improvement of nearly 51% in terms of system gain and spectral efficiency.
Reputation-based security model for detecting biased attacks in big data Vinod Desai; Dinesha Hagare Annappaiah
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1567-1576

Abstract

As internet of things (IoT) devices are increasing since the emergence of these devices in 2010, the data stored by these devices should have a proper security measure so that it can be stored without getting in hands of an attacker. The data stored has to be analyzed whether the data is safe or malicious, as the malicious data can corrupt the whole information. The security model in big data has many challenges such as vulnerability to fake data generation, troubles with cryptographic protection, and absent security audits. As cyber-attacks are increasing the main objective of each organization is to secure the data efficiently. This paper presents a model of reputation security for the detection of biased attacks on big data. The proposed model provides various evaluation models to identify biased attack in malicious IoT devices and provide a secure communication metric for big data. The results show better rates in terms of attack detection rate, attack detection failure rata, system throughput and number of dead nodes when the attack rate is increased when compared with the existing reputation-based security (ERS) model. Moreover, this model reputation-based biased attack detection (RBAD) increases the security of the IoT devices in the big data and reduces the biased attack coming from various malicious nodes.
Automation and electrical control of a mortising machine with 12 synchronous perforations in the manufacture of stairs Daniel López-Borjas; Omar Chamorro-Atalaya; Florcita Aldana-Trejo; Vidalina Chaccara-Contreras; Nestor Alvarado-Bravo; Erika Zevallos-Vera; Evelyn Anicama-Navarrete
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1364-1373

Abstract

With the constant technological development, industries have been incorporating technologies into their manufacturing processes, which generate benefits in the productive field. In the manufacturing process of wooden stairs, the faults of the products, generates that an adequate homogeneity is not achieved, often because the manual operation is carried out without having established parameters in the handling of the mortiser. In this sense, the present article develops an automatism and electrical control of a 12 synchronous perforation mortiser, in order to improve the productivity of the perforation stage in the manufacture of wooden stairs. As part of the development, the electrical, pneumatic and mechanical control system is carried out using Autodesk Inventor software, while the KOP programming is carried out in Tía Portal V14 with connection to S7 PLCSIM V14 using the programmable logic controller (PLC) 1214C. Once the automation has been implemented, a reduction in the processing time per wooden strip of 74.68% is obtained. Likewise, with the automatic process, it is possible to produce 2,460 units of slats, that is, the monthly production increases by 294.9%, in other words, the productivity is 58 units of slats manufactured per hour.
Preconditioned successive over relaxation iterative method via semi-approximate approach for Burgers’ equation Nur Farah Azira Zainal; Jumat Sulaiman; Azali Saudi; Nur Afza Mat Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1606-1613

Abstract

This paper proposes the combination of a preconditioner applied with successive over relaxation (SOR) iterative method for solving a sparse and huge scale linear system (LS) in which its coefficient matrix is a tridiagonal matrix. The purpose for applying the preconditioner is to enhance the convergence rate of SOR iterative method. Hence, in order to examine the feasibility of the proposed iterative method which is preconditioner SOR (PSOR) iterative method, first we need to derive the approximation equation of one-dimensional (1D) Burgers’ equation through the discretization process in which the second-order implicit finite difference (SIFD) scheme together with semi-approximate (SA) approach have been applied to the proposed problem. Then, the generated LS is modified into preconditioned linear system (PLS) to construct the formulation of PSOR iterative method. Furthemore, to analyze the feasibility of PSOR iterative method compared with other point iterative methods, three examples of 1D Burgers’ equation are considered. In conclusion, the PSOR iterative method is superior than PGS iterative method. The simulation results showed that our proposed iterative method has low iteration numbers and execution time.
Agri-PAD: a scalable framework for smart agriculture Tehreem Qamar; Narmeen Zakaria Bawany
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1597-1605

Abstract

More recently, big data tools and technologies have been applied in the agriculture sector leading to major benefits. Many frameworks have been proposed that employ big data technologies in the field of agriculture, however, such existing frameworks are focused on a particular aspect of agriculture and do not consider multiple stakeholders and applications. The objective of this research is to develop a holistic framework named Agri-PAD that encompasses almost all aspects of agriculture including crop selection, crop monitoring, soil monitoring, weather conditions, precision farming, and market demand. The Agri-PAD framework includes three major categories of machine learning based agriculture applications that is precision, recommendation, and enterprise applications. The Agri-PAD framework is capable of providing remote sensing of fields, precision farming, effective supply chain, and support informed decision making leading to enhanced productivity. To validate the efficacy of the proposed framework, the two most prominent agricultural applications, crop production forecasting and crop harvesting recommendation have been investigated and accuracy of 99% has been achieved. We believe that the Agri-PAD framework enables all stakeholders in the agriculture cycle to connect and apply big data analytics at every step leading to a more efficient and smarter agriculture ecosystem.
Deep learning approach for detecting and localizing brain tumor from magnetic resonance imaging images Abu Shahed Shah. Md. Nazmul Arefin; Shah Mohd. Ishtiaque Ahammed Khan Ishti; Mst. Marium Akter; Nusrat Jahan
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1729-1737

Abstract

Brain is the most important part of the nervous system. Brain tumor is mainly a mass or growth of abnormal tissues in a brain. Early detection of brain tumor can reduce complex treatment process. Magnetic resonance images (MRI) are used to detect brain tumor. In this paper, we have introduced a deep convolutional neural network (CNN) to automatic brain tumor segmentation using MRI medical images which can solve the vanishing gradient problem. Classifying the brain MRI images with Resnet-50 and InceptionV3 in order to identify whether there is tumor or not. After this step, we have compared the accuracy level of both of the CNN models. Thereafter, applied U-Net architecture individually with encoder Resnet-50 and InceptionV3 to avieved promising results. The publicly available low grade gliomas (LGG) segmentation dataset has been utilized to test the model. Before applying the model on the MRI images preprocessing and several augmentation techniques have been done to obtain quality a dataset. U-net architecture with InceptionV3 provided 99.55% accuracy. On the other hand, our proposed method U-net with encoder ResNet-50 showed 99.77% accuracy.
Cloud computing: google firebase firestore optimization analysis Andi Bahtiar Semma; Mukti Ali; Muh Saerozi; Mansur Mansur; Kusrini Kusrini
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1719-1728

Abstract

Cloud computing is a new paradigm that provides end users with a secure, personalized, dynamic computing environment with guaranteed service quality. One popular solution is Google cloud firestore, a global-scale not only structured query language (NoSQL) document database for mobile and web apps. Recent research on cloud-based NoSQL databases often discusses the difference between them and SQL databases and their performance. However, using cloud-based NoSQL databases such as firestore is tricky without any scientific comparison methodology, and it needs analysis of how its particular systems work. This study aims to discover what is the best design that could be implemented to optimize data read cost, response size, and time regarding the cloud firestore database. In this study, we develop a grade point average (GPA)-report mocking application to assess data read based on our institution’s needs. This application consists of three functions. Add the graduated GPA and students’ names, and view the ten highest GPAs, GPA average, and total graduated students. The finding indicates that aggregating data on the client side or utilizing the Google cloud function trigger, then updating aggregation data in one transaction significantly reduces document read count (cost), response size, and time.
Embedded electronic system for evaluation of photovoltaic modules based on a current-voltage curve tracer Ricardo Yauri; Rafael Espino
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1281-1289

Abstract

The rapid growth of the market for the use of renewable energy has increased the use of solar energy which has a significant role in power generation. This requires the insertion of equipment capable of providing precise measurements of the photovoltaic modules, either to verify the operation of the installation or to find specific problems. In this scenario, the current versus voltage curve tracer is used to describe the electrical behavior of the photovoltaic system through all the operating possibilities, but it has an excessive cost for small installations. This paper presents the development of a current-voltage curve tracer, capable of performing current, voltage and power measurements, contributing to the creation of equipment to test photovoltaic installations. The methods to obtain the I-V curves are presented and the characteristics of the embedded electronic system, which is based on an electronic load, are defined. As results, the simulations carried out for the variable load control, acquisition circuits and the implemented system are shown. In addition, the operation of the human-machine interface and the comparison with a commercial equipment are shown for reference.
Optimization of wireless sensor networks energy consumption by the clustering method based on the firefly algorithm Ismaila Diakhate; Boudal Niang; Ahmed Dooguy Kora; Roger Marcelain Faye
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1456-1465

Abstract

Wireless sensor networks (WSNs) contain an inordinate number of sensor nodes that are spatially distributed. The network is composed of entities that determine its lifetime. The WSN nodes are equipped with a battery whose autonomy is limited in duration. In this paper, different solutions are introduced to improve the overall energy consumption of the network in order to improve its lifetime. Contrary to many works considering the clustering algorithm as one potential candidate to improve the network's lifetime, this study has investigated the firefly algorithm optimization where an optimal cluster head is selected from a group of nodes. The set-up process of the cluster head is based on a set of conditions. To measure the performance of the proposed approach, the number of dead nodes and data packets received by the base station (BS) or sink node are considered. The results are tested on 100 nodes for 5000 transmission rounds, the amount of data transported is 20 million bits a little more than the other methods. It has been shown that the proposed solution outperformed the traditional low energy adaptive clustering hierarchy (LEACH), threshold sensitive energy efficient sensor network (TEEN), and developed distributed energy-efficient clustering (DEEC) approaches.

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