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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
Design of an orthopedic smart splint using nickel-titanium shape memory alloy Azza Alhialy; Warqaa H. Alkhaled; Tahani G. Al-Sultan; Zaid H. Al-Sawaff; Fatma Kandimerli
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.pp1300-1309

Abstract

People with broken bones suffer from symptoms of muscular atrophy as a result of a lack of movement, so it was necessary to find effective solutions due to the relative pain they cause and the difficulty of movement after healing. In this paper, we proposed a smart splint made of nickel-titanium shape memory alloys (SMA) wires. These alloys have unique properties compared to other materials, the most important of which is maintaining the original shape during manufacturing at a certain temperature. Temperature, pressure, as well as humidity, were analyzed and monitored while the patient wore the splint to reach the best possible results by using a microcontroller. The results showed that there was a significant improvement for the muscles in a short time when using the proposed splint, as the percentage of qualified muscle recovery increased by more than 70% when using the usual splint. The wires used had an effective role in rehabilitating these muscles by performing a permanent local massage. due to the different diameters of these wires, a different response to temperature change was recorded.
Feature based analysis of endometriosis using machine learning Visalaxi Sankaravadivel; Sudalaimuthu Thalavaipillai; Surya Rajeswar; Pon Ramlingam
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.pp1700-1707

Abstract

Machine learning is a cutting-edge technology used for predicting and diagnosing various diseases. Various machine learning algorithm facilitates the prediction. The decision tree belongs to learning algorithm that performs both classification and prediction. The decision tree constructs the tree-like to evaluate the best features. The decision tree performs well in the prediction of various diseases. Endometriosis is a recurrence disease that creates an emotional impact in women. Endometriosis is a lump-like structure that appears at several locations in reproductive organs of women. The diagnosis of endometriosis was predicted through scanning procedures and laparoscopic procedures. The symptoms identified from laparoscopic surgery were used as the features for predicting the severity of endometriosis. The symptoms include mass-like structure, tissue size, variation in tissue colour, and blockages in fallopian tubes. The decision tree analyze the features of endometriosis by using two criteria such as entropy and Gini index. The entropy and Gini index construct the tree by identifying the size of tissue as major influencing attributes. The Gini index outperforms well with training accuracy of 84.08% and test accuracy of 84.85.
Machine learning classification-based portscan attacks detection using decision table Mahdi Nsaif Jasim; Ali Munther Abdul Rahman; Muthanna Jabbar Abdulredhi
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.pp1466-1472

Abstract

Port scanner attackers are typically used to identify weak points or vulnerabilities in an organization's network. When attackers send a detective message to a port number, the response tells them whether the port is open and assists them in identifying potential vulnerabilities. However, machinelearning approaches are the most effective techniques for detecting and identifying port scanner attacks. This attack is regarded as one of the most dangerous internet threats. This research aims to strengthen the detection accuracy and reduce the detection time. Tagged network traffic data sets are used to train the classification machine learning techniques. On the other hand, network traffic analysis is used by unsupervised method to detect attacks. This study modifies the decision table and OneR classification algorithms as a supervised technique for portscan detection. The proposed algorithm uses the CICIDS2017 dataset for both training and testing. The proposed hybrid feature selection methods use and apply multiple training and testing through a sequence of experiments, the proposed method is capable of detecting the portscan attack with 99.8% accuracy, which is competitive in addition to the proposed combination's fast response.
Improve the performance of automatic voltage regulator for power system using self-tuning fuzzy-PID controller Wafaa Saeed Majeed; Amal Ibrahem Nasser; Kassim Rasheed Hameed
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.pp1247-1257

Abstract

The optimal design of the automatic voltage regulators for a synchronous machine are positively reflected on the quality of voltage stability. This paper is concerned with the design of an AVR by adopting three control techniques. The first one was designed according to the traditional proportional integration-derived (PID) controller while the fuzzy logic was adopted in design the second powerful controller, finally the fuzzy PID controller for an automatic voltage regulator (AVR) based on fuzzy logic technology, selftuning fuzzy proportional integration-derived (STFPID) have been designed to tuning the gains of the PID controller (KP, KI and KD). To confirm the efficiency of the proposed control systems, a simulation was carried out, and the results showed that the designed STFPID controller achieves the best performance of the AVR system, and gives the preferable tracking low rise time, lower overshoot, least stetting time, minimal steady state error, and gives the ideal response against PID and fuzzy logic technology.
VM queuing optimal scheduling in cloud using heuristic ant colony optimal based multi-objective genetic approach Madhina Banu Dawood Ali; Enayathullah Syed Mohamed
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.pp1542-1550

Abstract

The usages of cloud based applications are increasing tremendously. The cloud computing task distribution is an unknown polynomial time issue that is challengeable to find the optimal solution. In solve above mentioned issue with large amount user’s job requests, heuristic ant colony optimal based multi-objective genetic (HACOMOG) approach based job allocation and resource optimization is proposed. Utilization basis scheduler recognizes the task order and optimal resources to be scheduled. The primary contribution of the proposed technique is to develop several online techniques to find solution for the virtual machines (VM) Packing problem sharing-aware and for performing a comprehensive number of studies in order to assess their efficiency with online sharing algorithms. The proposed algorithm considers the utilization basis scheduler output and identified the optimzed task allocation technique based on job execution time, MakeSpan and throughput. The experimental outcomes show that the proposed HACOMOG Algorithm reduces 0.70 seconds job execution time (JET), 0.13 MakeSpan and improve 1.98 throughput on given parameters for 100, 200, and 500 tasks with conventional methodologies.
Performance analysis of frequent pattern mining algorithm on different real-life dataset Rakshit khajuria; Anuj Sharma; Sunny Sharma; Ashok Sharma; Jyoti Narayan Baliya; Parveen Singh
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.pp1355-1363

Abstract

The efficient finding of common patterns: a group of items that appear frequently in a dataset is a critical task in data mining, especially in transaction datasets. The goal of this paper is to look into the efficiency of various algorithms for frequent pattern mining in terms of computing time and memory consumption, as well as the problem of how to apply the algorithms to different datasets. In this paper, the algorithms investigated for mining the frequent patterns are; Pre-post, Pre-post+, FIN, H-mine, R-Elim, and estDec+ algorithms. These algorithms have been implemented and tested on four real-life datasets that are: The retail dataset, the Accidents dataset, the Chess dataset, and the Mushrooms dataset. From the results, it has been observed that, for the Retail dataset, estDec+ algorithm is the fastest among all algorithms in terms of run time as well as consumes less memory for its execution. Pre-post+ algorithm performs better than all other algorithms in terms of run time and maximum memory for the Mushrooms dataset. Pre-Post outperforms other algorithms in terms of performance. And for Accident datasets, in terms of execution time and memory consumption, the FIN method outperforms other algorithms.
Data storage architecture for e-government interoperability: Morocco case Hanane Benaddi; Naziha Laaz; Anass Bouhlal; Elyoussfi El Kettani
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.pp1678-1686

Abstract

Nowadays, the amount of data created by the government and public sector organizations is growing at an exponential rate. Data sharing and the interoperability of e-government systems pose technological challenges. The lack of technical interoperability prevents the successful exchange and sharing of information among public organizations. To meet this challenge, enhancing interconnection and communication between different public infrastructures is an essential condition. To optimize the provisioning of storage resources, software defined storage (SDS) solutions add flexibility and adaptability to the storage process by isolating the hardware from the software. Hyper-converged infrastructure (HCI) is an emerging set of SDS solutions that provide compute, network and storage in a single platform. This paper presents a storage HCI-based architecture to store public data from different public entities, enhance collaboration and improve technical interoperability. The relevance of this approach of e-government interoperability is to allow public organization to store their data in an efficient and flexible manner on one hand, and to participate to Morocco’s e-government project on the other hand.
Design of traveling wave slotted waveguide array antenna with high efficiency Najat Shyaa Jasim Mohammed; Manal Hadi Jaber
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.pp1496-1501

Abstract

The slotted waveguide antenna is one of the most important antennas used in high-frequency applications, in radars, navigation systems, remote sensing systems and communications because of its efficiency and high gains. In this paper, the slotted waveguide antenna was designed and simulated with suitable specifications with a working frequency range of 2-2.45 where this antenna was checked by plotting S parameters in the designed frequency band and we got a very good reflection coefficient for the designed antenna (S11) at the operating frequency, draw and illustrate the three-dimensional radiation pattern of the designed antenna that shows the gain and bandwidth at the operating frequency. The performance of a 9-element slotted waveguide array antenna with an operating frequency of up to 12 GHz was also investigated by plotting the S11 parameters and illustrating the designed antenna directivity diagram.We obtained the reflection coefficient of the designed array antenna (S11) below -23 dB at the operating frequency, and the SWG antenna directivity pattern with a maximum value of=13.2 dB and a minimum value of=-23 dB.
A deep learning content-based image retrieval approach using cloud computing Mahmoud S. Sayed; Ahmed A. A. Gad-Elrab; Khaled A. Fathy; Kamal R. Raslan
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.pp1577-1589

Abstract

Due to the rapid growth in multimedia content and its visual complexity, contentbased image retrieval (CBIR) has become a very challenging task. Existing works achieve high precision values at first retrieval levels such as top 10 and top 20 images, but low precision values at subsequent levels such as top 40, 50, and 70, so the goal of this paper is to propose a new CBIR approach that achieves high precision values at all retrieval levels. The proposed method combines features extracted from the pre-trained AlexNet model and discrete cosine transform (DCT). Then principal components analysis (PCA) is performed on AlexNet’s features and feeding these combination to multiclass support vector machine (SVM). The euclidean distance is used to measure the similarity between query and stored images features within the predicted class by SVM. Finally top similar images are ranked and retrieved. All above techniques require huge computational power which may not be available on client machine thus, the processing of these tasks is processed on cloud. Experimental results on the benchmark Corel-1k show that the proposed method achieves high precision value 97% along all retrieval levels top 10, 20 and 70 images and requiring less memory compared to other methods.
Mobile application for care and health control of camelids Roberto Demmis Muñoz Villacorta; Carlos Manuel Oscco Aguero; Laberiano Andrade-Arenas
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.pp1769-1779

Abstract

Due to the events caused by COVID-19, several activities were paralyzed, such as the export of camelids. In the present study, it was observed that many of the camelids that are located in the highest of the Andes, are exposed to diseases that originate from climatic changes or from the infrastructure in which they are inhabiting. For this reason, the veterinary mobile application for camelids was implemented, which will help care as well as sanitary control, this application was developed through the agile scrum methodology, since it adapts to the various modules used, which would be consulta of diseases, recommendations for breeding and contacts with veterinary experts. As a result, the optimal mobile application was obtained for the needs of the people who live in that sector. In addition, it made it easier for the farms, as well as for the people who are in the frozen areas, so that they have better care and control of this species of animals, since the camelids are part of the fauna of the Andes and above all all its fiber and its derivatives are exported, which generates great economic sustenance for that sector.

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