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International Journal of Electrical and Computer Engineering

IJECE
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Published by Institute of Advanced Engineering and Science

ISSN : 20888708 EISSN : 27222578 DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Electrical & Electronics Engineering

International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.

Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)

Articles 6,301 Documents

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Geometric and Grayscale Template Matching for Saudi Arabian Riyal Paper Currency Recognition Suci Aulia; Bagus Budhi L.; Angga Rusdinar; Yuyun Siti R.
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v8i6.pp4230-4238

Detecting the authenticity of paper currencies using automated based Paper Currency Recognition (PCR) with image processing techniques was still a hot topic of discussion, due to the circulation of counterfeit currency that was still overwhelming in some countries. There was a downside along with this advancement in technology in the field of color printing, duplication, and scanning, because it was became one of the supporting factors of the increasing crime rate in production of counterfeit money. Our system has performed a PCR approach based on image processing techniques. In this study, the SAR banknote was the object to be recognized and detected its authenticity with the development of the previous method, which was incorporating the Geometric Template Matching and Grayscale Template Matching. In addition to the pattern recognition process, the classification process on 1 SAR, 2 SAR, 5 SAR, and 10 SAR was also performed. From PCR test up to 100 sample data, for each tested banknote value obtained the average value of the best accuracy level from incorporating GeoMatchingScore and GrayMatchingScore for the classification process was 95.25%. While the average level of system accuracy in recognizing counterfeit money on each banknote obtained a maximum value of 100%.

Counselove: Marital Counseling Android-based Application to Promote Marital Satisfaction Widodo Budiharto; Meliana Meliana; Pingkan C.B. Rumondor
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 1: February 2017
Publisher : Institute of Advanced Engineering and Science

This paper presents the development of Android-based framework for improving marital satisfaction. Classic research in psychology found that stability of marriage is based on the ability to create and maintain a positive interaction ratio five times more than negative interactions. Based on that, we present Counselove, a mobile application intended to record information of daily positive behaviors (joking, showing affection) of couples who use the application. We propose a method where the apps can determine users’ marital satisfaction level and also can help users increasing their marital satisfaction based on the relationship satisfaction questionnaire and the assessment of user’s self reported behaviors to their partners using fuzzy logic. The experimental results shown the application is running well on mobile devices based on Android platform. Lastly, we provide result of in depth interview with two users. Further research and development of the Counselove apps are discussed.

Power consumption prediction in cloud data center using machine learning Deepika T.; Prakash P.
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

The flourishing development of the cloud computing paradigm provides several services in the industrial business world. Power consumption by cloud data centers is one of the crucial issues for service providers in the domain of cloud computing. Pursuant to the rapid technology enhancements in cloud environments and data centers augmentations, power utilization in data centers is expected to grow unabated. A diverse set of numerous connected devices, engaged with the ubiquitous cloud, results in unprecedented power utilization by the data centers, accompanied by increased carbon footprints. Nearly a million physical machines (PM) are running all over the data centers, along with (5 – 6) million virtual machines (VM). In the next five years, the power needs of this domain are expected to spiral up to 5% of global power production. The virtual machine power consumption reduction impacts the diminishing of the PM’s power, however further changing in power consumption of data center year by year, to aid the cloud vendors using prediction methods. The sudden fluctuation in power utilization will cause power outage in the cloud data centers. This paper aims to forecast the VM power consumption with the help of regressive predictive analysis, one of the Machine Learning (ML) techniques. The potency of this approach to make better predictions of future value, using Multi-layer Perceptron (MLP) regressor which provides 91% of accuracy during the prediction process.

QoS Design Consideration for Enterprise and Provider’s Network at Ingress and Egress Router for VoIP protocols Manjur Kolhar; Mosleh M Abualhaj; Faiza Rizwan
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 1: February 2016
Publisher : Institute of Advanced Engineering and Science

Compliance with the Service Level Agreement (SLA) metric is a major challenge in a Multiprotocol Label Switching Virtual Private Network (MPLS VPN) because mandatory models must be maintained on both sides of the MPLS VPN in order to achieve end-to-end service levels. The end-to-end service of an MPLS VPN can be degraded owing to various issues such as distributed denial of service (DDoS), and Random Early Detection (RED) that prevents congestion and differentiates between legitimate and illegitimate user traffic. In this study, we propose a centralized solution that uses a SLA Violation Detector (SLAVD) and intrusion detection to prevent SLA violation.

An Efficient Cloud Scheduling Algorithm for the Conservation of Energy through Broadcasting Kavita Arjun Sultanpure; Abhishek Gupta; L. S. S. Reddy
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science

Method of broadcasting is the well known operation that is used for providing support to different computing protocols in cloud computing. Attaining energy efficiency is one of the prominent challenges, that is quite significant in the scheduling process that is used in cloud computing as, there are fixed limits that have to be met by the system. In this research paper, we are particularly focusing on the cloud server maintenance and scheduling process and to do so, we are using the interactive broadcasting energy efficient computing technique along with the cloud computing server. Additionally, the remote host machines used for cloud services are dissipating more power and with that they are consuming more and more energy. The effect of the power consumption is one of the main factors for determining the cost of the computing resources. With the idea of using the avoidance technology for assigning the data center resources that dynamically depend on the application demands and supports the cloud computing with the optimization of the servers in use.

Capacitive Interferences Modeling and Optimization between HV Power Lines and Aerial Pipelines Rabah Djekidel; Djillali Mahi
International Journal of Electrical and Computer Engineering (IJECE) Vol 4, No 4: August 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (216.042 KB)

Metal pipelines are widely used for the transport of fluids and liquid and gaseous hydrocarbons. When these pipelines are installed near overhead power transmission lines, AC interference can occur between the high voltage power lines and pipelines. This interference can cause the appearance of induced voltages that present a risk of electric shock to the operator safety, direct effects on the pipeline, such as corrosion of the coating and steel. Evaluation of this coupling is necessary to ensure the safety of personnel and equipment connected to the pipeline. In this paper, an optimization method combining PSO with CSM is proposed to simulate the capacitive coupling between the HV power lines and aerial pipelines and analyze the different factors that affect the level of this coupling, the simulation results were compared with a previous study of specialty, the results are found in good agreement.DOI:http://dx.doi.org/10.11591/ijece.v4i4.6289

A Low Cost Wearable Medical Device for Vital Signs Monitoring in Low-Resource Settings Muhammad Niswar; Muhammad Nur; Idar Mappangara
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Medical devices are often expensive, so people in low-income countries cannot afford them. This paper presents the design of a low-cost wearable medical device to measure vital signs of a patient including heart rate, blood oxygen saturation level (SpO2) and respiratory rate. The wearable medical device mainly consists of a microcontroller and two biomedical sensors including airflow thermal sensor to measure respiratory rate and pulse oximeter sensor to measure SpO2 and heart rate. We can monitor the vital signs from a smartphone using a web browser through IEEE802.11 wireless connectivity to the wearable medical device. Furthermore, the wearable medical device requires simple management to operate; hence, it can be easily used. Performance evaluation results show that the designed wearable medical device works as good as a standard SpO2 device and it can measure the respiratory rate properly. The designed wearable medical device is inexpensive and appropriate for low-resource settings. Moreover, as its components are commonly available in the market, it easy to assembly and repair locally.

Model-based Automatic Segmentation of Ascending Aorta from Multimodality Medical Data Noha Seada; Safwat Hamad; Mostafa G. M. Mostafa
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 6: December 2016
Publisher : Institute of Advanced Engineering and Science

Automatic Ascending Aorta Segmentation is one of the important steps towards automatic segmentation of the whole cardiac tree. This paper presents a novel approach for the automatic segmentation of the ascending aorta from two imaging modalities: CTA (Computed Tomography Angiography) and PC-MRI (Phase-Contrast Magnetic Resonance Images). The novel approach is an algorithm that works without the need for setting manual seed points or applying preprocessing steps or setting a region of interest. Instead, the proposed algorithm automatically detects and segments the ascending aorta using an ascending aorta model built from its anatomical features. The proposed segmentation algorithm begins with aorta detection through features model fitting augmented with Hough transform, where the ascending aorta is identified from the descending aorta and any other circular structures based on the proposed model. After detection, the whole ascending aorta is segmented up from the aortic arch down to the ostia points using a novel automatic seeded region growing algorithm. The proposed algorithm is fully automatic, works in real-time and robust as parameters used are the same for all the tested datasets. The detection and segmentation of the ascending aorta succeeded in all test cases acquired from the two imaging modalities; proving the robustness of the proposed ascending aorta model and algorithm for the automatic segmentation process even on data from different modalities and different scanner types. The accuracy of the segmentation has a mean Dice Similarity Coefficient (DSC) of 94.72% for CTA datasets and 97.13% for PC-MRI datasets.

Research methods of V/F control for matrix converter use direct space vector modulation Bogdan Vasilev; Le Van Tung
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

Matrix converter (MC) is direct AC to AC converter built on bidirectional switches with more outstanding advantages compared to the indirect AC - DC-AC converter such as power exchange in two directions, allowing regenerative braking performance amount returned grid. However, the modulation method for Matrix converter has the disadvantage of low voltage transmission ratio, current at the input and output current, the voltage of converter has many high-order harmonic components. The paper presents the technique of directly modulating the space vector which will improve the quality of matrix converter such as input and output currents with sine form, power factor input is nearly 1 and can be adjusted. Also, build V/F control method for matrix converter to control three-phase alternating current induction motors. Research results are tested by Matlab & Simulink software.

A Comparative Analysis on the Evaluation of Classification Algorithms in the Prediction of Diabetes Ratna Patil; Sharavari Tamane
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Data mining techniques are applied in many applications as a standard procedure for analyzing the large volume of available data, extracting useful information and knowledge to support the major decision-making processes. Diabetes mellitus is a continuing, general, deadly syndrome occurring all around the world. It is characterized by hyperglycemia occurring due to abnormalities in insulin secretion which would in turn result in irregular rise of glucose level. In recent years, the impact of Diabetes mellitus has increased to a great extent especially in developing countries like India. This is mainly due to the irregularities in the food habits and life style. Thus, early diagnosis and classification of this deadly disease has become an active area of research in the last decade. Numerous clustering and classifications techniques are available in the literature to visualize temporal data to identify trends for controlling diabetes mellitus. This work presents an experimental study of several algorithms which classifies Diabetes Mellitus data effectively. The existing algorithms are analyzed thoroughly to identify their advantages and limitations. The performance assessment of the existing algorithms is carried out to determine the best approach.

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Tole Sutikno

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Location
Kota yogyakarta,

Daerah istimewa yogyakarta

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Tole Sutikno

Contact Email ijece@iaesjournal.com

Phone -

Journal Mail Official ijece@iaesjournal.com

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Location Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Tole Sutikno

Contact Email
ijece@iaesjournal.com

Phone
-

Journal Mail Official
ijece@iaesjournal.com

Editorial Address
-

Location
Kota yogyakarta,

Daerah istimewa yogyakarta

INDONESIA