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INDONESIA
Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
ISSN : 20893272     EISSN : -     DOI : -
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of electrical engineering. Its scope encompasses the engineering of Telecommunication and Information Technology, Applied Computing & Computer, Instrumentation & Control, Electrical (Power), Electronics, and Informatics.
Arjuna Subject : -
Articles 783 Documents
A Robust Controller Design for Simple Robotic Human Arm Wajdi Sadik Aboud; Hadeel K. Aljobouri; Hayder Sabah Abd Al-Amir
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3895

Abstract

Nowadays, the manipulator of two degrees of freedom (2DOF) has many applications. One is a human arm that may be utilized in robotic rehabilitation. The 2DOF controlled robot manipulator usually acts like human arms. This paper aims to design a robust, stable controller for the upper limb robotic model. A sliding mode control (SMC) approach is proposed to realize stability, tracing accuracy, and robustness for 2DOF robotic manipulator. Based on the general manipulator equation of motion, two SMCs are designed. The first is designed according to the input–output stability constraints. The second is designed according to the adaptive law. Not only the trajectory tracking is guaranteed but also stability is ensured. The stability of the controllers is examined based on Lyapunov stability criteria. The controllers and the robotic arm are formulated analytically. The MATLAB platform is adopted to examine and validate the proposed controller’s performance. The addition of adaptation law in the SMC scheme improves the results for the two designed controllers and shows remarkable trajectory tracking and system stability as well. The improvement rate shows an enhancement of 40.5% and 36.7% for manipulator joints 1 and 2, respectively.
On the Audio-Visual Emotion Recognition using Convolutional Neural Networks and Extreme Learning Machine Arselan Ashraf; Teddy Surya Gunawan; Fatchul Arifin; Mira Kartiwi; Ali Sophian; Mohamed Hadi Habaebi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3879

Abstract

The advances in artificial intelligence and machine learning concerning emotion recognition have been enormous and in previously inconceivable ways. Inspired by the promising evolution in human-computer interaction, this paper is based on developing a multimodal emotion recognition system. This research encompasses two modalities as input, namely speech and video. In the proposed model, the input video samples are subjected to image pre-processing and image frames are obtained. The signal is pre-processed and transformed into the frequency domain for the audio input. The aim is to obtain Mel-spectrogram, which is processed further as images. Convolutional neural networks are used for training and feature extraction for both audio and video with different configurations. The fusion of outputs from two CNNs is done using two extreme learning machines. For classification, the proposed system incorporates a support vector machine. The model is evaluated using three databases, namely eNTERFACE, RML, and SAVEE. For the eNTERFACE dataset, the accuracy obtained without and with augmentation was 87.2% and 94.91%, respectively. The RML dataset yielded an accuracy of 98.5%, and for the SAVEE dataset, the accuracy reached 97.77%. Results achieved from this research are an illustration of the fruitful exploration and effectiveness of the proposed system.
Characteristic Control of SWCNT-FET by Varying Its Chirality and Dimensions Zahraa Eisa; Haider Al-Mumen
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.4046

Abstract

Carbon nanotube (CNT) has witnessed great importance due to its electronic and mechanical properties. The CNTFET was designed to provide high-performance electronic devices. Therefore, the carbon nanotube is representing a potential material for future microelectronic devices. In this paper, COMSOL Multiphysics was used to design and a simulate single-walled carbon nanotube field-effect transistor with a back gate. The insulation layer used in the model was silicon dioxide. The influence of changing its thickness on the drain current was discussed.  In addition, the specification of carbon nanotubes was investigated in terms of changing their diameter and length. Moreover, this paper reveals the current transport of CNTFET for different applied gate voltage and drain voltage. In our work, the CNTFET behaves as n-type FET with transconductance gm≈1.25uA and electron mobility equal to 4.77×10-26cm2v-1s-1. To obtain semiconducting properties for the CNT material, it must consider the chirality when altering the carbon nanotubes diameter. In the proposed device, the diameter values range from 1nm to 4.5nm. It was found that increasing the diameter range resulted in decreasing bandgap from 0.497 eV to 0.110 eV and increasing drain current from 4.075 uA to 31.33 uA.
Hinders of Cloud Computing Usage in Higher Education in Iraq: A Model Development Hayder Salah Hashim; Ali Salah Alasady; Zainab Amin Al-Sulam
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3908

Abstract

Cloud computing (CC) is a trendy technology that is being used in business and daily life. However, limited studies is found on higher education usage. The barriers and obstacles that confront the usage is not clear and in particular in developing countries. The purpose of this study is to examine the barriers and obstacle that confront the usage CC services in Barash University in Iraq. Using the technology organization environment framework and the internal external factor (IE-TOE), the study proposed the conceptual framework. The data was collected from academic, non-academic staff and students using convivence sampling technique. The data was analyzed using Smart PLS. The findings showed that organizational obstacle followed by technological, internal and external factors, and environmental factors are the most severe obstacles that confront the university in using CC services. Decision makers can benefit from the developed model to ease the implementation of CC.
Improvement of Multiple Antenna Sensing Technique for Detecting the White Space in a Spectrum Sharing System Zachaeus Kayode Adeyemo; Samson Iyanda Ojo; Saheed Abiona Abolude; Damilare Oluwole Akande; Hammed O. Lasisi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3802

Abstract

Exact detection of White Space (WS) is one of the actions in a Spectrum Sharing System (SSS) to determine unused spectrum for proper utilization. However, exact detection of WS is being affected by channel impairments, resulting in harmful interference. The Existing Multiple Antenna Spectrum Sensing (EMASS) technique used in addressing this effect is characterized with noise uncertainty leading to low detection rate due to setting of thresholds that is based on noise variance. Hence, this paper proposes an Improved Multiple Antenna Spectrum Sensing (IMASS) for detecting the WS in a SSS. Various copies of licensed user’s signals are received through the unlicensed user antennas over different antenna configuration. The received signals are combined using a modified equal gain combiner and energy of the combined signal is determined using Parseval’s relation for a discrete time signal. The received signal is used to form a square matrix which is converted to covariance matrix. Characteristic equation is obtained from covariance matrix to determine the minimum eigenvalue. The ratio of energy to minimum eigenvalue of the received signal is obtained and used as test statistics. The IMASS technique is evaluated using Probability of Detection (PD) and Total Error Probability (TEP) by comparing with EMASS. The proposed IMASS technique gives better performance with higher PD and lower TEP values than EMASS at all different antenna configurations.
Dynamic Security Assessment For Power System Using Attribute Selection Technique Mohannad Abdulkhaliq Alhubaity; Saraa Ismaeel Khalel; Mohammed Ali Al-Rawe
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3928

Abstract

The evaluation of the dynamic security of the electrical power system after the occurrence of disturbances in the network is one of the most important tools that the control center uses to maintain the system in a safe operating mode, as well as prevent cases of system out of control and cases of complete shutdown. With the annual increase in the size of the electrical system and its distribution over a very wide geographical area, this led to a new challenge to assess dynamic security assessment (DSA), which is dealing with a huge and varied amount of data that requires processing in a very short time. To address these challenges, this study presented a new technique of artificial intelligence, which is the attribute selection technique, to reduce the size of this data and thus improve the accuracy and speed of results. This method relied on the combination of decision tree algorithms and a technique (Attribute selection) in the data obtained from the test system (IEEE-30Bus). The results of this method showed a significant reduction in the number of data used, which amounted to (45.55%) of the total data, Which led to an improvement in the classification accuracy, as the classification accuracy reached (97.27%). This reduction is very important when dealing in the online operating environment, as it saves the time necessary to reach the most accurate evaluation decision and thus issue gives a greater opportunity to take the appropriate decision in the event of disturbances and keep the electrical system in a secure state.
Early Detection of Diabetic Retinopathy Based Artificial Intelligent Techniques Aseel Nusrat Abdullah; Ayca Kurnaz Turkben
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 4: December 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i4.4156

Abstract

The eye is impacted by several disorders, either directly or indirectly. As a result, eye exams are a crucial component of general healthcare. One of the effects of diabetes is diabetic retinopathy (DR), which affects the blood vessels that supply and nourish the retina and causes severe visual loss. One of the prevalent eye conditions and a consequence of diabetes that affects the eyes is diabetic retinopathy. The symptoms of diabetic retinopathy may be absent or minimal. It may eventually result in blindness. Therefore, seeing symptoms early could aid in preventing blindness. This paper aims to research automatic methods for detecting diabetic retinopathy and create a reliable system for doing so. A modified extracted feature for the automatic identification of DR in digital fundus pictures is presented. The properties of exudates, blood vessels, and microaneurysms—three elements of diabetic retinopathy—are reported utilizing a variety of image processing techniques. Back Propagation Neural Networks (BPNN) and Support Vector Machine (SVM) classifiers are used to categorize the phases. SVM, which has accuracy, sensitivity, and specificity of 96.5, 97.2, and 93.3 percent, respectively, is the model that performs the best overall.The eye is impacted by several disorders, either directly or indirectly. As a result, eye exams are a crucial component of general healthcare. One of the effects of diabetes is diabetic retinopathy (DR), which affects the blood vessels that supply and nourish the retina and causes severe visual loss. One of the prevalent eye conditions and a consequence of diabetes that affects the eyes is diabetic retinopathy. The symptoms of diabetic retinopathy may be absent or minimal. It may eventually result in blindness. Therefore, seeing symptoms early could aid in preventing blindness. This paper aims to research automatic methods for detecting diabetic retinopathy and create a reliable system for doing so. A modified extracted feature for the automatic identification of DR in digital fundus pictures is presented. The properties of exudates, blood vessels, and microaneurysms—three elements of diabetic retinopathy—are reported utilizing a variety of image processing techniques. Back Propagation Neural Networks and Support Vector Machine classifiers are used to categorize the phases. SVM, which has accuracy, sensitivity, and specificity of 96.5, 97.2, and 93.3 percent, respectively, is the model that performs the best overall..
Measurement and Analysis with KPIs based on an AMI system Kevin Morgado; Álvaro Zambrano; Javier Rosero Garcia
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 4: December 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i4.3864

Abstract

This paper presents the development of a series of key performance indicators (KPI´s) for the electrical system of the campus of the National University of Colombia based on the deployed smart metering infrastructure (AMI). In order to develop the proposed indicators, it was necessary to use different sources of information to complement the data provided by the AMI system. For each of the proposed indicators is presented the way in which each selected indicator is calculated, and an analysis of the behavior obtained for each KPI. It was possible to observe how, based on the results obtained from the different indicators proposed, periods of inefficiency in terms of electricity consumption were identified. Finally, the conclusions obtained during the development of the project are presented.
Multi-Channel Configuration for improving received signal strength in non-line-of-sight environments of indoor visible light communication localization Hilal A. Fadhil; Feras H. AlAttar; Tariq Adnan Fadil; Haider J. Abd
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 4: December 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i4.3880

Abstract

In modern engineering technologies, energy conservation is a factor of primary concern. A feature of Light-emitting diode (LED) light sources is the ability to transmit information in addition to illumination at no additional cost. VLC (Visible Light Communication) is gaining an upper hand over the traditional RF data communication model, as it utilizes a technology by which light can be used to transmit data. It is commonly seen that dealing with non-line of sight (NLOS) is a major challenge for VLC systems as the light intensity is reflected in a variety of directions. To overcome this drawback, a new technique based on multichannel configuration is utilized to enhance the overall system performance. An indoor VLC model is designed and simulated on the basis of the eye-diagram, bit error rate, and received power of the proposed model. We also investigated the model under the influence of ambient light noise. The corresponding results are compared with the conventional NLOS system and an inference made shows the significant improvement for the next-generation optical communication system.
Novel Robust Control Using a Fractional Adaptive PID Regulator for an unstable system Yassine Bensafia; Abdelhakim Idir; Khatir Khettab; Muhammad Saeed Akhtar; Sarwat Zahra
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 4: December 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i4.4034

Abstract

Recent advances in fractional order calculus led to the improvement of control theory and resulted in potential use of fractional adaptive PID controller in advanced academic and industrial applications as compared to the conventional adaptive PID controller. Basically, a fractional order  adaptive PID  controller  is  an  improved version of classical  integer  order  adaptive PID  controller that outperformed  its classical  counterpart. In case of a closed loop system, a minute change would result in instability of the overall system. An efficient PID controller can be used to control the response of such system.  Among various parameters of an instable system, speed of the system is an important parameter to be controlled efficiently. The current research work presents the speed controlling mechanism for an uncertain instable system by using fractional order adaptive PID controller.To validate the arguments, effectiveness and robustness of the proposed fractional order adaptive PID controller have been studied in comparison to the classical adaptive PID controller using The Criterion of quadratic error. Simulation findings and comparisons demonstrated that the proposed controller has superior control performance and outstanding robustness in terms of percentage overshoot, settling time, rising time, and disturbance rejection.