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INDONESIA
Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Published by IAES Indonesia Section and Partners
ISSN : 20893272     EISSN : -     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
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
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Closed-Loop Tuning of Cascade Controller for Load Frequency Control of Multi-Area Distributed Generation Resources Optimized by ASOS Algorithm Sunita Pahadasingh; Chitralekha Jena; Chinmoy Kumar Panigrahi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 2: June 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i2.3524

Abstract

This paper provides closed loop tuning of cascaded-tilted integral derivative controller (CC-TID) for load frequency control (LFC) of micro grid system. A micro grid system is the arrangement of distributed generation resources such as wind turbine generator (WTG), fuel cell (FC), aqua electrolyser (AE), diesel engine generator (DEG) and battery energy storage system (BESS). Different controllers such as proportional integral derivative (PID), two degree of freedom (2DOFPID), three degree of freedom (3DOFPID) and tilted integral derivative (TID) are used not only to sustain the disparity between real power generation and load demand but also accomplish zero steady state error to enrich the frequency and tie power regulations. The anticipated controller encompasses both the value of cascade (CC) and fractional order (FO) controls for better elimination of system instabilities. In the proposed CC-3DOFPID-TID controller, TID controller is castoff as a slave controller and 3DOFPID controller aided the role of dominant controller. The controlled parameters are optimized by adaptive symbiotic organism search (ASOS) algorithm for keen results of difficulties in LFC. To persist in ecosystem, symbiotic relations are predictable by organism through imitators. Further the dynamic behaviours of controller optimized by ASOS, teaching learning based optimization (TLBO) and differential evolution particle swarm optimization (DEPSO) are compared by extensive simulations in MATLAB/SIMULINK. Moreover the supremacy of proposed controller is performed through system dynamics comparison among PID, 2DOFPID, 3DOF-PID and CC-3DOFPID-TID controllers. Finally sensitivity of proposed controller has proven though random load perturbation.
Multimodal Based Audio-Visual Speech Recognition for Hard-of-Hearing: State of the Art Techniques and Challenges Shabina Bhaskar; Thasleema Thazhath Madathil
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 2: June 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i2.3683

Abstract

Multimodal Integration (MI) is the study of merging the knowledge acquired by the nervous system using sensory modalities such as speech, vision, touch, and gesture. The applications of MI expand over the areas of Audio-Visual Speech Recognition (AVSR), Sign Language Recognition (SLR), Emotion Recognition (ER), Bio Metrics Applications (BMA), Affect Recognition (AR), Multimedia Retrieval (MR), etc. The fusion of modalities such as hand gestures- facial, lip- hand position, etc., are mainly used sensory modalities for the development of hearing-impaired multimodal systems. This paper encapsulates an overview of multimodal systems available within literature towards hearing impaired studies. This paper also discusses some of the studies related to hearing-impaired acoustic analysis. It is observed that very less algorithms have been developed for hearing impaired AVSR as compared to normal hearing. Thus, the study of audio-visual based speech recognition systems for the hearing impaired is highly demanded for the people who are trying to communicate with natively speaking languages.  This paper also highlights the state-of-the-art techniques in AVSR and the challenges faced by the researchers for the development of AVSR systems.
The Future of Renewable Energy in Iraq: Potential and Challenges Omar Sharaf Al-Deen Al-Yozbaky; Saraa Ismaeel Khalel
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 2: June 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i2.3756

Abstract

Renewable energy (RE) is currently viewed as a planned and effective option to achieve development sustainability, as it provides an appropriate answer to climate change and also meets the power requirements. With regards to the current scenario in Iraq, a grave deficit with regards to electric power has been looming in the country and this serious shortage in equipped power started decades ago. Various prospects exist regarding the adoption of renewable energy in order to deal with the current issue pertaining to power shortage. This present study is a crucial examination of the existing and future electrical power needs in Iraq and the ongoing planning and challenges that are deliberated, for a better understanding of the prospects of utilizing Renewable energy sources for investment as well as to be able to provide energy to all those who need it in Iraq. Hopefully, this study can support researchers in earning an in-depth understanding of previous research efforts on this subject, and in exploring directions for future research.
A Study for Remote Monitoring of Water Points in Mauritania Based on IoT (LoRa) Technology Hassine Ali Abeidi; Bedine Kerim; Mohamedade Farouk Nanne
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 2: June 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i2.3733

Abstract

Wetlands in Mauritania contain the most important water sources necessary for the survival of rural communities in the country. In these areas, the main rural activities such as animal husbandry, agriculture, and fishing take place. Lack of water or flooding must be monitored to plan solutions in advance. After a comparative study of IoT wireless technologies, we proposed that LoRa technology is the most suitable for our field of application. However, in certain areas where access to the cellular network is difficult, we propose the addition of satellite communication in the LoRamonitoring system to achieve information collected at any point in the world via the cloud and the Internet. We carried out a practical case for the areas covered by the UMTS (3G) cellular network using devices integrating LoRaWAN to evaluate the performance of this technology. The results show the success of the communication over a distance of 14 km.
The Influence of the Mixed Electric Line Poles on the Distribution of Magnetic Field Ghanim Thiab Hasan; Ali Hlal Mutlaq; Kamil Jadu Ali
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 2: June 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i2.3572

Abstract

With the wide spread of the transmission line
Tilt Integral Derivative Controller Optimized by Battle Royale Optimization for Wind Generator Connected to Grid Mohamed Samir; Gagan Singh; Nafees Ahamad
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 2: June 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i2.3658

Abstract

Globally the countries are focusing on reducing the carbon footprint leading to a greater effort for electrical energy generation by renewable energy sources, particularly wind. The wind turbines are invariably using doubly fed asynchronous generator. In this paper a controller has been designed for a doubly fed induction motor. The proposed Tilt Integral Derivate controller for was compared with commonly used PI, PID controllers. Several optimization algorithms were used for tuning of controllers and the best one was selected for each type of controller. The controller has been optimized using battlefield optimization. It had been compared with proportional integral controller, fractional order proportional integral derivative controller. Other controllers were optimized using meta heuristic algorithms. The controller enhanced the system response in terms of settling time, rise time and other parameters. The Tilt controller gave the overall superior performance in terms of parameters like rise time, settling time, settling minimum, peak, and peak time. The results were obtained using MATLAB. This paper discusses operation of doubly fed induction motor operation and optimization methods.
Single Input Single Head CNN-GRU-LSTM Architecture for Recognition of Human Activities Updesh Verma; Pratibha Tyagi; Manpreet Kaur
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 2: June 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i2.3475

Abstract

Due to its applications for the betterment of human life, human activity recognition has attracted more researchers in the recent past. Anticipation of intension behind the motion and behaviour recognition are intensive applications for research inside human activity recognition. Gyroscope, accelerometer, and magnetometer sensors are heavily used to obtain the data in time series for every timestep. The selection of temporal features is required for the successful recognition of human motion primitives. Different data pre-processing and feature extraction techniques were used in most past approaches with the constraint of sufficient domain knowledge. These approaches are heavily dependent on the quality of handcrafted features and are also time-consuming and not generalized. In this paper, a single head deep neural network-based approach with the combination of a convolutional neural network, Gated recurrent unit, and Long Short Term memory is proposed. The raw data from wearable sensors are used with minimum pre-processing steps and without the involvement of any feature extraction method. 93.48 % and 98.51% accuracy are obtained on UCI-HAR and WISDM datasets. This single-head deep neural network-based model shows higher classification performance over other architectures under deep neural networks.
Study and Analysis of Power System Stability Based on FACT Controller System Yousif Al Mashhadany; Ahmed K. Abbas; Sameer Algburi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 2: June 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i2.3630

Abstract

Energy framework soundness is identified with standards rotational movement and the swing condition administering electromechanical unique conduct. In the exceptional instance of two limited machines, the basis of equivalent territory security can be utilized to ascertain the basic clearing point in the force framework, It is important to look after synchronization, in any case the degree of administration for customers won't be accomplished. This term steadiness signifies "looking after synchronization." This paper is an audit of three kinds of consistent state. The main sort of adjustment, consistent state steadiness clarifies the most extreme consistent state quality and force point chart. The transient solidness clarifies the wavering condition and the idleness steady while dynamic soundness manages the transient security time frame. There are a few different ways to improve framework soundness a portion of the techniques are clarified. Versatile AC Transmission Frameworks (FACTS) Flexible AC Transmission System (FACTS) regulators have been utilized frequently to comprehend the different issues of a non-variable force structure. Versatile AC Transmission Frames or FACTS are devices that permit versatile and dynamic control of intensity outlines. Improving casing respectability has been explored with FACTS regulators. This examination focuses to the upsides of utilizing FACTS apparatuses with the explanation behind improving electric force tire activity. There has been discussion of an execution check for different FACTS regulators.
A Multimodal Deep Learning Approach for Identification of ‎Severity of Reflective Depression ‎ Hanen Karamti; Eatedal Alabdulkreem; Hedia Zardi; Abeer M Mahmoud
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 2: June 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i2.3457

Abstract

Social media consumes a greate time of our dialy times that generate a significant amount of information through expressing feeling and activities, sharing admiral contents, viewing, and more. This information mostly contains valuable discoveries. Despite many attempts to mining such produced data, it is still unexploited in certain issues and attracts many research areas. In this paper, we use the data extracted from social media from female’s pages to detect possibility of depression. A new deep learning model based on the psycholinguistic vocabulary to create the embedding words is developed. First, we extract the features from the data before and after the preprocessing phase. Second, the Convolutional Neural Network (CNN) is used to label the data for extracting the remaining features. Based on the previouse two phases; the developed model succeeded to predict the depression possibilty. Adetailed comparative analysis is also presented for the evaluation of the proposed system. The proposed indicator model proved promising results in predicting depression.
PV Systems based High Gain Converter using CI and SCC Techniques S. Sankarananth; P. Sivaraman
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 2: June 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i2.3677

Abstract

In this paper, new techniques of a CI and SCC-based step-up higher-level voltage DC_DC converter were implemented. The CI and SC charging and discharging the energy respectively to attain higher gain. The stress in switching volt level and inductance leakage is detached using the clamp circuitry. The reversed retrieval problem in the diode was eradicated with the help of Coupled Inductor (CI). The new topology to get more gain of the voltage and improved efficiency. The steady state analysis with the operation procedures of novel DC_DC converter is discussed here. In proposed model, input voltage is 24V & Vo is 410V, Pmax is 150W was given to get ηmaximum of 96.4%.

Page 49 of 79 | Total Record : 783

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