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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 27, No 1: July 2022" : 64 Documents clear
Masked face with facial expression recognition based on deep learning Nawal Younis Abdullah; Ahmed Mamoon Fadhil Alkababji
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp149-155

Abstract

Wearing masks contributed to slowing the spread of the coronavirus disease (COVID-19) as the World Health Organization (WHO) recommended wearing face masks especially with the spreading of virus variants like omicron. Although people accept the idea of wearing these masks, it is still unknown the effect of covering parts of the face on social interaction among people in general and children in particular. Moreover, Social isolation affects emotional moods, which causes stress, sadness, and depression. In the current study, we have been exploring the emotional inferences on faces with and without a mask. The system can pick up the universal emotions: fear, disgust, anger, surprise, contempt, sadness, and happiness. The researchers in deep learning are concerned with global pandemic COVID-19 to enhance public health service. The proposed model is developed with a machine learning algorithm through the Haar feature-based cascade classifiers. The built model can detect people's emotions with mask and without a mask with high accuracy.
Neuromorphic solutions: digital implementation of bio-inspired spiking neural network for electrocardiogram classification Dze Rynn Chen; Yan Chiew Wong
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp528-537

Abstract

Conventional techniques of off-chip processing for wearable devices cause high hardware resource usage which leads to heat generation and increased power consumption. Hence, edge computing methods such as neuromorphic computing are considered the most promising modern technology to replace conventional processing. It is beneficial to employ neuromorphic processing in electrocardiogram (ECG) classification, enabling engineers to overcome the constraints of heat generation caused by hardware utilization. Thus, this work aims to investigate common building blocks in a spiking neural network (SNN), analyze the spike-based plasticity mechanism and implement ECG classification on a neuromorphic circuit. The MIT-BIH Arrhythmia database (MITDB) is preprocessed in MATLAB, then used to train and test an SNN designed for field programmable gate arrays (FPGA), employing spike-based plasticity and Izhikevich neurons. The behaviour of spike timing dependent plasticity (STDP) in a neuromorphic circuit is also visualized in this work. The state-of the-art performance of this work lies in providing a generic mechanism to adapt ECG classification into a neuromorphic solution, a non-Von Neumann architecture. The proposed digital design utilizes 1.058% of hardware resources on a Zedboard. Application-wise, this work provides a foundation for development of neuromorphic computing in wearable medical devices that perform continuous monitoring of ECG.
Cost-effective resource and task scheduling in fog nodes Ali Hussein Shamman; Hussein Ali Alasadi; Hussein Ali Ameen; Zaid Ibrahim Rasol; Hassan Muwafaq Gheni
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp466-477

Abstract

Cloud services are the cutting edge technology, however the growing demand for the internet of things has certain limitations which are high latency expectation and high cost of cloud resources, and this is caused by long-distance between application and cloud. Fog computing is a distributed extension of the cloud, which provide storage and computation at the network level. It consists of an internet of things (IoT) application, a fog control node, and a fog access node. This research works towards minimizing the cloud cost in scheduling. For this purpose, a cost-effective task and user scheduling algorithm are performed. The first task scheduling model is composed based on composers' roles after that task scheduling algorithm is performed to handle the various task at the fog access node in an optimized manner. Finally, the reallocation mechanism reduces the time and service delay. For the analysis purpose extensive simulation is carried out and performance statistics were compared with other existing algorithms. It was observed that the proposed algorithm provides highly cost-optimized user and task scheduling with better performance statistics and reduces the delay in the task by providing optimization in the concurrent task at the fog node.
Enhancement of single-mode optical fiber quality factor-bit error rate by using uniform fiber Bragg grating Alaa Husein Ali; Raed Khalid Ibrahim
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp336-346

Abstract

The properties of optical fibers transmission systems based on Bragg gratings and uniform fibers, which are discussed in detail in this paper. Two - fiber optic communication channels Bragg gratings are used, along with Optisystem software for simulations. It is widely used in a variety of optical communication systems, such as, dispersion compensators, band filters, amplifiers and in - fiber sensors or fiber grating lasers, because of its versatility. In this design, the distance has been changed from 10 km up to 100 km, as well as the input power from 2 dBm to 16 dBm, and the calculation of both the bit error rate (BER) and quality (Q) f actor at the receiver could be studied by modelling the model of a communication system and employing the syste m's most suited settings, such as fiber cable length (km) and input power (dBm).
Prototype for wireless remote control of underwater robotic development Huthaifa Ahmad Al-Issa; Wesam Fouad Swedan; Duha Ahmad Al-Shyyab; Ruwa Ma’mon Altobosh; Ayeh Okleh Altarabsheh
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp238-245

Abstract

Human beings have been substituted with robots in the performance of tedious and risky activities that human beings do not like or are incapable of performing due to the size of restrictions or the existence of the world, such as outer space or the ocean's depths. It has evolved into a low-cost, dependable, and inexpensive medium that can be used by both scientific societies and different industries for various surveys, mapping, and other underwater activities. In this study of underwater robotics power, we create an underwater robot that can fly in three dimensions: up-down, left-right, and front-back. The robot's motion is monitored by three motors, which also enable it to perform other tasks. Due to the fact that one-third of the world's population lives within 100 kilometers of the ocean, and that we are so focused on land and atmospheric problems that we ignore the seas, it is important to observe marine life and calculate the temperature and strength of light underwater. This application allows determining the appropriate temperature and intensity for living sea creatures to preserve their lives.
Hybrid multi criteria decision methods for optimal cloud selection in mobile cloud computing Sindhu Kurup; Hassan Sadashiva Guruprasad
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp404-412

Abstract

Cloud computing provides the users with flexibility of using computational systems on demand at nominal cost. Execution of resource intensive task on mobile devices is still a big challenge due to resource constraints of mobile devices. Utilizing the servi ces of resource rich cloud servers for offloading the task from mobile device can overcome the resource constraint issues of mobile devices. When offloading the task, there is a need to choose an optimal cloud server from a pool of available cloud servers offering similar services. The proposed work uses three hybrid multicriteria decision methods for choosing the optimal cloud server and comparative analysis of the three methods are presented. Real time cloud servers located at four different regions are c onsidered with six quality of service ( QoS) attributes. The results indicate that all the three methods are viable solutions in selecting the optimal cloud server with multi - objective optimization on the basis of ratio anal ysis (MOORA) providing a faster response compared to other two methods. Sensitivity analysis performed proves the correctness and effectiveness of the proposed methodology.
Classification of specialities in textual medical reports based on natural language processing and feature selection Hasanen Abdul-Jawad Hussain Almuhana; Hawraa Hassan Abbas
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp163-170

Abstract

Nowadays, a great deal of detailed information about patients, including disease status, medication history, and side effects, is collected in an electronic format; called an electronic medical record (EMR), and the data serves as a valuable resource for further analysis, diagnosis, and treatment. The huge q uantity of detailed patient information in these medical texts produces a huge challenge in terms of processing this data efficiently, however. Machine learning (ML) algorithms, artificial intelligence techniques, and natural language processing tools can have the potential effect of simplifying unstructured data, which could positively affect medical report analysis. Natural language processing (NLP) has recently made huge advances on a variety of tasks. In this paper, an automatic system was thus produced to classify specialist consultant interactions based on patients’ medical reports. NLP was used as a pre-processing step on a dataset formed of unstructured medical reports. Feature extraction and selection methods were used to convert the textual reports into sets of features and to extract the most effective features to increase classification accuracy and reduce execution time. Various classification methods were then applied (ML perceptron, logistic regression random forest (RF), and linear support vec tor classifier (LSVC)). The highest accuracy (99.39%) was achieved in ML-perceptron classification techniques .
Light fidelity performance via hybrid free space optic/fiber optic communication under atmospheric disturbance Satea Hikmat Alnajjar; Ahmed Majid Hameed
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp355-365

Abstract

Light f idelity (Li-Fi) considers technology in optical wireless communication (OWC) that utilize visible light for transmission in free space, visible light communication (VLC) technology was chosen to overcome the interference issues of radio frequency (RF) communication and it also has higher bandwidth and is more secure. This paper aims to analyse the influence of atmospheric attenuation on the end-users of VLC system that consisted of five light-emitting diodes (LEDs) distributed in a room, which in t urn linked with the hybrid optical system includes a multi-channel of free space optic (FSO) connected with a fiber-optic channel (FOC). The hybrid system to the end-user was estimated in terms of bit error rate, quality factor, and signal power under dust-rain weather conditions. In the dust scenario, the suggested system achieved acceptable bit-error-rate (BER) to a distance of 1, 100 m. In rainy conditions, the performance accomplished acceptable BER to a distance of 3000 m. The VLC system's end-user also was evaluated under the effectiveness of the variation of irradiance and incident angles. Despite the harsh environmental conditions imposed on the communication network, VLC has proven its ability to maintain acceptable performance in end-user.
Analysis study of quality factor and bit error rate at wavelength change Fadhela Thaeer Mahmood; Alaa H. Ali; Alaa H. Ali Haeder
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp301-308

Abstract

Gigabit - per - second data speeds can be achieved via free space optics (FSO) lines, which needless system complexity. On the other hand, the link's availability across a wide range of atmospheric circumstances is a major worry. As a result of the increased signal attenuation caused by the linkages being weather - dependent, their efficiency decreases. Up to 70 dB/km of attenuation can be caused by bad weather on a 500 - meter free space optics link. In this work, transmission windows of 1310 nm, 850 nm , and 1550 nm are analyzed and compared using the free space optics link. by using the Simulation program o pti system such as the q uality factor, the minimal bit error rate (BER), and the e ye diagram is taken into account. Analyzer findings are compared to establish the optimal wavelength for a transmitter under poor weather conditions.
Prediction of student satisfaction on mobile-learning by using fast learning network Laman Radi Sultan; Salwa Khalid Abdulateef; Bushra Abdullah Shtyat
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp488-495

Abstract

The rapid advancement of mobile technologies over the past decade has had a significant impact on the appearance of M-learning applications. The research proposes the fast learning network model to investigate and identify the factors that affect student satisfaction in M-learning for the University of Tikrit students. The research model is conducted utilizing a questionnaire of 300 participating students based on variables. This research showed that the proposed model's perfor mance was superior to artificial neural network, k-nearest neighbors, and multilayer perceptron algorithms. The accuracy and specificity of predicting the student satisfaction coefficients in M-learning were 91.6% and 92.85%, respectively. The proposed findings demonstrate that diversity in the evaluation, teacher attitude and response, and quality of technology are key operators of student satisfaction.

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