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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 9,174 Documents
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IoT-based communal garbage monitoring system for smart cities Nur Latif Azyze Mohd Shaari Azyze; Ida Syafiza Md Isa; Thomas See Chin
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.pp37-43

Abstract

In Malaysia, approximately 38,000 metric tons of garbage are generated due to human daily activities. This is due to the growing population in the urban area, hence increasing the tendency of overflowing garbage due to the insufficient space in the garbage container. In addition, the tight schedule of the garbage collection allows the spreading of the toxic odor as the garbage start to rotten up, hence leading to air pollution. Therefore, a systematic waste management system is important to provide a healthy and clean environment to the community. In this work, a communal garbage monitoring system has been developed to notify the administrator of the status of the container. Besides monitoring the level of garbage, the system is also designed to monitor the temperature, humidity, and air quality of the garbage container. These monitored data will be uploaded at the cloud for real-time monitoring. Compared to the other work, a real test-bed implementation has been conducted considering different types of waste including food waste, paper, bottles and metal; to determine the accuracy of the developed system. The results show that the system has high reliability and high accuracy with 96% for food waste and 98% for other types of waste.
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.
Experimental and numerical studies for parameters identification of direct current motor Mohamad Nazir Abdullah; Mohd Khairunaz Mat Desa; Elmi Abu Bakar; Mohammad Nishat Akhtar
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp592-600

Abstract

Direct current (DC) motors are widely used in many applications especially those require a speed control, direction and closed-loop control system. In electric vehicle drive system, DC motor is commonly used for the propulsion of low power (<250 W) electric bicycle (e-bike) because it can operate directly from rechargeable batteries with a smart controller. In driving an e-bike in a closed loop control system, it is important to identify and estimate the dynamic of electrical and mechanical parameters. In this paper, the parameters such as armature resistance, armature inductance, back emf constant, torque constant, moment of inertia and viscous friction coefficient are ideally identified using dynamic responses experiments and tests focusing on no load motor and transient input tests. The motor is then modeled in MATLAB/Simulink using the identified motor parameters and its open loop speed and current responses are studied.
Potential development of an optical sensor to determine the quality of heated palm cooking oil Wan Shafiq Salleh; Nurulain Shaipuzaman; Muhd Sharfi Najib; Mohd Rashidi Salim; Hadi Manap
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp659-666

Abstract

Palm oil is an edible vegetable oil yielded from the mesocarp of the palm oil’s fruit. It is commonly used as cooking oil as compared to other cooking oil such as olive or coconut oil because it is inexpensive and has high oxidative stability when used for frying. However, after frequent frying, the oil undergoes some physical and chemical reactions which affect the quality. This leads to the formation of compound that is dangerous to human body which is called free fatty acid (FFA). Therefore, a measurement device needs to be developed to determine the quality of heated cooking oil. In this paper, a spectroscopy study using an open-path method which focus on the palm cooking oil is proposed to examine the reaction of palm oil upon prolonged heating process. Open-path method is a technique where the incident beam will travel through the sample (palm oil) before it is detected by a spectrometer. The result shows that the FFA samples have the optimum absorbance peak at the UV wavelength 339.15 nm and each prolonged heated oil show different absorbance value. Hence, there is a potential to develop an optical sensor to determine the quality of the heated cooking oil.
The impacts of (Ba,Sr)3BP3O12:Eu2+ on the luminous flux of phosphor-converted-white light emitting diode packages Van Liem Bui; Dieu An Nguyen Thi
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp685-691

Abstract

The use of (Ba,Sr)3BP3O12:Eu2+ in the remote phosphor structure has been proposed and analysed to offer significant improvement to the lighting performance of the phosphor-converted white light emitting diode (LED). The phosphor emits green and blue spectra centred at 520 nm and 465 nm, respectively. Thus, the phosphor can compensate the blue and green light energy components in the white-light spectral band, helping to enhance the luminous efficiency and colour uniformity of the dual-layer remote phosphor package. The increase in (Ba,Sr)3BP3O12:Eu2+ however is not advantageous to the colour rendering index because of the lower red emission. The backscattered and back-reflected lights are degraded when the (Ba,Sr)3BP3O12:Eu2+ phosphor layer appears in the structure. The stable chromaticity and luminous flux at good values are observed when 10% weight percentage of (Ba,Sr)3BP3O12:Eu2+ is applied.
Gender and race classification using geodesic distance measurement Zahraa Shahad Marzoog; Ashraf Dhannon Hasan; Hawraa Hassan Abbas
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp820-831

Abstract

Gender and ethnicity classifications are a long-standing challenge in the face recognition’s field. They are key-demographic traits of individuals and applied in real-world applications such as biometric and demographic research, human-computer interaction (HCI), law enforcement and online advertisements. Thus, many methods have been proposed to address gender or/and race classifications and achieved various accuracies. This research improves race and gender classification by employing a geodesic path algorithm to extract discriminative features of both gender and ethnicity. PCA is also utilized for dimensionality reduction of Gender-feature and race-feature matrices. KNN and SVM are used to classify the extracted feature. This research was tested on the face recognition technology (FERET) dataset, with classification results demonstrating high-level performance (100%) in distinguishing gender and ethnicity.
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).
Effects of titanium dioxide quantum dots on the color deviation and luminous flux of white light-emitting diodes Thanh Binh Ly; Phung Ton That; Phan Xuan Le
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp611-617

Abstract

The application of quantum dots has been considered as a promising approach to the advancement of phosphor-converted light-emitting diodes (pc-LEDs) since they perform an excellent extinction coefficient. Yet, it is challenging to manage their influences on the optical properties of LEDs due to their different nanometers in size. Hence, the object of this research is to analyze the influences of quantum dot (QDs) to figure out the solution to control the enhancement of LED lighting performances. Particularly, the study worked on investigating the scattering and absorption features of titanium dioxide (TiO2) QDs. It demonstrated that the radiant efficiency and luminous stability of the TiO2 QDs-converted LEDs (QC-LEDs) was inferior due to the strong light absorption and reabsorption occurring inside the LED packages. Additionally, it also presented low uniformity of color distribution because the scattering ability of QDs is weak. Therefore, reducing the concentration of QDs when adding to the LED structure seems to be possible to enhance the luminous output of QC-LEDs. We propose 0.05% wt. TiO2 for white LED to reduce the illumination losing caused by re-absorbent and total internal backscattering, resulting in approximate 31% lumen improvement and high color rendering index (CRI) measured at about 85, at a high color temperature of 7500 K.

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