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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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Enhancement of the lighting quality for white light-emitting diodes with CaSc2O4:Ce3+ phosphor Phuc Dang Huu; Phung Ton That; Phan Xuan Le; Nguyen Le Thai
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1282-1289

Abstract

For the task of realizing greater progress for the light output in white light-emitting diodes (WLEDs), this study focuses on the luminescence temperature subordination feature of CaSc2O4:Ce3+ phosphor (abbreviated to CaS for this study). Some other aspects of the phosphor were also included in this piece of paper: Huang-Rhys coupling factor, Stokes shift, triggering power, abatement temperature and especially, abatement behavior in CaSc2O4:Ce3+. Creating the bluish-green LEDs by the combination of blue InGaN chip and CaSc2O4:Ce3+ is the primary purpose. CaSc2O4:Ce3+ appears to be a decent green phosphor that can be used in WLEDs made of blue InGaN chip. Production tasks may be based on our investigation for the task of making desirable WLED devices that meet the production demands.
Fuzzy logic system for drug storage based on the internet of things: a survey Shivan Mohammed Othman; Maiwan Bahjat Abdulrazzaq
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1382-1392

Abstract

The rapid development of internet of things (IoT) technology over the course of recent history has made it possible to connect a large number of smart things and sensors, as well as to establish an environment in which data can be seamlessly exchanged between them. This has led to an increase in the demand for data analysis and storage platforms such as cloud computing and fog computing. One of the application areas for the internet of things that has garnered a lot of interest from the business world, academic institutions, and the government is healthcare. The IoT and fuzzy logic are being used in the medical business to improve patient safety, the overall quality of care, and the overall efficiency of medical operations. The most important healthcare studies that are pertinent to pharmacies have been used as the basis for this research. The purpose of this research is to investigate recent advancements in medical modules, remotes, and detector patterns, as well as current innovations in IoT and fuzzy logic-based health care, and current policies from around the world, with the intention of determining how well they support the long-term growth of IoT and fuzzy logic in healthcare.
Algebraic fields and rings as a digital signal processing tool Dinara Kutlimuratovna Matrassulova; Yelizaveta Sergeevna Vitulyova; Sergey Vladimirovich Konshin; Ibragim Esenovich Suleimenov
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp206-216

Abstract

It is shown that algebraic fields and rings can become a very promising tool for digital signal processing. This is mainly due to the fact that any digital signals change in a finite range of amplitudes and, therefore, there are only a finite set of levels that can correspond to the amplitudes of a signal reduced to a discrete form. This allows you to establish a one-to-one correspondence between the set of levels and such algebraic structures as fields, rings, etc. This means that a function that takes values in any of the algebraic structures containing a finite set of elements can serve as a model of a signal reduced to a discrete form. A special case of such a signal model are functions that take values in Galois fields. It is shown that, along with Galois fields, in certain cases, algebraic rings contain zero divisors can be used to construct signal models. This representation is convenient because in this case it becomes possible to independently operate with the digits of the number that enumerates the signal levels. A simple and intuitive method for constructing rings is proposed, based on an analogy with the method of algebraic extensions.
Recognition of crowd abnormal activities using fusion of handcrafted and deep features Manasi Pathade; Madhuri Khambete
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp1076-1087

Abstract

Constant vigilance is extremely important at crowded public places where some unusual activities such as sudden dispersion or continuous gathering of people may lead to chaotic and disastrous situations. Automatic recognition of such collective activities of people is indeed an important task to ensure people safety. In this view, we propose a novel approach for automatic recognition of crowd merging and sudden dispersion events. The proposed method detects dispersion and merging using fusion of features extracted by deep networks with a novel set of optical flow based and density based handcrafted features. These proposed features are not affected by occlusion and illumination. These features complement the features extracted by deep network and their fusion improves the performance of event recognition by significant amount. The method is tested profoundly on benchmark public datasets as well as private datasets. Abnormal activity recognition data often suffers from high class imbalance. However, the proposed method could successfully recognize sudden dispersion and merging activities on such very small datasets having class imbalance. This proves the effectiveness and robustness of the proposed features. The proposed method also shows better performance than other state of the art methods based on deep networks.
Adaptive weight grey wolf algorithm application on path planning in unknown environments Mustafa Salah Abed; Omar Farouq Lutfy; Qusay Fadhel Al-Doori
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1375-1387

Abstract

Autonomous mobile robots developed using metaheuristic algorithms are increasingly becoming a hot topic in control and computer sciences. Specifically, finding the shortest route to the goal and avoiding hurdles are current subjects of autonomous mobile robots. The Modified Grey Wolf Optimization (MGWO) is demonstrated in this work using two approaches: first, the Adaptive Adjustment Approach of the Control Parameters, and second, the Adaptive Variable Weights method. Those two methods are utilized for updating the wolf position, accelerate convergence, and cut down on time. The proposed online optimization approach is used in three different environments including an environment with unknown static obstacles, dynamic obstacles, and an environment with a dynamic target. The online optimization method is performed using two phases which are the sensors reading phase and the path calculation phase. The proposed approach can solve a local minima problem in the static obstacles. A comparison study result between the proposed method and two other algorithms revealed that the proposed algorithm performed better in avoiding obstacles, which include the situation with the local minima. Finally, when put to comparison with Hybrid Fuzzy-Wind Driven Optimization and Adaptive Particle Swarm Optimization the average improvement rates in route length are 2.86% and 4.70391%, respectively.
Implementation of a sensor node for monitoring and classification of physiological signals in an edge computing system Ricardo Yauri; Antero Castro; Rafael Espino; Segundo Gamarra
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp98-105

Abstract

We describe the design and development of sensor nodes, based on Edge computing technologies, for the processing and classification of events detected in physiological signals such as the electrocardiographic signal (ECG is the electrical signal of the heart), temperature, heart rate, and human movement. The edge device uses a 32-bit Tensilica microcontroller-based module with the ability to transmit data wirelessly using Wi-Fi. In addition, algorithms for classification and detection of movement patterns were implemented to be implemented in devices with limited resources and not only in high-performance computers. The Internet of Things and its application in smart environments can help non-intrusive monitoring of daily activities by implementing support vector machine (SVM is a machine learning algorithm) for implementation in embedded systems with low hardware resources. This paper shows experimental results obtained during the acquisition, transmission, and processing of physiological signals in a edge computing system and their visualization in a web application.
Design of novel high speed parallel prefix adder Deepak Kumar Athur; Bhuvanesh Narayanan; Amshuman Gopalakrishnan; Sasipriya Palanisamy; Anita Angeline Augustine
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1345-1354

Abstract

Adders are crucial logical building blocks found almost in all the modern electronic system designs. In the adder architecture design, the fundamental issue is the propagation latency in the carry chain. As the length of the input operands increases, the length of the carry chain along with it. Parallel prefix adders, which address the problem of carry propagation in adders, are the most efficient adder topologies for hardware implementation. However, delay reduction still could be achieved for very high speed applications. Hence, in this paper design of 16bit novel parallel prefix adder is proposed and compared against the existing parallel prefix adder architectures. The design and simulation are carried out using xilinx vivado for field- programmable gate array (FPGA) simulation and Cadence® for ASIC. The results of ASIC implementation demonstrate 17.8% delay reduction while compared to sparse kogge-stone adder.
Mobile application for control and management of citizen security Alejandro Boza-Chua; Laberiano Andrade-Arenas; Avid Roman-Gonzalez
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp1063-1074

Abstract

Currently, Peru is one of the countries with the highest levels of citizen insecurity in Latin America, and its capital is considered the thirtieth most populated city in the world, thus being one of its territories with the highest percentage of citizen insecurity, providing a poor quality of life to its citizens as they feel unsafe when passing through different places and being victims of any criminal act. Therefore, this research work is developed to support this problem through the implementation of a mobile application that manages and controls citizen insecurity. Applying the research method based on design and scrum methodology, which together generate greater control over changes during project development. In addition, resources and the support of different tools were used for its study and execution, such as marvelApp for the design and prototyping of the mobile application and android studio. Obtaining highly viable results for the support of citizen security through a suitable and fully viable mobile application.
Detection and classification of plant diseases in leaves through machine learning Hasan Ahmed; Md Alomgir Hossain; Ismail Hossain; Sharmin Sultana Akhi; Ifrat Jahan Lima
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1676-1683

Abstract

Plant diseases cause significant productivity and economic losses, as well as a reduction in agricultural product quality and quantity. One principal impact on low crop yield is sickness due to bacteria, virus and fungus It is possible to avoid it by employing plant disease detection and categorization procedures. We used machine learning to detect and classify diseases in plant leaves because it evaluates data from several perspectives and categorizes it into one of several predefined classifications. In this research we create a model for the classification task which is sequential model. We trained a convolutional neural network (CNN) with help of the plant village dataset, which have 55,000 images divided into 39 completely distinct categories of each healthy and effected leaves. We trained data by using Adam optimization technique because it almost constantly plays quicker and higher global minimal convergence in comparison to the alternative optimization techniques. We achieved a validation accuracy of 98.74% using the architecture of CNN containing optimized parameters. CNNs, as can be observed, have a high-stop overall performance, making them surprisingly suitable for computerized identification of plant illnesses using simple plant leaf images. The experiment effects completed are similar with different current strategies in literature.
Predicting the value of sperm analysis using an electronic nose Raden Aa Koesoema Wijaya; Ahmad Kusumaatmaja; Dicky Moch Rizal
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp174-182

Abstract

Total motile sperm count and DNA fragmentation Index are two parameters in sperm analysis that have recently been used to determine the outcome of the management of cases of male infertility. Total Motile Sperm Count is one of the values considered better than the 2010 World Health Organization standard sperm analysis in terms of predictive value for the success of the spontaneous ongoing pregnancy rate. High DNA Fragmentation Index values were associated with lower pregnancy success and an increased risk of low fertilization rate or total fertilization failure. In this study, we developed a method to classify sperm analysis based on total motility sperm count and DNA Fragmentation Index values by using an electronic nose. In the total motility sperm count (TMSC) study, we use four algorithms with the result of accuracy values 95% and in the DNA fragmentation Index study, we get a fairly good accuracy value for two algorithms with the accuracy values 70%.

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