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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 9,138 Documents
 813   814   815   816   817 
A standard ranking algorithm for robust iris template protection Mohammed Ali Hameed Yassir; Rudzidatul Akmam Dziyauddin; Norshaliza Kamaruddin; Norulhusna Ahmad
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp1214-1225

Abstract

In iris biometric recognition systems, protecting the storage and transmission of iris templates is crucial, and template protection techniques are pivotal for ensuring their security. A prevalent approach involves using indexing methods as an effective algorithm for iris template protection, leveraging the index or rank of the extracted iris code to generate a secure iris template. Meantime, many privacy threats to biometric data have emerged, necessitating heightened protection measures. Specifically, protecting the privacy of iris data is imperative within the context of iris template protection during recognition processes. As stipulated by the international standard ISO/IEC 30136, effective iris template protection must concurrently meet the criteria of irreversibility, revocability, and unlinkability. Nevertheless, existing indexing methods on iris template protection faced the formidable challenge of simultaneously fulfilling these three privacy requirements while maintaining the efficacy of iris recognition. This paper introduces a standard ranking (standardR) algorithm, named standardR, designed to enhance the security of iris templates by transforming each iris template into an irreversible representation. The experimental results on the benchmarked Casia-Iris-interval dataset, along with two additional iris datasets MMU1 and UBRIS 1, demonstrate the efficacy of the proposed algorithm. The proposed standardR algorithm achieves an equal error rate (EER) of 0.1695% and an area under the curve of 0.93011% with the Casia-Iris-Interval dataset. Furthermore, the algorithm maintains efficient recognition with a reduced iris code length of 1280 bits, a time complexity of O(n log n), and satisfies the biometric template protection (BTP) requirements in irreversibility, unlinkability, and renewability.
Cultivating excellence: a case study of enterprise architecture transformational journey in higher education Fatimah Azzaharah Amin; Surya Sumarni Hussein; Nor Aziah Daud; Nur Azaliah Abu Bakar; Wan Azlin Zurita Wan Ahmad
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 1: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i1.pp548-555

Abstract

An enterprise architecture (EA) is a critical framework that clarifies the complex elements of organizations, including business processes and technology. It coordinates the interaction of these elements to achieve predetermined business goals. Higher education institutions (HEIs) may become susceptible to rigidity, duplication, and intricate operations without a comprehensive EA. The primary aims of this study are to ascertain the necessary information for each EA domain: business, data, and application at Universiti Teknologi MARA (UiTM) and to design the landscape map viewpoint architecture for UiTM by utilizing the EA framework. This research uses qualitative methods, namely interviews and document analysis, to comprehensively comprehend the intricacies and prerequisites within every EA domain. Critical insights for each UiTM domain: business, data, application, and technology were uncovered through the discernments. From the thematic analysis, the frequency of issues according to the EA domain is business 13 issues, application eight issues, data seven issues, and technology seven issues. Following a thorough analysis, these findings led to the development of the landscape map viewpoint architecture diagram. In conclusion, the results of this research hold the potential to provide HEIs with invaluable knowledge for enhancing their organizational transformation via EA, thereby propelling the overall quality and efficacy of higher education systems forward.
Advanced control of double stage grid-tied three phase photovoltaic systems with shunt active power filter Zaghar, Fatim-Zahra; Hekss, Zineb; Rafi, Mohamed; Ridah, Abderraouf; Adhiri, R’hma
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 2: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i2.pp673-682

Abstract

This paper explores the challenges associated with the control of a two-stage three-phase electrical grid connected to a photovoltaic (PV) system. The objectives encompass: i) maximizing the available PV power, ii) controlling the DC-link voltage to a predetermined setpoint, and iii) considering that power quality has become an important measure in a distribution electrical network where different loads are connected, the third objective will mainly focus on ensuring power factor correction (PFC). To achieve these objectives, two loops of nonlinear controller are developed. In the outer loop, the duty cycle of a boost converter is controlled using a hybrid technique of backstepping technique and the perturb & observe (P&O) algorithm. In addition, the inner loop employs a hybrid automaton approach to tackle the challenges of a three-phase shunt active power filter (SAPF). The results have been verified through numerical simulation using MATLAB/Simulink power systems environment.
Automated hydroponic nutrient control system for smart agriculture Ambidi Naveena; Shaik Nannu Saheb; Ratnababu Mamidi; Godavarthi Lakshmi Narasimha Murthy
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 2: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i2.pp839-846

Abstract

Hydroponics is a type of soil-free farming that uses less water and other resources than conventional soil-based farming methods. Hydroponic cultivation system has high yield per acre of land with minimal consumption of water and can be a possible to meet the growing food demand of the world. The hydroponic plants fertility must be preserved, proper nutrition, a environmental temperature, and nutrient stability are crucial. It will be simpler for a farmer to keep track of all hydroponic plants by automatically monitoring nutrient flow and ambient temperature stability. By implementing artificial intelligence-based regulating algorithms in the agriculture industry, recent technology advancements are highly helpful in resolving these issues. This paper presents, automated hydroponic nutrient control system (AHNCS) for smart agriculture. System architecture is consisting of sensors network, Raspberry pi 4 microcontroller and actuators. Raspberry pi 4 microcomputer read sensor values from sensors process and activates particular actuator. The automation of the hydroponic system helps to avoid human intervention. The utilization of sensors and actuators, promptly act for the needs of the plant without any delay. The AHNCS having high accuracy, high efficiency and less delay. Hence, automation of the existing hydroponic system can reduce human dependency, provide accurate results, constant monitoring of plant health.
Fuzzy adaptive resonance theory failure mode effect analysis non-healthcare setting for infectious disease: review Aysha Samjun; Kasumawati Lias; Mohd. Zulhilmi Firdaus Rosli; Hazrul Mohamed Basri; Chai Chee Shee; Kuryati Kipli
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp236-247

Abstract

Fuzzy adaptive resonance theory (ART) is an ART network that is developed as one of the alternative methods to evaluate risk priority number (RPN) in failure mode and effect analysis (FMEA). Not only is FMEA are common technique as an analysis tool in industrial sectors, but also, especially during the global emergency COVID-19 pandemic hits, FMEA is used in prevention and mitigation measures. Many alternative methods have been proposed. However, not many investigations use clustering models such as Fuzzy ART in FMEA. This paper aims to provide a comprehensive review and then propose a model for systematic risk analysis which implement the fuzzy ART model, named clustering- transmission causes and effects analysis (c-TCEA), for the prevention and mitigation of infectious diseases.
Game-based augmented reality learning of Sarawak history in enhancing cultural heritage preservation Clive Lai Yi Cheng; Goh Eg Su; Johanna Binti Ahmad; Tole Sutikno
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i3.pp1718-1729

Abstract

The augmented reality (AR) technology had been proliferating for years. However, the implementation of AR technology still has room to be explored, especially in the form of cultural heritage preservation. The aim of this study is to enhance AR technology in game-based cultural heritage and history preservation in Sarawak, as well as supplement the gamified experiences in learning James Brooke’s history. Three research objectives are proposed: to design an AR game prototype for the history of James Brooke; to develop an AR game prototype with a collaborative learning element; and to evaluate an AR game prototype for enhancing cultural heritage preservation. This study proposes a game-based prototype that contains AR markers to assign each with different game features. Furthermore, collaborative learning theory is enhanced through AR experiences with multiplayer support. The game-based prototype is evaluated by a group of participants through prototype measuring and testing. The participants feel mediocre about the challenge and knowledge factors of the prototype. Overall, this study highlights the enhancement of cultural heritage preservation through AR game-based experiences intensively learned from James Brooke’s history in Sarawak. These implementations have an apparent promising contribution to make in protecting the available cultural heritage in Sarawak and extensively to the country’s cultural heritage preservation.
Processes monitoring using adaptive confidence limit based on T-S fuzzy model and Luenberger observer Bouzenad, Khaled; Rahmouni, Salah; Ramdani, Messaoud
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 2: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i2.pp844-852

Abstract

In hazard-sensitive processes, the monitoring upsets and malfunctions correctly is an important challenge to operation safely and enhance the performance. Conventional process monitoring frequently assumes that process data follow only one Gaussian distribution, which generates a constant confidence limit and hence produces a high number of false alarms. However, in fact, industrial processes usually include various operating modes. To ovoid this drawback, the suggested approach employs an adaptive confidence limit (ACL) when a substantial number of false alarms are created. The fundamental concept underlying this study is to extract internally several local linear sub-modes of the monitored variables. In typical operating circumstances, the Gaussian mixture model (GMM) is utilized to extract several local linear sub-modes, followed by fuzzy linearization using the Takagi-Sugeno model, thereafter a bank of Luenberger observers to construct the residual spaces. An abnormal event is detected when the squared prediction error (SPE) is too great or exceeds the adaptive threshold designed to prevent the false alarms. Furthermore, an enhanced contribution plots is effectively used to identify the defective variable.
Towards a consulting model for a good urban generation of social housing districts in terms of equipment Lamyae Alaoui; sakina elhadi; Abdellah Lakhouili; Abdelaziz Merzak
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 3: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i3.pp1866-1875

Abstract

Social housing in Morocco is housing built with state assistance. It is subject to precise rules of construction, management and allocation and governed by specifications defining requirements in a manual manner. This work which is done manually can produce errors either at the level of calculations or at the level of equipment proposal. The objective of this article is to computerize this area as there is a lack of tools and platforms. To solve this problem, we have created an advisory platform for good urban planning for residents which will help engineers. Based on mathematical formulas. This tool will allow architects and urban planners to design autonomous populations in terms of equipment.
Design, security and implementation of learning focal point algorithm in a docker container Salah Eddine Mansour; Abdelhak Sakhi; Larbi Kzaz; Oussama Tali; Abderrahim Sekkaki
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp416-424

Abstract

Artificial intelligence is not smart enough. This is why we are looking for complementary algorithms in order to increase the performance of machine learning and neural networks (NN). We have innovated an algorithm called learning focal point (LFP). This algorithm will help us increase the intelligence of machine learning and the NN. In this article, we will present the algorithm in detail, starting with the mathematical and theoretical principles, passing through the development and deployment in cloud docker containers, and ending with the security of its application programming interface (API). Finally, we are going to do a test in which we apply it in the case of using tin cans.
Real-time monitoring system for blood pressure monitoring based on internet of things Ngurah Desnanjaya, I Gusti Made; Aditya Nugraha, I Made
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 1: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i1.pp62-69

Abstract

Blood pressure is an important cardiovascular health indicator, with normal values set by the WHO at 140 mmHg for systole and 90 mmHg for diastole. Excess of these values indicates hypertension, which increases the risk of serious medical complications. This research developed an internet of things (IoT)-based blood pressure monitoring device, which facilitates digital blood pressure measurement and data transmission to widely accessible applications and websites. The device uses an MPX5050GP pressure sensor, Arduino Nano, and NodeMCU ESP32, as well as other components programmed using the Arduino IDE. Test results obtained from 10 subjects, the device showed an average difference in systole of 7.9 mmHg and diastole of 5.4 mmHg. This complies with recognized accuracy standards of a maximum error of 10 mmHg and indicates that the device operates effectively with the designed concept.

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