Indonesian Journal of Electrical Engineering and Computer Science
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Published By Institute Of Advanced Engineering And Science

2502-4760, 2502-4752

Author(s):  
Jung kyu Park

<pre>There are several differences between the two types of alarm systems, conventional systems and addressable systems. It is important to carefully determine the introduction of a fire alarm system according to the installation environment. Talking about the main difference relates to how the connected device communicates with the main control panel by sending a signal. Cost is another factor that can be a determinant of your chosen fire alarm system. In this paper, we proposed smart addressable fire detection system. In the proposed system, <span>IoT</span> was used and the network was constructed using <span>ZigBee</span> module. In the configured network, it consists of a local server and a control server. The local server controls the addressing sensor and sends the information obtained from the sensor to the control server. The control server receives data transmitted from the local server and enables quick fire action. In the actual implementation, the local server used the Lycra controller and <span>ZigBee</span> module. In addition, the control server used the Raspberry Pi and <span>ZigBee</span> modules and connected to the Ethernet so that the administrator could monitor or control the local server.</pre>


Author(s):  
Mohd Kamir Yusof ◽  
Wan Mohd Amir Fazamin Wan Hamzah ◽  
Nur Shuhada Md Rusli

The coronavirus COVID-19 is affecting 196 countries and territories around the world. The number of deaths keep on increasing each day because of COVID-19. According to World Health Organization (WHO), infected COVID-19 is slightly increasing day by day and now reach to 570,000. WHO is prefer to conduct a screening COVID-19 test via online system. A suitable approach especially in string matching based on symptoms is required to produce fast and accurate result during retrieving process. Currently, four latest approaches in string matching have been implemented in string matching; characters-based algorithm, hashing algorithm, suffix automation algorithm and hybrid algorithm. Meanwhile, extensible markup language (XML), JavaScript object notation (JSON), asynchronous JavaScript XML (AJAX) and JQuery tehnology has been used widelfy for data transmission, data storage and data retrieval. This paper proposes a combination of algorithm among hybrid, JSON and JQuery in order to produce a fast and accurate results during COVID-19 screening process. A few experiments have been by comparison performance in term of execution time and memory usage using five different collections of datasets. Based on the experiments, the results show hybrid produce better performance compared to JSON and JQuery. Online screening COVID-19 is hopefully can reduce the number of effected and deaths because of COVID.


Author(s):  
Mohd Syafiq Mispan ◽  
Aiman Zakwan Jidin ◽  
Muhammad Raihaan Kamarudin ◽  
Haslinah Mohd Nasir

An emerging technology known as Physical unclonable function (PUF) can provide a hardware root-of-trust in building the trusted computing system. PUF exploits the intrinsic process variations during the integrated circuit (IC) fabrication to generate a unique response. This unique response differs from one PUF to the other similar type of PUFs. Static random-access memory PUF (SRAM-PUF) is one of the memory-based PUFs in which the response is generated during the memory power-up process. Non-volatile memory (NVM) architecture like SRAM is available in off-the-shelf microcontroller devices. Exploiting the inherent SRAM as PUF could wide-spread the adoption of PUF. Therefore, in this study, we evaluate the suitability of inherent SRAM available in ATMega2560 microcontroller on Arduino platform as PUF that can provide a unique fingerprint. First, we analyze the start-up values (SUVs) of memory cells and select only the cells that show random values after the power-up process. Subsequently, we statistically analyze the characteristic of fifteen SRAM-PUFs which include uniqueness, reliability, and uniformity. Based on our findings, the SUVs of fifteen on-chip SRAMs achieve 42.64% uniqueness, 97.28% reliability, and 69.16% uniformity. Therefore, we concluded that the available SRAM in off-the-shelf commodity hardware has good quality to be used as PUF.


Author(s):  
Basim Abood ◽  
Abeer Naser Faisal ◽  
Qasim Abduljabbar Hamed

In this paper, elliptic curves Diffie Hellman-Rivest Shamir Adleman algorithm (ECDH-RSA) is a novel encryption method was proposed, which based on ECDH and RSA algorithm to secure transmitted data in heterogeneous wireless sensor networks (HWSNs). The proposed encryption is built under cheesboard clustering routing method (CCRM). The CCRM used to regulate energy consumption of the nodes. To achieve good scalability and performance by using limited powerful max-end sensors besides a large powerful of min-end sensors. ECDH is used for the sharing of public and private keys because of its ability to provide small key size high protection. The proposed authentication key is generated by merging it with the reference number of the node, and distance to its cluster head (CH). Decreasing the energy intake of CHs, RSA encryption allows CH to compile the tha data which encrypted with no need to decrypt it. The results of the simulation show that the approach could maximize the life of the network by nearly (47%, and 35.7%) compare by secure low-energy adaptive clustering hierarchy (Sec-LEACH and SL-LEACH) approches respectively.


Author(s):  
Uoc Quang Ngo ◽  
Duong Tri Ngo ◽  
Hoc Thai Nguyen ◽  
Thanh Dang Bui

Increasingly <span>emerging technologies in agriculture such as computer vision, artificial intelligence technology, not only make it possible to increase production. To minimize the negative impact on climate and the environment but also to conserve resources. A key task of these technologies is to monitor the growth of plants online with a high accuracy rate and in non-destructive manners. It is known that leaf area (LA) is one of the most important growth indexes in plant growth monitoring system. Unfortunately, to estimate the LA in natural outdoor scenes (the presence of occlusion or overlap area) with a high accuracy rate is not easy and it still remains a big challenge in eco-physiological studies. In this paper, two accurate and non-destructive approaches for estimating the LA were proposed with top-view and side-view images, respectively. The proposed approaches successfully extract the skeleton of cucumber plants in red, green, and blue (RGB) images and estimate the LA of cucumber plants with high precision. The results were validated by comparing with manual measurements. The experimental results of our proposed algorithms achieve 97.64% accuracy in leaf segmentation, and the relative error in LA estimation varies from 3.76% to 13.00%, which could meet the requirements of plant growth monitoring </span>systems.


Author(s):  
Abdullah Al-Yaari ◽  
Hamzah Sakidin ◽  
Yousif Alyousifi ◽  
Qasem Al-Tashi

This study involves new notions of continuity of mapping between quasi-cone metrics spaces (QCMSs), cone metric spaces (CMSs), and vice versa. The relation between all notions of continuity were thoroughly studied and supported with the help of examples. In addition, these new continuities were compared with various types of continuities of mapping between two QCMSs. The continuity types are 𝒇𝒇-continuous, 𝒃𝒃-continuous, 𝒇𝒃-continuous, and 𝒃𝒇-continuous. The results demonstrated that the new notions of continuity could be generalized to the continuity of mapping between two QCMSs. It also showed a fixed point for this continuity map between a complete Hausdorff CMS and QCMS. Overall, this study supports recent research results.


Author(s):  
Aiman Mustaffa ◽  
Faiz Arith ◽  
Nurin Izzati Fauzi Peong ◽  
Nurul Rafiqah Jaffar ◽  
Evelyn Larwy Linggie ◽  
...  

Oil palm is an important industry that has contributed to income and support to the economic sector especially for Malaysia and Indonesia. However, most of the equipment in the oil palm industry is still operated manually. This work developed a system to separate bunches of oil palm fruit using color sensors according to maturity level. Fruit color plays a decisive point in determining fruit maturity. Here, a specific threshold point of red green blue (RGB) was obtained for the determination of the maturity level of oil palm fruit. Point values of &lt; 120, 120 &lt; x &lt; 150 and &gt; 150 represent the maturity levels of unripe, under ripe and ripe, respectively. This paper is the first to report the RGB points for use in the development of automated oil palm segregation system in the oil palm plantation industry. Thus, this paper will pave the way in producing an accurate and reliable oil palm separation system, which in turn has a positive effect in reducing human error. In the future, a set of sensors is proposed to detect a bunch of the oil palm fruits. This further can speed up the segregation process and more suitable for adaptation to the industry.


Author(s):  
Ahmed Shihab Ahmed ◽  
Hussein Ali Salah

The technology <span>of the multimodal brain image registration is the key method for accurate and rapid diagnosis and treatment of brain diseases. For achieving high-resolution image registration, a fast sub pixel registration algorithm is used based on single-step discrete wavelet transform (DWT) combined with phase convolution neural network (CNN) to classify the registration of brain tumors. In this work apply the genetic algorithm and CNN clasifcation in registration of magnetic resonance imaging (MRI) image. This approach follows eight steps, reading the source of MRI brain image and loading the reference image, enhencment all MRI images by bilateral filter, transforming DWT image by applying the DWT2, evaluating (fitness function) each MRI image by using entropy, applying the genetic algorithm, by selecting the two images based on rollout wheel and crossover of the two images, the CNN classify the result of subtraction to normal or abnormal, “in the eighth one,” the Arduino and global system for mobile (GSM) 8080 are applied to send the message to patient. The proposed model is tested on MRI Medical City Hospital in Baghdad database consist 550 normal and 350 abnormal and split to 80% training and 20 testing, the proposed model result achieves the 98.8% </span>accuracy.


Author(s):  
Maha Yousif Hasan ◽  
Dheyaa Jasim Kadhim

Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is satisfied. It divides the measured data for actual power (A_p ) of the electrical model into two portions: the training portion is selected for different maximum actual powers, and the validation portion is determined based on the minimum output power consumption and then used for comparison with the actual required input power. Simulation results show the energy expenditure problem can be solved with good accuracy in energy consumption by reducing the maximum rate (A_p ) in a given time (24) hours for a single house, as well as electricity’s bill cost, is reduced.


Author(s):  
Oussama Elallam ◽  
Mohamed Hamlich

The magnetic resonance imaging (MRI) machine cooling system has a vital role in the conduct of MRI examinations because a shutdown of the MRI cooling system in the absence of the manipulators can lead to grave consequences over time, like quench, which is the vaporization of helium liquid in the MRI tank, and it's the most expensive MRI failure. To limit the risks of this problem, several companies have tried to develop a monitoring system to track MRI cooling system failures but all solutions proposed are complicated and demand many connections with MRI. The proposed solution is simple, easy, and efficient requires only one joint with the helium compressor, and it has a humidity and temperature sensor to detect quench incident, it works using an advanced monitoring algorithm that evaluates the status of the cooling system and identifies breakdowns, in case of failure our system will send short message service (SMS) notifications and emails to the customer service team. The proposed solution shows the potential for starting the research to understand the relationship between the behavior of the MRI cooling system and the quench using machine learning algorithms.


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