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Journal of Applied Engineering and Technological Science (JAETS)
Published by Yayasan Pendidikan Riset dan Pengembangan Intelektual
ISSN : 27156087     EISSN : 27156079     DOI : -
Core Subject : Science, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering
Journal of Applied Engineering and Technological Science (JAETS) is published by Yayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI), Pekanbaru, Indonesia. It is academic, online, open access, peer reviewed international journal. It aims to publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. Journal of Applied Engineering and Technological Science (JAETS) is published annually 2 times every June and Desember.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 358 Documents
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Safety Assessment of Tunnel Lining Structure with Underlying Cavities Based on Fuzzy Comprehensive Evaluation in Mudstone Stratum Yiming Wang; Haoxuan Wang
Journal of Applied Engineering and Technological Science (JAETS) Vol. 5 No. 2 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v5i2.3690

Abstract

This paper presents a study on the structural safety assessment of tunnel linings with underlying cavities based on a fuzzy comprehensive evaluation model in mudstone stratum. The weight and membership degree are determined using an improved method: field data analysis and numerical simulation. Field data analysis revealed that the proportion of cavities in the surrounding rocks of class ? and at the vault was the largest. Cavity length between 1m and 3m and cavity depth between 20cm and 40cm occupied the most significant proportion. Additionally, the impact of defect parameter changes on structural safety was investigated through numerical simulation. It is well known that the lining safety factors are greatly impacted by changes in surrounding rock classifications, cavity locations and depths. In contrast, changes in cavity lengths do not significantly affect the lining safety. The developed fuzzy comprehensive evaluation model consists of factor set, comment set, membership degree and weight set. They are determined according to the previous field data analysis and numerical analysis results. The developed evaluation model is validated by means of the numerical simulation based on the evaluation work of the specific engineering case.
Lung Nodule Detection For CT-Guided Biopsy Images Using Deep Learning B. Prashanthi; S.P. Angelin Claret
Journal of Applied Engineering and Technological Science (JAETS) Vol. 5 No. 2 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v5i2.3716

Abstract

The recent advancements in artificial intelligence enhance the detection and classification of lung nodules via computed tomography scans, addressing the critical need for early diagnosis of lung cancer. The lung cancer when identified at the earlier stages, the chance of survival is higher. The methodology encompasses a modern deep-learning approach applied to a private dataset obtained from the Barnard Institute of Radiology at Madras Medical College, Chennai, which has been granted ethical approval.  The results from applying the proposed Convolutional Neural Network model are promising, with an accuracy of 99.3% in malignancy detection, signifying a notable advancement in the precise diagnosis of lung cancer through non-invasive imaging techniques. Beyond academia, the findings of this study have significant implications for real-world healthcare settings. By providing a reliable and automated solution for lung nodule detection, this research contributes to early diagnosis and personalized treatment strategies for lung cancer patients. The value of the present work lies in its potential to reduce morbidity through the early detection of lung cancer, thus contributing to both clinical practice and the ongoing development of AI applications in healthcare. Our research may serve as a model for further studies in digital health care at Madras Medical College, aiming to improve patient outcomes through technology-driven diagnostics.
Deep Learning and Its Role in Diagnosing Heart Diseases Based on Electrocardiography (ECG) Qaswaa Khaled Abood
Journal of Applied Engineering and Technological Science (JAETS) Vol. 5 No. 2 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v5i2.3746

Abstract

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was adopted, which is considered a challenge for researchers because it includes different age groups. Many diseases, and the results obtained by the system were 96% accurate.
Effect of High Temperature Heating on Chemical Compounds in Magnesium Composite Materials Rezza Ruzuqi; Eko Tavip Maryanto
Journal of Applied Engineering and Technological Science (JAETS) Vol. 5 No. 2 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v5i2.3749

Abstract

The development of magnesium composite-based seawater battery anode technology is actively pursued, especially in its ability to transmit and store electrical energy. However, many overlook the possibility that significant temperature changes during the process may lead to chemical compound alterations, potentially affecting the battery's performance. Therefore, this research examines the changes in chemical compounds in magnesium composite-based seawater battery anodes caused by high temperatures. In this study, the synthesis process of magnesium composite material composed of MgAlSnMn with variations of Manganese (wt.-%) 14.8, 15, 15.2, 15.4, 15.6. Then it was milled for 60 minutes. Next, the materials were pelletized using a manual compacting machine with a diameter and compressive strength of 10 mm and 150 kg/cm2 respectively. After that, all materials were sintered at 7500C with a muffle furnace for 60 minutes. In this study, XRD equipment was utilized to determine chemical compound changes. The results indicate that magnesium composite materials undergo significant chemical compound alterations at high temperatures, including MgO (Magnesium Oxide Periclase), Al18Mg3Mn2, and the remaining Al elements. This could potentially disrupt the performance of seawater batteries when applied. It is hoped that further research will be conducted in the future to enhance the quality and performance of the product.
Identification of Landslide Hazard in Residential Area Kubang Tangah District, Sawahlunto Andriani Andriani; Bambang Istijono; Alfito Alfito; Farid Akmal; Bayu Martanto Adji
Journal of Applied Engineering and Technological Science (JAETS) Vol. 5 No. 2 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v5i2.3893

Abstract

The residential area in Kubang Tangah, Sawahlunto, is an area that has the potential for significant landslide hazard. With rapid residential growth and environmental change, risks to the security and well-being of residents are becoming increasingly prominent. This research aims to identify factors that trigger landslide hazard and analyze potential risks in the residential context of Kubang Tangah. Analysis of regional geotechnical and topographic characteristics, land use modeling, and review of the impact of human activities on slope stability. The analysis method uses the Plaxis 2D program to obtain slope safety factors in the Kubang Tangah residential area, Sawahlunto. The research results show that residential areas in Kubang Tangah have a high level of landslide risk, influenced by slope, soil type, and changes in land use. Varying rainfall levels significantly contribute to the potential for landslide hazard. Mitigation recommendations are suggested to involve wise land use changes, strengthening infrastructure, and increasing public awareness of the dangers of landslides.
Malaria Disease Prediction Based on Convolutional Neural Networks Dhrgam AL Kafaf; Noor N. Thamir; Samara S. AL-Hadithy
Journal of Applied Engineering and Technological Science (JAETS) Vol. 5 No. 2 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v5i2.3947

Abstract

This study delves into the investigation of the efficacy of Convolutional Neural Networks (CNNs) in identifying malaria through the examination of cell images. The dataset employed encompasses a total of 27,558 images, harvested from the renowned Malaria Cell Images Dataset on Kaggle, encompassing cells of diverse nature. The architectonics of the CNN model is meticulously devised, comprising of six blocks and three interconnected blocks, thereby rendering an efficient extraction of features and subsequent classification of the cells. Creative paraphrasing: Various strategies such as dropout, batch normalization, and global average pooling are artfully utilized to refine and fortify the model, ensuring its robustness and adaptability. In order to confront the challenge of diminishing gradient and facilitate the attainment of convergence, the activation function known as Rectified Linear Unit (ReLU) is ingeniously employed. Assessing the efficacy of the model via a perplexity grid produces outcomes. Exhibiting a precision rate of 99.59%, a specificity measure of 99.69%, an Sensitivity of 99.40%, F1 Measurement of 99.44%, and a Precision of 99.48, it showcases its capacity to effectively distinguish betwixt malaria-afflicted cells and unafflicted cells. The focal point of this research highlights the substantial potential of CNNs in facilitating the automated identification of malaria using image analysis. By harnessing their unique architecture and regularization techniques, CNNs have the capability to enhance the results and potentially bring about better outcomes in areas with prevalent cases of malaria.
Preparation, Synthesis and Characterization of La(1-x)Sr(x)MnO3 Alloy Ramlan Ramlan; Fatma Husaini; Jan Setiawan; Ferry Budhi Susetyo; Hamdan Akbar Notonegoro; Silviana Simbolon; Dwi Nanto; Yunasfi Yunasfi
Journal of Applied Engineering and Technological Science (JAETS) Vol. 5 No. 2 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v5i2.3962

Abstract

Magnetic particles have been used for hyperthermia by inserting ferromagnetic material into tumor tissue. La(1-x)Sr(x)MnO3 is one of the best candidates for hyperthermia due to higher magnetic at ambient temperature and their Curie temperature easily adjusted. This research synthesized La(1-x)Sr(x)MnO3 using the ball milling technique. Several heat treatments were also conducted after ball milling processing. Various investigations, including SEM-EDS, XRD, DSC, and VSM, were conducted. LaMnO3 has a hexagonal structure, which has the space group R -3 c. From the diffraction pattern seen in LaMnO3 and La0.9Sr0.1MnO3 seen at angles 32.376 and 32.706, it looks separate like the database diffraction pattern. In La0.9Sr0.1MnO3, these two peaks are seen to be increasingly separated. In contrast to the diffraction patterns of La0.7Sr0.3MnO3 and La0.5Sr0.5MnO3 at an angle of 32.376, there is a decrease in intensity. The specific heat capacity of the alloy with Sr substitution of 0.3 has a greater value than that without substitution and the lowest occurs in the alloy with Sr substitution of 0.1. The magnetization value for Sr substitution is 0.3 higher than for other alloys.
Lightweight Block and Stream Cipher Algorithm: A Review Suaad Ali Abead; Nada Hussein M. Ali
Journal of Applied Engineering and Technological Science (JAETS) Vol. 5 No. 2 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v5i2.3966

Abstract

Most of the Internet of Things (IoT), cell phones, and Radio Frequency Identification (RFID) applications need high speed in the execution and processing of data. this is done by reducing, system energy consumption, latency, throughput, and processing time. Thus, it will affect against security of such devices and may be attacked by malicious programs. Lightweight cryptographic algorithms are one of the most ideal methods Securing these IoT applications. Cryptography obfuscates and removes the ability to capture all key information patterns ensures that all data transfers occur Safe, accurate, verified, legal and undeniable.  Fortunately, various lightweight encryption algorithms could be used to increase defense against various attacks to preserve the privacy and integrity of such applications. In this study, an overview of lightweight encryption algorithms, and methods, in addition, a modern technique for these algorithms also will be discussed. Besides, a survey for the algorithm that would use minimal power, require less time, and provide acceptable security to low-end IoT devices also introduced, Evaluating the results includes an evaluation of the algorithms reviewed and what was concluded from them. Through the review, we concluded that the best algorithms depend on the type of application used. For example, Lightweight block ciphers are one of the advanced ways to get around security flaws.
An Analytical Study on the Most Important Methods and Data Sets Used to Identify People Through ECG: Review Abdullah Najm Abed Alzaki; Mohammed Al-Tamimi
Journal of Applied Engineering and Technological Science (JAETS) Vol. 5 No. 2 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v5i2.3992

Abstract

The electrocardiogram is a topic of great importance from a medical and biometric perspective, especially recently, as researchers have begun to search for new biometric methods other than the palm print, fingerprint, or iris as alternative systems. Researchers discovered that ECG has unique features that are not common among humans, making it a good topic for researchers in biometric systems for identifying people. In this research paper, the goal is to shed light on the most important basic concepts that are related to ECG in terms of the methods used by researchers and in terms of the most critical data sets used by researchers, and also to shed light on some previous studies that achieved a high rate of citations, and also to shed light on the most important basic concepts that make Its features are unique and intelligence methods can be used effectively.
The Role of Artificial Intelligence in Providing People With Privacy: Survey Salar Raees; Mohammed Al-Tamimi
Journal of Applied Engineering and Technological Science (JAETS) Vol. 5 No. 2 (2024): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v5i2.4013

Abstract

Images privacy involves assessing the amount of information leakage from images, assessing risks associated with identification, and examining controls on this information. It was discussed various types of protection available and most commonly used in providing privacy to a person in images, including single-stage and two-stage detection algorithms. The results of each algorithm are organized in detailed tables, and the [YOLO] algorithm expands on all versions. The paper also clarifies the dataset used for testing the algorithms and its relevance to achieving desired results. It presents a comprehensive understanding of the process of detecting persons in digital images and assesses various tools and algorithms for recognizing persons, faces, and identities. It added an extensive examination of the several methods used to identify persons in digital images, with a specific emphasis on safeguarding their privacy. The task at hand is assessing various face recognition and identification tools and algorithms, with a specific emphasis on those that exhibit superior accuracy and efficiency in presenting outcomes. The study concluded that using the yolov8 algorithm in conjunction with blurring techniques effectively conceals individuals' information in digital images while maintaining the integrity of the overall image. The research paper's implications and information can practically contribute to the development of algorithms for detecting and protecting people in digital images, as well as the development of applications in this field. Theoretically, it can enhance understanding of the process of detecting and protecting people, and potentially contribute to the development of new theories in the field of protection and discovery.

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