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Applied Engineering and Technology
Published by Association for Scientific Computing Electronics and Engineering
ISSN : -     EISSN : 28294998     DOI : http://dx.doi.org/10.31763/aet
Core Subject : Science, Engineering,
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology
Applied Engineering and Technology provides a forum for information on innovation, research, development, and demonstration in the areas of Engineering and Technology applied to improve the optimization operation of engineering and technology for human life and industries. The journal publishes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gaps between research, development, and implementation. The breadth of coverage ranges from innovative technologies and systems of implementation and application development to better human life and industry. The following scope are welcome: Aerospace Engineering, Automobile Engineering, Applied Mathematics, Applied Physics, Bioinformatics, Biophysics, Biotechnology, Chemical Engineering, Chemical Physics, Civil Engineering, Computational Physics, Computer Engineering, Electrical Engineering, Electronic Engineering, Energy Engineering, Environment Engineering, Information Technology, Marine engineering, Mechanical engineering, Medical Engineering, Medical imaging, Medical Physics, Nanotechnology, Ocean Engineering, Optical engineering, Photonics, Robotics, Urban Engineering and Other related engineering topics in general.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 7 Documents
 1 
Search results for , issue "Vol 2, No 3 (2023): December 2023" : 7 Documents clear
Optimization of a bio-based drilling fluid from waste Dacryodes Edulis (local pear) for oil exploration Effiom, Precious-Chibuzo Oliver
Applied Engineering and Technology Vol 2, No 3 (2023): December 2023
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v2i3.1082

Abstract

This study focused on the development and optimization of a bio-based drilling fluid from local pear seed for oil exploration, which can help lessen the environmental impact of oil spills. Local pear seed being a biodegradable material was collected, prepared, its oil extracted, modified and optimized to obtain an eco-friendly and cost-effective drilling fluid. The selected materials used for this study was Local pear oil. The drilling fluid was characterized for proximate parameters and ultimate parameters. The prepared drilling fluid was optimized using response surface methodology (RSM) provided by Design-Expert software 13.0. Central composite design (CCD) was applied to study the variables affecting rheology of drilling fluid. The process factors which include pH (A), viscosity (B), mud density (c), temperature (D), rheology (E) interacted to produce the response (drilling fluid yield) for the studied sample. The optimized drilling fluid yield and the optimum values were obtained through iterations of one hundred (100) solutions and the best yield was selected at iteration number seven (95th solution), at a pH of 1, Viscosity of 119.783cP, mud density of 10.473kg/L, Temperature of 100°C, and Rheology of 76.809s-1, and the optimized drilling fluid yield value was 91.144%. The acidity and the alkalinity of the drilling fluid were measured by the concentration of the 9.5 ion in the fluid. Therefore, the biomaterial studied has demonstrated its optimal effectiveness and potential application as an additive for the development of drilling fluid for oil exploration.
Semi-supervised labelling of chest x-ray images using unsupervised clustering for ground-truth generation Agughasi, Victor Ikechukwu; Srinivasiah, Murali
Applied Engineering and Technology Vol 2, No 3 (2023): December 2023
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v2i3.1143

Abstract

Supervised classifiers require a lot of data with accurate labels to learn to recognize chest X-ray images (CXR). However, manually labeling an extensive collection of CXR images is time-consuming and costly. To address this issue, a method for the semi-supervised labelling of extensive collections of CXR images is proposed leveraging unsupervised clustering with minimum expert knowledge to generate ground truth images. The proposed methodology entails: using unsupervised clustering techniques such as K-Means and Self-Organizing Maps. Second, the images are fed to five different feature vectors to utilize the potential differences between features to their full advantage. Third, each data point gets the label of the cluster’s center to which it belongs. Finally, a majority vote is used to decide the ground truth image. The number of clusters created by the method chosen strictly limits the amount of human involvement. To evaluate the effectiveness of the proposed method, experiments were conducted on two publicly available CXR datasets, namely VinDR-CXR and Montgomery datasets. The experiments showed that, for a KNN classifier, manually labeling only 1% (VinDr-CXR), or 10% (Montgomery) of the training data, gives a similar performance as labeling the whole dataset. The proposed methodology efficiently generates ground-truth images from publicly available CXR datasets. To our knowledge, this is the first study to use the VinDr-CXR and Montgomery datasets for ground truth image generation. Extensive experimental analysis using machine learning and statistical techniques shows that the proposed methodology efficiently generates ground truth images from CXR datasets.
Development and implementation of the MobILcaps application for the teaching and development of information literacy in Higher Education Mariscal, David Caballero; Pinto, María; Segura, Alicia
Applied Engineering and Technology Vol 2, No 3 (2023): December 2023
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v2i3.1145

Abstract

This paper aims at develop, implement and evaluate the effectiveness of the MobIlCaps mobile application. On the basis of cognitive, constructivist and connectivist theories, it has been developed on an instructional design model, based on the user experience. In the context of mobile teaching in higher education, an innovative application is proposed for the self-learning of information literacy by students of Social Sciences. With the collaboration of both teachers and students, the application was developed, following the ADDIE model, through the phases of analysis, design, development, implementation and evaluation. The last phase provided the improvement proposals for the optimization of the final version of the tool, a progressive open access website. The application is organized into six capsules that follow the framework of ACRL (2015): learn, search, evaluate, create, research and disseminate. It includes multimedia resources in the form of microcontents that highlight readability, organization and visualization as characteristics. The app focuses on the user and is a relevant instrument to facilitate teaching The different analyses, followed by proposals for improvement and revisions, led to the achievement of a very useful application for students, teachers and library
Assessment of safety and economic impact of boil-off-gas in LPG storage tanks Princewill, Nwadinobi Chibundo; Ubasom, Kanu Allwell; David, Chukwudi Onyebuchi
Applied Engineering and Technology Vol 2, No 3 (2023): December 2023
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v2i3.1092

Abstract

This study was carried out to assess the effect of boil-off gas (BOG) on the safety and economic effectiveness of LPG storage tanks. It includes analysis of the thermodynamic properties of LPG; heat absorbed from ambient air by the storage tank that leaks into the LPG, and consequently generates boil-off gas in the supply chain, by utilizing appropriate thermodynamic and heat transfer equations. Analyzing the heat leakage required the estimations of the convective heat transfer coefficient of the ambient air in the supply location and the LPG supply chain, which amounted to 3335.9W/m2K and 21.058W/m2K, respectively, in the system under study. Analyzing the thermodynamic properties, such as specific volume, entropy, and enthalpy of the LPG, shows that the entropy of LPG in the storage tank is negative, which suggests an endothermic process, validating that heat is added to the system from the surroundings. The heat absorbed in the LPG from the ambient air by the storage tank amounted to 1.785kW. The boil-off generation rate due to the storage tank heat leakage was 0.0049kg/s, which translates to a cost equivalent loss of 0.0069$/s at an LPG selling price of 1.42$/kg. It was recommended that maintenance of insulation and other external factors such as wind speed, solar radiation, ambient temperature, and thermal conductivity of the storage tank material are key factors in minimizing the heat leaks into LPG; hence BOG generation, which is of utmost importance in ensuring safety and economic loss in the LPG supply chain.
AdPisika: an adaptive e-learning system utilizing k-means clustering, decision tree, and bayesian network based on felder-silverman model to enhance physics academic performance Riva, Gabriel Dela; Chongco, James; Paguio, Jezreel Joy; Purisima, Joefel Mark; Salvador, Geoffrey; Luna, Robert de; Tubola, Orland
Applied Engineering and Technology Vol 2, No 3 (2023): December 2023
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v2i3.1144

Abstract

Amid the shift to online learning during the COVID-19 outbreak, the academic performance of students has become a concern. To address this, Adaptive Learning Systems (ALS) have emerged, these help in assessing students and delivering personalized content. This study develops an ALS incorporating K-means Clustering, Decision Tree, and Bayesian Network techniques, based on the Felder-Silverman Learning Style Model (FSLSM). The aim is to optimize learning materials based on students' current Knowledge Level (KL) and their Learning Style (LS). The students who utilized the proposed system showed substantial improvements in their performance across the Electromagnetic Spectrum, Light, Electricity, and Magnetism modules, with increases of 28.8%, 41.4%, 31.9%, and 32.9%, respectively. These findings provide strong evidence that the adaptive e-learning system had a significant positive impact on post-test scores compared to pre-test scores, surpassing the outcomes achieved with the traditional learning approach. With a silhouette score of 0.7 for K-Means clustering, an accuracy of 87.5% for Decision Tree, and a 95.1% acceptance value for the distribution of learning objects using the Bayesian Network, the proposed adaptive system demonstrated successful implementation of these machine learning algorithms. Furthermore, the proposed system received "excellent" ratings for functional stability, performance efficiency, compatibility, and reliability, with mean values of 4.49, 4.43, 4.43, 4.8, and 4.47 respectively.
Numerical study optimation design of CPU cooling system analysis using CFD method Yudanto, Fajar Dwi; Inderanata, Rochmad Novian; Johan, Arif Bintoro; Setuju, Setuju
Applied Engineering and Technology Vol 2, No 3 (2023): December 2023
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v2i3.1207

Abstract

Computers often experience damage to the CPU, especially the mainboard and processor, due to several factors, including human error or excessive use and environmental conditions. Component placement is frequently utilized to improve the CPU room conditions to keep it cool. This research numerically investigates desktop PC processors and heatsink configurations for mechanical engineering vocational learning. The kind of metal material, number of fans, and fan arrangement were all tested at three levels. The computer components in this research are the CPU, heatsink, fan, and processor—a 65-watt Thermal Design Power (TDP) CPU with a constant air intake speed of 5 m/s. The criteria investigated include metal type (steel, aluminum, and copper), cooling design (horizontal, vertical, and mixed), and fan count (2-4-8). The methods used in this research are the Computational Fluid Dynamics (CFD) method and the Taguchi method to examine fluid flow characteristics and temperature. Numerical results show the maximum temperature is 123 °C in the vertical, eight-fan, and steel configurations. Minimum temperature 39.22 °C in mixed configuration, eight fans, and copper. These findings reveal that the kind of metal material, number of fans, and fan arrangement all impact the CPU cooler and heatsink configuration. However, the Taguchi method can provide a more detailed understanding of configuration.
[AET Volume 2 Nomor 3] Environmental, medical, and educational research sustainability in the age of technology: An editorial review Pranolo, Andri; Hernandez, Leonel; Wibawa, Aji Prasetya
Applied Engineering and Technology Vol 2, No 3 (2023): December 2023
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v2i3.1363

Abstract

The six articles on Applied Engineering and Technology Volume 2 No 3 December 2023 have significant relevance in current engineering and technological developments to the three sectors: Environmental sustainability, Medical, and Education. First, in an era that increasingly pays attention to environmental sustainability, as reflected in efforts to mitigate the environmental impact of the oil and gas industry, Effiom's research on developing bio-based drilling fluid becomes relevant and reflects the industry's efforts to adopt environmentally friendly solutions in the oil and gas exploration process [1]. This research develops and optimizes local pear seed-based biocyte fluid. Throughout the world, oil exploration and exploitation have had severe environmental impacts. So, it is very important to develop drilling fluid for oil exploration. This research optimizes drilling fluids by using biodegradable materials. The optimized drilling fluid contains environmentally friendly and cost-effective characteristics and is expected to be widely used in oil exploration, reducing adverse environmental impacts. Princewill et al. [2] conducted a safety and economic evaluation of boil-off gas (BOG) in global petroleum (LPG) storage tanks. BOG production impacts safety and economic profitability in the liquefied petroleum gas supply chain. This research evaluates BOG production due to heat leaks in storage tanks by analyzing thermodynamic properties and heat transfer equations. The research results show that maintaining isolation and external factors minimizes BOG formation. Therefore, this research provides essential guidance and suggestions for the safety and economic benefits of the liquefied petroleum gas supply chain. Finally, Yudanto et al. [3] used computational fluid dynamics (CFD) and Taguchi methods to calculate the CPU cooling system. The performance and stability of electronic devices are significant for users in today's rapid development of information technology. This study analyzes the impact of different cooling system configurations on CPU temperatures and provides practical insights into electronic thermite design. Through numerical simulations, the research results provide an essential reference for developing computer hardware design. Second, Agughasi and Srinivasiah [4] developed a semisupervised method for characterizing multiple chest X-ray images in the medical field. Accurate marker images are critical for training supervised learning models in medical image handling. However, manually tagging a large number of images requires time and effort. Therefore, this study suggests using unsupervised cluster technology-based K-Means and Self-Organizing Maps to produce reliable images. In this way, medical imaging processing costs can be reduced significantly, speeding up the research and application process. Meanwhile, in the education sector, Mariscal et al. [5] developed the mobile application MobILcaps to improve information literacy for social science students in higher education as a relevant instrument to facilitate teaching. Information literacy is crucial for developing individuals and society in today's information era. Based on cognitive, constructivist, and connectivity theories, this application has provided multimedia resources for students to facilitate independent learning. By working with teachers and students, this application provides practical tools and avenues for increasing students' information literacy levels. In addition, Riva et al. [6] developed AdPisika as an electronic learning system tailored to improve student academic achievement. In today's educational environment, personalized learning is critical to increasing the impact of learning for students. This research, based on learning style models and machine learning algorithms, personally optimizes learning materials, thereby improving students' learning performance. This system has significantly improved students' academic performance through experimental verification, providing practical ways to align education. In conclusion, these studies make essential contributions and provide valuable references and guidance for applying engineering and technology research and practice in the fields of Environmental sustainability, Medical, and Education. Future research could investigate the depth and breadth of these areas and test the feasibility and effectiveness of such research through practical applications and experimental testing. In the context of environmental sustainability potential research includes exploration in the development of bio-based drilling fluid using alternative materials that are more environmentally friendly, research on green technology to reduce the impact of boil-off gas (BOG) in the LPG industry, and research on processor types and system configurations as well as the development of more efficient materials and more innovative cooling technology to improve the performance of the CPU cooling system. In the medical field, deepen semi-supervised labeling methods for medical image processing can focus on developing more sophisticated algorithms and further validation of various medical datasets. Meanwhile, in the educational context, developing broader mobile applications could increase information literacy. It could be useful if it adapted to various disciplines and research on integrating more advanced AI technology for adaptive e-learning systems more effectively.

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