Advances in Technology Innovation
https://ojs.imeti.org/index.php/AITI
<p style="margin: 0cm 0cm 0pt;"><strong><em>Advances in Technology Innovation</em></strong> (AITI), ISSN 2518-2994 (Online), ISSN 2415-0436 (Print), is an international, multidiscipline, peer-reviewed scholarly journal. The official abbreviated title is <em><strong>Adv. technol. innov.</strong></em> It is dedicated to providing a platform for fast communication between the newest research works on the innovations of Technology & Engineering. </p> <p>AITI is indexed by:</p> <p><span style="color: black; font-family: 'Noto Sans'; font-size: 10.5pt;"><img style="width: 136px; height: 26px;" src="https://ojs.imeti.org/public/site/images/allen/image001.png" alt="" width="171" height="53" /></span> <img src="https://ojs.imeti.org/public/site/images/ijeti/DOAJ4.png" alt="" /> <img src="https://ojs.imeti.org/public/site/images/ijeti/google5.png" alt="" /> <img src="https://ojs.imeti.org/public/site/images/ijeti/CNKI.png" alt="" /> <img src="https://ojs.imeti.org/public/site/images/allen/ProQuest-41.png" /> <img src="https://ojs.imeti.org/public/site/images/ijeti/CAB_ABSTRACTS4.png" alt="" /> <img src="https://ojs.imeti.org/public/site/images/ijeti/Resarch_Bible5.png" alt="" /> <img src="https://ojs.imeti.org/public/site/images/ijeti/WorldCat5.png" alt="" /> <img src="https://ojs.imeti.org/public/site/images/allen/academia-12.png" /> <img src="https://ojs.imeti.org/public/site/images/ijeti/TOCs5.jpg" alt="" /> <img src="https://ojs.imeti.org/public/site/images/allen/Publons-22.5_1.png" /> <img src="https://ojs.imeti.org/public/site/images/allen/crossref3.png" width="92" height="42" /></p> <p style="margin: 0cm 0cm 0pt;"><span style="color: black; font-family: 'Noto Sans'; font-size: 10.5pt;"> Under evaluation of SCI, EI(Compendex), INSPEC, etc.</span></p> <p style="margin: 0cm 0cm 0pt;"> </p>Taiwan Association of Engineering and Technology Innovationen-USAdvances in Technology Innovation2415-0436<hr style="font: 12px/normal Verdana, Arial, Helvetica, sans-serif; color: rgb(0, 0, 0); text-transform: none; text-indent: 0px; letter-spacing: normal; word-spacing: 0px; white-space: normal; cursor: default; widows: 1; font-size-adjust: none; font-stretch: normal; -webkit-text-stroke-width: 0px;"> <p style="line-height: 150%;"><span style="font-family: Times New Roman;">Submission of a manuscript implies: that the work described has not been published before that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication. Authors can retain copyright in their articles with no restrictions. is accepted for publication. Authors can retain copyright of their article with no restrictions.</span></p> <p style="line-height: 150%;"> </p> <p style="line-height: 150%;"><img alt="" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAFAAAAAPCAYAAABzyUiPAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAFiUAABYlAUlSJPAAAAKdSURBVFhH7Zffa1JhGMcfJVjQbP64WBCrpnVZXSj+ATZhsEFB6EXC7qZ05yD8cReMUgsyqC7mbYFBBRUbjLR/QPRiRrPR0KtYg+aPbUGDYPl9PK876FFnuJuDH3h53+d5z3vOeT++7zlHDREd1suQ/4QF1mlEQ/pCo9EcCXz78U0jKyP96TMtvViiaDRKwWBQyrbjdDopk8nQw8cPaPzcOOcuTlwip8NJtWqNY7UBZxColeI2tn9uU/Jlsqc8kEqlyG6307P4cylDVK1VacG/IEXqpaPA5KvXZDKZesoTQPTGtw16/+4Dx7XdKk3PTtPM7AzHaqWjwPxannw+H7dzuRxZLBZestiulUqFa8TIo99qtdLU1BStf13nMUCr1XKuFSx/UQTyNmiN5XQ7Fu1uYweNosD82hfa291jKcDtdnMbN4Y6FouxtHK5zCu0WCzycejb/L7JbYBtjK2tBD+A60VMVt5GjbgbSpLEOPm5ThpFgb/397k2GAy82iBIyMRWRWw2m7nf6/WSy+XiPtB4LzU4OPhDmlPKIjDBVlFi4vKcOA5FTi9J8nOcJIoCz4yOcg15kARZWHEAWxc5SER/KBSiRCLBfUA+qZGR03T4V3mSmGAvCUAcpySk2/he5x0UigKvXb9KOp2uKQ2rLp1O8w1DJmKsSKPRyHnxnMtmszRpmeQ20I/p+fNGCUwQRUlMP8jHC6GDOO9xwVXq12v/DnzyKE5bP7aoVCpJme5Ats1mI8+ch27dvsm5ifMXaPH+Iq0sr3CsJsSP1PEt7Jm7Qzs7v3i1HYdAIECXr1ia8sbO6ml1eVWV8uR0FIh/FPN35ykcDlMkEpGyyjhuOKhQKJD/nl/KNLZv/GlcitRLcwsP6R9sYRbYCIf0D9E/OaEy32Ci2m0AAAAASUVORK5CYII="></p> <p style="line-height: 150%;"><span style="font-family: Times New Roman, Times, serif;">Since Jan. 01, 2019, AITI will publish new articles with Creative Commons Attribution Non-Commercial License, under <a href="https://creativecommons.org/licenses/by-nc/4.0/">The Creative Commons Attribution Non-Commercial 4.0 International (CC BY-NC 4.0) License</a>.<br>The Creative Commons Attribution Non-Commercial (CC-BY-NC) License permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.</span></p> <p style="line-height: 150%;"><span style="font-family: Times New Roman;"> </span></p>Estimating Macronutrient Content of Paddy Soil Based on Near-Infrared Spectroscopy Technology Using Multiple Linear Regression
https://ojs.imeti.org/index.php/AITI/article/view/12683
<p>This study investigates the feasibility of employing near-infrared (NIR) spectroscopy with multiple linear regression (MLR) to estimate macronutrients in paddy soil compared with partial least squares (PLS) and principal component regression (PCR). Seventy-nine soil samples from West Java Province, Indonesia, are subject to conventional nutrient analysis and NIR spectroscopy (1000-2500 nm). The reflectance data undergoes various pretreatment techniques, and MLR models are calibrated using the forward method to achieve correlations exceeding 0.90. The best model calibrations are selected based on high correlation coefficients, determination coefficients, RPD, and low RMSE values. Meanwhile, the comparison of performance MLR is made with the PLS and PCR models. Results indicate that simple MLR models perform less than PLS for all nutrients, better than PCR for nitrogen, and below PCR for phosphorus and potassium. However, MLR reliably estimates soil nitrogen, phosphorus, and potassium content with ratio of performance to deviation (RPD) exceeding 2.0. This study demonstrates the potential of MLR for precise macronutrient estimation in paddy soil.</p>Jonni FirdausUsman AhmadI Wayan BudiastraI Dewa Made Subrata
Copyright (c) 2023 Jonni Firdaus, Usman Ahmad, I Wayan Budiastra, I Dewa Made Subrata
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2024-01-012024-01-0191506410.46604/aiti.2023.12683The Prediction of Low-Rise Building Construction Cost Estimation Using Extreme Learning Machine
https://ojs.imeti.org/index.php/AITI/article/view/12687
<p>This study aims to predict the possibility of low-rise building construction costs by applying machine learning models, and the performance of each model is evaluated and compared with ensemble methods. The artificial neural network (ANN) emerges as the top-performing individual model, attaining an accuracy of 0.891, while multiple linear regression and decision trees follow closely with accuracies of 0.884 and 0.864 respectively. Ensemble methods like maximum voting ensemble (MVE) improve the accuracy beyond individual models with an impressive accuracy rate of 0.924. Meanwhile, the stacking ensemble and averaging ensemble also demonstrate competitive performance with accuracies of 0.883 and 0.871, respectively. These findings can result in more informed decision-making, which is valuable for the real estate industry.</p>Kittisak LathongKittipol Wisaeng
Copyright (c) 2023 Kittisak Lathong, Kittipol Wisaeng
http://creativecommons.org/licenses/by-nc/4.0
2024-01-012024-01-0191122710.46604/aiti.2023.12687Efficient Object Detection and Intelligent Information Display Using YOLOv4-Tiny
https://ojs.imeti.org/index.php/AITI/article/view/12682
<p>This study aims to develop an innovative image recognition and information display approach based on you only look once version 4 (YOLOv4)-tiny framework. The lightweight YOLOv4-tiny model is modified by replacing convolutional modules with Fire modules to further reduce its parameters. Performance reductions are offset by including spatial pyramid pooling, and they also improve the model’s detection ability for objects of various sizes. The pattern analysis, statistical modeling, and computational learning visual object classes (PASCAL VOC) 2012 dataset are used, the proposed modified YOLOv4-tiny architecture achieves a higher mean average precision (mAP) that is 1.59% higher than its unmodified counterpart. This study addresses the need for efficient object detection and recognition on resource-constrained devices by leveraging YOLOv4-tiny, Fire modules, and SPP to achieve accurate image recognition at a low computational cost.</p>Ying-Tung HsiaoJia-Shing SheuHsu Ma
Copyright (c) 2023 Ying-Tung Hsiao, Jia-Shing Sheu, Hsu Ma
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2024-01-012024-01-0191424910.46604/aiti.2023.12682Utilizing Ultra-High Performance Concrete Overlay for Road Pavement Repair and Strengthening Applications
https://ojs.imeti.org/index.php/AITI/article/view/12587
<p>This study aims to develop a new thixotropic ultra-high-performance concrete (UHPC) overlay for the repair and strengthening of damaged hot mix asphalt (HMA) pavements. The overlay is purposely designed to accommodate the roadway slope of up to 10% due to presence of viscosifying agent materials. The original UHPC materials are comprised of granite aggregate, ultra-fine calcium carbonate, shrinkage-reducing admixture, viscosifying agent, and expansive agent. The study is conducted with three sets of samples provided and considers thixotropic and mitigated shrinkage properties through comparing control (non-thixotropic) overlay 1 (thixotropic), and overlay 2 (thixotropic) mixtures. Based on the obtained results, only overlay 1 corresponds to the minimum requirement for pavement rehabilitation, with 160-200 mm flowability and -545.3 µm/m free shrinkage. As a result, an average 50 mm thick overlay 1 is selected to repair a damaged HMA pavement (1800 m<sup>2</sup>), while the field implementation procedures and drawing details are also presented in this paper.</p>Lay Boon TanMilad HafezolghoraniAzman MohamedKhaled GhaediYen Lei Voo
Copyright (c) 2023 Lay Boon Tan, Milad Hafezolghorani, Azman Mohamed, Khaled Ghaedi, Yen Lei Voo
http://creativecommons.org/licenses/by-nc/4.0
2023-09-282023-09-289129030210.46604/aiti.2023.12587Synthesis and Characterization of Phase Change Microcapsules Containing Nano-Graphite
https://ojs.imeti.org/index.php/AITI/article/view/12576
<p>This study uses the sol-gel method to modify the phase change microcapsules. The phase change material (PCM) is encapsulated by a polymer shell to reduce the leakage in the solid-liquid transition. Furthermore, the nano-graphite particle (NGP) is introduced into the shell to increase its thermal conductivity. The particle size and enthalpy value of the obtained microcapsules are approximately 3 μm and 150.3 J/g, respectively. The results show that the encapsulation efficiency of PCM in the prepared microcapsules is increased and the crystallization rate of PCM becomes faster when the NGP is added. The obtained microcapsules and wood flour are incorporated into high-density polyethylene (HDPE) to form a wood-plastic composite (WPC). The results indicate that the tensile and impact strengths of the WPC are 24.1 MPa and 48.7 J/m, respectively. Moreover, it is observed that the addition of these phase-change microcapsules can improve the heat dissipation of HDPE and accelerate the speed of thermal diffusion.</p>Yeng-Fong ShihHong-Hao Chen
Copyright (c) 2023 Yeng-Fong Shih, Hong-Hao Chen
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2024-01-012024-01-0191011110.46604/aiti.2023.12576Challenges and Solutions to Criminal Liability for the Actions of Robots and AI
https://ojs.imeti.org/index.php/AITI/article/view/12038
<p>Civil liability legislation is currently being developed, but little attention has been paid to the issue of criminal liability for the actions of robots. The study describes the generations of robots and points out the concerns about robots’ autonomy. The more autonomy robots obtain, the greater capacity they have for self-learning, yet the more difficulty in proving the failure foreseeability when designing and whether culpability or the elements of a specific crime can be considered. In this study, the tort liability depending on the category of robots is described, and the possible solutions are analyzed. It is shown that there is no need to introduce new criminal law constructions, but to focus on the process of proof. Instead of changing the legal system, it is necessary to create the most detailed audit trail telling about the robot’s actions and surroundings or to have a digital twin of the robot.</p>Vladimír SmejkalJindřich Kodl
Copyright (c) 2023 Vladimír Smejkal, Jindřich Kodl
http://creativecommons.org/licenses/by-nc/4.0
2024-01-012024-01-0191658410.46604/aiti.2023.12038