Pub Date : 2023-08-31DOI: 10.46604/peti.2023.12415
Se-Hyun Lee, Seung-Taek Oh, Jae-Hyun Lim
This study proposes a fade lighting control method to ensure the visual comfort of indoor occupants through gradual illuminance control while saving energy. The illuminance sensor measures the indoor illuminance and calculates the required illuminance for achieving a reference illuminance of 500 Lux. The control illuminance for each lighting is derived based on the required illuminance, and it is confirmed to fall within the threshold range of 20%. The illuminance values and time intervals for fade lighting control are calculated, ensuring that the amount of illuminance adjustment is divided by the size of the threshold range or less. In the performance evaluation, the proposed method (experimental group) was compared with the influence-based control method (control group). The result shows that this fade lighting control method minimizes the visual discomfort of occupants caused by sudden changes in lighting, and the same energy-saving of 11-42% is achieved as the control group.
{"title":"Fade Lighting Control Method for Visual Comfort and Energy Saving","authors":"Se-Hyun Lee, Seung-Taek Oh, Jae-Hyun Lim","doi":"10.46604/peti.2023.12415","DOIUrl":"https://doi.org/10.46604/peti.2023.12415","url":null,"abstract":"This study proposes a fade lighting control method to ensure the visual comfort of indoor occupants through gradual illuminance control while saving energy. The illuminance sensor measures the indoor illuminance and calculates the required illuminance for achieving a reference illuminance of 500 Lux. The control illuminance for each lighting is derived based on the required illuminance, and it is confirmed to fall within the threshold range of 20%. The illuminance values and time intervals for fade lighting control are calculated, ensuring that the amount of illuminance adjustment is divided by the size of the threshold range or less. In the performance evaluation, the proposed method (experimental group) was compared with the influence-based control method (control group). The result shows that this fade lighting control method minimizes the visual discomfort of occupants caused by sudden changes in lighting, and the same energy-saving of 11-42% is achieved as the control group.","PeriodicalId":33402,"journal":{"name":"Proceedings of Engineering and Technology Innovation","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46401084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-31DOI: 10.46604/peti.2023.11997
K. Korniejenko, K. Pławecka, Patrycja Bazan, B. Figiela, B. Kozub, Katarzyna Mróz, M. Łach
This study aims to design and investigate foamed geopolymers as a green material dedicated to the circular economy. For synthesis as raw material, the main waste materials of two Polish coal mines, Wieczorek and Staszic, are applied. Additionally, various foaming methods are employed to utilize the by-product of energy production, especially the fly ash generated by the Skawina power plant. In this study, the main issues addressed are related to the selection of the most appropriate foaming agent and the optimization of the process parameters, including temperature, time, and mixture components. Hydrogen peroxide, aluminum powder, and a commercial foaming agent are selected as foaming agents in this research. During the process of sample preparation, stabilizers are applied in the form of polyglycol and cellulose. Through the conducted test, the results show that hydrogen peroxide and aluminum powder emerged as the two most optimal foaming agents.
{"title":"Green Building Materials for Circular Economy - Geopolymer Foams","authors":"K. Korniejenko, K. Pławecka, Patrycja Bazan, B. Figiela, B. Kozub, Katarzyna Mróz, M. Łach","doi":"10.46604/peti.2023.11997","DOIUrl":"https://doi.org/10.46604/peti.2023.11997","url":null,"abstract":"This study aims to design and investigate foamed geopolymers as a green material dedicated to the circular economy. For synthesis as raw material, the main waste materials of two Polish coal mines, Wieczorek and Staszic, are applied. Additionally, various foaming methods are employed to utilize the by-product of energy production, especially the fly ash generated by the Skawina power plant. In this study, the main issues addressed are related to the selection of the most appropriate foaming agent and the optimization of the process parameters, including temperature, time, and mixture components. Hydrogen peroxide, aluminum powder, and a commercial foaming agent are selected as foaming agents in this research. During the process of sample preparation, stabilizers are applied in the form of polyglycol and cellulose. Through the conducted test, the results show that hydrogen peroxide and aluminum powder emerged as the two most optimal foaming agents.","PeriodicalId":33402,"journal":{"name":"Proceedings of Engineering and Technology Innovation","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45352290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-28DOI: 10.46604/peti.2023.10536
Do Phuoc Thien, Le Hoai Phuong
This study proposes a forward kinematic model for soft actuators that utilize pneumatic control to predict their bending motion, which is simulated using Ansys software. Firstly, a bending motion test is conducted with a 2-air chamber actuator to derive an equation that establishes the relationship between the bending angle and input pressure. Next, a serial model for the overall soft actuator is developed using forward kinematics with the DH method. The angle variables in the soft actuator are then replaced with an equation that relates the deformed angle and compressed air. Finally, the proposed serial model is used to predict the bending motion of 4-air and 6-air chamber actuators, and the results are compared to simulations and real experiments. The comparison shows that the proposed model could accurately predict the bending motion of the real actuators within an acceptable tolerance of 10%.
{"title":"Forward Kinematics Based Prediction for Bending Motion of Soft Pneumatic Actuators with Various Air Chambers","authors":"Do Phuoc Thien, Le Hoai Phuong","doi":"10.46604/peti.2023.10536","DOIUrl":"https://doi.org/10.46604/peti.2023.10536","url":null,"abstract":"This study proposes a forward kinematic model for soft actuators that utilize pneumatic control to predict their bending motion, which is simulated using Ansys software. Firstly, a bending motion test is conducted with a 2-air chamber actuator to derive an equation that establishes the relationship between the bending angle and input pressure. Next, a serial model for the overall soft actuator is developed using forward kinematics with the DH method. The angle variables in the soft actuator are then replaced with an equation that relates the deformed angle and compressed air. Finally, the proposed serial model is used to predict the bending motion of 4-air and 6-air chamber actuators, and the results are compared to simulations and real experiments. The comparison shows that the proposed model could accurately predict the bending motion of the real actuators within an acceptable tolerance of 10%.","PeriodicalId":33402,"journal":{"name":"Proceedings of Engineering and Technology Innovation","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42689434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-28DOI: 10.46604/peti.2023.10200
V. S. Kulkarni, S. Chorage
Nanometer-sized carbon particulates generated by incomplete combustion in heavy-duty vehicles are harmful to human health. A high-resolution technique is needed to detect and measure these pollutants. This study aims to optimize a capacitive sensor design for detecting and measuring particulates. Firstly, the effect of design parameters on particulate detection and sensor compliance sensitivity is investigated by using the finite element method. By comparing the simulation results with literature findings for performance validation, the sensor structure is optimized to detect lower particulate concentrations. The simulation result shows that particulate detection sensitivity has linear variations with changes in particulate mass. With optimum electrode spacing and top insulation layer thickness of 5 µm, the sensor can detect a particulate deposition of 0.033 mg/min and generate a maximum capacitance of 581 pF. Since the optimized design can measure particulate deposition at a lower range and with higher sensitivity, it is suitable to be applied to detect nanometer-sized carbon particulates.
{"title":"Design Optimization of a Capacitive Sensor for Mass Measurement of Nanometer-Sized Exhaust Carbon Particles","authors":"V. S. Kulkarni, S. Chorage","doi":"10.46604/peti.2023.10200","DOIUrl":"https://doi.org/10.46604/peti.2023.10200","url":null,"abstract":"Nanometer-sized carbon particulates generated by incomplete combustion in heavy-duty vehicles are harmful to human health. A high-resolution technique is needed to detect and measure these pollutants. This study aims to optimize a capacitive sensor design for detecting and measuring particulates. Firstly, the effect of design parameters on particulate detection and sensor compliance sensitivity is investigated by using the finite element method. By comparing the simulation results with literature findings for performance validation, the sensor structure is optimized to detect lower particulate concentrations. The simulation result shows that particulate detection sensitivity has linear variations with changes in particulate mass. With optimum electrode spacing and top insulation layer thickness of 5 µm, the sensor can detect a particulate deposition of 0.033 mg/min and generate a maximum capacitance of 581 pF. Since the optimized design can measure particulate deposition at a lower range and with higher sensitivity, it is suitable to be applied to detect nanometer-sized carbon particulates.","PeriodicalId":33402,"journal":{"name":"Proceedings of Engineering and Technology Innovation","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48329644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-28DOI: 10.46604/peti.2023.11150
Min-Joon Choi, Je-Hong Park, Min-Seok Jie, Won-Hyuk Choi
This study aims to develop an appropriate chaff dispensing program to deceive the target tracking radar (TTR) effectively. Chaff is a countermeasure commonly used by fighter aircraft to deceive TTR. However, there has been a lack of methodology for calculating chaff dispense programs that take into account the specific characteristics of the fighter, chaff, and TTR. This study proposes a methodology that considers these variables to calculate chaff dispense programs and addresses this gap. The proposed method is demonstrated through TESS engagement, which shows its effectiveness in various engagement situations.
{"title":"Development of a Chaff Dispense Program for Target Tracking Radar Deception","authors":"Min-Joon Choi, Je-Hong Park, Min-Seok Jie, Won-Hyuk Choi","doi":"10.46604/peti.2023.11150","DOIUrl":"https://doi.org/10.46604/peti.2023.11150","url":null,"abstract":"This study aims to develop an appropriate chaff dispensing program to deceive the target tracking radar (TTR) effectively. Chaff is a countermeasure commonly used by fighter aircraft to deceive TTR. However, there has been a lack of methodology for calculating chaff dispense programs that take into account the specific characteristics of the fighter, chaff, and TTR. This study proposes a methodology that considers these variables to calculate chaff dispense programs and addresses this gap. The proposed method is demonstrated through TESS engagement, which shows its effectiveness in various engagement situations.","PeriodicalId":33402,"journal":{"name":"Proceedings of Engineering and Technology Innovation","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44556357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-28DOI: 10.46604/peti.2023.10594
Suvodip Som, Pritam Kumar Gayen, Sudip Das
Automatic license plate recognition (ALPR) systems are widely used for various applications, including traffic control, law enforcement, and toll collection. However, the performance of ALPR systems is often compromised in challenging weather and lighting conditions. This research aims to improve the effectiveness of ALPR systems in foggy, low-light, and rainy weather conditions using a hybrid preprocessing methodology. The research proposes the combination of dark channel prior (DCP), non-local means denoising (NMD) technique, and adaptive histogram equalization (AHE) algorithms in CIELAB color space. And used the Python programming language comparisons for SSIM and PSNR performance. The results showed that this hybrid approach is not merely robust to a variety of challenging conditions, including challenging weather and lighting conditions but significantly more accurate for existing ALPR systems.
{"title":"Improved Preprocessing Strategy under Different Obscure Weather Conditions for Augmenting Automatic License Plate Recognition","authors":"Suvodip Som, Pritam Kumar Gayen, Sudip Das","doi":"10.46604/peti.2023.10594","DOIUrl":"https://doi.org/10.46604/peti.2023.10594","url":null,"abstract":"Automatic license plate recognition (ALPR) systems are widely used for various applications, including traffic control, law enforcement, and toll collection. However, the performance of ALPR systems is often compromised in challenging weather and lighting conditions. This research aims to improve the effectiveness of ALPR systems in foggy, low-light, and rainy weather conditions using a hybrid preprocessing methodology. The research proposes the combination of dark channel prior (DCP), non-local means denoising (NMD) technique, and adaptive histogram equalization (AHE) algorithms in CIELAB color space. And used the Python programming language comparisons for SSIM and PSNR performance. The results showed that this hybrid approach is not merely robust to a variety of challenging conditions, including challenging weather and lighting conditions but significantly more accurate for existing ALPR systems.","PeriodicalId":33402,"journal":{"name":"Proceedings of Engineering and Technology Innovation","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41455372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aims to design a circularly polarized compact antenna using characteristic mode analysis (CMA). The proposed antenna consists of a substrate with a slotted annular ring-shaped patch and partial ground. The excitation position of the antenna and its optimal dimensions are determined through the analysis of different operation modes with CMA. After that, an optimized antenna is designed, and an antenna prototype is fabricated for validation. The experimental results show that the reflection coefficient achieves a -10dB impedance bandwidth of 6.85 GHz, a 3dB-axial ratio bandwidth of 0.7 GHz, and a peak gain of 3.2 dBi. These characteristics agree with simulations and make the circularly polarized compact antenna suit for C-band and sub-6 GHz 5G wireless applications.
{"title":"Compact Circularly Polarized Monopole Antenna Using Characteristic Mode Analysis","authors":"Samineni Peddakrishna, Lulu Wang, Vamshi Kollipara, Jayendra Kumar","doi":"10.46604/peti.2023.11274","DOIUrl":"https://doi.org/10.46604/peti.2023.11274","url":null,"abstract":"This study aims to design a circularly polarized compact antenna using characteristic mode analysis (CMA). The proposed antenna consists of a substrate with a slotted annular ring-shaped patch and partial ground. The excitation position of the antenna and its optimal dimensions are determined through the analysis of different operation modes with CMA. After that, an optimized antenna is designed, and an antenna prototype is fabricated for validation. The experimental results show that the reflection coefficient achieves a -10dB impedance bandwidth of 6.85 GHz, a 3dB-axial ratio bandwidth of 0.7 GHz, and a peak gain of 3.2 dBi. These characteristics agree with simulations and make the circularly polarized compact antenna suit for C-band and sub-6 GHz 5G wireless applications.","PeriodicalId":33402,"journal":{"name":"Proceedings of Engineering and Technology Innovation","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41330944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Magnetic resonance imaging (MRI) combined with artificial intelligence (AI) algorithms to detect brain tumors is one of the important medical applications. In this study, a Convolutional neural network (CNN) model is proposed to detect meningioma and pituitary, which was tested with a dataset consisting of two categories of tumors with 1,800 MRI images from several persons. The CNN model is trained via a Python library, namely TensorFlow, with an automatic tuning approach to obtain the highest testing accuracy of tumor detection. The CNN model used Python programming language in Google Colab to detect sensitivity, precision, the area under the PR and receiver operating characteristic (ROC), error matrix, and accuracy. The results show that the proposed CNN model has a high performance in the detection of brain tumors. It achieves an accuracy of 95.78% and a weighted average precision of 95.82%.
{"title":"A Convolutional Neural Network for Automatic Brain Tumor Detection","authors":"Saeed Mohsen, Wael Mohamed Fawaz Abdel-Rehim, Ahmed Emam, Hossam Mohamed Kasem","doi":"10.46604/peti.2023.10307","DOIUrl":"https://doi.org/10.46604/peti.2023.10307","url":null,"abstract":"Magnetic resonance imaging (MRI) combined with artificial intelligence (AI) algorithms to detect brain tumors is one of the important medical applications. In this study, a Convolutional neural network (CNN) model is proposed to detect meningioma and pituitary, which was tested with a dataset consisting of two categories of tumors with 1,800 MRI images from several persons. The CNN model is trained via a Python library, namely TensorFlow, with an automatic tuning approach to obtain the highest testing accuracy of tumor detection. The CNN model used Python programming language in Google Colab to detect sensitivity, precision, the area under the PR and receiver operating characteristic (ROC), error matrix, and accuracy. The results show that the proposed CNN model has a high performance in the detection of brain tumors. It achieves an accuracy of 95.78% and a weighted average precision of 95.82%.","PeriodicalId":33402,"journal":{"name":"Proceedings of Engineering and Technology Innovation","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49002925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study proposes a computer vision and machine learning (ML)-based approach to classify gender and breed in native chicken production industries with minimal human intervention. The supervised ML and feature extraction algorithms are utilized to classify eleven Indian chicken breeds, with 17,600 training samples and 4,400 testing samples (80:20 ratio). The gray-level co-occurrence matrix (GLCM) algorithm is applied for feature extraction, and the principle component analysis (PCA) algorithm is used for feature selection. Among the tested 27 classifiers, the FG-SVM, F-KNN, and W-KNN classifiers obtain more than 90% accuracy, with individual accuracies of 90.1%, 99.1%, and 99.1%. The BT classifier performs well in gender and breed classification work, achieving accuracy, precision, sensitivity, and F-scores of 99.3%, 90.2%, 99.4%, and 99.5%, respectively, and a mean absolute error of 0.7.
{"title":"An Effective Supervised Machine Learning Approach for Indian Native Chicken’s Gender and Breed Classification","authors":"Thavamani Subramani, Vijayakumar Jeganathan, Sruthi Kunkuma, Balasubramanian","doi":"10.46604/peti.2023.11361","DOIUrl":"https://doi.org/10.46604/peti.2023.11361","url":null,"abstract":"This study proposes a computer vision and machine learning (ML)-based approach to classify gender and breed in native chicken production industries with minimal human intervention. The supervised ML and feature extraction algorithms are utilized to classify eleven Indian chicken breeds, with 17,600 training samples and 4,400 testing samples (80:20 ratio). The gray-level co-occurrence matrix (GLCM) algorithm is applied for feature extraction, and the principle component analysis (PCA) algorithm is used for feature selection. Among the tested 27 classifiers, the FG-SVM, F-KNN, and W-KNN classifiers obtain more than 90% accuracy, with individual accuracies of 90.1%, 99.1%, and 99.1%. The BT classifier performs well in gender and breed classification work, achieving accuracy, precision, sensitivity, and F-scores of 99.3%, 90.2%, 99.4%, and 99.5%, respectively, and a mean absolute error of 0.7.","PeriodicalId":33402,"journal":{"name":"Proceedings of Engineering and Technology Innovation","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47121218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-28DOI: 10.46604/peti.2023.11525
W. Boonchouytan, J. Chatthong, Nantapong Pongpiriyadecha
This study aims to develop the mixing and pressing processes of split-gill mushroom spawn blocks through the development and construction of a semi-automatic mushroom spawn mixing. The developed machine uses a 0.5 hp motor to drive the mixing tank and the press cylinder, which are connected to a 1:60 reduction gear. The results show that the semi-automatic mushroom spawns mixing and pressing machine developed in this study are within the standard ranges, that the split-gill mushroom spawn blocks with an average weight of 598 g, an average height of 10.2 cm, and an average density of 0.33 g/cm3. As for production capacity, manual pressing produced 40 mushroom spawn blocks per hour while the developed machine produced 112 mushroom spawn blocks per hour, which is 2.8 times faster.
{"title":"Development of Mixing and Pressing Processes of Split-Gill Mushroom Spawn Blocks","authors":"W. Boonchouytan, J. Chatthong, Nantapong Pongpiriyadecha","doi":"10.46604/peti.2023.11525","DOIUrl":"https://doi.org/10.46604/peti.2023.11525","url":null,"abstract":"This study aims to develop the mixing and pressing processes of split-gill mushroom spawn blocks through the development and construction of a semi-automatic mushroom spawn mixing. The developed machine uses a 0.5 hp motor to drive the mixing tank and the press cylinder, which are connected to a 1:60 reduction gear. The results show that the semi-automatic mushroom spawns mixing and pressing machine developed in this study are within the standard ranges, that the split-gill mushroom spawn blocks with an average weight of 598 g, an average height of 10.2 cm, and an average density of 0.33 g/cm3. As for production capacity, manual pressing produced 40 mushroom spawn blocks per hour while the developed machine produced 112 mushroom spawn blocks per hour, which is 2.8 times faster.","PeriodicalId":33402,"journal":{"name":"Proceedings of Engineering and Technology Innovation","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45888497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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