Pub Date : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227244
Shang-Wen Wong, Yu-Chen Chiu, Chi-Yi Tsai
This paper proposes a pose estimation system for robot grasping based on a novel Object Affordance Detection and Segmentation (OADS) network. The proposed system consists of four modules: (1) OADS network; (2) point cloud extraction; (3) object pose estimation; (4) grasp pose estimation. Based on the OADS network, the proposed system achieves affordance-based object pose estimation results. The proposed grasp pose estimation system is evaluated on a laboratory-made dual-arm robot. Experimental results show that the proposed system achieves high detection rate and high accuracy in affordance detection and segmentation tasks, leading to a high success rate in object grasping tasks with lab-made dual-arm robot.
{"title":"A Real-time Affordance-based Object Pose Estimation Approach for Robotic Grasp Pose Estimation","authors":"Shang-Wen Wong, Yu-Chen Chiu, Chi-Yi Tsai","doi":"10.1109/ICSSE58758.2023.10227244","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227244","url":null,"abstract":"This paper proposes a pose estimation system for robot grasping based on a novel Object Affordance Detection and Segmentation (OADS) network. The proposed system consists of four modules: (1) OADS network; (2) point cloud extraction; (3) object pose estimation; (4) grasp pose estimation. Based on the OADS network, the proposed system achieves affordance-based object pose estimation results. The proposed grasp pose estimation system is evaluated on a laboratory-made dual-arm robot. Experimental results show that the proposed system achieves high detection rate and high accuracy in affordance detection and segmentation tasks, leading to a high success rate in object grasping tasks with lab-made dual-arm robot.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132735874","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227213
Thuong Ngo-Phi, N. Nguyen-Quang
Induction heating (IH) converts electrical energy into heat at a high efficiency, allowing fast, and localized heating which is desirable in forging and hardening applications. With power quality standards getting stricter and stricter, the power supply used for induction heating system would need to improve input power factor and input current total harmonics distortion. There have been many topologies and modulation methods proposed to solve this problem. Single-stage and power factor correction (PFC) front-end topologies are attractive due to their low cost, and high performance. Supporting the PFC front-end solution, this paper proposes the use of an active SWISS rectifier and a novel variable pulse density modulation for three-phase input currents shaping, as the first stage of a two-stage IH system, achieving high input power factor, wide power control range, and good efficiency. Simulation and experimental results confirmed the feasibility of the proposed topology and modulation algorithm.
{"title":"Performance Evaluation of Variable Pulse Density Modulation Algorithm in SWISS Rectifier for Induction Heating","authors":"Thuong Ngo-Phi, N. Nguyen-Quang","doi":"10.1109/ICSSE58758.2023.10227213","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227213","url":null,"abstract":"Induction heating (IH) converts electrical energy into heat at a high efficiency, allowing fast, and localized heating which is desirable in forging and hardening applications. With power quality standards getting stricter and stricter, the power supply used for induction heating system would need to improve input power factor and input current total harmonics distortion. There have been many topologies and modulation methods proposed to solve this problem. Single-stage and power factor correction (PFC) front-end topologies are attractive due to their low cost, and high performance. Supporting the PFC front-end solution, this paper proposes the use of an active SWISS rectifier and a novel variable pulse density modulation for three-phase input currents shaping, as the first stage of a two-stage IH system, achieving high input power factor, wide power control range, and good efficiency. Simulation and experimental results confirmed the feasibility of the proposed topology and modulation algorithm.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133529373","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227148
D. Truong, V. Ta, M. N. Thi, V. Ngo, H. Nguyen, Xuan-Hoa Pham Thi
A microgrid system is a distributed energy system that can operate autonomously or connected to the utility grid. It typically consists of renewable energy sources such as solar photovoltaics (PV) and energy storage systems such as batteries. The transient stability of a microgrid system refers to its ability to maintain a stable voltage and frequency when subjected to sudden changes in load or generation. Transient stability can result in system failure or damage to the equipment, which can affect the reliability and resiliency of the system. To address this issue, a new controller has been developed to improve the transient stability of a PV-battery based microgrid system. The proposed Adaptive neuro fuzzy inference system (ANFIS) controller is designed to optimize the power flow between the PV array, battery storage, and load, and to ensure a stable voltage and frequency during sudden changes in the system. The application of this new controller has shown promising results in improving the transient stability of PV-battery based microgrid systems. It has been tested under various operating conditions, including sudden changes in load and solar irradiance, and has demonstrated superior performance compared to traditional control methods such as PID controller.
{"title":"Improving Transient Stability of a PV-battery based Microgrid System","authors":"D. Truong, V. Ta, M. N. Thi, V. Ngo, H. Nguyen, Xuan-Hoa Pham Thi","doi":"10.1109/ICSSE58758.2023.10227148","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227148","url":null,"abstract":"A microgrid system is a distributed energy system that can operate autonomously or connected to the utility grid. It typically consists of renewable energy sources such as solar photovoltaics (PV) and energy storage systems such as batteries. The transient stability of a microgrid system refers to its ability to maintain a stable voltage and frequency when subjected to sudden changes in load or generation. Transient stability can result in system failure or damage to the equipment, which can affect the reliability and resiliency of the system. To address this issue, a new controller has been developed to improve the transient stability of a PV-battery based microgrid system. The proposed Adaptive neuro fuzzy inference system (ANFIS) controller is designed to optimize the power flow between the PV array, battery storage, and load, and to ensure a stable voltage and frequency during sudden changes in the system. The application of this new controller has shown promising results in improving the transient stability of PV-battery based microgrid systems. It has been tested under various operating conditions, including sudden changes in load and solar irradiance, and has demonstrated superior performance compared to traditional control methods such as PID controller.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123628443","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227188
Song-Kyoo (Amang) Kim, U. Wong
This research endeavors to examine the impact of Chat Generative Pre-trained Transformer (ChatGPT) on the education system, specifically in the realm of academia and the challenges that it poses. The incorporation of ChatGPT into academic practices may necessitate a reevaluation of current assessment and evaluation systems. The integration of ChatGPT into the academic world raises important questions regarding the ethics of AI-generated authorship and the implications it has on the value of creative work. This new chatbot has the potential to revolutionize various fields, particularly education and creative works, including art, music, creative writing, and all areas of humanity subjects. The paper presents a qualitative analysis of the implications of ChatGPT on the education system and academic research domain. The future trajectory of this new technology is not unlike that of other previous technological innovations but AI-chatbot technology is expected to reshape the value of knowledge. This study aims to shed light on these pressing issues and present a possible compromise strategy for resolving them.
{"title":"ChatGPT Impacts on Academia","authors":"Song-Kyoo (Amang) Kim, U. Wong","doi":"10.1109/ICSSE58758.2023.10227188","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227188","url":null,"abstract":"This research endeavors to examine the impact of Chat Generative Pre-trained Transformer (ChatGPT) on the education system, specifically in the realm of academia and the challenges that it poses. The incorporation of ChatGPT into academic practices may necessitate a reevaluation of current assessment and evaluation systems. The integration of ChatGPT into the academic world raises important questions regarding the ethics of AI-generated authorship and the implications it has on the value of creative work. This new chatbot has the potential to revolutionize various fields, particularly education and creative works, including art, music, creative writing, and all areas of humanity subjects. The paper presents a qualitative analysis of the implications of ChatGPT on the education system and academic research domain. The future trajectory of this new technology is not unlike that of other previous technological innovations but AI-chatbot technology is expected to reshape the value of knowledge. This study aims to shed light on these pressing issues and present a possible compromise strategy for resolving them.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124750235","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227242
D. C. Huynh, Loc D. Ho, M. Dunnigan, Corina Barbalata
Microgrid is receiving more and more attention, which is considered one of the solutions to efficiently supply electrical energy to loads. During the operation of the microgrid, the power loss and voltage stability of the microgrid are the main indicators to evaluate the operational efficiency. The solution of using distributed generators (DG) is becoming more and more popular to improve the performance of the microgrid. The main challenge of this solution is the determination of the optimal allocation of DGs in the microgrid. This paper proposes a water wave optimization (WWO) algorithm to identify the optimal allocation of DGs in the microgrid for power loss reduction and voltage stability improvement. The WWO algorithm-based achievements are compared with those using a genetic algorithm (GA) and a particle swarm optimization (PSO) algorithm to confirm the effectiveness of the proposal in the minimization of power loss and improvement of voltage stability.
{"title":"Operation Optimization of a Microgrid based on Minimization of Power Loss and Improvement of Voltage Stability","authors":"D. C. Huynh, Loc D. Ho, M. Dunnigan, Corina Barbalata","doi":"10.1109/ICSSE58758.2023.10227242","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227242","url":null,"abstract":"Microgrid is receiving more and more attention, which is considered one of the solutions to efficiently supply electrical energy to loads. During the operation of the microgrid, the power loss and voltage stability of the microgrid are the main indicators to evaluate the operational efficiency. The solution of using distributed generators (DG) is becoming more and more popular to improve the performance of the microgrid. The main challenge of this solution is the determination of the optimal allocation of DGs in the microgrid. This paper proposes a water wave optimization (WWO) algorithm to identify the optimal allocation of DGs in the microgrid for power loss reduction and voltage stability improvement. The WWO algorithm-based achievements are compared with those using a genetic algorithm (GA) and a particle swarm optimization (PSO) algorithm to confirm the effectiveness of the proposal in the minimization of power loss and improvement of voltage stability.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130257939","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227231
Thinh Le Vinh, Huan Tran Thien, Trung Nguyen Huu, S. Bouzefrane
Modern office buildings, apartments, and commercial skyscrapers are designed with advanced evacuation systems to ensure people can evacuate quickly and safely during emergencies, such as natural disasters, terrorism, or explosions. However, older buildings, traditional markets, and crowded areas, such as fairs or music tours, often lack efficient and integrated evacuation systems, relying primarily on exit signal panels that do not provide adequate warnings or alternative escape routes. These areas are particularly vulnerable during emergencies, and thus, this article proposes a new model called TEVAC to address these shortcomings. TEVAC is a highly integrated system that utilizes Fog computing to take advantage of its availability, high performance, and the close proximity of IoT devices to provide a trusted and optimal way to help people evacuate dangerous situations. In addition to smart signs that indicate the best escape routes, TEVAC allows users to rely on their smartphones to find the safest direction using local Wi-Fi and broadband cellular networks, supported by Fog computing. By leveraging these technologies, TEVAC can significantly enhance the evacuation process, particularly in areas that lack modern evacuation systems.
{"title":"TEVAC: Trusted Evacuation System based Fog Computing","authors":"Thinh Le Vinh, Huan Tran Thien, Trung Nguyen Huu, S. Bouzefrane","doi":"10.1109/ICSSE58758.2023.10227231","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227231","url":null,"abstract":"Modern office buildings, apartments, and commercial skyscrapers are designed with advanced evacuation systems to ensure people can evacuate quickly and safely during emergencies, such as natural disasters, terrorism, or explosions. However, older buildings, traditional markets, and crowded areas, such as fairs or music tours, often lack efficient and integrated evacuation systems, relying primarily on exit signal panels that do not provide adequate warnings or alternative escape routes. These areas are particularly vulnerable during emergencies, and thus, this article proposes a new model called TEVAC to address these shortcomings. TEVAC is a highly integrated system that utilizes Fog computing to take advantage of its availability, high performance, and the close proximity of IoT devices to provide a trusted and optimal way to help people evacuate dangerous situations. In addition to smart signs that indicate the best escape routes, TEVAC allows users to rely on their smartphones to find the safest direction using local Wi-Fi and broadband cellular networks, supported by Fog computing. By leveraging these technologies, TEVAC can significantly enhance the evacuation process, particularly in areas that lack modern evacuation systems.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128743318","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}
Medical image segmentation is a crucial first step in the development of healthcare and rehabilitation systems, particularly for the identification and planning of cardiovascular issues. In recent years, convolutional neural networks (CNNs) have produced outstanding results on a number of medical image segmentation tasks. Particularly the U-shaped architecture, also known as U-Net, has been extremely successful and set the de facto standard. U-Net often demonstrates difficulties in clearly expressing long-range dependency, nevertheless, as a result of the innate locality of convolution operations. In this study, we propose a new neural network architecture, namely CPA-Unet for problems involving cardiac image segmentation. The CPA-Unet model, which employs cutting-edge Deep Learning methods, more successfully provides better extraction of features for the segmentation of desired segmented objects, whereas earlier models did not contribute much because they ignored the details of the channel, spatial, and contextualization on big datasets. Our experiments upon this Sunnybrook Cardiac dataset and the ACDC dataset show that CPA-Unet outperforms other modern models in terms of the Dice coefficient and IoU metric, highlighting it’s own applicability for biomedical image segmentation solutions.
{"title":"CPA-Unet: A Solution for Left Ventricle Segmentation from Magnetic Resonance Images","authors":"Ngoc-Tu Vu, Viet-Tien Pham, Van-Truong Pham, Thi-Thao Tran","doi":"10.1109/ICSSE58758.2023.10227237","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227237","url":null,"abstract":"Medical image segmentation is a crucial first step in the development of healthcare and rehabilitation systems, particularly for the identification and planning of cardiovascular issues. In recent years, convolutional neural networks (CNNs) have produced outstanding results on a number of medical image segmentation tasks. Particularly the U-shaped architecture, also known as U-Net, has been extremely successful and set the de facto standard. U-Net often demonstrates difficulties in clearly expressing long-range dependency, nevertheless, as a result of the innate locality of convolution operations. In this study, we propose a new neural network architecture, namely CPA-Unet for problems involving cardiac image segmentation. The CPA-Unet model, which employs cutting-edge Deep Learning methods, more successfully provides better extraction of features for the segmentation of desired segmented objects, whereas earlier models did not contribute much because they ignored the details of the channel, spatial, and contextualization on big datasets. Our experiments upon this Sunnybrook Cardiac dataset and the ACDC dataset show that CPA-Unet outperforms other modern models in terms of the Dice coefficient and IoU metric, highlighting it’s own applicability for biomedical image segmentation solutions.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124474106","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227234
Hoang Minh Vu Nguyen, T. N. Le, N. N. Au, Anh H. Quyen, Trieu Tan Phung, Thai An Nguyen, Phuong Nam Nguyen
The ranking of loads in the Microgrid system plays an important role in handling emergency situations such as power shortage, overload or short circuit. These situations can destabilize the Microgrid system and load shedding solutions must be immediately implemented to keep it stable. In this paper, a method of raking the loads in the Microgrid based on the principle of Moody Chart is presented. This principle is primarily implemented based on the number of votes. The rating of these loads takes the following criteria into account: priority load ratio, maximum power utilization hours and damage costs. The proposed method is applied to the 16-bus Microgrid model and has achieved accurate and reliable results. This ranking result is then used to serve the problem of ranking the load shedding order in the power grid. In addition, this approach can provide utility operators and related professionals with useful information to design and build power systems that meet the complex requirements in terms of operation.
{"title":"Application of Moody Chart Method in Load Ranking in Power System","authors":"Hoang Minh Vu Nguyen, T. N. Le, N. N. Au, Anh H. Quyen, Trieu Tan Phung, Thai An Nguyen, Phuong Nam Nguyen","doi":"10.1109/ICSSE58758.2023.10227234","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227234","url":null,"abstract":"The ranking of loads in the Microgrid system plays an important role in handling emergency situations such as power shortage, overload or short circuit. These situations can destabilize the Microgrid system and load shedding solutions must be immediately implemented to keep it stable. In this paper, a method of raking the loads in the Microgrid based on the principle of Moody Chart is presented. This principle is primarily implemented based on the number of votes. The rating of these loads takes the following criteria into account: priority load ratio, maximum power utilization hours and damage costs. The proposed method is applied to the 16-bus Microgrid model and has achieved accurate and reliable results. This ranking result is then used to serve the problem of ranking the load shedding order in the power grid. In addition, this approach can provide utility operators and related professionals with useful information to design and build power systems that meet the complex requirements in terms of operation.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115636558","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227141
Manh-Tuan Do, Manh-Hung Ha, Duc-Chinh Nguyen, Kim Thai, Quang-Huy Do Ba
This study presents a new method for human detection in UAVs using Yolo backbones transformer. The proposed framework utilizes backbones YoloV8s, SC3T (Based Transformer), with RGB inputs to accurately perceive human detection. Experimental results demonstrate that the proposed method achieves an average accuracy of around 90.0% mAP@0.5 for human detection in the Human UAVs dataset, surpassing the performance of competitive baselines. The superior performance of our Deep Neural Network (DNN) can provide context awareness to UAVs. Furthermore, the proposed method can be easily adapted to detect UAVs in various applications. This work highlights the potential of the Yolo backbones transformer for enhancing human detection in UAVs, demonstrating its superiority over conventional methods. Overall, the proposed framework can pave the way for future research in UAV detection applications. Training code and self-collected Human detection dataset are released in https://github.com/Tyler-Do/Yolov8-Transformer.
{"title":"Human Detection Based Yolo Backbones-Transformer in UAVs","authors":"Manh-Tuan Do, Manh-Hung Ha, Duc-Chinh Nguyen, Kim Thai, Quang-Huy Do Ba","doi":"10.1109/ICSSE58758.2023.10227141","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227141","url":null,"abstract":"This study presents a new method for human detection in UAVs using Yolo backbones transformer. The proposed framework utilizes backbones YoloV8s, SC3T (Based Transformer), with RGB inputs to accurately perceive human detection. Experimental results demonstrate that the proposed method achieves an average accuracy of around 90.0% mAP@0.5 for human detection in the Human UAVs dataset, surpassing the performance of competitive baselines. The superior performance of our Deep Neural Network (DNN) can provide context awareness to UAVs. Furthermore, the proposed method can be easily adapted to detect UAVs in various applications. This work highlights the potential of the Yolo backbones transformer for enhancing human detection in UAVs, demonstrating its superiority over conventional methods. Overall, the proposed framework can pave the way for future research in UAV detection applications. Training code and self-collected Human detection dataset are released in https://github.com/Tyler-Do/Yolov8-Transformer.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121828401","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 : 2023-07-27DOI: 10.1109/ICSSE58758.2023.10227187
Yi-Wen Cheng, Sung-Chih Chen, Cheng-Yi Lin, Ting Yu, Changguo Yang
This research aims to establish a software Programmable Logic Controller (software PLC) solution on the EtherCAT fieldbus environment to comply with Microsoft Windows operating system as an industrial network backbone. Utilizing a built-up socket and its open architecture, the study develops the network backbone based on an underlying open-source code to provide an open and standardized reference architecture which IEC 61131-3 and EtherCAT specifications can be followed-up. A system was thus developed. With the developed system, the integrity of the development was tested using the ST language, which is a standard part defined in the international IEC 61131-3 specifications, to demonstrate that the software PLC concept based on EtherCAT can be realistically embedded finally. The successful embedding meets the standards of IEC 61131.
{"title":"Software PLC on EtherCAT – An Implementation Example","authors":"Yi-Wen Cheng, Sung-Chih Chen, Cheng-Yi Lin, Ting Yu, Changguo Yang","doi":"10.1109/ICSSE58758.2023.10227187","DOIUrl":"https://doi.org/10.1109/ICSSE58758.2023.10227187","url":null,"abstract":"This research aims to establish a software Programmable Logic Controller (software PLC) solution on the EtherCAT fieldbus environment to comply with Microsoft Windows operating system as an industrial network backbone. Utilizing a built-up socket and its open architecture, the study develops the network backbone based on an underlying open-source code to provide an open and standardized reference architecture which IEC 61131-3 and EtherCAT specifications can be followed-up. A system was thus developed. With the developed system, the integrity of the development was tested using the ST language, which is a standard part defined in the international IEC 61131-3 specifications, to demonstrate that the software PLC concept based on EtherCAT can be realistically embedded finally. The successful embedding meets the standards of IEC 61131.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115477908","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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