Skin cancer is a common illness that claims thousands of lives annually in the United States alone. Accurately identifying malignant tumors is crucial to survival but can be challenging as the visual distinctions between benign and life-threatening tumors are minimal. The purpose of this project is to explore deep learning algorithms that can be trained to systematically classify skin cancer images, create a program to execute the algorithm, and exemplify an optimization process for the program that can serve as a reference for future works. The project will adopt a transfer learning algorithm based on previous studies on the subject and select a pre-trained model given practical restraints. Then a program will be coded in Python to retrieve datasets, process images, train the model, and evaluate accuracy. Finally, the algorithm will be optimized by tuning model parameters and training restraints. The experiments revealed that the algorithm was able to perform the task with an accuracy of around 70%. Model parameters such as optimizer choice and learning rate and training restraints such as batch size and epoch count have significant impacts on the training results and require precise values for maxima accuracy and minimal overfitting.
{"title":"Skin cancer image classification optimization through transfer learning with Tensorflow and InceptionV3","authors":"Tianyu Cao","doi":"10.1117/12.2672699","DOIUrl":"https://doi.org/10.1117/12.2672699","url":null,"abstract":"Skin cancer is a common illness that claims thousands of lives annually in the United States alone. Accurately identifying malignant tumors is crucial to survival but can be challenging as the visual distinctions between benign and life-threatening tumors are minimal. The purpose of this project is to explore deep learning algorithms that can be trained to systematically classify skin cancer images, create a program to execute the algorithm, and exemplify an optimization process for the program that can serve as a reference for future works. The project will adopt a transfer learning algorithm based on previous studies on the subject and select a pre-trained model given practical restraints. Then a program will be coded in Python to retrieve datasets, process images, train the model, and evaluate accuracy. Finally, the algorithm will be optimized by tuning model parameters and training restraints. The experiments revealed that the algorithm was able to perform the task with an accuracy of around 70%. Model parameters such as optimizer choice and learning rate and training restraints such as batch size and epoch count have significant impacts on the training results and require precise values for maxima accuracy and minimal overfitting.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127001863","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}
Light and small UAVs have attracted widespread attention due to their good adaptability, low cost, and high temporal resolution. With the continuous development of technology, multi-UAV cooperation has become a research hot spot. The route planning problem of multi-UAV cooperation can be decomposed into two sub-problems: task allocation and route planning. In this paper, a task allocation method based on reinforcement learning is proposed for multi-UAV cooperation. Considering the task requirements, the capabilities of the UAV, the influence of the environment and the conflict of the task, we construct a MDP process include the state space, action space, reward function and discount factor with the constraints and optimization functions. In this paper, the task allocation process is combined with the trajectory planning based on maximizing information throughput, and a large number of simulation tests are carried out to verify the stability of the method.
{"title":"Task allocation and route planning in multi-UAV collaboration","authors":"Jian Zhou, Yuhe Qiu","doi":"10.1117/12.2671804","DOIUrl":"https://doi.org/10.1117/12.2671804","url":null,"abstract":"Light and small UAVs have attracted widespread attention due to their good adaptability, low cost, and high temporal resolution. With the continuous development of technology, multi-UAV cooperation has become a research hot spot. The route planning problem of multi-UAV cooperation can be decomposed into two sub-problems: task allocation and route planning. In this paper, a task allocation method based on reinforcement learning is proposed for multi-UAV cooperation. Considering the task requirements, the capabilities of the UAV, the influence of the environment and the conflict of the task, we construct a MDP process include the state space, action space, reward function and discount factor with the constraints and optimization functions. In this paper, the task allocation process is combined with the trajectory planning based on maximizing information throughput, and a large number of simulation tests are carried out to verify the stability of the method.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117029771","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}
The handrail is an important part of the escalator, which moves synchronously with the steps to ensure the safety of passengers. It is one of the common failures of escalator equipment that the handrail is out of synchronization with the step operation. If the handrail is not synchronized with the step operation or even stops running, passengers will fall down. In this paper, a failure case of the driving chain of the escalator handrail is analyzed macroscopically and microscopically. The research results show that the serious wear of the pin shaft and sleeve of the escalator handrail drive chain is the main reason for the handrail drive chain.
{"title":"Failure analysis of drive chain of escalator handrail","authors":"Fa-cai Ren","doi":"10.1117/12.2671825","DOIUrl":"https://doi.org/10.1117/12.2671825","url":null,"abstract":"The handrail is an important part of the escalator, which moves synchronously with the steps to ensure the safety of passengers. It is one of the common failures of escalator equipment that the handrail is out of synchronization with the step operation. If the handrail is not synchronized with the step operation or even stops running, passengers will fall down. In this paper, a failure case of the driving chain of the escalator handrail is analyzed macroscopically and microscopically. The research results show that the serious wear of the pin shaft and sleeve of the escalator handrail drive chain is the main reason for the handrail drive chain.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134337739","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}
To combat the threat posed by "low-small-slow" UAVs, this paper examines the attack modes of UAVs, focusing on single attack and swarm attacks. Based on the performance of the existing mainstream anti-UAV system, the type of UAV attack, and the features of defense, "triangular joint defense" tactics are presented for the usual scene of key point defense. Through UAV single machine and swarm deduction of critical point attacks, it evaluates the defense potential of an anti-UAV system at various attack distances. It designs an emergency response mode to deal with the challenge of short countermeasure time swarm close-range attacks in mind. This research serves as a technical reference for the deployment of key point defense power and the development of anti-UAV measures.
{"title":"Research on key point defense strategies of anti-UAV","authors":"Wei Zhang, Zengli Wang, Qianqian Wang, Na Li, Yuchao Wang, Zhong Wenan","doi":"10.1117/12.2672300","DOIUrl":"https://doi.org/10.1117/12.2672300","url":null,"abstract":"To combat the threat posed by \"low-small-slow\" UAVs, this paper examines the attack modes of UAVs, focusing on single attack and swarm attacks. Based on the performance of the existing mainstream anti-UAV system, the type of UAV attack, and the features of defense, \"triangular joint defense\" tactics are presented for the usual scene of key point defense. Through UAV single machine and swarm deduction of critical point attacks, it evaluates the defense potential of an anti-UAV system at various attack distances. It designs an emergency response mode to deal with the challenge of short countermeasure time swarm close-range attacks in mind. This research serves as a technical reference for the deployment of key point defense power and the development of anti-UAV measures.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"739 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123864460","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}
When the robot grasps the U-shaped snap on the automatic production line, the pose detection and the positioning of the gripping point of the snap should be solved. To solve this problem, we propose the improved algorithm of YOLOv5, which can obtain the rotation angle and gripping point coordinates of the U-shaped snap. Firstly, the training sample angle information is obtained by roLabellmg. Secondly, in order to obtain the predicted angle, the algorithm adds a new angle prediction dimension and replaces the original positive box IOU with the minimum external rectangle IOU of the rotating box containing the angle information when calculating the IOU. Finally, the gripping point coordinates are determined on different poses of the U-shaped snap according to the robotic gripping rules, respectively. On the homemade U-shaped snap data set, the mAP value reaches 91.2%, which proves the effectiveness of the proposed method.
{"title":"Rotating U-shaped snap gripping point positioning method based on YOLOv5","authors":"Jingyang Zhou, Jinbo Lu, Jinling Chen","doi":"10.1117/12.2673007","DOIUrl":"https://doi.org/10.1117/12.2673007","url":null,"abstract":"When the robot grasps the U-shaped snap on the automatic production line, the pose detection and the positioning of the gripping point of the snap should be solved. To solve this problem, we propose the improved algorithm of YOLOv5, which can obtain the rotation angle and gripping point coordinates of the U-shaped snap. Firstly, the training sample angle information is obtained by roLabellmg. Secondly, in order to obtain the predicted angle, the algorithm adds a new angle prediction dimension and replaces the original positive box IOU with the minimum external rectangle IOU of the rotating box containing the angle information when calculating the IOU. Finally, the gripping point coordinates are determined on different poses of the U-shaped snap according to the robotic gripping rules, respectively. On the homemade U-shaped snap data set, the mAP value reaches 91.2%, which proves the effectiveness of the proposed method.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128923843","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}
At present, the common profile processing machine tools have a single function, and the use cost of the machining center series is high. In order to save costs and realize the multi-functional processing of profiles, a profile sawing and milling machine is designed. Mainly study the dynamic characteristics of the machine tool, suppress the vibration of the machine tool, and improve the machining accuracy. Through 3D modeling, ADAMS simulation, changing the thickness of the worktable, adding damping force and other methods, the natural frequency of the machine tool, the milling cutter mechanism and the amplitude of the worktable are obtained, and the structure of the machine tool is optimized. The results show that the resonance frequency of the self-excited vibration of the machine tool is mainly concentrated in the low frequency range of 0.1-100 Hz. The maximum frequency response of the machine tool is 18.19Hz with an amplitude of 39.84mm. The thickness of the worktable is increased by 20%, the maximum frequency response of the machine tool is shifted to the left by 0.41Hz, and the maximum amplitude of the worktable is reduced by 6.15mm. Adding the damping force, the maximum amplitude of the y+ and z- milling cutters is reduced by 3.96mm and 7.33mm respectively. It can be seen that the two optimal designs can effectively suppress the self-excited vibration of the machine tool, improve the machining accuracy, and make the machine tool design structure more completed and feasible.
{"title":"Vibration analysis and optimization design of profile sawing and milling machine tool","authors":"Qing Zhao, Xiaolong Ren","doi":"10.1117/12.2672284","DOIUrl":"https://doi.org/10.1117/12.2672284","url":null,"abstract":"At present, the common profile processing machine tools have a single function, and the use cost of the machining center series is high. In order to save costs and realize the multi-functional processing of profiles, a profile sawing and milling machine is designed. Mainly study the dynamic characteristics of the machine tool, suppress the vibration of the machine tool, and improve the machining accuracy. Through 3D modeling, ADAMS simulation, changing the thickness of the worktable, adding damping force and other methods, the natural frequency of the machine tool, the milling cutter mechanism and the amplitude of the worktable are obtained, and the structure of the machine tool is optimized. The results show that the resonance frequency of the self-excited vibration of the machine tool is mainly concentrated in the low frequency range of 0.1-100 Hz. The maximum frequency response of the machine tool is 18.19Hz with an amplitude of 39.84mm. The thickness of the worktable is increased by 20%, the maximum frequency response of the machine tool is shifted to the left by 0.41Hz, and the maximum amplitude of the worktable is reduced by 6.15mm. Adding the damping force, the maximum amplitude of the y+ and z- milling cutters is reduced by 3.96mm and 7.33mm respectively. It can be seen that the two optimal designs can effectively suppress the self-excited vibration of the machine tool, improve the machining accuracy, and make the machine tool design structure more completed and feasible.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114787317","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}
Implicit discourse relation classification, identifying relationships between arguments without explicit linguistic cues, is a challenging task. Previous studies have shown that connectives are important for recognizing implicit discourse relations. Most previous works applied connective prediction as an auxiliary task to promote knowledge transfer from connectives to labels which did not make full use of the relational mapping information of connectives. In this work, we propose an innovative Connective-aware Interactive Attention (CAIA) joint learning approach. Specifically, we use BERT to predict connectives and incorporate connective information into the interaction of the attention mechanism. Our experimental results on the PDTB dataset show that our approach achieves competitive results compared to recent state-of-the-art systems.
{"title":"Connective-aware interaction attention for implicit discourse relation classification","authors":"Yatian Shen, Ning Liu","doi":"10.1117/12.2672170","DOIUrl":"https://doi.org/10.1117/12.2672170","url":null,"abstract":"Implicit discourse relation classification, identifying relationships between arguments without explicit linguistic cues, is a challenging task. Previous studies have shown that connectives are important for recognizing implicit discourse relations. Most previous works applied connective prediction as an auxiliary task to promote knowledge transfer from connectives to labels which did not make full use of the relational mapping information of connectives. In this work, we propose an innovative Connective-aware Interactive Attention (CAIA) joint learning approach. Specifically, we use BERT to predict connectives and incorporate connective information into the interaction of the attention mechanism. Our experimental results on the PDTB dataset show that our approach achieves competitive results compared to recent state-of-the-art systems.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127449575","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}
SAR systems have played a huge role in ocean monitoring. However, the fast and reliable interpretation of SAR images is still a challenge. SAR image simulations of sea surface for different states facilitates a deeper understanding of the intrinsic scattering mechanism in SAR images. In this paper, based on an improved semi-deterministic facet method, SAR images of different marine environments are simulated by fast calculation of the sea surface scattering field. This approach is no longer sensitive to changes in both cutoff scale and surface element size and is suitable for SAR imaging of large size sea surface. The simulation results reasonably show the effects of the ocean scattering mechanism on the SAR images, which is helpful for the image analysis and interpretation.
{"title":"SAR image simulation of ocean surface based on electromagnetic scattering model","authors":"Tong Wang, Zhaolong Wang, C. Tong","doi":"10.1117/12.2672291","DOIUrl":"https://doi.org/10.1117/12.2672291","url":null,"abstract":"SAR systems have played a huge role in ocean monitoring. However, the fast and reliable interpretation of SAR images is still a challenge. SAR image simulations of sea surface for different states facilitates a deeper understanding of the intrinsic scattering mechanism in SAR images. In this paper, based on an improved semi-deterministic facet method, SAR images of different marine environments are simulated by fast calculation of the sea surface scattering field. This approach is no longer sensitive to changes in both cutoff scale and surface element size and is suitable for SAR imaging of large size sea surface. The simulation results reasonably show the effects of the ocean scattering mechanism on the SAR images, which is helpful for the image analysis and interpretation.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126000042","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}
In order to study the hydrodynamic performance of an aquaculture fish cage, the hydrodynamic model of the cage was established based on the potential flow theory and Morrison equation, and the motion response amplitude operator (RAO) of the cage was analyzed. Based on the quasi-static method, the full chain and three-segment mooring systems are designed respectively. The motion response of the cage under the combined action of wind, wave, and current was calculated and the two mooring schemes were compared. This study shows that the three-segment mooring scheme can effectively reduce the maximum tension of the mooring line and reduce the weight of the mooring line under 50-year extreme environmental loads.
{"title":"Hydrodynamic analysis and design of mooring system for an aquaculture fish cage","authors":"Hongfu Wang, X. Xiang, Gongying Lan, Fuzhen Pang","doi":"10.1117/12.2672219","DOIUrl":"https://doi.org/10.1117/12.2672219","url":null,"abstract":"In order to study the hydrodynamic performance of an aquaculture fish cage, the hydrodynamic model of the cage was established based on the potential flow theory and Morrison equation, and the motion response amplitude operator (RAO) of the cage was analyzed. Based on the quasi-static method, the full chain and three-segment mooring systems are designed respectively. The motion response of the cage under the combined action of wind, wave, and current was calculated and the two mooring schemes were compared. This study shows that the three-segment mooring scheme can effectively reduce the maximum tension of the mooring line and reduce the weight of the mooring line under 50-year extreme environmental loads.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127278031","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}
Fei Wang, Fanyong Cheng, Mingyang Zhang, Hong Zhang
Aiming at the problems of insufficient labeled samples and high missed detection rate in common textured surface anomaly detection, the paper designs a self-supervised learning model based on masked Autoencoder, which can realize accurate detection and location of anomalies without providing mass anomaly samples. Autoencoder is widely used, but it is difficult to detect and locate anomalies by reconstruction error due to its strong generalization ability reconstructed anomalies with small errors. Then, masked reconstruction method is proposed to reduce the generalization performance. First, each input image is masked to obtain multiple masked input images which are sequentially reconstruct by the Autoencoder. Second, these reconstructed images are complementarily masked and recombined to obtain the final reconstructed image. Finally, anomaly detection and localization are achieved by evaluating the reconstruction error between the input and reconstructed image. The experiment results indicate that the anomaly detection rate of this method is 95.09 % and the anomaly location rate is 93.32% under the anomaly detection standard metric，and the performance can be significantly improved.
{"title":"Self-supervised learning for textured surface anomaly detection and localization","authors":"Fei Wang, Fanyong Cheng, Mingyang Zhang, Hong Zhang","doi":"10.1117/12.2673155","DOIUrl":"https://doi.org/10.1117/12.2673155","url":null,"abstract":"Aiming at the problems of insufficient labeled samples and high missed detection rate in common textured surface anomaly detection, the paper designs a self-supervised learning model based on masked Autoencoder, which can realize accurate detection and location of anomalies without providing mass anomaly samples. Autoencoder is widely used, but it is difficult to detect and locate anomalies by reconstruction error due to its strong generalization ability reconstructed anomalies with small errors. Then, masked reconstruction method is proposed to reduce the generalization performance. First, each input image is masked to obtain multiple masked input images which are sequentially reconstruct by the Autoencoder. Second, these reconstructed images are complementarily masked and recombined to obtain the final reconstructed image. Finally, anomaly detection and localization are achieved by evaluating the reconstruction error between the input and reconstructed image. The experiment results indicate that the anomaly detection rate of this method is 95.09 % and the anomaly location rate is 93.32% under the anomaly detection standard metric，and the performance can be significantly improved.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"12596 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129697630","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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