Pub Date : 2020-07-20DOI: 10.1109/INDIN45582.2020.9442174
Wanlu Zhu, Jian Shi, Pengfei Zhi, Ye Yang, Xiaoguang Wei, G. Lim
In the recent years, the automatous operation of All Electric Ships (AES) has gained a lot of attention from both academia and industrial researchers as one of the most promising prospects for the transformational control development of new generation electric ships. In this paper, the reconfiguration problem of shipboard power system (SPS) considering external threats is investigated from the perspective of hybrid and distributed. By constructing a two-layer distributed control framework, mission commands are interpreted by coordinator and then send to zonal controllers, while reconfiguration actions can be performed in-zone by zonal controllers or among multi-zones by coordinator to complete the mission. Based on the extended hybrid model of SPS developed, the subsystem reconfiguration and coordinate algorithm are proposed. Finally the practical example of SPS facing threats is provided to illustrate the process to choose the optimal reconfiguration strategy.
{"title":"Mission Based Reconfiguration for Hybrid Shipboard Power Systems Considering Threats*","authors":"Wanlu Zhu, Jian Shi, Pengfei Zhi, Ye Yang, Xiaoguang Wei, G. Lim","doi":"10.1109/INDIN45582.2020.9442174","DOIUrl":"https://doi.org/10.1109/INDIN45582.2020.9442174","url":null,"abstract":"In the recent years, the automatous operation of All Electric Ships (AES) has gained a lot of attention from both academia and industrial researchers as one of the most promising prospects for the transformational control development of new generation electric ships. In this paper, the reconfiguration problem of shipboard power system (SPS) considering external threats is investigated from the perspective of hybrid and distributed. By constructing a two-layer distributed control framework, mission commands are interpreted by coordinator and then send to zonal controllers, while reconfiguration actions can be performed in-zone by zonal controllers or among multi-zones by coordinator to complete the mission. Based on the extended hybrid model of SPS developed, the subsystem reconfiguration and coordinate algorithm are proposed. Finally the practical example of SPS facing threats is provided to illustrate the process to choose the optimal reconfiguration strategy.","PeriodicalId":185948,"journal":{"name":"2020 IEEE 18th International Conference on Industrial Informatics (INDIN)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128932323","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 : 2020-07-20DOI: 10.1109/INDIN45582.2020.9442143
David Heik, Javad Ghofrani, Dirk Reichelt
Being successful and competitive on the market means that companies have to adapt to the demands of their customers. Personalised products are increasingly becoming a matter of course for consumers, which leads to a reduction in the number of similar orders for manufacturing companies. To satisfy these requirements, new information and communication technologies are needed in industrial manufacturing. Industry 4.0 aims to address these challenges. However, many approaches are not yet implemented or mature, so there is a need for further research in this field. For this reason, a comprehensive and systematic mapping study was conducted to structure and categorize the current state of research in the field of self-describing and self-organizing manufacturing. The literature considered was published between January 2014 and May 2019. The research carried out is based on the guidelines for conducting systematic mapping studies. With regard to the technical implementation of this technology, a number of research questions are carefully defined. Based on these questions, data from different levels of information are extracted and analyzed for the considered papers. The study results show in which areas more work is required and where there are future research perspectives. Furthermore, this study can help to better understand the field of research and the research gaps identified.
{"title":"Adaptive Management Shell for Mapping the Process Capability of Manufacturing Components: A Systematic Mapping Study","authors":"David Heik, Javad Ghofrani, Dirk Reichelt","doi":"10.1109/INDIN45582.2020.9442143","DOIUrl":"https://doi.org/10.1109/INDIN45582.2020.9442143","url":null,"abstract":"Being successful and competitive on the market means that companies have to adapt to the demands of their customers. Personalised products are increasingly becoming a matter of course for consumers, which leads to a reduction in the number of similar orders for manufacturing companies. To satisfy these requirements, new information and communication technologies are needed in industrial manufacturing. Industry 4.0 aims to address these challenges. However, many approaches are not yet implemented or mature, so there is a need for further research in this field. For this reason, a comprehensive and systematic mapping study was conducted to structure and categorize the current state of research in the field of self-describing and self-organizing manufacturing. The literature considered was published between January 2014 and May 2019. The research carried out is based on the guidelines for conducting systematic mapping studies. With regard to the technical implementation of this technology, a number of research questions are carefully defined. Based on these questions, data from different levels of information are extracted and analyzed for the considered papers. The study results show in which areas more work is required and where there are future research perspectives. Furthermore, this study can help to better understand the field of research and the research gaps identified.","PeriodicalId":185948,"journal":{"name":"2020 IEEE 18th International Conference on Industrial Informatics (INDIN)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127567330","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 : 2020-07-20DOI: 10.1109/INDIN45582.2020.9442138
Husain Kanchwala, Jasvir Singh Dhillon
Off-Road Environment Simulator (ORES) is a realtime Hardware-in-the-Loop (HIL) platform to simulate the dynamic characteristics of off-road vehicles. This paper focuses on the model development and validation of an All-Wheel-Drive (AWD) vehicle on the ORES test rig. Off-road vehicles primarily operate on bumpy terrains and are subjected to different ground excitations. This results in non-unique resistive wheel torques because of differences in ground friction conditions and wheel loads. If engine torque is not distributed in accordance with resistive wheel torques, it may lead to transmission windup resulting in failure of various driveline components. The purpose of this platform is to reduce transmission development time by replacing field trials with lab testing. The vehicle is driven over a rectangular bump in rig simulation. For these discontinuous short-wavelength ground excitations, terrain enveloping plays a significant role in determining effective ground excitation. An effective terrain profile is obtained using a two-point follower technique. These ground excitations are given as inputs to a detailed seven degree of freedom vehicle ride model which calculates the wheel loads. The ride model is then integrated with longitudinal dynamics, tire, driveline and test-rig models. Vehicle axle acceleration, wheel speed and drive torque responses are measured for validating the simulation results against rig trials. The match is fairly well which validates the suitability of the proposed modeling approach.
{"title":"A real-time hardware-in-the-loop vehicle simulator","authors":"Husain Kanchwala, Jasvir Singh Dhillon","doi":"10.1109/INDIN45582.2020.9442138","DOIUrl":"https://doi.org/10.1109/INDIN45582.2020.9442138","url":null,"abstract":"Off-Road Environment Simulator (ORES) is a realtime Hardware-in-the-Loop (HIL) platform to simulate the dynamic characteristics of off-road vehicles. This paper focuses on the model development and validation of an All-Wheel-Drive (AWD) vehicle on the ORES test rig. Off-road vehicles primarily operate on bumpy terrains and are subjected to different ground excitations. This results in non-unique resistive wheel torques because of differences in ground friction conditions and wheel loads. If engine torque is not distributed in accordance with resistive wheel torques, it may lead to transmission windup resulting in failure of various driveline components. The purpose of this platform is to reduce transmission development time by replacing field trials with lab testing. The vehicle is driven over a rectangular bump in rig simulation. For these discontinuous short-wavelength ground excitations, terrain enveloping plays a significant role in determining effective ground excitation. An effective terrain profile is obtained using a two-point follower technique. These ground excitations are given as inputs to a detailed seven degree of freedom vehicle ride model which calculates the wheel loads. The ride model is then integrated with longitudinal dynamics, tire, driveline and test-rig models. Vehicle axle acceleration, wheel speed and drive torque responses are measured for validating the simulation results against rig trials. The match is fairly well which validates the suitability of the proposed modeling approach.","PeriodicalId":185948,"journal":{"name":"2020 IEEE 18th International Conference on Industrial Informatics (INDIN)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121272824","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 : 2020-07-20DOI: 10.1109/INDIN45582.2020.9442227
Zhiyu Zhu, Shiyu Cui
Due to the strict data conditions of machine learning for fault diagnosis, the application of fault diagnostic method based on the transfer kernel locality preserving projection is proposed. It solves the seawater pump's problem of low diagnostic accuracy due to insufficient fault samples and complex and variable operating conditions. This method uses the vibration signal of seawater pumps as the object, and the historical data came from different working conditions of the pump to prepare for the proposed model. By preserving the prior distribution structure of seawater pumps fault training data, the fault data is mapped into high-dimensional space. Then, transfer learning minimizes the distribution discrepancy between different datasets by the maximum mean discrepancy (MMD) in the Hilbert space. By this means, the samples with same class in different datasets could cluster together. Resulting with a classifier SVM trained to diagnose the fault class of the seawater pump by the different datasets combined. Through experiments, the results show that the proposed algorithm is effective, having better diagnostic accuracy than several learning algorithms.
{"title":"Fault diagnosis of seawater pump based on transfer kernel locality preserving projection","authors":"Zhiyu Zhu, Shiyu Cui","doi":"10.1109/INDIN45582.2020.9442227","DOIUrl":"https://doi.org/10.1109/INDIN45582.2020.9442227","url":null,"abstract":"Due to the strict data conditions of machine learning for fault diagnosis, the application of fault diagnostic method based on the transfer kernel locality preserving projection is proposed. It solves the seawater pump's problem of low diagnostic accuracy due to insufficient fault samples and complex and variable operating conditions. This method uses the vibration signal of seawater pumps as the object, and the historical data came from different working conditions of the pump to prepare for the proposed model. By preserving the prior distribution structure of seawater pumps fault training data, the fault data is mapped into high-dimensional space. Then, transfer learning minimizes the distribution discrepancy between different datasets by the maximum mean discrepancy (MMD) in the Hilbert space. By this means, the samples with same class in different datasets could cluster together. Resulting with a classifier SVM trained to diagnose the fault class of the seawater pump by the different datasets combined. Through experiments, the results show that the proposed algorithm is effective, having better diagnostic accuracy than several learning algorithms.","PeriodicalId":185948,"journal":{"name":"2020 IEEE 18th International Conference on Industrial Informatics (INDIN)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115417239","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 : 2020-07-20DOI: 10.1109/INDIN45582.2020.9442146
Yanmin Zhu, C. Yeung, E. Lam
Micro-objects, such as microplastics and particulate pollution, need to be accurately observed and detected by high-precision optical systems. Digital holography is a powerful tool to detect such microscopic objects. However, traditional digital holography requires additional image processing such as phase unwrapping, de-noising, and refocusing, which costs a lot of time and does not have a consistently better performance in micro-object detection. Here, we propose an intelligent holographic classifier, which is a deep learning-based lensless inline digital holography system to detect the micro-object directly on the raw holograms and show the quantitative information of micro-objects for individual hologram by automatic object classification. In a demonstration where we capture the holograms of microplastics particles, which are easily confused with dust particles, we arrive at an accuracy above 97%. Compared with other leading classifiers, our method has shorter training time, faster classification and quantitative analysis, higher accuracy, and better robustness. Furthermore, this intelligent digital holography system, which requires only a light-emitting diode (LED), a sample slide, and a CMOS camera, can be used as a portable low-cost microplastics counting and classification tool, driving the development of microplastics detection in the ecological environment.
{"title":"Holographic Classifier: Deep Learning in Digital Holography for Automatic Micro-objects Classification","authors":"Yanmin Zhu, C. Yeung, E. Lam","doi":"10.1109/INDIN45582.2020.9442146","DOIUrl":"https://doi.org/10.1109/INDIN45582.2020.9442146","url":null,"abstract":"Micro-objects, such as microplastics and particulate pollution, need to be accurately observed and detected by high-precision optical systems. Digital holography is a powerful tool to detect such microscopic objects. However, traditional digital holography requires additional image processing such as phase unwrapping, de-noising, and refocusing, which costs a lot of time and does not have a consistently better performance in micro-object detection. Here, we propose an intelligent holographic classifier, which is a deep learning-based lensless inline digital holography system to detect the micro-object directly on the raw holograms and show the quantitative information of micro-objects for individual hologram by automatic object classification. In a demonstration where we capture the holograms of microplastics particles, which are easily confused with dust particles, we arrive at an accuracy above 97%. Compared with other leading classifiers, our method has shorter training time, faster classification and quantitative analysis, higher accuracy, and better robustness. Furthermore, this intelligent digital holography system, which requires only a light-emitting diode (LED), a sample slide, and a CMOS camera, can be used as a portable low-cost microplastics counting and classification tool, driving the development of microplastics detection in the ecological environment.","PeriodicalId":185948,"journal":{"name":"2020 IEEE 18th International Conference on Industrial Informatics (INDIN)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115455308","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}
From the mutual empowerment of two high-speed development technologies: artificial intelligence and edge computing, we propose a tailored Edge Intelligent Video Surveillance (EIVS) system. It is a scalable edge computing architecture and uses multitask deep learning for relevant computer vision tasks. Due to the potential application of different surveillance devices are widely different, we adopt a smart IoT module to normalize the video data of different cameras, thus the EIVS system can conveniently found proper data for a specific task. In addition, the deep learning models can be deployed at every EIVS nodes, to make computer vision tasks on the normalized data. Meanwhile, due to the training and deploying of deep learning model are usually separated, for the related tasks in the same scenario, we propose to collaboratively train the depth learning models in a multitask paradigm on the cloud server. The simulation results on the publicly available datasets show that the system continuously supports intelligent monitoring tasks, has good scalability, and can improve performance through multitask learning.
{"title":"Multitask Deep Learning for Edge Intelligence Video Surveillance System","authors":"Jiawei Li, Zhilong Zheng, Yiming Li, Rubao Ma, Shutao Xia","doi":"10.1109/INDIN45582.2020.9442166","DOIUrl":"https://doi.org/10.1109/INDIN45582.2020.9442166","url":null,"abstract":"From the mutual empowerment of two high-speed development technologies: artificial intelligence and edge computing, we propose a tailored Edge Intelligent Video Surveillance (EIVS) system. It is a scalable edge computing architecture and uses multitask deep learning for relevant computer vision tasks. Due to the potential application of different surveillance devices are widely different, we adopt a smart IoT module to normalize the video data of different cameras, thus the EIVS system can conveniently found proper data for a specific task. In addition, the deep learning models can be deployed at every EIVS nodes, to make computer vision tasks on the normalized data. Meanwhile, due to the training and deploying of deep learning model are usually separated, for the related tasks in the same scenario, we propose to collaboratively train the depth learning models in a multitask paradigm on the cloud server. The simulation results on the publicly available datasets show that the system continuously supports intelligent monitoring tasks, has good scalability, and can improve performance through multitask learning.","PeriodicalId":185948,"journal":{"name":"2020 IEEE 18th International Conference on Industrial Informatics (INDIN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132413783","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 : 2020-07-20DOI: 10.1109/INDIN45582.2020.9442131
Rafael Pischke Garske, E. P. Freitas, R. V. Henriques
Urban mobility is one of the main problems faced by big cities. The electric multiple unit (EMU) is the best alternative since it transports a high volume of people at a low cost. Failures during operation cause delays and inconvenience for passengers and operators. This article deals with failures in DC traction motors and their control systems in a transport company operating urban trains. The study focuses on identifying the main causes and consequences of these failures through a statistical analysis. Initially, the study proposes multidimensional scaling to analyze these observations and concludes with the use of neural networks. The acquired results are useful for actions in traction motors during preventive maintenance and in corrective maintenance.
{"title":"Failure history analysis using multidimensional scaling and neural networks in railway systems","authors":"Rafael Pischke Garske, E. P. Freitas, R. V. Henriques","doi":"10.1109/INDIN45582.2020.9442131","DOIUrl":"https://doi.org/10.1109/INDIN45582.2020.9442131","url":null,"abstract":"Urban mobility is one of the main problems faced by big cities. The electric multiple unit (EMU) is the best alternative since it transports a high volume of people at a low cost. Failures during operation cause delays and inconvenience for passengers and operators. This article deals with failures in DC traction motors and their control systems in a transport company operating urban trains. The study focuses on identifying the main causes and consequences of these failures through a statistical analysis. Initially, the study proposes multidimensional scaling to analyze these observations and concludes with the use of neural networks. The acquired results are useful for actions in traction motors during preventive maintenance and in corrective maintenance.","PeriodicalId":185948,"journal":{"name":"2020 IEEE 18th International Conference on Industrial Informatics (INDIN)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127512200","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 : 2020-07-20DOI: 10.1109/INDIN45582.2020.9442185
S. Majidi, R. Obermaisser, Sudam Wasala, Mario Qosja
A common problem in Systems of Systems (SoS) is how to effectively coordinate the Constituent Systems (CSs) to realize the emerging services of the overall system when these CSs have independent internal purposes, while also serving the overall goal of the SoS. The conflict between the individual purposes and SoS goals, make it difficult to find a good scheduling solution for the system. This situation is even complicated in safety-critical real-time SoS, where malfunctions may result in danger to the environment or humans. In this paper, we introduce a scheduler based on a two-level interactive Genetic Algorithm (GA) along with fault-tolerance techniques to satisfy the requirements of these types of systems in the presence of faults. The performance of the model is evaluated by comparing the results from different generated scenarios. The results show that the scheduler significantly improves the reliability and timeliness of safety-critical SoS.
在系统的系统(Systems of Systems)中，如何有效地协调各组成系统(Constituent Systems, CSs)，在各组成系统具有独立内部目的的情况下，实现整个系统的新兴服务，同时又服务于各个组成系统的总体目标，是一个常见的问题。个体目的与组织目标之间的冲突，使得系统难以找到一个好的调度解决方案。在对安全至关重要的实时SoS中，这种情况甚至更为复杂，因为故障可能会对环境或人类造成危险。本文提出了一种基于两级交互遗传算法(GA)和容错技术的调度程序，以满足这类系统在存在故障时的要求。通过比较不同生成场景的结果来评估模型的性能。结果表明，该调度程序显著提高了安全关键SoS的可靠性和时效性。
{"title":"Fault-Tolerant Scheduler with Genetic Algorithm for Safety-Critical Time-Triggered Systems of Systems","authors":"S. Majidi, R. Obermaisser, Sudam Wasala, Mario Qosja","doi":"10.1109/INDIN45582.2020.9442185","DOIUrl":"https://doi.org/10.1109/INDIN45582.2020.9442185","url":null,"abstract":"A common problem in Systems of Systems (SoS) is how to effectively coordinate the Constituent Systems (CSs) to realize the emerging services of the overall system when these CSs have independent internal purposes, while also serving the overall goal of the SoS. The conflict between the individual purposes and SoS goals, make it difficult to find a good scheduling solution for the system. This situation is even complicated in safety-critical real-time SoS, where malfunctions may result in danger to the environment or humans. In this paper, we introduce a scheduler based on a two-level interactive Genetic Algorithm (GA) along with fault-tolerance techniques to satisfy the requirements of these types of systems in the presence of faults. The performance of the model is evaluated by comparing the results from different generated scenarios. The results show that the scheduler significantly improves the reliability and timeliness of safety-critical SoS.","PeriodicalId":185948,"journal":{"name":"2020 IEEE 18th International Conference on Industrial Informatics (INDIN)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116876408","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 : 2020-07-20DOI: 10.1109/INDIN45582.2020.9442190
Song Xie, Jingjing Cao, Zhou Wu, Kai Liu, Xiaohui Tao, Haoran Xie
The popularity of the Internet has brought profound influence to electronic commerce. A kind of review-oriented consumption mode is gradually expanding in the market and consumers will refer to the reviews provided by consumers who bought the product in the past. How to accurately analyze users' sentiments from massive data of e-commerce reviews has become one of the key issues for e-commerce platforms. Current standard sentiment analysis classifies overall sentiment of e-commerce reviews without an extended description of the entity. We set up an optimized Aspect-based sentiment analysis (ABSA) that includes four elements: aspect, category, polarity, and opinion. Aiming at the above problems, this paper proposes a Chinese e-commerce reviews sentiment analysis algorithm based on BERT. By using pre-training model, we use the BIO(B-begin,I-inside,O-outside) data labeling pattern to label entities and study sentiment analysis by the annotation data. Experimental results on the Taobao cosmetics review datasets show that compared with the ordinary deep learning methods, our approach in the accuracy rate and the F1 score has significant improvement.
{"title":"Sentiment Analysis of Chinese E-commerce Reviews Based on BERT","authors":"Song Xie, Jingjing Cao, Zhou Wu, Kai Liu, Xiaohui Tao, Haoran Xie","doi":"10.1109/INDIN45582.2020.9442190","DOIUrl":"https://doi.org/10.1109/INDIN45582.2020.9442190","url":null,"abstract":"The popularity of the Internet has brought profound influence to electronic commerce. A kind of review-oriented consumption mode is gradually expanding in the market and consumers will refer to the reviews provided by consumers who bought the product in the past. How to accurately analyze users' sentiments from massive data of e-commerce reviews has become one of the key issues for e-commerce platforms. Current standard sentiment analysis classifies overall sentiment of e-commerce reviews without an extended description of the entity. We set up an optimized Aspect-based sentiment analysis (ABSA) that includes four elements: aspect, category, polarity, and opinion. Aiming at the above problems, this paper proposes a Chinese e-commerce reviews sentiment analysis algorithm based on BERT. By using pre-training model, we use the BIO(B-begin,I-inside,O-outside) data labeling pattern to label entities and study sentiment analysis by the annotation data. Experimental results on the Taobao cosmetics review datasets show that compared with the ordinary deep learning methods, our approach in the accuracy rate and the F1 score has significant improvement.","PeriodicalId":185948,"journal":{"name":"2020 IEEE 18th International Conference on Industrial Informatics (INDIN)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114393797","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 paper presents the design and implementation of a novel magnetic actuated flexible-joint robotic surgery (MAFRS) camera system with four-degree-of-freedom(4-DOF) for single incision laparoscopic surgery. The design is based on the idea of motion decoupling and consists of an external driving device and a motor-free insertable wireless camera device with a flexible joint. Meanwhile, the design features a unified mechanism for anchoring, navigating, and tilting an insertable camera by an externally generated magnetic field. The control of the insertable camera without onboard motors has always been a problem. We have creatively adopted flexible materials and the new magnetic circuit design. It not only simplifies the structural design of the insertable camera but also meets the requirements of application scenarios. The initial prototype results in a compact insertable camera robot with a 19mm diameter and a 108.5mm length. The design concepts are analyzed theoretically and verified experimentally. The experiments validate that the proposed capsule robot design provides reliable camera anchoring and translation capabilities under various testing conditions, and the tilt angle of the camera can meet the practical application requirements.
{"title":"Design and Implementation of A Magnetic Actuated Capsule Camera Robot System for Single Incision Laparoscopic Surgery*","authors":"Dong Xu, Yuanlin Zhang, Wenshuai Tan, Hongxing Wei, Ping Xu","doi":"10.1109/INDIN45582.2020.9442197","DOIUrl":"https://doi.org/10.1109/INDIN45582.2020.9442197","url":null,"abstract":"This paper presents the design and implementation of a novel magnetic actuated flexible-joint robotic surgery (MAFRS) camera system with four-degree-of-freedom(4-DOF) for single incision laparoscopic surgery. The design is based on the idea of motion decoupling and consists of an external driving device and a motor-free insertable wireless camera device with a flexible joint. Meanwhile, the design features a unified mechanism for anchoring, navigating, and tilting an insertable camera by an externally generated magnetic field. The control of the insertable camera without onboard motors has always been a problem. We have creatively adopted flexible materials and the new magnetic circuit design. It not only simplifies the structural design of the insertable camera but also meets the requirements of application scenarios. The initial prototype results in a compact insertable camera robot with a 19mm diameter and a 108.5mm length. The design concepts are analyzed theoretically and verified experimentally. The experiments validate that the proposed capsule robot design provides reliable camera anchoring and translation capabilities under various testing conditions, and the tilt angle of the camera can meet the practical application requirements.","PeriodicalId":185948,"journal":{"name":"2020 IEEE 18th International Conference on Industrial Informatics (INDIN)","volume":"200 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114442202","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：