2022 IEEE 20th International Conference on Industrial Informatics (INDIN)最新文献_第2页

Enhancing Reliability by Combining Manufacturing Processes and Private 5G Networks 结合制造工艺和专用5G网络，提高可靠性

2022 IEEE 20th International Conference on Industrial Informatics (INDIN) Pub Date : 2022-07-25 DOI: 10.1109/INDIN51773.2022.9976081

M. Müller, Janina Knorr, D. Behnke, Christian Arendt, S. Böcker, Caner Bektas, C. Wietfeld

引用次数: 1

Fault diagnosis for bilinear stochastic distribution systems with actuator fault 带有执行器故障的双线性随机分配系统故障诊断

2022 IEEE 20th International Conference on Industrial Informatics (INDIN) Pub Date : 2022-07-25 DOI: 10.1109/INDIN51773.2022.9976169

Bo Cao, L. Yao

引用次数: 0

Study on the Relationship between Mixed Tail Risk and Expected Stock Returns 混合尾部风险与股票预期收益关系研究

2022 IEEE 20th International Conference on Industrial Informatics (INDIN) Pub Date : 2022-07-25 DOI: 10.1109/INDIN51773.2022.9976110

Wenrui Zhao, Chengyi Pu

{"title":"Study on the Relationship between Mixed Tail Risk and Expected Stock Returns","authors":"Wenrui Zhao, Chengyi Pu","doi":"10.1109/INDIN51773.2022.9976110","DOIUrl":"https://doi.org/10.1109/INDIN51773.2022.9976110","url":null,"abstract":"The relationship between risk and asset returns is an important basis for investment decision.The mystery of \"idiosyncratic volatility\" shows that this relationship is still unclear.How to measure the correlation of risk and returns accurately has always been a popular investment spot. Traditional research of tail risk from one-dimensional and multi-dimensional perspective is relatively rich, using conditional heteroscedasticity model or extreme value theory to measure the basic risk indicators such as Value at Risk(VaR) and Expected Shortfall(ES),or estimating the common tail risk factor based on cross-sectional data of stocks.Existing research does not consider the same direction changes between asset and market returns,which is more pronounced during market crashes.In this paper, we examine the impact of mixed tail risk on the expected stock returns from multi-dimensional perspective based on coupla method.We find that: (1) The coefficient of lower tail dependence(LTD) can capture market crashes,we can use LTD as an warning indicator for market crashes. Stocks traded on Shenzhen Main Board with strong LTD have higher future returns than that with weaker LTD, but this conclusion does not apply to the stocks traded on Small and Mid Enterprise board(SME board) and Growth Enterprise market(GEM). (2) In the period of financial crisis, the positive impact of stock mixed tail risk on stock expected return will be significantly enhanced.High circulation market capitalization and high turnover rate can reduce this impact. (3) Non-tradable Share Reform increases the liquidity of stocks,reducing the risk premium of mixed tail risk.","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129015746","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}

引用次数: 0

Product Quality Control in Assembly Machine under Data Restricted Settings 数据受限条件下的装配机产品质量控制

2022 IEEE 20th International Conference on Industrial Informatics (INDIN) Pub Date : 2022-07-25 DOI: 10.1109/INDIN51773.2022.9976173

Fatemeh Kakavandi, R. D. Reus, C. Gomes, Negar Heidari, A. Iosifidis, P. Larsen

{"title":"Product Quality Control in Assembly Machine under Data Restricted Settings","authors":"Fatemeh Kakavandi, R. D. Reus, C. Gomes, Negar Heidari, A. Iosifidis, P. Larsen","doi":"10.1109/INDIN51773.2022.9976173","DOIUrl":"https://doi.org/10.1109/INDIN51773.2022.9976173","url":null,"abstract":"Evaluating the product quality in an assembly machine is critical yet time-consuming since, in product assessment in batch manufacturing, a certain amount of products should be investigated in an invasive manner. However, continuous manufacturing ensures product quality assessment during assembly with high efficiency and traceability. This paper proposes a quality assessment method for an industrial use case. First, the data is prepared based on two indicators and expert knowledge. Then two data classification approaches (one-class classification and binary classification) are applied to evaluate the products’ quality by analysing the related data. Finally, the most efficient model is selected to predict the product labels and deviate anomalies from normal products. For the studied use case and the limited number of products, the binary classifier guarantees to detect 100% of defective products. The proposed approach can provide the engineers and operators with understandable extracted process knowledge, and can therefore be adapted to a high-speed manufacturing line where large data volume and process complexity can be problematic.","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":"262 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115953676","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}

引用次数: 2

A multi-attribute auctioning system for the circular economy with Ricardian contracts 基于李嘉图契约的循环经济多属性拍卖系统

2022 IEEE 20th International Conference on Industrial Informatics (INDIN) Pub Date : 2022-07-25 DOI: 10.1109/INDIN51773.2022.9976104

Eric Chiquito, Ulf Bodin, K. Synnes

{"title":"A multi-attribute auctioning system for the circular economy with Ricardian contracts","authors":"Eric Chiquito, Ulf Bodin, K. Synnes","doi":"10.1109/INDIN51773.2022.9976104","DOIUrl":"https://doi.org/10.1109/INDIN51773.2022.9976104","url":null,"abstract":"In this paper, we define a multi-attribute auctioning system for the circular economy and the trade of products, components and materials subject to recycling. The increasing popularity of auctioning systems for buying and selling goods has led to the adaptation of them to diverse and particular scenarios, many of which require support for attributes like delivery time, quality, etc. Such attributes allow for more explicit and precise negotiations than traditional auctioning systems where only price is taken into account. The circular economy concept replaces end-of-life with the reuse of various goods, aiming to keep as much value as possible of any asset. By allowing users to adjust attributes in multi-step negotiations according to their economic and ecological needs, better deals can be achieved. We address this potential with our multi-attribute, and multi-step auctioning system. The system is based on transparency and fairness principles, and addresses requirements for flexibility in what attributes can be used, and the need for a semi-transparent auctioning procedure. We present a winner determination approach based on scoring protocol based on weights for different input attributes. Our auctioning system uses a signature chain data structure to provide transaction traceability. We demonstrate using a generic example that the proposed system supports simple and flexible multi-attribute auctions.","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123841927","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}

引用次数: 0

Migrating legacy production lines into an Industry 4.0 ecosystem 将传统生产线迁移到工业4.0生态系统中

2022 IEEE 20th International Conference on Industrial Informatics (INDIN) Pub Date : 2022-07-25 DOI: 10.1109/INDIN51773.2022.9976084

J. Palmeira, Gustavo Coelho, A. Carvalho, P. Carvalhal, Paulo Cardoso

引用次数: 0

Robustifying cooperative awareness in autonomous vehicles through local information diffusion 通过局部信息扩散增强自动驾驶车辆的协同意识

2022 IEEE 20th International Conference on Industrial Informatics (INDIN) Pub Date : 2022-07-25 DOI: 10.1109/INDIN51773.2022.9976168

Nikos Piperigkos, A. Lalos, K. Berberidis

{"title":"Robustifying cooperative awareness in autonomous vehicles through local information diffusion","authors":"Nikos Piperigkos, A. Lalos, K. Berberidis","doi":"10.1109/INDIN51773.2022.9976168","DOIUrl":"https://doi.org/10.1109/INDIN51773.2022.9976168","url":null,"abstract":"Cooperative Intelligent Transportation Systems envision the integration of cooperative intelligence as a key operational part of autonomous driving. In this way, a fleet or swarm of Connected and Automated Vehicles collectively coordinates its driving actions in order to maximize its performance. To realize this ambition, vehicles need to be fully location-aware of their surrounding environment, through distributed AI intelligence. Motivated by this requirement, we develop in this paper a distributed cooperative awareness scheme which performs multi-modal fusion of heterogeneous sensor sources along with V2V communication information, using graph Laplacian matrix and Least-Mean-Squares algorithm. The intuition behind our approach is that neighboring vehicles are interested in estimating common positions of other vehicles. We build upon our previous work on global awareness though local information diffusion, and prove that the proposed distributed framework is able to address highly efficient the case of lacking any information about other networked vehicles. More specifically, our approach achieves high enough convergence speed as well as location accuracy. The evaluation study has been performed in CARLA autonomous driving simulator and verifies the proposed method’s benefits over other related solutions.","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127773554","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}

引用次数: 0

A Lazy Engine for High-utilization and Energy-efficient ReRAM-based Neural Network Accelerator 基于reram的高效节能神经网络加速器懒引擎研究

2022 IEEE 20th International Conference on Industrial Informatics (INDIN) Pub Date : 2022-07-25 DOI: 10.1109/INDIN51773.2022.9976171

Wei-Yi Yang, Ya-Shu Chen, Jinqi Xiao

引用次数: 0

Integration of Machine Learning Task Definition in Model-Based Systems Engineering using SysML 基于模型的系统工程中基于SysML的机器学习任务定义集成

2022 IEEE 20th International Conference on Industrial Informatics (INDIN) Pub Date : 2022-07-25 DOI: 10.1109/INDIN51773.2022.9976107

S. Rädler, E. Rigger, Juergen Mangler, S. Rinderle-Ma

{"title":"Integration of Machine Learning Task Definition in Model-Based Systems Engineering using SysML","authors":"S. Rädler, E. Rigger, Juergen Mangler, S. Rinderle-Ma","doi":"10.1109/INDIN51773.2022.9976107","DOIUrl":"https://doi.org/10.1109/INDIN51773.2022.9976107","url":null,"abstract":"In order to allow Systems Engineers to utilize data produced in cyber-physical systems (CPS), they have to cooperate with data-scientists for custom data-extraction, data-preparation, and/or data-transformation mechanisms. While interfaces in CPS systems might be generic, the data that is produced for custom application needs has to be transformed and merged in very specific ways, to allow systems engineers proper interpretation and insight-extraction. In order to enable efficient cooperation between systems engineers and data scientists, the systems engineers have to provide a fine-grained specification that (a) describes all parts of the CPS, (b) how they might interact, (c) what data is exchanged between them, and (d) how the data inter-relates. A data scientists can then iteratively (including further refinements of the specification) prepare the necessary custom machine-learning models and components. Therefore, this work introduces a method supporting the collaborative definition of machine learning tasks by leveraging model-based systems engineering in the formalization of the systems modeling language SysML. The method supports the identification and integration of various data sources, the required definition of semantic connections between data attributes and the definition of the data processing steps within the machine learning support. Integrating machine learning-specific properties in systems engineering techniques allows non-data scientists to define a machine learning problem, document knowledge on the data, and further supports data scientists to use the formalized knowledge as input for an implementation.","PeriodicalId":359190,"journal":{"name":"2022 IEEE 20th International Conference on Industrial Informatics (INDIN)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134489936","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}

引用次数: 1

Unsupervised Object Re-identification via Instances Correlation Loss 基于实例相关损失的无监督对象再识别

2022 IEEE 20th International Conference on Industrial Informatics (INDIN) Pub Date : 2022-07-25 DOI: 10.1109/INDIN51773.2022.9976073

Qing Tang, K. Jo

引用次数: 0