Proceedings of the 14th International Conference on Management of Digital EcoSystems最新文献_第2页

A Parallel Processing Architecture to Optimize Runtime in Aggregated SPARQL Queries 优化聚合SPARQL查询运行时的并行处理架构

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564836

A. Rabhi, R. Fissoune, M. Tabaa, Hassan Badir

引用次数: 0

Detecting Attacks on Computer Networks Using Artificial Intelligence Algorithms 利用人工智能算法检测计算机网络攻击

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564830

Lukasz Krolik, M. Kedziora, Jolanta Mizera-Pietraszko, I. Józwiak

引用次数: 0

Towards a Strong Containment for Efficient Matching of Expressive Graph Patterns 表达图模式高效匹配的强包容

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564851

Houari Mahfoud

{"title":"Towards a Strong Containment for Efficient Matching of Expressive Graph Patterns","authors":"Houari Mahfoud","doi":"10.1145/3508397.3564851","DOIUrl":"https://doi.org/10.1145/3508397.3564851","url":null,"abstract":"We consider conditional graph patterns (CGPs) that allow querying data graphs with complex features like quantification, negation and predicates. To overcome the prohibitive cost of subgraph isomorphism, we consider matching of CGPs under simulation semantics which can be conducted in quadratic time. In emerging applications that deal with large data graphs, one would like to reduce more this matching time. We consider the optimization problem that checks whether match results of some pattern P1, over any data graph, can be extracted from those of another pattern P2. This allows an efficient matching of P1 using only match results of P2 which may be much smaller than the underlying data graph. We show that when patterns are very simple then the traditional containment can be used to meet our optimization goal. However, in case of complex pattern features, the containment semantics does not suffice since containment between two patterns does not imply a possible extraction between their match results. Hence, we propose an enhanced semantics, called strong containment, that consists in checking match results extraction between two patterns. We show that strong containment can be decided in cubic time for CGPs by providing such an algorithm. This new semantics can be applied in many emerging applications such as view-based answering, query optimization and caching systems maintenance.","PeriodicalId":266269,"journal":{"name":"Proceedings of the 14th International Conference on Management of Digital EcoSystems","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127133561","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

Binary Classification Architecture for Edge Computing Based on Cognitive Services and Deep Neural Networks 基于认知服务和深度神经网络的边缘计算二元分类体系结构

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564828

Cristian Chancusig, Sergio Tumbaco, D. Alulema, L. Iribarne, J. Criado

{"title":"Binary Classification Architecture for Edge Computing Based on Cognitive Services and Deep Neural Networks","authors":"Cristian Chancusig, Sergio Tumbaco, D. Alulema, L. Iribarne, J. Criado","doi":"10.1145/3508397.3564828","DOIUrl":"https://doi.org/10.1145/3508397.3564828","url":null,"abstract":"Systems based on computer vision and artificial intelligence are an alternative for repetitive inspection processes. However, it is possible to extend the learning capacity of these systems to classify multiple objects using edge computing. This allows combining local processing with cloud processing to expand the possibilities and reduce the response time. In this work, a classification architecture based on remote web services and local neural networks is proposed. To test this architecture, Microsoft Azure cognitive web services and its Computer Vision API have been used, combined with the use of transfer learning and ResNet 50. The cloud service allows the identification and labelling of image content, while the Edge service, based on the neural network, allows the generation of classification models for those objects not identified or incorrectly identified by the remote service. The architecture allows to extend the possibility of image recognition by integrating web services that combined with edge processing accelerate the identification process. The proposed architecture is composed of three layers; (a) a physical layer, for the mechanical and electronic structure; (b) a logical layer, which defines the interaction of the remote and local image recognition web services, and (c) an application layer, for the integration of the monitoring and control interfaces. Finally, the architecture was evaluated through functionality testing and performance metrics of classification models, as well as load and usability testing.","PeriodicalId":266269,"journal":{"name":"Proceedings of the 14th International Conference on Management of Digital EcoSystems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130779670","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

About Ergonomics of Computer Interfaces Designing a System: Designing a System for Human Computational Collective Use 设计一个系统:设计一个供人类计算集体使用的系统

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564823

C. Jouis, Mercedes Orus-Lacord, S. Pemberton

引用次数: 0

Quality Classification for Testing Work in DevOps DevOps中测试工作的质量分类

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564840

Daiju Kato, Ayumu Shimizu, H. Ishikawa

{"title":"Quality Classification for Testing Work in DevOps","authors":"Daiju Kato, Ayumu Shimizu, H. Ishikawa","doi":"10.1145/3508397.3564840","DOIUrl":"https://doi.org/10.1145/3508397.3564840","url":null,"abstract":"Since software quality model is defined, many quality assurance teams use the model of analysis of software products for quality control. In case of DevOps, a pipeline is built in the CI/CD process, testing work is placed in the pipeline, and automation of testing work is promoted for efficient product development, but most of DevOps projects have used classic quality metrics, as like bug ratio, test coverage rate so on. By categorizing the quality ensured by CI/CD pipeline testing by quality characteristics, the progress of the quality required for the released system can be visualized and controlled by quality model. In addition, by defining software quality goals with quality characteristics before the project starts, it is possible to use quality characteristics as KPIs. Using quality characteristics as KPIs needs to manage the results of tests in each pipeline and compare with results with past builds. This paper explains how to visualize the quality ensured by the CI/CD process, which is indispensable for DevOps, as well as the advantages of using quality characteristics as KPIs, and proposes method of achievement for rapid and high-quality products development.","PeriodicalId":266269,"journal":{"name":"Proceedings of the 14th International Conference on Management of Digital EcoSystems","volume":"264 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122541633","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

Transfer Learning Based Architecture for Urban Transportation Big Data Fusion 基于迁移学习的城市交通大数据融合体系结构

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564844

Salah Ghodhbani, S. Elkosantini, W. Suh, Mark A. Lee

{"title":"Transfer Learning Based Architecture for Urban Transportation Big Data Fusion","authors":"Salah Ghodhbani, S. Elkosantini, W. Suh, Mark A. Lee","doi":"10.1145/3508397.3564844","DOIUrl":"https://doi.org/10.1145/3508397.3564844","url":null,"abstract":"Recently, intelligent transportation system (ITS) is considered as one of the most important issues in smart city applications. Its supports urban and regional development and promotes economic growth, social development, and enhances human well-being. ITS integrates new technologies of information and communication including sensors, social media IoT devices which can generate a massive amount of heterogeneous and multimodal data known as big data term. In this context, Data Fusion techniques (DF) seem promising and have emerged from transportation applications and hold a promising opportunities to deal with imperfect raw data for capturing reliable, valuable and accurate information. Literature. In literature many DF techniques based on machine learning remarkably renovates fusion techniques by offering the strong ability of computing and predicting. In this paper, we propose new Hybrid method based on TL (transfer learning) combine tow pertained DL models such as irregular CNN [1], and bi-directional LSTM [2] models to fuse multimodal and spatial temporal data. the propose method use CBOA algorithm for feature selection in to order to provide effective exploration of significant features with faster convergence. The proposed model demonstrated its effective results on the applied dataset by offering good results and outcome over traditional methods.","PeriodicalId":266269,"journal":{"name":"Proceedings of the 14th International Conference on Management of Digital EcoSystems","volume":"9 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114035733","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

Optimal Set Up for Manufacturing Inspection System via Mapping, and 3D Scanning 通过绘图和三维扫描优化制造检测系统

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564829

Yosri Ben Salah, Liu Weiguo, Tian Ailing, Lamia Sellami, A. Hamida, Saber Zardoumi

引用次数: 0

Towards a Discovery Model for the Web of Things 面向物联网的发现模型

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564827

J. Llopis, Manel Mena, J. Criado, L. Iribarne, A. Corral

{"title":"Towards a Discovery Model for the Web of Things","authors":"J. Llopis, Manel Mena, J. Criado, L. Iribarne, A. Corral","doi":"10.1145/3508397.3564827","DOIUrl":"https://doi.org/10.1145/3508397.3564827","url":null,"abstract":"The Internet of Things (IoT) is composed of many heterogeneous pieces. The Web of Things (WoT) was created to establish a common device definition language, the Thing Description (TD), that would allow developers to set an interaction mechanism without understanding the different device implementations. Besides a definition language, a WoT ecosystem must be characterized by a robust discovery system in which the other Thing Descriptions of the devices can be easily located, registered and consulted. According to these two pillars (description and discovering), this article presents a Discovery Service model for the WoT, capable of working proactively, searching for IoT devices compatible with the Thing Description, and passively being able to register, query or list different devices when the client chooses. Furthermore, Digital Dice is used in the proposal, a software abstraction of IoT devices for managing devices, adding some features and taking advantage of microservices architectures. Finally, in the recent updates and modifications over the WoT recommendations, one of the main problems researchers may face is that there are few public domain implementations. This article also presents a fully interactive solution using the Discovery Service and Digital Dice to address this problem.","PeriodicalId":266269,"journal":{"name":"Proceedings of the 14th International Conference on Management of Digital EcoSystems","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123477277","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

Sectorial Analysis Impact on the Development of Credit Scoring Machine Learning Models 行业分析对信用评分机器学习模型发展的影响

Proceedings of the 14th International Conference on Management of Digital EcoSystems Pub Date : 2022-10-19 DOI: 10.1145/3508397.3564835

Ayoub El Qadi, M. Trocan, Thomas Frossard, Natalia Díaz Rodríguez

{"title":"Sectorial Analysis Impact on the Development of Credit Scoring Machine Learning Models","authors":"Ayoub El Qadi, M. Trocan, Thomas Frossard, Natalia Díaz Rodríguez","doi":"10.1145/3508397.3564835","DOIUrl":"https://doi.org/10.1145/3508397.3564835","url":null,"abstract":"Small and Medium-sized Enterprises play an essential role in the growth of the global economy. The access to credit for these companies allows them to fund the development of their activities. Artificial Intelligence has emerged as a potential tool to help financial and insurance institutions to assess Small and Medium-sized companies and thus, accelerate their activities. The economic sector in which companies operate is an essential factor when it comes to determining the risk of default. On the other hand, to introduce Artificial Intelligence in a highly regulated industry, the principal actors need to understand the behavior of the models. In this paper, we focus on the development of Artificial Intelligence-based models for different economic sectors Furthermore, we analyze the model behavior using SHapley Additive exPlanations. We compare both the performance and the explanations of the different economic sector models with the global model. Our study shows that there is a slight improvement in terms of performance when creating the different sectorial models. The comparison between the explanations for each model reveals certain disagreements in terms of the most relevant features.","PeriodicalId":266269,"journal":{"name":"Proceedings of the 14th International Conference on Management of Digital EcoSystems","volume":"2018 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121668432","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