2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)最新文献_第2页

Duplicate record detection approach based on sentence embeddings 基于句子嵌入的重复记录检测方法

2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) Pub Date : 2020-09-01 DOI: 10.1109/WETICE49692.2020.00059

Hafsa Lattar, A. Salem, H. Ghézala

引用次数: 2

Organization 组织

2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) Pub Date : 2020-09-01 DOI: 10.6027/9789289331302-7-en

G. N. Kaplan, M. Ridao, Miriam Sayão, N. Madhavji, Juan Carlos Lazo

引用次数: 1886

SANDMAN: a Self-Adapted System for Anomaly Detection in Smart Buildings Data Streams SANDMAN:智能建筑数据流异常检测的自适应系统

2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) Pub Date : 2020-09-01 DOI: 10.1109/WETICE49692.2020.00011

Maxime Houssin, S. Combettes, M. Gleizes, B. Lartigue

引用次数: 1

Track report of Future Internet Services and Applications (FISA’2020) 未来互联网服务和应用跟踪报告(FISA ' 2020)

2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) Pub Date : 2020-09-01 DOI: 10.1109/WETICE49692.2020.00034

Abderrahim Ait Wakrime, Riadh Ben Halima, M. Sellami

引用次数: 1

Representation and Evolution of Knowledge Structures to Detect Anomalies in Financial Statements 财务报表异常检测的知识结构表征与演变

2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) Pub Date : 2020-09-01 DOI: 10.1109/WETICE49692.2020.00020

Chip Venters, Rao V. Mikkilineni

{"title":"Representation and Evolution of Knowledge Structures to Detect Anomalies in Financial Statements","authors":"Chip Venters, Rao V. Mikkilineni","doi":"10.1109/WETICE49692.2020.00020","DOIUrl":"https://doi.org/10.1109/WETICE49692.2020.00020","url":null,"abstract":"Deep learning, has delivered a variety of practical uses in the past decade. It has revolutionized customer experience and machine translation. It has made language recognition, autonomous vehicles and computer vision a reality. A multitude of other AI applications are common now. With Deep Learning we gain insights about hidden correlations. We extract features and distinguish categories. But we lack transparency of reasoning behind these conclusions. Most importantly, there is the absence of common sense. Deep learning models might be the best at perceiving patterns. Yet they cannot comprehend what the patterns mean. And they lack the ability to model their behaviors and reason about them.We present a new approach to augment Deep Learning using model based Deep Reasoning and its application to address fraud detection using financial statements. Recent theoretical models of computing structures with cognizing agents go beyond neural networks to provide models of observations, abstractions and generalizations from experience and create time dependent evolution and history to provide reasoning and predictive. We use Knowledge Structures defined therein to represent relevant domain knowledge. In this case, in a company’s financial statements. We analyze their history to detect potential fraud based on specific rules and observations. We use information from governance and compliance rules and experience of past violations. We analyze SEC 10-K statements using Deep Learning and model based Deep Reasoning. We use the Knowledge Structures to identify red flags and anomalies.","PeriodicalId":114214,"journal":{"name":"2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125534790","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

Capturing and Exploiting Citation Knowledge for Recommending Recently Published Papers 获取和利用引文知识推荐最近发表的论文

2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) Pub Date : 2020-09-01 DOI: 10.1109/WETICE49692.2020.00054

Anita Khadka, Iván Cantador, Miriam Fernández

引用次数: 1

Dissimilarity-based approach for Identity Link Invalidation 基于差异的身份链接失效方法

2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) Pub Date : 2020-09-01 DOI: 10.1109/WETICE49692.2020.00056

Anderson Carlos Ferreira Da Silva, Fatiha Saïs, E. Waller, F. Andrès

引用次数: 1

A Learning based Secure Anomaly Detection for Healthcare Applications 用于医疗保健应用程序的基于学习的安全异常检测

2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) Pub Date : 2020-09-01 DOI: 10.1109/WETICE49692.2020.00032

Frikha Hounaida, Wided Ben Daoud, A. Meddeb-Makhlouf, F. Zarai

{"title":"A Learning based Secure Anomaly Detection for Healthcare Applications","authors":"Frikha Hounaida, Wided Ben Daoud, A. Meddeb-Makhlouf, F. Zarai","doi":"10.1109/WETICE49692.2020.00032","DOIUrl":"https://doi.org/10.1109/WETICE49692.2020.00032","url":null,"abstract":"The wireless body sensor network (WBSN) is an emerging technology in the healthcare domain, which collects data from vital parameters of the patient’s body, using small portable components such as sensors. It allows to continuously monitor patients without restricting their movements and to inform the health specialist of the evolution of their states. However, the deployment of new technologies in health applications without taking into account data security makes the privacy of patients vulnerable. Thus, these systems have insufficient performance for large and varied data sets, because they do not process information sufficiently diverse to cover all scenarios. Moreover, the interpretation of physiological signals is a tedious process in which human errors can be caused.To address these issues, we propose, in this paper, an effective health system that ensures the secure collection and transfer of patient data to the physician, to facilitate the diagnosis and the detection of life threatening diseases. Our main contribution is to offer real-time, high quality processing, learning and analysis capabilities, in a smart and secure system. For that, we have collected real patient datasets from Tunisian doctors.To achieve this goal, we used ANN and XgBoost as learning algorithms and AES as an encryption protocol for sending secure data to medical personnel for diagnostic purposes. The results show an accuracy of 80% with an execution time of 1.54 s.","PeriodicalId":114214,"journal":{"name":"2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130738384","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

Adaptive Computing (and Agents) for Enhanced Collaboration (ACEC 2020) 用于增强协作的自适应计算(和代理)(ACEC 2020)

2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) Pub Date : 2020-09-01 DOI: 10.1109/WETICE49692.2020.00008

F. Bergenti, M. Blake, Giacomo Cabri, U. Wajid

引用次数: 0

Communication management for reliable service based IoT systems 基于可靠服务的物联网系统的通信管理

2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) Pub Date : 2020-09-01 DOI: 10.1109/WETICE49692.2020.00030

Patryk Schauer, Lukasz Falas

{"title":"Communication management for reliable service based IoT systems","authors":"Patryk Schauer, Lukasz Falas","doi":"10.1109/WETICE49692.2020.00030","DOIUrl":"https://doi.org/10.1109/WETICE49692.2020.00030","url":null,"abstract":"Internet of Things (IoT) systems are becoming more and more popular. Moreover, service-based approach to IoT systems development is practically a standard utilized in their architecture. uti. IoT communication problems ware discussed in many articles about wireless communication, sensor networks or cloud computing. However the topic of high-level end to end communication in IoT systems is much less often the point of researchers’ interest. Despite that, the reliability of communication makes much more sense especially when it is considered at the application layer. Furthermore, networks utilized in IoT systems are usually virtual and software-based. Due to this fact, it is reasonable to take consider this problem with a novel and adequate approach, rather with classical models of communication resource allocation. In this article authors presented an idea of reliable communication management for IoT systems based on resource allocation. This idea is discussed in context of service-based IoT system lifecycle, especially considering the stages of resource allocation and services execution. Concerning the presented concept, three algorithms were prepared and tested in the simulation process.","PeriodicalId":114214,"journal":{"name":"2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133040143","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