{"title":"Robotic Entertainments as Personalizable Workflow of Services: a Home-Care Case Study","authors":"C. Napoli, E. Grosso, Silvia Rossi","doi":"10.1109/WETICE.2019.00012","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00012","url":null,"abstract":"Socially Assistive Robotics is becoming a promising technology for home care support to patients affected by neurological disorders, such as dementia. Several requirements needs to be addressed when such technology has to be adopted in realistic scenarios both from an economic and an acceptance point of view. In this work we present the approach adopted in designing and implementing a prototype of an assistive robotic system composed of low cost and general purpose devices that can be easily deployed in the patient homes, to support them in performing cognitive and physical stimulation activities that are known to have a beneficial effect on the progression of the disease. In order to improve the acceptability level of an invasive technology as a robotic system, activities are represented in terms of workflow of services, where the delivery mode of each service is personalized for an individual patient classified considering the cognitive status, and the personality profile. The system is composed of different layers, with a middleware able to automatically select the services that are more suitable to the patient profile, and to schedule them according to the daily routine of the patient.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124056555","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}
Stefanie Urchs, Lorenz Wendlinger, Jelena Mitrović, M. Granitzer
{"title":"MMoveT15: A Twitter Dataset for Extracting and Analysing Migration-Movement Data of the European Migration Crisis 2015","authors":"Stefanie Urchs, Lorenz Wendlinger, Jelena Mitrović, M. Granitzer","doi":"10.1109/WETICE.2019.00039","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00039","url":null,"abstract":"In the 2015 migration crisis thousands of refugees and migrants crossed the border to Hungary, Austria and Germany. The movements of these people are reflected in social media, especially on Twitter. In this paper we present a dataset of 3275 Tweets from the months September and October 2015. These Tweets are annotated regarding their relevance of containing quantitative movement information of refugees/migrants into Hungary, Austria and Germany. We present this dataset for a posterior analysis of the 2015 migration crisis or as a basis for creating an automated extraction / prediction system.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132627518","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}
M. Fugini, Jacopo Finocchi, Filippo Leccardi, Paolo Locatelli, A. Lupi
{"title":"A Text Analytics Architecture for Smart Companies","authors":"M. Fugini, Jacopo Finocchi, Filippo Leccardi, Paolo Locatelli, A. Lupi","doi":"10.1109/WETICE.2019.00064","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00064","url":null,"abstract":"This paper presents an architecture for Big Data Analytics regarding unstructured content. The architecture is proposed as an industrial solution in a real setting. In particular, the paper focuses on BD (Big Data) for Smart Companies and on Enterprise Content Management for extraction of information from textual BD. It presents the process architecture and discusses some experiments done as part of a larger BD Analytics project.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131729373","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}
{"title":"Handling Class Imbalance in High-Dimensional Biomedical Datasets","authors":"B. Pes","doi":"10.1109/WETICE.2019.00040","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00040","url":null,"abstract":"When dealing with biomedical data, the first and most challenging issue is often the huge dimensionality, i.e. the presence of a very high number of features for each of the problem instances at hand. A vast literature is available on different dimensionality reduction techniques that can be suitable for handling such kind of data, with a special focus on feature selection algorithms that allow to discard uninformative/useless features. In most cases, however, the dimensionality issue is addressed without a joint consideration of other potential problems in the data, including an imbalanced class distribution that may hinder the construction of effective classification models. Class imbalance, in turn, has been mostly treated in literature as an independent problem, especially in application fields where the number of features is not so critical. But several biomedical datasets are both high-dimensional and class-imbalanced, so there is a strong need for designing and evaluating learning strategies that can properly deal with both the issues simultaneously. In this work, we experiment with using feature selection techniques in conjunction with sampling-based class balancing methods and cost-sensitive classification, in order to gain insight into the most effective strategies to use when dealing with such complex data.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122427401","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}
{"title":"How Much Enhancing Confidentiality and Integrity on Data Can Affect Mobile Multi-Cloud: The \"ARIANNA\" Experience","authors":"R. D. Pietro, M. Scarpa, A. Puliafito","doi":"10.1109/WETICE.2019.00077","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00077","url":null,"abstract":"Ensuring confidentiality and integrity on data in Cloud computing is still a big challenge. With the advent of the 'Mobile Cloud Computing (MCC)\", confidentiality and integrity issues has reemerged inheriting all the limitations introduced by the use of the mobile devices. ARIANNA is an Android application representing the software enabler which allows to extend the SSME Cloud Service, the experimental multi-Cloud system deployed and maintained at the \"Cloud Data Center - University of Messina\", towards the mobile world represented by the smart devices. In this paper, we present a quantitative performance analysis comparing some commercial Cloud storage services such as Google Drive, Dropbox and OpenStack Swift, with the multi-Cloud approach enabled by the ARIANNA application. In order to evaluate \"how much\" the overhead introduced by ARIANNA approach costs, we conducted several experiments taking into account the mobile application in real and dynamic multi-Cloud scenarios. The paper discusses some consideration about the actual adoptability of this approach in real application domain and some software and architectural improvements to further improve ARIANNA's performance.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131406182","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}
Mouna Rhahla, T. Abdellatif, Rabah Attia, W. Berrayana
{"title":"A GDPR Controller for IoT Systems: Application to e-Health","authors":"Mouna Rhahla, T. Abdellatif, Rabah Attia, W. Berrayana","doi":"10.1109/WETICE.2019.00044","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00044","url":null,"abstract":"General Data Protection Regulation (GDPR) targets personal data protection of the European Union citizens, with a strong input on the rights of people to control their data. Current GDPR solutions are adhoc and are still challenging for scalable systems like Internet of Things (IoT). In this paper, we propose a general solution of a GDPR Controller in IoT systems. The controller gives the data owner a full control of his data: setting security policies, modifying them on run time, tracking data flow and notifying him for any illicit access. The controller architecture is validated and evaluated using an e-health use case with acceptable overhead on the system performance.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128365633","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}
Meriem Guerar, Luca Verderame, M. Migliardi, A. Merlo
{"title":"2GesturePIN: Securing PIN-Based Authentication on Smartwatches","authors":"Meriem Guerar, Luca Verderame, M. Migliardi, A. Merlo","doi":"10.1109/WETICE.2019.00074","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00074","url":null,"abstract":"Smartwatches offer new capabilities to develop sophisticated applications that make daily life easier and more convenient for consumers and are becoming increasingly ubiquitous. The kind of services these devices are capable to provide include applications for mobile payment, ticketing, identification, access control, etc. While this makes modern smartwatches very powerful devices, it also makes them very attractive targets for attackers. PINs and Pattern Lock have been widely used in smartwatches for user authentication, however, those types of passwords are not robust against various forms of attacks, such as side channel, phishing, smudge, shoulder surfing, and videorecording attacks. In this work, we propose 2GesturePIN, a new authentication method that allows users to authenticate securely to their smartwatches and sensitive services through solely two gestures. It leverages the rotating bezel or the crown which are the most intuitive channels to interact with a smartwatch. 2GesturePIN enhances the resilience of the regular PIN to common attacks while maintaining a high level of usability.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130375305","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}
Zakaria Afkir, Hatim Guermah, M. Nassar, S. Ebersold
{"title":"Machine Learning Based Approach for Context Aware System","authors":"Zakaria Afkir, Hatim Guermah, M. Nassar, S. Ebersold","doi":"10.1109/WETICE.2019.00017","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00017","url":null,"abstract":"Machine learning approaches propose a promising solution for extracting and analyzing contextual information from different data sources. Especially, in the E-health field, the need for Improvement in risk prediction, early detection and prevention of disease remains an essential task for the well-being of patients at risk. In this paper, we aim to explore the added value of using machine learning based approach to predict contextual situations in context-aware systems, and more specifically the field of E-health.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126344129","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}
{"title":"Web of Things Data Visualization: From Devices to Web Via Fog and Cloud Computing","authors":"George Pacheco Pinto, Cássio V. S. Prazeres","doi":"10.1109/WETICE.2019.00038","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00038","url":null,"abstract":"Web of Things (WoT) uses current Web protocols and languages as an integration platform of physical devices on the Internet. Previsions estimate that by 2020, 20 to 50 billion such devices will be connected - producing, collecting, and transmitting data over the Internet. The amount of data associated with such a gigantic number of available devices represents a real challenge in data visualization. This paper proposes a Data Visualization model for WoT, based on Fog Computing concepts, more specifically the Fog of Things paradigm. The aim of our proposal is to enable the creation of different data visualizations that take into account the hierarchical levels in an architecture involving Fog and Cloud. In order to demonstrate our proposal, a prototype of the Web of Things application was developed, which is used to perform usability evaluation through the USE questionnaire technique.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127884207","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}
{"title":"Reducing Implementation Efforts in Continuous Auditing Certification Via an Audit API","authors":"Dorian Knoblauch, Christian Banse","doi":"10.1109/WETICE.2019.00025","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00025","url":null,"abstract":"Continuous auditing reduces the frequency in which compliance is verified. This results in more trustworthiness for the cloud service and therefore lowers the barrier of adopting cloud for customers in high-risk sectors such as banking. However, implementing continuous auditing as of today is a tedious task and not standardized, which leaves the service providers implementing the whole audit process and the technical infrastructure. We are proposing a solution for this problem by defining a standardized way of establishing the continuous auditing process for an IT infrastructure as well as providing the necessary tools as a reference implementation. In this paper we present how complexity in setting up the technical requirements for continuous auditing can be highly reduced by providing an easy to implement Audit API and continuous auditing methodology.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132474919","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}