| 1. |
- Jusufi, Ilir, 1983-, et al.
(författare)
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TapVis : A Data Visualization Approach for Assessment of Alternating Tapping Performance in Patients with Parkinson's Disease
- 2018
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Ingår i: EuroVis 2018 - Short Papers. - : Eurographics - European Association for Computer Graphics. - 9783038680604 ; , s. 55-59
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Konferensbidrag (refereegranskat)abstract
- Advancements in telemedicine have been helpful for frequent monitoring of patients with Parkinson's disease (PD) from remote locations and assessment of their individual symptoms and treatment-related complications. These data can be useful for helping clinicians to interpret symptom states and individually tailor the treatments by visualizing the physiological information collected by sensor-based systems. In this paper we present a visualization metaphor that represents symptom information of PD patients during tapping tests performed with a smartphone. The metaphor has been developed and evaluated with a clinician. It enabled the clinician to observe fine motor impairments and identify motor fluctuations regarding several movement aspects of patients that perform the tests from their homes.
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| 2. |
- Kebande, Victor R., 1985-, et al.
(författare)
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A blockchain-based multi-factor authentication model for a cloud-enabled internet of vehicles
- 2021
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Ingår i: Sensors. - : MDPI. - 1424-8220. ; 21:18
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Tidskriftsartikel (refereegranskat)abstract
- Continuous and emerging advances in Information and Communication Technology (ICT) have enabled Internet-of-Things (IoT)-to-Cloud applications to be induced by data pipelines and Edge Intelligence-based architectures. Advanced vehicular networks greatly benefit from these architectures due to the implicit functionalities that are focused on realizing the Internet of Vehicle (IoV) vision. However, IoV is susceptible to attacks, where adversaries can easily exploit existing vulnerabilities. Several attacks may succeed due to inadequate or ineffective authentication techniques. Hence, there is a timely need for hardening the authentication process through cutting-edge access control mechanisms. This paper proposes a Blockchain-based Multi-Factor authentication model that uses an embedded Digital Signature (MFBC_eDS) for vehicular clouds and Cloud-enabled IoV. Our proposed MFBC_eDS model consists of a scheme that integrates the Security Assertion Mark-up Language (SAML) to the Single Sign-On (SSO) capabilities for a connected edge to cloud ecosystem. MFBC_eDS draws an essential comparison with the baseline authentication scheme suggested by Karla and Sood. Based on the foundations of Karla and Sood’s scheme, an embedded Probabilistic Polynomial-Time Algorithm (ePPTA) and an additional Hash function for the Pi generated during Karla and Sood’s authentication were proposed and discussed. The preliminary analysis of the proposition shows that the approach is more suitable to counter major adversarial attacks in an IoV-centered environment based on the Dolev–Yao adversarial model while satisfying aspects of the Confidentiality, Integrity, and Availability (CIA) triad. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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| 3. |
- Martin, Eva Garcia, et al.
(författare)
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Hashtags and followers An experimental study of the online social network Twitter
- 2016
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Ingår i: Social Network Analysis and Mining. - : Springer. - 1869-5450 .- 1869-5469. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- We have conducted an analysis of data from 502,891 Twitter users and focused on investigating the potential correlation between hashtags and the increase of followers to determine whether the addition of hashtags to tweets produces new followers. We have designed an experiment with two groups of users: one tweeting with random hashtags and one tweeting without hashtags. The results showed that there is a correlation between hashtags and followers: on average, users tweeting with hashtags increased their followers by 2.88, while users tweeting without hashtags increased 0.88 followers. We present a simple, reproducible approach to extract and analyze Twitter user data for this and similar purposes.
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| 4. |
- Lagerspetz, E., et al.
(författare)
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Pervasive Communities in the Internet of People
- 2018
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Ingår i: 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018. - : Institute of Electrical and Electronics Engineers Inc.. - 9781538632277 ; , s. 40-45
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Konferensbidrag (refereegranskat)abstract
- The Internet has traditionally been a device-oriented architecture where devices with IP addresses are first-class citizens, able to serve and consume content or services, and their owners take part in the interaction only through those devices. The Internet of People (IoP) is a recent paradigm where devices become proxies of their users, and can act on their behalf. To realize IoP, new policies and rules for how devices can take actions are required. The role of context information grows as devices act autonomously based on the environment and existing social relationships between their owners. In addition, the social profiles of device owners determine e.g. how altruistic or resourceconserving they are in collaborative computing scenarios. In this paper we focus on community formation in IoP, a prerequisite for enabling collaborative scenarios, and discuss main challenges and propose potential solutions. © 2018 IEEE.
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| 5. |
- Erlandsson, Fredrik
(författare)
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On social interaction metrics : social network crawling based on interestingness
- 2014
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- With the high use of online social networks we are entering the era of big data. With limited resources it is important to evaluate and prioritize interesting data. This thesis addresses the following aspects of social network analysis: efficient data collection, social interaction evaluation and user privacy concerns. It is possible to collect data from online social networks via their open APIs. However, a systematic and efficient collection of online social networks data is still challenging. To improve the quality of the data collection process, prioritizing methods are statistically evaluated. Results suggest that the collection time can be reduced by up to 48% by prioritizing the collection of posts. Evaluation of social interactions also require data that covers all the interactions in a given domain. This has previously been hard to do, but the proposed crawler is capable of extracting all social interactions from a given page. With the extracted data it is for instance possible to illustrate indirect interactions between different users that do not necessarily have to be connected. Methods using the same data to identify and cluster different opinions in online communities have been developed. These methods are evaluated with the too Linguistic Inquiry and Word Count. The privacy of the content produced; and the users’ private information provided on social networks is important to protect. Users must be aware of the consequence of posting in online social networks in terms of privacy. Methods to protect user privacy are presented. The proposed crawler in this thesis has, over the period of 20 months, collected over 38 million posts from public pages on Facebook covering: 4 billion likes and 340 million comments from over 280 million users. The performed data collection yielded one of the largest research dataset of social interactions on Facebook today, enabling qualitative research in form of social network analysis.
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| 6. |
- Henesey, Lawrence, et al.
(författare)
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Improved load planning of RoRo vessels by adopting blockchain and internet-of-things
- 2020
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Ingår i: 22nd International Conference on Harbor, Maritime and Multimodal Logistics Modelling and Simulation, HMS 2020. - : Dime University of Genoa. - 9788885741478 ; , s. 58-65
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Konferensbidrag (refereegranskat)abstract
- Ports are vital to the global economy, as up to 90% of goods are transferred through seaports. With increasing vessel sizes, cargo volumes and higher demand for supply-chain optimization, seaports are required to be more efficient and competitive. In the present study, a proposed solution incorporating IoT and Blockchain is considered into automating many of the activities in the load planning process, which is then evaluated via simulation. Real data is collected concerning different types of cargo for RoPax vessels with the intended goal of reducing planning time in a seaport. The results contribute as one piece of the mosaic on the avenue towards becoming a “Smart Port”, which deploys various digitalization technologies in order to become a fully automated port. The suggested approach to be integrated, builds upon IoT sensors in combination with the lightweight version of a Blockchain to improve balance indicators on a trim of a vessel. A developed simulation tool was used for evaluating a number of scenarios, with each scenario run set to 2500 times. The simulation results indicate an improvement of 50-160% from the current load planning operations for RoPax vessels. © 2020 The Authors.
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| 7. |
- Hernández, Francisca, et al.
(författare)
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Xml for Libraries, Archives, and Museums : The Project Covax
- 2003
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Ingår i: Applied Artificial Intelligence. - : Taylor & Francis. - 0883-9514 .- 1087-6545. ; 17:8-9, s. 797-816
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Tidskriftsartikel (refereegranskat)abstract
- The purpose of COVAX is to analyze and create the technical solutions required to provide access through the Internet to homogeneously-encoded document descriptions of archive, library, and museum collections based in the application of XML. This paper describes the development of the project, and the main achievements in building an information system of distributed XML databases containing document descriptions from libraries, archives, and museums emphasizing the conversion processes needed to transform legacy data to an XML environment.
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| 8. |
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| 9. |
- Hu, Yan, et al.
(författare)
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A Virtual Community Design for Home-Based Chronic Disease Healthcare
- 2016
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Ingår i: Lecture Notes in Computer Science. - Cham : Springer Publishing Company. - 9783319459158 - 9783319459165
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Konferensbidrag (refereegranskat)abstract
- The internet based social network has been applied to serve many social functions, such as democratic decision making, knowledge sharing, educa‐ tion, and healthcare. In this paper, we provide a prototype of virtual community designed for home-based chronic diseases healthcare. We studied the concept “community” from the activity theory model in order to design the prototype with a solid theoretical base. Then we conducted a questionnaire from healthcare recipients and interviewed healthcare providers to gather the requirements for the design of the community. With some user stories we described the requirements as use cases for our design and a conceptual prototype is built based on the requirements. This virtual community servers as a shared platform for all the stakeholders who are engaged in the healthcare activity. With this shared community platform, the interoperability problems of current healthcare systems can be moderated
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| 10. |
- Cheddad, Abbas
(författare)
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On Box-Cox Transformation for Image Normality and Pattern Classification
- 2020
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Ingår i: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 8, s. 154975-154983
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Tidskriftsartikel (refereegranskat)abstract
- A unique member of the power transformation family is known as the Box-Cox transformation. The latter can be seen as a mathematical operation that leads to finding the optimum lambda (λ) value that maximizes the log-likelihood function to transform a data to a normal distribution and to reduce heteroscedasticity. In data analytics, a normality assumption underlies a variety of statistical test models. This technique, however, is best known in statistical analysis to handle one-dimensional data. Herein, this paper revolves around the utility of such a tool as a pre-processing step to transform two-dimensional data, namely, digital images and to study its effect. Moreover, to reduce time complexity, it suffices to estimate the parameter lambda in real-time for large two-dimensional matrices by merely considering their probability density function as a statistical inference of the underlying data distribution. We compare the effect of this light-weight Box-Cox transformation with well-established state-of-the-art low light image enhancement techniques. We also demonstrate the effectiveness of our approach through several test-bed data sets for generic improvement of visual appearance of images and for ameliorating the performance of a colour pattern classification algorithm as an example application. Results with and without the proposed approach, are compared using the AlexNet (transfer deep learning) pretrained model. To the best of our knowledge, this is the first time that the Box-Cox transformation is extended to digital images by exploiting histogram transformation.
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