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24th Pan-Hellenic Conference on informatics, PCI 2020

作者： Tsoukas, Vasileios Gkogkidis, Anargyros Kakarountas, Athanasios Intelligent Systems Laboratory Dpt. of Computer Science and Biomedical Informatics University of Thessaly Lamia Greece

ISBN: (纸本)9781450388979

The rapid evolution of mobile phone devices resulted in the conversion of a simple communication device to a complicated small portable computer offering a plethora of features and services. Sensitive data are now stored in devices that can be easily lost, stolen, or compromised. A mobile user survey was conducted to get a better understanding of what the users think about the data stored in their devices, the authentication methods they use, and their willingness to try a new one. This paper presents the results derived from 81 mobile users. The results reveal that the users still use text-based authentication methods, with the preferred method being the Pin-Code. The bio-metric authentication adopters have a better understanding of what sensitive data are and feel they are not fully protected. The analysis also revealed that the majority of users, regardless of their preferred authentication method are willing to try new authentication methods that promise to offer a higher level of security for their personal data. © 2020 ACM.

关键词： Sensitive data

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Recognition of food-texture attributes using an in-ear microphone

arXiv

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arXiv 2021年

作者： Mars, Monica Diou, Christos Papapanagiotou, Vasileios van den Boer, Janet Delopoulos, Anastasios Multimedia Understanding Group Dpt. Electrical and Computer Engineering Faculty of Engineering Aristotle University of Thessaloniki Greece Department of Informatics and Telematics Harokopio University of Athens Greece Dpt. of Biomedical Signals and Systems Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Netherlands Division of Human Nutrition and Health Wageningen University Netherlands

Food texture is a complex property;various sensory attributes such as perceived crispiness and wetness have been identified as ways to quantify it. Objective and automatic recognition of these attributes has applications in multiple fields, including health sciences and food engineering. In this work we use an in-ear microphone, commonly used for chewing detection, and propose algorithms for recognizing three food-texture attributes, specifically crispiness, wetness (moisture), and chewiness. We use binary SVMs, one for each attribute, and propose two algorithms: one that recognizes each texture attribute at the chew level and one at the chewing-bout level. We evaluate the proposed algorithms using leave-one-subject-out cross-validation on a dataset with 9 subjects. We also evaluate them using leave-one-food-type-out cross-validation, in order to examine the generalization of our approach to new, unknown food types. Our approach performs very well in recognizing crispiness (0.95 weighted accuracy on new subjects and 0.93 on new food types) and demonstrates promising results for objective and automatic recognition of wetness and chewiness. Copyright © 2021, The Authors. All rights reserved.

关键词： Wearable technology

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Enriching social analytics with latent Twitter image information

Enriching social analytics with latent Twitter image informa...

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International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： Gerasimos Razis Georgios Theofilou Ioannis Anagnostopoulos Computer Science and Biomedical Informatics Dpt. University of Thessaly Lamia Greece School of Electrical & Computer Engineering National Technical University of Athens Athens Greece

ISBN: (数字)9781728159195

ISBN: (纸本)9781728159201

In this paper, we propose a framework that uses latent information from Twitter images by employing the Google Cloud Vision API platform aiming at enriching social analytics with semantics and textual information. Our study reveals that user-generated content, linked data as well as hidden concepts and textual information from social images can be highly considered for enriching social analytics. Finally, we publish our annotated dataset for further use and evaluation from our research community.

关键词： Social networking (online) Linked data Conferences Semantics Blogs User-generated content

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Wearable panic attack detection system 2017

Wearable panic attack detection system

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21st Pan-Hellenic Conference on informatics, PCI 2017

作者： Sapounaki, Maria Polychronou, Ioanna Gkonta, Maria Vogiatzoglou, Angeliki Kakarountas, Athanasios University of Thessaly Dpt. of Computer Science and Biomedical Informatics Lamia Greece

ISBN: (纸本)9781450353557

The paper proposes a wearable system for panic attack detection, constructed by COTS products. It is the first open hardware/open software prototype of its kind to the best of the authors knowledge. In this paper, the requirements of the system are presented, as well as the development of the system using open hardware and open software. All the components are described and the system is detailed in order to be repeated for use as a reference system forpanic attack detection. © 2017 Association for Computing Machinery.

关键词： Software prototyping

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Systolic binary counter using a cellular automaton-based prescaler 2017

Systolic binary counter using a cellular automaton-based pre...

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21st Pan-Hellenic Conference on informatics, PCI 2017

作者： Chioktour, Vasileios Spathoulas, Georgios Kakarountas, Athanasios University of Thessaly Dpt. of Computer Science and Biomedical Informatics Lamia Greece

ISBN: (纸本)9781450353557

Counters are among the fundamental digital circuits in every computing system. For this reason, counter design is of great interest in the design of computers and embedded systems, in terms of area requirements,power dissipation and performance. Many techniques have been proposed in the past specifically to increase the counter's speed without increasing design complexity. Traditionally, it is of great concern to make a fast counter suitable for many applications, without adding to the critical path and keeping speed independent of its size. In this work, a binary counter is proposed, based on 1D Cellular Automata (CA), which is used as a prescaler in a systolic structure, that offers constant delay for counters of various bit-widths. © 2017 Association for Computing Machinery.

关键词： Cellular automata

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Home assistive system for dementia 2017

Home assistive system for dementia

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21st Pan-Hellenic Conference on informatics, PCI 2017

作者： Boumpa, Eleni Charalampou, Ioanna Gkogkidis, Anargyros Kakarountas, Athanasios University of Thessaly Dpt. of Computer Science and Biomedical Informatics Lamia Greece

ISBN: (纸本)9781450353557

This work proposes an innovative home assisted system, based on the interaction of the stimulus earpiece. It addresses a need of people suffering from dementia as well as their familiars to be recognized by them and have better interaction and collaboration. The project aims not only to people already suffering from dementia at early stages but also people with genetic predisposition who may be trained appropriately to discover and create acoustical stimuli associated to their familiars. The system offers an ubiquitous recognition system, without the need for extensive training of the patient, based on the principles of music therapy and the features of wireless communication. To the best of the authors knowledge, this is the first system of its kind ever reported in the literature.

关键词： Ubiquitous computing

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Efficient big data analysis on a single machine using apache spark and self-organizing map libraries

Efficient big data analysis on a single machine using apache...

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International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： David Andrešić Petr Šaloun Ioannis Anagnostopoulos Faculty of Electrical Engineering and Computer Science VŠB - Technical University of Ostrava Ostrava Czech republic Computer Science and Biomedical Informatics Dpt. University of Thessaly Lamia Greece

Apache Spark is commonly used as a big data analytical platform on powerful computer clusters, as it primarily employ the main computer memory for the evaluation. Our attempt adds self-organizing map software libraries onto a single big data analytical stack and is efficient and fast enough even on a standard single computer. This innovative approach brings the big data analysis to researchers with limited resources. Our genuine idea was experimentally confirmed and is described here. As a case study for our method we we used the available #Brexit data and the sentiment analysis of corresponding tweets and the correlation with the stock exchange data.

关键词： Sparks Stock markets Correlation Twitter Finance Big Data Industries

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Thematic labeling of Twitter accounts using DBpedia properties

Thematic labeling of Twitter accounts using DBpedia properti...

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International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： Gerasimos Razis Ioannis Anagnostopoulos Petr Saloun Computer Science and Biomedical Informatics Dpt. University of Thessaly Lamia Greece Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Czech Republic

ISBN: (纸本)9781509052479

In this paper, we propose an iterative algorithm towards the automatic labeling of Twitter accounts in respect to thematic categories derived from DBpedia properties. We describe the rationale behind the selection of these thematic categories, and discuss their evaluation assessment. Finally, we propose and analyze two generic and adaptable methodologies for discovering the necessary linked data resources for further enhancing the thematic description of Twitter accounts.

关键词： Twitter Labeling Measurement Classification algorithms Tagging Semantics Algorithm design and analysis

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Semantic social analytics and linked open data cloud

Semantic social analytics and linked open data cloud

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International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： Gerasimos Razis Ioannis Anagnostopoulos Michalis Vafopoulos Computer Science and Biomedical Informatics Dpt. University of Thessaly Lamia Greece NCSR “Demokritos” Software and Knowledge Engineering Laboratory Athens Greece

ISBN: (纸本)9781467383967

In this paper, we propose an ontology schema towards linking semantified Twitter social analytics with the Linked Open Data cloud. The ontology is deployed over a publicly available service that measures how influential a Twitter account is by combining its social activity in Twitter. According to our knowledge this is the first work that combines social analytics with the Linked Open Data (LOD) cloud.

关键词： Twitter Ontologies Resource description framework Measurement Semantics Tagging

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InfluenceTracker: Rating the impact of a twitter account

IFIP Advances in Information and Communication Technology

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IFIP Advances in Information and Communication Technology 2014年 437卷 184-195页

作者： Razis, Gerasimos Anagnostopoulos, Ioannis Computer Science and Biomedical Informatics Dpt University of Thessaly Lamia Greece

This paper describes a methodology for rating the influence of a Twitter account in this famous microblogging service. Then it is evaluated over real accounts, under the belief that influence is not only a matter of quantity (amount of followers), but also a mixture of quality measures that reflect interaction, awareness, and visibility in the social sphere. The authors of this paper have created "InfluenceTracker", a publicly available website1 where anyone can rate and compare the recent activity of any Twitter account. © IFIP International Federation for Information Processing 2014.

关键词： Social networking (online)

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