Pub Date : 2019-07-01DOI: 10.1109/IISA.2019.8900697
Panagiota Polymeropoulou, C. Pierrakeas, Spiros A. Borotis, A. Kameas
It has been observed that the fast pace of the adoption of ICT in the museum sector concluded to a detachement between formal education or training and the labor market. Museum professionals need to acquire new skills and competences in order to deal with the digital challenges in their everyday work life. The adoption of new technologies and the continuous vocational development for the scientific personnel of a museum is considered a great asset. For this reason, the goal of Mu.SA (Museum Sector Alliance) project is to underline and deal with the lack of digital and transferable competences in the sector [1]. In this paper, will be presented the aim, the action plan, the main outputs and the first research results of Mu.SA, a Sector Skills Alliances EU funding project. The Mu.SA project develops an updated training programme adapted to the needs of museum professionals based on surveys and interviews conducted within the project across Europe. Also, it produces a range of innovative outcomes, including European profiles of emerging job roles in museums that serve as a common reference at European level, a staged VET methodology based on learning outcomes, policies and tools for assessment and validation of non-formal/ informal learning as well as modular VET curricula. The MOOC delivered in the first trimester of year 2019 raised the interest of participated museum professionals from all over the world
{"title":"Implementing a MOOC course for Museum Professionals with a worldwide effect","authors":"Panagiota Polymeropoulou, C. Pierrakeas, Spiros A. Borotis, A. Kameas","doi":"10.1109/IISA.2019.8900697","DOIUrl":"https://doi.org/10.1109/IISA.2019.8900697","url":null,"abstract":"It has been observed that the fast pace of the adoption of ICT in the museum sector concluded to a detachement between formal education or training and the labor market. Museum professionals need to acquire new skills and competences in order to deal with the digital challenges in their everyday work life. The adoption of new technologies and the continuous vocational development for the scientific personnel of a museum is considered a great asset. For this reason, the goal of Mu.SA (Museum Sector Alliance) project is to underline and deal with the lack of digital and transferable competences in the sector [1]. In this paper, will be presented the aim, the action plan, the main outputs and the first research results of Mu.SA, a Sector Skills Alliances EU funding project. The Mu.SA project develops an updated training programme adapted to the needs of museum professionals based on surveys and interviews conducted within the project across Europe. Also, it produces a range of innovative outcomes, including European profiles of emerging job roles in museums that serve as a common reference at European level, a staged VET methodology based on learning outcomes, policies and tools for assessment and validation of non-formal/ informal learning as well as modular VET curricula. The MOOC delivered in the first trimester of year 2019 raised the interest of participated museum professionals from all over the world","PeriodicalId":371385,"journal":{"name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130183357","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}
Pub Date : 2019-07-01DOI: 10.1109/IISA.2019.8900696
V. Poulopoulos, Manolis Wallace, Iraklis Varlamis, G. Caridakis, Panagiotis Tsantilas
This paper describes the national funded project entitled PaloAnalytics, which develops an innovative platform that enables organizations, which operate in many countries, to monitor and analyze, in depth, the markets’ interest to their products and successfully manage their marketing and communication plans, with data and insights collected from the local media. The project scope is to explore, design and develop a range of algorithms and tools in order to collect and manage big data from heterogeneous online news sources, social networks and open sources; to extract knowledge from textual references in a multilingual environment, and to interconnect information together by making user-friendly visualisations. In this paper, we specifically focus on the architecture of the system that performs trending topics extraction from the Twitter platform, presenting some early results from its implementation.
{"title":"PaloAnalytics: project concept, scope and early results from the system implementation","authors":"V. Poulopoulos, Manolis Wallace, Iraklis Varlamis, G. Caridakis, Panagiotis Tsantilas","doi":"10.1109/IISA.2019.8900696","DOIUrl":"https://doi.org/10.1109/IISA.2019.8900696","url":null,"abstract":"This paper describes the national funded project entitled PaloAnalytics, which develops an innovative platform that enables organizations, which operate in many countries, to monitor and analyze, in depth, the markets’ interest to their products and successfully manage their marketing and communication plans, with data and insights collected from the local media. The project scope is to explore, design and develop a range of algorithms and tools in order to collect and manage big data from heterogeneous online news sources, social networks and open sources; to extract knowledge from textual references in a multilingual environment, and to interconnect information together by making user-friendly visualisations. In this paper, we specifically focus on the architecture of the system that performs trending topics extraction from the Twitter platform, presenting some early results from its implementation.","PeriodicalId":371385,"journal":{"name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122581218","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}
Pub Date : 2019-07-01DOI: 10.1109/IISA.2019.8900773
Dimitris G. Tsarmpopoulos, A. Papanikolaou, S. Kotsiantis, T. Grapsa, G. Androulakis
Multi-objective optimization is undoubtedly one field with many applications in real life situations and constitutes a highly active research area. In this paper, a comparison among high-performing multi-objective metaheuristics optimization algorithms is provided. For the comparison, three well-known multi-objective optimization algorithms and the Random Search algorithm are utilized on benchmark multi-objective optimization test families. Their results are compared with the use of two different metrics in order to be fully and effectively assessed. Their results are also discussed, and some future research points are proposed.
{"title":"Performance Evaluation and Comparison of Multi-objective optimization Algorithms","authors":"Dimitris G. Tsarmpopoulos, A. Papanikolaou, S. Kotsiantis, T. Grapsa, G. Androulakis","doi":"10.1109/IISA.2019.8900773","DOIUrl":"https://doi.org/10.1109/IISA.2019.8900773","url":null,"abstract":"Multi-objective optimization is undoubtedly one field with many applications in real life situations and constitutes a highly active research area. In this paper, a comparison among high-performing multi-objective metaheuristics optimization algorithms is provided. For the comparison, three well-known multi-objective optimization algorithms and the Random Search algorithm are utilized on benchmark multi-objective optimization test families. Their results are compared with the use of two different metrics in order to be fully and effectively assessed. Their results are also discussed, and some future research points are proposed.","PeriodicalId":371385,"journal":{"name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"41 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123596586","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}
Pub Date : 2019-07-01DOI: 10.1109/IISA.2019.8900786
Oxana Kalita, V. Denisenko, G. Pavlidis
In this paper we present an innovative architecture for mobile learning that extends the capabilities of existing platforms for distance learning and enhances the educational infrastructure in terms of technology, process and content; two facts that lead to a higher cultural level of the educational community.
{"title":"Upgrading the Mobile Distance Learning System Architecture","authors":"Oxana Kalita, V. Denisenko, G. Pavlidis","doi":"10.1109/IISA.2019.8900786","DOIUrl":"https://doi.org/10.1109/IISA.2019.8900786","url":null,"abstract":"In this paper we present an innovative architecture for mobile learning that extends the capabilities of existing platforms for distance learning and enhances the educational infrastructure in terms of technology, process and content; two facts that lead to a higher cultural level of the educational community.","PeriodicalId":371385,"journal":{"name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127941923","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}
Pub Date : 2019-07-01DOI: 10.1109/IISA.2019.8900751
Leonidas Akritidis, Athanasios Fevgas, Panayiotis Bozanis, M. Alamaniotis
News aggregators are on-line services that collect articles from numerous reputable media and news providers and reorganize them in a convenient manner with the aim of assisting their users to access the information they seek. One of the most important tools offered by news aggregators is based on the classification of the articles into a fixed set of categories. In this article, we introduce a supervised classification method for news articles that analyzes their titles and constructs multiple types of tokens including single words and n-grams of variable sizes. In the sequel, it employs several statistics, such as frequencies and token-class correlations, to assign two importance scores to each token. These scores reflect the ambiguity of a token; namely, how significant it is for the classification of an article to a category. The tokens and their scores are stored in a support structure that is subsequently used to classify the unlabeled articles. In addition, we propose a dimensionality reduction approach that reduces the size of the model without significant degradation of its classification performance. The algorithm is experimentally evaluated by employing a popular dataset of news articles and is found to outperform standard classification methods.
{"title":"A Self-Pruning Classification Model for News","authors":"Leonidas Akritidis, Athanasios Fevgas, Panayiotis Bozanis, M. Alamaniotis","doi":"10.1109/IISA.2019.8900751","DOIUrl":"https://doi.org/10.1109/IISA.2019.8900751","url":null,"abstract":"News aggregators are on-line services that collect articles from numerous reputable media and news providers and reorganize them in a convenient manner with the aim of assisting their users to access the information they seek. One of the most important tools offered by news aggregators is based on the classification of the articles into a fixed set of categories. In this article, we introduce a supervised classification method for news articles that analyzes their titles and constructs multiple types of tokens including single words and n-grams of variable sizes. In the sequel, it employs several statistics, such as frequencies and token-class correlations, to assign two importance scores to each token. These scores reflect the ambiguity of a token; namely, how significant it is for the classification of an article to a category. The tokens and their scores are stored in a support structure that is subsequently used to classify the unlabeled articles. In addition, we propose a dimensionality reduction approach that reduces the size of the model without significant degradation of its classification performance. The algorithm is experimentally evaluated by employing a popular dataset of news articles and is found to outperform standard classification methods.","PeriodicalId":371385,"journal":{"name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121238132","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}
Pub Date : 2019-07-01DOI: 10.1109/IISA.2019.8900709
N. Tsagkas, Panagiotis Tsinganos, A. Skodras
In the past few years, a great interest for the classification of hand gestures with Deep Learning methods based on surface electromyography (sEMG) signals has been developed in the scientific community. In line with latest works in the field, the objective of our work is the construction of a novel Convolutional Neural Network architecture, for the classification of hand-gestures. Our model, while avoiding overfitting, did not perform significantly better compared to a much shallower network. The results suggest that the lack of diversity in the sEMG recordings between certain hand-gestures limits the performance of the model. In addition, the classification accuracy on a database we developed using a commercial device (Myo Armband) was substantially higher (approximately 24%) than a similar benchmark dataset recorded with the same device.
{"title":"On the Use of Deeper CNNs in Hand Gesture Recognition Based on sEMG Signals","authors":"N. Tsagkas, Panagiotis Tsinganos, A. Skodras","doi":"10.1109/IISA.2019.8900709","DOIUrl":"https://doi.org/10.1109/IISA.2019.8900709","url":null,"abstract":"In the past few years, a great interest for the classification of hand gestures with Deep Learning methods based on surface electromyography (sEMG) signals has been developed in the scientific community. In line with latest works in the field, the objective of our work is the construction of a novel Convolutional Neural Network architecture, for the classification of hand-gestures. Our model, while avoiding overfitting, did not perform significantly better compared to a much shallower network. The results suggest that the lack of diversity in the sEMG recordings between certain hand-gestures limits the performance of the model. In addition, the classification accuracy on a database we developed using a commercial device (Myo Armband) was substantially higher (approximately 24%) than a similar benchmark dataset recorded with the same device.","PeriodicalId":371385,"journal":{"name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130560292","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}
Pub Date : 2019-07-01DOI: 10.1109/iisa.2019.8900753
{"title":"IISA 2019 TOC","authors":"","doi":"10.1109/iisa.2019.8900753","DOIUrl":"https://doi.org/10.1109/iisa.2019.8900753","url":null,"abstract":"","PeriodicalId":371385,"journal":{"name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133333742","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}
Pub Date : 2019-07-01DOI: 10.1109/IISA.2019.8900701
Ioannis Daramouskas, V. Kapoulas, Theodoros Pegiazis
This survey provides a comprehensive review on localization systems and algorithms for LPWAN (Low Power Wide Area Networks). In particular, we are dealing with localization techniques for sensors in LoRa network technology, and we present methods for localizing mobile objects through that kind of network using different sensor measurements. Also, methods for improving the localization error are presented. The survey concludes with research directions, and a mention at the future work and trends.
{"title":"A survey of methods for location estimation on Low Power Wide Area Networks","authors":"Ioannis Daramouskas, V. Kapoulas, Theodoros Pegiazis","doi":"10.1109/IISA.2019.8900701","DOIUrl":"https://doi.org/10.1109/IISA.2019.8900701","url":null,"abstract":"This survey provides a comprehensive review on localization systems and algorithms for LPWAN (Low Power Wide Area Networks). In particular, we are dealing with localization techniques for sensors in LoRa network technology, and we present methods for localizing mobile objects through that kind of network using different sensor measurements. Also, methods for improving the localization error are presented. The survey concludes with research directions, and a mention at the future work and trends.","PeriodicalId":371385,"journal":{"name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116406487","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}
Pub Date : 2019-07-01DOI: 10.1109/IISA.2019.8900763
Angeliki Leonardou, Maria Rigou, J. Garofalakis
Achieving multiplication table fluency is a major concern during all primary school years and for many pupils it is considered a challenge. ‘Rote memory’ approaches that have been deployed for years in the traditional school curriculum have contributed to the prevailing assumption of pupils that Mathematics is unpleasant and uninviting. This paper presents a game-based approach to assess and gradually improve multiplication skills by combining an adaptive mechanism for identifying and resolving pupil weaknesses, while exposing parts of the learner model to the user through easily perceivable visualizations. Moreover, the game offers social comparison information and pupils can access progress data about their peers or their entire class a feature that is expected to improve self-reflection, allow for self-regulated learning and increase user motivation. This paper also presents the feedback received by the preliminary testing of the game with a representative sample of pupils and discusses the effect of allowing access to the progress of peers and summative class scores.
{"title":"Adding Social Comparison to Open Learner Modeling","authors":"Angeliki Leonardou, Maria Rigou, J. Garofalakis","doi":"10.1109/IISA.2019.8900763","DOIUrl":"https://doi.org/10.1109/IISA.2019.8900763","url":null,"abstract":"Achieving multiplication table fluency is a major concern during all primary school years and for many pupils it is considered a challenge. ‘Rote memory’ approaches that have been deployed for years in the traditional school curriculum have contributed to the prevailing assumption of pupils that Mathematics is unpleasant and uninviting. This paper presents a game-based approach to assess and gradually improve multiplication skills by combining an adaptive mechanism for identifying and resolving pupil weaknesses, while exposing parts of the learner model to the user through easily perceivable visualizations. Moreover, the game offers social comparison information and pupils can access progress data about their peers or their entire class a feature that is expected to improve self-reflection, allow for self-regulated learning and increase user motivation. This paper also presents the feedback received by the preliminary testing of the game with a representative sample of pupils and discusses the effect of allowing access to the progress of peers and summative class scores.","PeriodicalId":371385,"journal":{"name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114806437","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}
Pub Date : 2019-07-01DOI: 10.1109/IISA.2019.8900662
Vasileios Gkamas, Maria Rigou, I. Perikos, I. Gueorguiev, P. Varbanov, Christina Todorova
Data Science and Internet of Things are currently among the key drivers of skills and competences required by the IT market. As a skills’ gap is projected in the Data Science and Internet of Things domains, substantial effort is required by training providers for the upskilling of IT workforce. In this work, we present the macro-level design of the learning outcomes of a multi-disciplinary VET program for Data Science and Internet of Things. The macro-level design is based on a desktop research and a survey conducted among the VET program beneficiaries, which are companies running Data Science and/or Internet of Things projects.
{"title":"Learning outcomes design for Data Science and Internet of Things training programs","authors":"Vasileios Gkamas, Maria Rigou, I. Perikos, I. Gueorguiev, P. Varbanov, Christina Todorova","doi":"10.1109/IISA.2019.8900662","DOIUrl":"https://doi.org/10.1109/IISA.2019.8900662","url":null,"abstract":"Data Science and Internet of Things are currently among the key drivers of skills and competences required by the IT market. As a skills’ gap is projected in the Data Science and Internet of Things domains, substantial effort is required by training providers for the upskilling of IT workforce. In this work, we present the macro-level design of the learning outcomes of a multi-disciplinary VET program for Data Science and Internet of Things. The macro-level design is based on a desktop research and a survey conducted among the VET program beneficiaries, which are companies running Data Science and/or Internet of Things projects.","PeriodicalId":371385,"journal":{"name":"2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116928496","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：