| 1. |
- Mitra, Karan, et al.
(författare)
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ALPINE : A Bayesian System For Cloud Performance Diagnosis And Prediction
- 2017
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Ingår i: 2017 IEEE International Conference on Services Computing (SCC). - Piscataway, NJ : IEEE. - 9781538620052 ; , s. 281-288
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Konferensbidrag (refereegranskat)abstract
- Cloud performance diagnosis and prediction is a challenging problem due to the stochastic nature of the cloud systems. Cloud performance is affected by a large set of factors such as virtual machine types, regions, workloads, wide area network delay and bandwidth. Therefore, necessitating the determination of complex relationships between these factors. The current research in this area does not address the challenge of modeling the uncertain and complex relationships between these factors. Further, the challenge of cloud performance prediction under uncertainty has not garnered sufficient attention. This paper proposes, develops and validates ALPINE, a Bayesian system for cloud performance diagnosis and prediction. ALPINE incorporates Bayesian networks to model uncertain and complex relationships between several factors mentioned above. It handles missing, scarce and sparse data to diagnose and predict stochastic cloud performance efficiently. We validate our proposed system using extensive real data and show that it predicts cloud performance with high accuracy of 91.93%.
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| 2. |
- Nugent, Christopher, et al.
(författare)
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Improving the Quality of User Generated Data Sets for Activity Recognition
- 2016
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Ingår i: Ubiquitous Computing and Ambient Intelligence, UCAMI 2016, PT II. - Amsterdam : Springer Publishing Company. - 9783319487991 - 9783319487984 ; , s. 104-110
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Konferensbidrag (refereegranskat)abstract
- It is fully appreciated that progress in the development of data driven approaches to activity recognition are being hampered due to the lack of large scale, high quality, annotated data sets. In an effort to address this the Open Data Initiative (ODI) was conceived as a potential solution for the creation of shared resources for the collection and sharing of open data sets. As part of this process, an analysis was undertaken of datasets collected using a smart environment simulation tool. A noticeable difference was found in the first 1-2 cycles of users generating data. Further analysis demonstrated the effects that this had on the development of activity recognition models with a decrease of performance for both support vector machine and decision tree based classifiers. The outcome of the study has led to the production of a strategy to ensure an initial training phase is considered prior to full scale collection of the data.
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| 3. |
- Saqr, Mohammed, et al.
(författare)
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People, Ideas, Milestones : A Scientometric Study of Computational Thinking
- 2021
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Ingår i: ACM Transactions on Computing Education. - : Association for Computing Machinery (ACM). - 1946-6226. ; 21:3
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Tidskriftsartikel (refereegranskat)abstract
- The momentum around computational thinking (CT) has kindled a rising wave of research initiatives andscholarly contributions seeking to capitalize on the opportunities that CT could bring. A number of literaturereviews have showed a vibrant community of practitioners and a growing number of publications. However,the history and evolution of the emerging research topic, the milestone publications that have shaped itsdirections, and the timeline of the important developments may be better told through a quantitative, scientometric narrative. This article presents a bibliometric analysis of the drivers of the CT topic, as well as itsmain themes of research, international collaborations, influential authors, and seminal publications, and howauthors and publications have influenced one another. The metadata of 1,874 documents were retrieved fromthe Scopus database using the keyword “computational thinking.” The results show that CT research has been US-centric from the start, and continues to be dominated by US researchers both in volume and impact. International collaboration is relatively low, but clusters of joint research are found between, for example, anumber of Nordic countries, lusophone- and hispanophone countries, and central European countries. The results show that CT features the computing’s traditional tripartite disciplinary structure (design, modeling, and theory), a distinct emphasis on programming, and a strong pedagogical and educational backdrop including constructionism, self-efficacy, motivation, and teacher training.
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| 4. |
- Balouji, Ebrahim, 1985, et al.
(författare)
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A LSTM-based Deep Learning Method with Application to Voltage Dip Classification
- 2018
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Ingår i: 2018 18TH INTERNATIONAL CONFERENCE ON HARMONICS AND QUALITY OF POWER (ICHQP). - Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE). - 2164-0610. - 9781538605172 - 9781538605172
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Konferensbidrag (refereegranskat)abstract
- In this paper, a deep learning (DL)-based method for automatic feature extraction and classification of voltage dips is proposed. The method consists of a dedicated architecture of Long Short-Term Memory (LSTM), which is a special type of Recurrent Neural Networks (RNNs). A total of 5982 three-phase one-cycle voltage dip RMS sequences, measured from several countries, has been used in our experiments. Our results have shown that the proposedmethod is able to classify the voltage dips from learned features in LSTM, with 93.40% classification accuracy on the test data set. The developed architecture is shown to be novel for feature learning and classification of voltage dips. Different from the conventional machine learning methods, the proposed method is able to learn dip features without requiring transition-event segmentation, selecting thresholds, and using expert rules or human expert knowledge, when a large amount of measurement data is available. This opens a new possibility of exploiting deep learning technology for power quality data analytics and classification.
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| 5. |
- Eriksson, Eva, 1976, et al.
(författare)
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Makerspace in school : Considerations from a large-scale national testbed
- 2018
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Ingår i: International Journal of Child-Computer Interaction. - : Elsevier. - 2212-8689 .- 2212-8697. ; 16, s. 9-15
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Tidskriftsartikel (refereegranskat)abstract
- Digital fabrication and making has received a growing interest in formal and informal learning environments. However, many of these initiatives often start from a grassroots perspective, with little coordination on a national level. This paper illustrates and discusses a study from an ongoing large-scale national testbed in Sweden named Makerspace in schools (Makerskola). The project embodies a series of considerations that arise when a maker approach is applied to a geographically widespread national education context. The results of this study are based on an analysis of the extensive project documentation and first-hand experiences from initiating and running a large-scale national testbed in Sweden, involving more than 30 formal actors and more than one thousand active partners in a national educational setting. The main contribution of this paper is the identification and discussion of five different considerations that have emerged during the project, and include Procurement practices, The teacher and leader perspective, Informing national policy making, Creating equal opportunities, and Progression in digital fabrication.
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| 6. |
- Heintz, Fredrik, et al.
(författare)
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Computing at School in Sweden - Experiences from Introducing Computer Science within Existing Subjects
- 2015
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Ingår i: Informatics in Schools. Curricula, Competences, and Competitions /Lecture Notes in Computer Science and General Issues. - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. - 9783319253954 - 9783319253961 ; 9378, s. 118-130
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Konferensbidrag (refereegranskat)abstract
- Computing is no longer considered a subject area only relevant for a narrow group of professionals, but rather as a vital part of general education that should be available to all children and youth. Since making changes to national curricula takes time, people are trying to find other ways of introducing children and youth to computing. In Sweden, several current initiatives by researchers and teachers aim at finding ways of working with computing within the current curriculum. In this paper we present case studies based on a selection of these initiatives from four major regions in Sweden and based on these case studies we present our ideas for how to move forward on introducing computational thinking on a larger scale in Swedish education.
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| 7. |
- Heintz, Fredrik, 1975-, et al.
(författare)
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Introducing Programming and Digital Competence in Swedish K-9 Education
- 2017
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Ingår i: Informatics in Schools. - Cham : Springer. - 1611-3349 .- 0302-9743. - 9783319714820 - 9783319714837 ; , s. 117-128
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Konferensbidrag (refereegranskat)abstract
- The role of computer science and IT in Swedish schools has varied throughout the years. In fall 2014, the Swedish government gave the National Agency for Education (Skolverket) the task of preparing a proposal for K–9 education on how to better address the competences required in a digitalized society. In June 2016, Skolverket handed over a proposal introducing digital competence and programming as interdisciplinary traits, also providing explicit formulations in subjects such as mathematics (programming, algorithms and problem-solving), technology (controlling physical artifacts) and social sciences (fostering aware and critical citizens in a digital society). In March 2017, the government approved the new curriculum, which needs to be implemented by fall 2018 at the latest. We present the new K–9 curriculum and put it in a historical context. We also describe and analyze the process of developing the revised curriculum, and discuss some initiatives for how to implement the changes.
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| 8. |
- Kim, Joochan, et al.
(författare)
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Detecting boredom from eye gaze and EEG
- 2018
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Ingår i: Biomedical Signal Processing and Control. - : Elsevier. - 1746-8094 .- 1746-8108. ; 46, s. 302-313
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Tidskriftsartikel (refereegranskat)abstract
- The recent proliferation of affordable physiological sensors has boosted research and development efforts of emotion-aware systems. Boredom has received relatively little attention as a target emotion, and we identified a lack of research on the relationship between eye gaze and electroencephalogram (EEG) when people feel bored. To investigate this matter, we first conducted a background study on boredom and its detection by physiological methods. Then, we designed and executed an experiment that uses a video stimulus – specifically designed for this experiment, yet general enough for other boredom research – with an eye tracker and EEG sensor to elicit and detect boredom. Moreover, a questionnaire was used to confirm the existence of boredom. The experiment was based on a hypothesis that participants may feel bored when their gaze deviates from an expected area of interest, thus indicating loss of attention. The results of the experiment indicated correlations between eye gaze data and EEG data with all participants (N = 13) when they felt bored. This study can be useful for researchers who have interest in developing boredom-aware systems.
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| 9. |
- Simistira Liwicki, Foteini, et al.
(författare)
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Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition
- 2023
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Ingår i: Scientific Data. - : Springer Nature. - 2052-4463. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- The recognition of inner speech, which could give a ‘voice’ to patients that have no ability to speak or move, is a challenge for brain-computer interfaces (BCIs). A shortcoming of the available datasets is that they do not combine modalities to increase the performance of inner speech recognition. Multimodal datasets of brain data enable the fusion of neuroimaging modalities with complimentary properties, such as the high spatial resolution of functional magnetic resonance imaging (fMRI) and the temporal resolution of electroencephalography (EEG), and therefore are promising for decoding inner speech. This paper presents the first publicly available bimodal dataset containing EEG and fMRI data acquired nonsimultaneously during inner-speech production. Data were obtained from four healthy, right-handed participants during an inner-speech task with words in either a social or numerical category. Each of the 8-word stimuli were assessed with 40 trials, resulting in 320 trials in each modality for each participant. The aim of this work is to provide a publicly available bimodal dataset on inner speech, contributing towards speech prostheses.
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| 10. |
- 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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