ADAPT started with the online Kickoff meeting, coordinated by Prof. Radu Prodan.
Prof. Radu Prodan is a keynote speaker at Memphis DATA 2021, 25th-26th March 2021.
Talk Abstract: We live in a digital world estimated to host around 4 billion Internet users and 10 billion of mobile connections generating 2.5 billion billion of data every day. Managing and extracting value from this sheer amount of raw data requires deep software analysis tools on massive distributed and parallel computing infrastructures aggregating billions of cores and threads. The talk gives an overview of the research activities at the University of Klagenfurt, Austria, on optimising system software support for extreme-scale data processing applications, with focus on scientific simulations, social media and massively multiplayer online games.
Title: WELFake: Word Embedding over Linguistic Features for Fake News Detection
Authors: Pawan Kumar Verma (Lovely Professional University, India | GLA University, India), Prateek Agrawal (University of Klagenfurt, Austria | Lovely Professional University, India), Ivone Amorin (MOG Technologies | University of Porto, Portugal), Radu Prodan (University of Klagenfurt, Austria)
Abstract: Social media is a popular medium for dissemination of real-time news all over the world. Easy and quick information proliferation is one of the reasons for its popularity. An extensive number of users with different age groups, gender and societal beliefs are engaged in social media websites. Despite these favorable aspects, a significant disadvantage comes in the form of fake news, as people usually read and share information without caring about its genuineness. Therefore, it is imperative to research methods for the authentication of news. To address this issue, this paper proposes a two phase benchmark model named WELFake based on word embedding (WE) over linguistic features for fake news detection using machine learning classification. The first phase pre-processes the dataset and validates the veracity of news content by using linguistic features. The second phase merges the linguistic feature sets with WE and applies voting classification. To validate its approach, this paper also carefully designs a novel WELFake dataset with approximately 72,000 articles, which incorporates different datasets to generate an unbiased classification output. Experimental results show that the WELFake model categorises the news in real and fake with a 96.73% which improves the overall accuracy by 1.31% compared to BERT and 4.25% compared to CNN models. Our frequency-based and focused analyzing writing patterns model outperforms predictive-based related works implemented using the Word2vec WE method by up to 1.73%.
Acknowledgement: ARTICONF project
The full paper has been accepted to the main-track of the International Conference on Computational Science (ICCS’21). Conference will be organized in a virtual format on 16-18 June, 2021.
Title: Monte-Carlo Approach to the Computational Capacities Analysis of the Computing Continuum
Authors: Vladislav Kashansky, Gleb Radchenko, Radu Prodan
Abstract: This article proposes an approach to the problem of computational capacities analysis of the computing continuum via theoretical framework of equilibrium phase-transitions and numerical simulations. We introduce the concept of phase transitions in computing continuum and show how this phenomena can be explored in the context of workflow makespan, which we treat as an order parameter. We simulate the behavior of the computational network in the equilibrium regime within the framework of the XY-model defined over complex agent network with Barabasi-Albert topology. More specifically, we define Hamiltonian over complex network topology and sample the resulting spin-orientation distribution with the Metropolis-Hastings technique. The key aspect of the paper is derivation of the bandwidth matrix, as the emergent effect of the “low-level” collective spin interaction. This allows us to study the first order approximation to the makespan of the “high-level” system-wide workflow model in the presence of data-flow anisotropy and phase transitions of the bandwidth matrix controlled by the means of “noise regime” parameter. For this purpose, we have built a simulation engine in Python 3.6. Simulation results confirm existence of the phase transition, revealing complex transformations in the computational abilities of the agents. Notable feature is that bandwidth distribution undergoes a critical transition from single to multi-mode case. Our simulations generally open new perspectives for reproducible comparative performance analysis of the novel and classic scheduling algorithms.
Keywords: Complex Networks, Computing Continuum, Phase Transitions, Computational Model, MCMC, Metropolis-Hastings, XY-model, Equilibrium Model
Acknowledgement: This work has received funding from the EC-funded project H2020 FETHPC ASPIDE (Agreement #801091)
The project “Kärntner Fog: A 5G-Enabled Fog Infrastructure for Automated Operation of Carinthia’s 5G Playground Application Use Cases” proposes a new infrastructure automation use case in the 5G Playground Carinthia (5GPG). Kärntner Fog plans to create and deploy a
distributed service middleware infrastructure over a diverse set of novel heterogeneous 5G edge devices, complemented by a high-performance Cloud data center accessible with low latency according to 5G standards. Such an infrastructure is currently missing in the 5GPG and will represent a horizontal backbone that interconnects and integrates the application use cases. Kärtner Fog will automate the development and operation of the applications use cases in the 5GPG in an integrated and more cost-effective fashion to enable more science and innovation within a limited budget.
Involved Organisations: BABEG, ITEC@AAU, ONDA TLC GmbH, FFG/KWF
Coordinator: Prof. Radu Prodan
Project Start: 01.01.2021
Project Duration: 48 months
The manuscript “Cloud, Fog or Edge: Where to Compute?” has been accepted for publication in an upcoming issue of IEEE Internet Computing.
Authors: Dragi Kimovski, Roland Mathá, Josef Hammer, Narges Mehran, Hermann Hellwagner and Radu Prodan
Abstract: The computing continuum extends the high-performance cloud data centers with energy-efficient and low-latency devices close to the data sources located at the edge of the network.
However, the heterogeneity of the computing continuum raises multiple challenges related to application management. These include where to offload an application – from the cloud to the edge – to meet its computation and communication requirements.
To support these decisions, we provide in this article a detailed performance and carbon footprint analysis of a selection of use case applications with complementary resource requirements across the computing continuum over a real-life evaluation testbed.
Prof. Radu Prodan ist guest of honor at the 9th International Workshop on Soft Computing Applications (SOFA), 27-29 Nov 2020, Arad, Romania. The title of his talk is “Distribute one Billion”.
The newspaper “Kronen Zeitung” published the article “IM KAMPF GEGEN CORONA: Universität Klagenfurt forscht mit den Chinesen” with Prof. Radu Prodan.
The newspaper “Kleine Zeitung” published the article “Medizinische Schutzausrüstung: Neue IT-Lösung soll Menschenleben retten” with Prof. Radu Prodan.