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Theodora Varvarigou

National Technical University of Athens

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Dimosthenis Kyriazis

University of Piraeus

Konstantinos Tserpes

Harokopio University of Athens

Andreas Menychtas

University of Piraeus

Vassiliki Andronikou

Cyprus Research and Innovation Center (Cyprus)

George Kousiouris

Harokopio University of Athens

Αντώνιος Λίτκε

National Technical University of Athens

Anastasios Doulamis

National Technical University of Athens

Kleopatra Konstanteli

National Technical University of Athens

Athanasios Voulodimos

National Technical University of Athens

Spyridon V. Gogouvitis

Siemens (Germany)

Cooperative Institutions

National Technical University of Athens

National and Kapodistrian University of Athens

Institute of Communication and Computer Systems

University of Patras

Harokopio University of Athens

University of Southampton

Atos (Spain)

Foundation for Research and Technology Hellas

University of Ioannina

Aristotle University of Thessaloniki

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A Threefold Dataset for Activity and Workflow Recognition in Complex Industrial Environments

IEEE Multimedia (2012)

Athanasios Voulodimos Dimitrios Kosmopoulos Georgios Vasileiou Emmanuel Sardis Vasileios Anagnostopoulos

Unlike any previous effort, the Workflow Recognition (WR) large-scale dataset is a collection of video sequences from the real industrial manufacturing environment of a major automobile manufacturer.

Activity Recognition

10.1109/mmul.2012.31

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Citations (35)

Software modernization and cloudification using the ARTIST migration methodology and framework

Scalable Computing Practice and Experience (2014)

Andreas Menychtas Kleopatra Konstanteli Juncal Alonso Leire Orue-Echevarria Jesús Gorroñogoitia

Cloud computing has leveraged new software development and provisioning approaches by changing the way computing, storage and networking resources are purchased and consumed.The variety of cloud offerings on both technical and business level has considerably advanced the development process and established new business models and value chains for applications and services.However, the modernization and cloudification of legacy software so as to be offered as a service still encounters many challenges.In this work, we present a complete methodology and a methodology instantiation framework for the effective migration of legacy software to modern cloud environments.

10.12694/scpe.v15i2.980

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Citations (22)

Clustering Documents using the 3-Gram Graph Representation Model

John Violos Konstantinos Tserpes Αθανάσιος Παπαοικονόμου Magdalini Kardara Theodora Varvarigou

In this paper we illustrate an innovative clustering method of documents using the 3-Gram graphs representation model and deducing the problem of document clustering to graph partitioning. For the latter we employ the kernel k-means algorithm. We evaluated the proposed method using the Test Collections of Reuters-21578, and compared the results using the Latent Dirichlet Allocation (LDA) Algorithm. The results are encouraging demonstrating that the 3-Gram graph method has much better Recall and F1 score but worse Precision. Further changes that will further improve the results are identified.

n-gram

Kernel (algebra)

Clustering coefficient

Gram

Representation

10.1145/2645791.2645812

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Citations (2)

Video summarization guiding evaluative rectification for industrial activity recognition

Athanasios Voulodimos Anastasios Doulamis Dimitrios Kosmopoulos Theodora Varvarigou

In this paper we present a video summarization method that extracts key-frames from industrial surveillance videos, thus dramatically reducing the number of frames without significant loss of semantic content. We propose to use the produced summaries as training set for neural network based Evaluative Rectification. Evaluative Rectification is a method that exploits an expert user's feedback regarding the correctness of an activity recognition framework on part of the data in order to enhance future classification results. The size of the training sample set usually depends on the topology of the network and on the complexity of the environment and activities observed. However, as is shown by the experiments conducted in a real-world industrial activity recognition dataset, using a much smaller but representative sample stemming from our summarization technique leads to significantly higher accuracy rates than those attained by a same size but randomly chosen set. To obtain comparable improvement in accuracy without the summarization technique, the experiments show that a far larger training sample set is needed, therefore requiring significantly increased human resources and computational cost.

Sample (material)

10.1109/iccvw.2011.6130354

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Citations (3)

Information Management in a Grid-Based E-Health Business Environment

IGI Global eBooks (2011)

Vassiliki Andronikou Gabriel Sideras Dimitrios Halkos Michael Firopoulos Theodora Varvarigou

E-business today has moved focus to information sharing and integration across organisational boundaries in an effort to transform business processes throughout the value chain and standardize collaboration among communicating entities. Healthcare comprises a strongly collaborative distributed business environment in which information value plays a strategic role and informational privacy comprises a great concern. This new era in e-business, however, is followed by a series of issues that need to be addressed both at application and infrastructural level, such as information heterogeneity, system interoperability, security and privacy. The Grid as a technology enables sharing, selection, and aggregation of a wide variety of distributed resources comes to fill these gaps. In this chapter, the communication of information among healthcare organisations operating over a Grid infrastructure will be presented and analysed both from a technical and a business perspective.

Information Sharing

10.4018/978-1-60566-988-5.ch090

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Special section: Real-time attributes in grids

Future Generation Computer Systems (2009)

Theodora Varvarigou Αντώνιος Λίτκε Dimosthenis Kyriazis

Section (typography)

Special section

10.1016/j.future.2009.03.003

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Citations (1)

SCAL-E: An Auto Scaling Agent for Optimum Big Data Load Balancing in Kubernetes Environments

Efstratios Karypiadis Anastasios Nikolakopoulos Achilleas Marinakis Vrettos Moulos Theodora Varvarigou

During the past years, the issue of effectively balancing incoming big data streams has been under serious research. It still allows for new solutions, even if load balancing is already being addressed by multiple frameworks. This paper proposes a smart agent, named "SCAL-E" that achieves balancing of big data loads and lives within the Kubernetes Environment. SCAL-E takes advantage of MongoDB's scaling, replicating & sharding capabilities and decides when to increase or decrease its repository's sub-components, based on the incoming load. This way, SCAL-E assures of proper resource allocation and gives efficiency to the jobs of big data storing & forwarding.

10.1109/cits55221.2022.9832990

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Citations (4)

Opportunistic Collaborative Service Networks: The Facilitator for Efficient Data and Services Exchange

Springer eBooks (2016)

Dimosthenis Kyriazis George Kousiouris Alexandros Psychas Andreas Menychtas Theodora Varvarigou

Facilitator

Provisioning

10.1007/978-3-319-47063-4_32

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Citations (1)

Retrieving, Storing, Correlating and Distributing Information for Cloud Management

Lecture notes in computer science (2012)

Spyridon V. Gogouvitis Gregory Katsaros Dimosthenis Kyriazis Athanasios Voulodimos Roman Talyansky

Service catalog

10.1007/978-3-642-35194-5_9

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Citations (3)

A Service Oriented Architecture Enabling Policy Simulation in Virtual Spaces

Magdalini Kardara Omri Fuchs Fotis Aisopos Αθανάσιος Παπαοικονόμου Konstantinos Tserpes

In order to be able to measure the impact of future government proposals and policies on a large scale, policy makers need artificial environments that enable mass participation and user interaction in contexts that simulate real life societies. These environments will be used as "sandboxes" where potential policies will be put to force and users' reactions will be captured and analyzed in order to make estimations about the effectiveness of the policy in real societies. Virtual spaces including 3D virtual worlds and social networks are ideal for this purpose as, due to their popularity as well as their similarity to the real world, they can be seen as a simulation of society, a micro-society. The +Spaces project aims to provide the technology enabling governments to use Virtual Spaces as testing environments where prospective policies can be applied, as well as the necessary tools for capturing, processing and analyzing public reactions to them. The current paper presents a SOA based architecture that resides on top of Virtual Spaces and allows users to deploy applications that enable policy simulation, monitor and evaluate users' reactions to the new policy and present the results to the policy maker in a meaningful way.

Popularity

Metaverse

10.1109/vs-games.2011.42

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Citations (1)

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