Theses e-submission tool at the National Technical University of Athens

Purpose – This paper's aim it to analyze added value that the theses e-submission system (tool) gave to the NTUA IR service. Design/methodology/approach – The paper describes the e-submission tool, its procedures and evaluates its use. Findings – The tool improved the IR service, which can be certified by the continuing evaluation process. This process produced the following main results: the automated batch importing feature should be integrated into the e-submission system; IR service tutorials should be given to the secretariats, faculty and students; and in-house service marketing should be conducted. Research limitations/implications – The present study provides a starting-point for further research in DL open source software. Originality/value – The paper shows that the tool helped NTUA users in submitting their e-theses, and the IR staff in organizing efficiently the service workflow and the data integration into the DSpace system. The process weaknesses rectifications will enhanse the service and allow its broadness to all NTUA departments. This tool implementation may start a debate to the DSpace community in using proxies between DSpace platform and the end user, as an alternative

Uncertainty-driven Ensemble Forecasting of QoS in Software Defined Networks

Software Defined Networking (SDN) is the key technology for combining networking and Cloud solutions to provide novel applications. SDN offers a number of advantages as the existing resources can be virtualized and orchestrated to provide new services to the end users. Such a technology should be accompanied by powerful mechanisms that ensure the end-to-end quality of service at high levels, thus, enabling support for complex applications that satisfy end users needs. In this paper, we propose an intelligent mechanism that agglomerates the benefits of SDNs with real-time “Big Data” forecasting analytics. The proposed mechanism, as part of the SDN controller, supports predictive intelligence by monitoring a set of network performance parameters, forecasting their future values, and deriving indications on potential service quality violations. By treating the performance measurements as time-series, our mechanism employs a novel ensemble forecasting methodology to estimate their future values. Such predictions are fed to a Type-2 Fuzzy Logic system to deliver, in real-time, decisions related to service quality violations. Such decisions proactively assist the SDN controller for providing the best possible orchestration of the virtualized resources. We evaluate the proposed mechanism w.r.t. precision and recall metrics over synthetic data

Uncertainty-driven Ensemble Forecasting of QoS in Software Defined Networks

Software Defined Networking (SDN) is the key technology for combining networking and Cloud solutions to provide novel applications. SDN offers a number of advantages as the existing resources can be virtualized and orchestrated to provide new services to the end users. Such a technology should be accompanied by powerful mechanisms that ensure the end-to-end quality of service at high levels, thus, enabling support for complex applications that satisfy end users needs. In this paper, we propose an intelligent mechanism that agglomerates the benefits of SDNs with real-time “Big Data” forecasting analytics. The proposed mechanism, as part of the SDN controller, supports predictive intelligence by monitoring a set of network performance parameters, forecasting their future values, and deriving indications on potential service quality violations. By treating the performance measurements as time-series, our mechanism employs a novel ensemble forecasting methodology to estimate their future values. Such predictions are fed to a Type-2 Fuzzy Logic system to deliver, in real-time, decisions related to service quality violations. Such decisions proactively assist the SDN controller for providing the best possible orchestration of the virtualized resources. We evaluate the proposed mechanism w.r.t. precision and recall metrics over synthetic data

Evaluating the NTUA institutional repository

The National Technical University of Athens (NTUA), through its Central Library, offers an Institutional Repository (IR) and ETD submission service, currently operating in a pilot testing period. The main objectives of this paper can be summarized into three major points. Primarily, to evaluate the IR service pilot period, focusing on the ETD submission process. Secondarily, to refine and improve the above mentioned process and, finally, to promote the concept of self-archiving and open access. The project was undertaken by implementing a web-based survey, targeting on the ETD submission users’ population. The data were imported into and processed by statistical analysis software. The key results were exposed online, as part of the IR system, updated in real time, since the survey is an ongoing procedure. The statistical analysis produced useful results regarding various aspects of the IR service. The major descriptive statistics focused on user groups, administrative staff and procedure grading, as well as access policy selection. Moreover, cross tabulations and correlations were created between all variables, for example “university department” and/or “ETD type” associated with “access policy”. A positive user attitude towards the procedure was noted, which motivates us to further enhance and expand the service. Our first milestone is to broaden the service to incorporate all the university departments. For that to happen, the statistical results will be used to forecast, define and, finally, determine the process needs, both in technical and human resources terms. Process weaknesses detected will be rectified, wherever possible, whereas process strengths will be used to market the service. At the same time, certain improvements, such as the transition from a semi-automated metadata importing process into the main IR (DSpace), to a fully automated one (batch), are already in development

Ψηφιακή χαρτογράφηση γεωλογικού χάρτη του τοπογραφικού φύλλου "Μοχός"

Η εργασία αφορά στην ηλεκτρονική επεξεργασία και αποτύπωση δεδομένων που έχουν ληφθεί στο ύπαιθρο σχετικά με τη γεωλογία και τον τεκτονισμό της περιοχής που απεικονίζεται στο τοπογραφικό φύλλο "Μοχός", που βρίσκεται στην κεντρική Κρήτη. Κατά τη διαδικασία αυτή ψηφιοποιήθηκαν τα όρια των γεωλογικών σχηματισμών του χάρτη και αποτυπώθηκαν οι στρωματογραφικές και οι τεκτονικές επαφές που υπάρχουν σε αυτόν.This work concerns the digital processing and recording of data received in the countryside, related to the stratigraphic and tectonic structures observed in the area of the topographic sheet "Mohos", which is located in the central Crete. During this process, the boundaries of the geological formations and the stratigraphic and tectonic contacts of the map were digitized

The Wisconsin Breast Cancer Problem: Diagnosis and DFS time prognosis using

probabilistic and generalised regression neural classifier