Daniel Vladusic

Daniel Vladusic
XLAB · Research

About

32
Publications
2,383
Reads
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164
Citations
Citations since 2017
9 Research Items
60 Citations
201720182019202020212022202305101520
201720182019202020212022202305101520
201720182019202020212022202305101520
201720182019202020212022202305101520
Introduction
Skills and Expertise

Publications

Publications (32)
Chapter
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This chapter presents the main characteristics of SODALITE to give the reader an overall picture, which will be detailed in the following chapters.
Chapter
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This chapter presents the motivation for SODALITE highlighting the difficulties faced by developers of complex applications when they need to deploy such applications in execution contexts where the usage of heterogeneous resources (HPC, Cloud and Edge) coexist. An overview of the state of the art to highlight gaps and open issues is also presented...
Preprint
Full-text available
In this paper, we present a novel system for predicting vessel turnaround time, based on machine learning and standardized port call data. We also investigate the use of specific external maritime big data, to enhance the accuracy of the available data and improve the performance of the developed system. An extensive evaluation is performed in Port...
Presentation
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This is the whitepaper used as a position paper, presenting the highlights of the value proposition of SODALITE.
Conference Paper
Full-text available
Testing is a vastly cost-intense part of automotive development, that intensifies with the introduction of autonomous driving features. Since real driving tests cannot cover all potential situations that can occur in the real world, we established an approach to test scenarios virtually and identify potential critical parameter combinations of the...
Article
The aim of the paper is to present a critical review of analytics and visualisation technology for big data, and propose future directions to overcome the shortcomings of the current technologies. The current machine learning and data-mining algorithms are operating mostly on predefined scales of aggregation, while in the vast amounts of data the p...
Article
In the age of digital photography, the amount of photos we have in our personal collections has increased substantially along with the effort needed to manage these new, larger collections. This issue has already been addressed in various ways: from organization by meta-data analysis to image recognition and social network analysis. We introduce a...
Article
This paper describes MTi, a biometric method for user identification on multitouch displays. The method is based on features obtained only from the coordinates of the 5 touchpoints of one of the user's hands. This makes MTi applicable to all multitouch displays large enough to accommodate a human hand and detect 5 or more touchpoints without requir...
Chapter
This paper describes our approach to hand detection on a multitouch surface i.e. detecting how many hands are currently on the surface and associating each touch point to its corresponding hand. Our goal was to find a general software-based solution to this problem applicable to all multitouch surfaces regardless of their construction. We therefore...
Article
Full-text available
This paper presents the web application, called Digital Encyclopaedia of Heritage (or DEDI) as a new milestone in the field of preservation and presentation of the Slovenian cultural and natural heritage. It introduces novel concepts, and aims for a more interactive search capability, and a greater presentation of the heritage to the general public...
Conference Paper
In this paper we tackle the problem of personalizing the experience of browsing through digital pictures. We address two questions: how to capture the user’s personal affinity for a particular picture and how to visualize a large collection of pictures. We propose a novel approach towards organizing pictures called ShoeBox that aims for automatic c...
Article
Full-text available
Predmet prispevka je predstavitev spletnega mesta Digitalne enciklopedije dediščine − DEDI, ki prinaša nove koncepte na področju varovanja in predstavljanja dediščine najširši javnosti. DEDI zagotavlja podporo znanstveno-raziskovalnemu delu, učenju, kulturnemu razvoju, utrjuje narodno identiteto ter prispeva k prepoznavnosti in konkurenčnosti Slove...
Article
The article presents the website of the Digital Heritage Encyclopaedia called DEDI, which introduces new concepts to the protection and presentation of heritage to the general public. DEDI provides support to scientific-research activities, learning and cultural development, strengthens the national identity, and contributes to Slovenia's recognisa...
Article
The project entitled "Digital encyclopaedia of Slovenian natural and cultural heritage" (DEDI II) has been evolved as a prototype research and development project (2009-2010). It represents the first attempt of multimedia-rich digital representation of Slovenian natural and cultural heritage by the means of interdisciplinary work of different cultu...
Article
This article focuses on mapping jobs to resources with use of off-the-shelf machine learning methods. The machine learning methods are used in the black-box manner, having a wide variety of parameters for internal cross validation. In the article we focus on two sets of experiments, both constructed with a goal of congesting the system. In the firs...
Conference Paper
This paper presents an attempt to improve job scheduling over heterogeneous GRID nodes by employing machine learning methods. Our proposed architecture takes into account the fact that GRID frameworks and their modules are not easy to modify or re-implement. It is therefore our aim to provide a plug-in which can be easily added to existing framewor...
Article
A load-balanced exact solver for computing the exact solutions of minimum k-center and related facility locations problems, is described. To achieve the load balance on a dedicated multiprocessor system, i.e., a cluster or a supercomputer, a new algorithm for parallel generation of a set of all k-combinations of n-things (without repetitions) is in...
Article
This paper describes modelling of time behaviour of phytoplankton and zooplankton in the Danish lake Glumso with a recently developed approach to machine learning in numerical domains, called Q2 learning. An essential part of this approach is qualitative constraints which were either handcrafted using knowledge from the Lotka‐Volterra predator‐prey...
Article
Full-text available
XtreemOS aims to build and promote a Linux based operating system to provide native Virtual Organization (VO) support in the next generation Grids. XtreemOS takes a different approach from many existing Grid middleware by: first, recognizing the fundamental role of VO in Grid computing and hence taking VO support into account from the very beginnin...
Article
In this paper we describe an application of Q 2 learning, a recently developed approach to machine learning in numerical domains (Šuc et al., 200329. Šuc , D. , D. Vladušič , and I. Bratko . 2003 . Qualitatively faithful quantitative prediction . Proceedings of the eighteenth International Joint Conference on Artificial Intelligence , 1052 – 1057 ,...
Article
In this paper, we describe an application of Q2 learning, a recently developed approach to machine learning in numerical domains, to the automated modelling of an aquatic ecosystem from measured data. We modelled the time behaviour of phytoplankton and zooplankton in Danish Lake Glumsø using data collected by S.E. Jørgensen. The novelty of Q2 learn...
Article
We describe a case study in which we applied Q2 learning (qualitatively faithful quantitative learning) to the analysis and prediction of ozone concentrations in the cities of Ljubljana and Nova Gorica, Slovenia. We used program QUIN to induce a qualitative model from numerical data that include the measurements of several meteorological and chemic...
Article
We describe a case study in which we applied Q2 learning (qualitatively faithful quantitative learning) to the analysis and prediction of ozone concentrations in the cities of Ljubljana and Nova Gorica, Slovenia. We used program QUIN to induce a qualitative model from numerical data that include the measurements of several meteorological and chemic...
Article
We describe an approach to machine learning from numerical data that combines both qualitative and numerical learning. This approach is carried out in two stages: (1) induction of a qualitative model from numerical examples of the behaviour of a physical system, and (2) induction of a numerical regression function that both respects the qualitative...
Article
In this paper we describe a case study in which we applied an approach to qualitative machine learning to induce, from system's behaviour data, a qualitative model of a complex, industrially relevant mechanical system (a car wheel suspension system). The induced qualitative model enables nice causal interpretation of the relations in the modelled s...
Conference Paper
Full-text available
Abstract We describe an approach to machine,learning from numerical data that combines,both qualitative and numerical learning. This approach is carried out in two stages: (1) induction of a qualitative model from numerical examples of the behaviour of a physical system, and (2) induction of a numerical,regression function that both respects the qu...
Article
Full-text available
This paper describes the Institution Finder, an approach to develop a simple web mining procedure to find the internet domain of the institution(s) that a given researcher is affiliated with. The Institution Finder starts several queries on public Web search engines and tries to extract from the hits the institution names and internet domains that...

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