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214 results on '"Savic, Milos"'

1. ASCAPE: An open AI ecosystem to support the quality of life of cancer patients

Author

Lampropoulos, Konstantinos, Kosmidis, Thanos, Autexier, Serge, Savic, Milos, Athanatos, Manos, Kokkonidis, Miltiadis, Koutsouri, Tzortzia, Vizitiu, Anamaria, Valachis, Antonios, and Padron, Miriam Quintero

Subjects
Computer Science - Artificial Intelligence
Abstract

The latest cancer statistics indicate a decrease in cancer-related mortality. However, due to the growing and ageing population, the absolute number of people living with cancer is set to keep increasing. This paper presents ASCAPE, an open AI infrastructure that takes advantage of the recent advances in Artificial Intelligence (AI) and Machine Learning (ML) to support cancer patients quality of life (QoL). With ASCAPE health stakeholders (e.g. hospitals) can locally process their private medical data and then share the produced knowledge (ML models) through the open AI infrastructure.

Published
2023
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2. ASCAPE - An Intelligent Approach to Support Cancer Patients

Author

Ilić, Mihailo, Ivanović, Mirjana, Jakovetić, Dušan, Kurbalija, Vladimir, Otlokan, Marko, Savić, Miloš, Vujnović-Sedlar, Nataša, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Rocha, Alvaro, editor, Adeli, Hojjat, editor, Dzemyda, Gintautas, editor, Moreira, Fernando, editor, and Colla, Valentina, editor

Published
2024
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4. Hub-aware Random Walk Graph Embedding Methods for Classification

Author

Tomčić, Aleksandar, Savić, Miloš, and Radovanović, Miloš

Subjects
Computer Science - Machine Learning, Computer Science - Social and Information Networks
Abstract

In the last two decades we are witnessing a huge increase of valuable big data structured in the form of graphs or networks. To apply traditional machine learning and data analytic techniques to such data it is necessary to transform graphs into vector-based representations that preserve the most essential structural properties of graphs. For this purpose, a large number of graph embedding methods have been proposed in the literature. Most of them produce general-purpose embeddings suitable for a variety of applications such as node clustering, node classification, graph visualisation and link prediction. In this paper, we propose two novel graph embedding algorithms based on random walks that are specifically designed for the node classification problem. Random walk sampling strategies of the proposed algorithms have been designed to pay special attention to hubs -- high-degree nodes that have the most critical role for the overall connectedness in large-scale graphs. The proposed methods are experimentally evaluated by analyzing the classification performance of three classification algorithms trained on embeddings of real-world networks. The obtained results indicate that our methods considerably improve the predictive power of examined classifiers compared to currently the most popular random walk method for generating general-purpose graph embeddings (node2vec)., Comment: Submitted to journal for possible publication

Published
2022

5. Local Intrinsic Dimensionality Measures for Graphs, with Applications to Graph Embeddings

Author

Savić, Miloš, Kurbalija, Vladimir, and Radovanović, Miloš

Subjects
Computer Science - Machine Learning, Computer Science - Social and Information Networks
Abstract

The notion of local intrinsic dimensionality (LID) is an important advancement in data dimensionality analysis, with applications in data mining, machine learning and similarity search problems. Existing distance-based LID estimators were designed for tabular datasets encompassing data points represented as vectors in a Euclidean space. After discussing their limitations for graph-structured data considering graph embeddings and graph distances, we propose NC-LID, a novel LID-related measure for quantifying the discriminatory power of the shortest-path distance with respect to natural communities of nodes as their intrinsic localities. It is shown how this measure can be used to design LID-aware graph embedding algorithms by formulating two LID-elastic variants of node2vec with personalized hyperparameters that are adjusted according to NC-LID values. Our empirical analysis of NC-LID on a large number of real-world graphs shows that this measure is able to point to nodes with high link reconstruction errors in node2vec embeddings better than node centrality metrics. The experimental evaluation also shows that the proposed LID-elastic node2vec extensions improve node2vec by better preserving graph structure in generated embeddings.

Published
2022

6. Tax Evasion Risk Management Using a Hybrid Unsupervised Outlier Detection Method

Author

Savić, Miloš, Atanasijević, Jasna, Jakovetić, Dušan, and Krejić, Nataša

Subjects
Computer Science - Machine Learning
Abstract

Big data methods are becoming an important tool for tax fraud detection around the world. Unsupervised learning approach is the dominant framework due to the lack of label and ground truth in corresponding data sets although these methods suffer from low interpretability. HUNOD, a novel hybrid unsupervised outlier detection method for tax evasion risk management, is presented in this paper. In contrast to previous methods proposed in the literature, the HUNOD method combines two outlier detection approaches based on two different machine learning designs (i.e, clustering and representational learning) to detect and internally validate outliers in a given tax dataset. The HUNOD method allows its users to incorporate relevant domain knowledge into both constituent outlier detection approaches in order to detect outliers relevant for a given economic context. The interpretability of obtained outliers is achieved by training explainable-by-design surrogate models over results of unsupervised outlier detection methods. The experimental evaluation of the HUNOD method is conducted on two datasets derived from the database on individual personal income tax declarations collected by the Tax Administration of Serbia. The obtained results show that the method indicates between 90% and 98% internally validated outliers depending on the clustering configuration and employed regularization mechanisms for representational learning., Comment: Submitted to Elsevier journal for possible publication

Published
2021

7. Deep Learning Anomaly Detection for Cellular IoT with Applications in Smart Logistics

Author

Savic, Milos, Lukic, Milan, Danilovic, Dragan, Bodroski, Zarko, Bajovic, Dragana, Mezei, Ivan, Vukobratovic, Dejan, Skrbic, Srdjan, and Jakovetic, Dusan

Subjects
Computer Science - Networking and Internet Architecture
Abstract

The number of connected Internet of Things (IoT) devices within cyber-physical infrastructure systems grows at an increasing rate. This poses significant device management and security challenges to current IoT networks. Among several approaches to cope with these challenges, data-based methods rooted in deep learning (DL) are receiving an increased interest. In this paper, motivated by the upcoming surge of 5G IoT connectivity in industrial environments, we propose to integrate a DL-based anomaly detection (AD) as a service into the 3GPP mobile cellular IoT architecture. The proposed architecture embeds autoencoder based anomaly detection modules both at the IoT devices (ADM-EDGE) and in the mobile core network (ADM-FOG), thereby balancing between the system responsiveness and accuracy. We design, integrate, demonstrate and evaluate a testbed that implements the above service in a real-world deployment integrated within the 3GPP Narrow-Band IoT (NB-IoT) mobile operator network., Comment: 12 pages, 9 figures, revised version, submitted to IEEE journal for possible publication

Published
2021

13. Evaluation of LID-Aware Graph Embedding Methods for Node Clustering

Author

Knežević, Dušica, Babić, Jela, Savić, Miloš, Radovanović, Miloš, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Skopal, Tomáš, editor, Falchi, Fabrizio, editor, Lokoč, Jakub, editor, Sapino, Maria Luisa, editor, Bartolini, Ilaria, editor, and Patella, Marco, editor

Published
2022
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14. Heterogeneous Tumour Modeling Using PhysiCell and Its Implications in Precision Medicine

Author

Savić, Miloš, Kurbalija, Vladimir, Balaz, Igor, Ivanović, Mirjana, Zelinka, Ivan, Series Editor, Adamatzky, Andrew, Series Editor, Chen, Guanrong, Series Editor, Abraham, Ajith, Editorial Board Member, Lucia, Ana, Editorial Board Member, Burguillo, Juan C., Editorial Board Member, Čelikovský, Sergej, Editorial Board Member, Chadli, Mohammed, Editorial Board Member, Corchado, Emilio, Editorial Board Member, Davendra, Donald, Editorial Board Member, Ilachinski, Andrew, Editorial Board Member, Lampinen, Jouni, Editorial Board Member, Middendorf, Martin, Editorial Board Member, Ott, Edward, Editorial Board Member, Pan, Linqiang, Editorial Board Member, Păun, Gheorghe, Editorial Board Member, Richter, Hendrik, Editorial Board Member, Rodriguez-Aguilar, Juan A., Editorial Board Member, Rössler, Otto, Editorial Board Member, Snasel, Vaclav, Editorial Board Member, Vondrák, Ivo, Editorial Board Member, Zenil, Hector, Editorial Board Member, and Balaz, Igor, editor

Published
2022
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15. Considering the Evolution of the STEM Mathematical Pathway at the University of Oklahoma Using Organizational Development and Change Theory

Author

Moore-Russo, Deborah, Kornelson, Keri, Savic, Milos, and Andrews, Candace

Abstract

In this case study, we use organizational development and change theory to look at how the University of Oklahoma (OU) has attended to the mathematical pathway leading to STEM fields. Using multiple sources of data, we are able to create an informative narrative that provides the particular context of the situation and in-depth picture of the campus response, including key changes and ongoing challenges that were noted over a five-year period. Through the use of both internal and external funding, OU has been able to improve its teaching and learning in the STEM mathematical pathway. OU has also been able to develop a First-Year Mathematics program based on national recommendations. We report how efforts have directly impacted hiring, placement, pedagogical methods, course coordination, TA training, as well as the collection and use of data in decision making.

Published
2021
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17. Local Intrinsic Dimensionality and Graphs: Towards LID-aware Graph Embedding Algorithms

Author

Savić, Miloš, Kurbalija, Vladimir, Radovanović, Miloš, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Reyes, Nora, editor, Connor, Richard, editor, Kriege, Nils, editor, Kazempour, Daniyal, editor, Bartolini, Ilaria, editor, Schubert, Erich, editor, and Chen, Jian-Jia, editor

Published
2021
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20. Analysis of Ontology Networks

Author

Savić, Miloš, Ivanović, Mirjana, Jain, Lakhmi C., Kacprzyk, Janusz, Series Editor, Jain, Lakhmi C., Series Editor, Savić, Miloš, and Ivanović, Mirjana

Published
2019
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23. Analysis of Software Networks

Author

Savić, Miloš, Ivanović, Mirjana, Jain, Lakhmi C., Kacprzyk, Janusz, Series Editor, Jain, Lakhmi C., Series Editor, Savić, Miloš, and Ivanović, Mirjana

Published
2019
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25. Introduction to Complex Networks

Author

Savić, Miloš, Ivanović, Mirjana, Jain, Lakhmi C., Kacprzyk, Janusz, Series Editor, Jain, Lakhmi C., Series Editor, Savić, Miloš, and Ivanović, Mirjana

Published
2019
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26. A Digital Game for Undergraduate Calculus

Author

Lee, Yu-Hao, primary, Dunbar, Norah E., additional, Kornelson, Keri, additional, Wilson, Scott N., additional, Ralston, Ryan, additional, Savic, Milos, additional, Stewart, Sepideh, additional, Lennox, Emily Ann, additional, Thompson, William, additional, and Elizondo, Javier, additional

Published
2022
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30. I Felt Like a Mathematician: Problems and Assessment to Promote Creative Effort

Author

Omar, Moham, Karakok, Gulden, Savic, Milos, El Turkey, Houssein, and Tang, Gail

Abstract

Challenging mathematics problems were posed as a substantial part of homework in an elective combinatorics course. The intent was to encourage undergraduate students' exploration as well as develop their technical writing skills. The bulk of students' grades on these problems rested on a three-page reflective write-up using a rubric on mathematical creativity, the Creativity-in-Progress Rubric on Proving. Through student reflections, this structure led to a self-reported boost in students' proving confidence and led them to view themselves as practicing mathematicians. Descriptions of the problems, how students used the rubric as their guide, and grading structure are detailed in this article.

Published
2019
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32. The Creativity-in-Progress Rubric on Proving: Two Teaching Implementations and Students' Reported Usage

Author

El Turkey, Houssein, Tang, Gail, Savic, Milos, Karakok, Gulden, Cilli-Turner, Emily, and Plaxco, David

Abstract

A growing body of mathematics education research points to the importance of fostering students' mathematical creativity in undergraduate mathematics courses. However, there are not many research-based instructional practices that aim to accomplish this task. Our research group has been working to address this issue and created a formative assessment tool, the "Creativity-in-Progress Rubric (CPR) on Proving". This tool is developed to help students evaluate their own proving process, as well as provide instructors insight into students' self-evaluation and process. In this paper, we provide a brief description of the CPR on Proving and explain its implementation in two courses at different institutions. Additionally, we share several students' usages of the CPR and provide some practical implementation suggestions.

Published
2018
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35. A Feature Selection Method Based on Feature Correlation Networks

Author

Savić, Miloš, Kurbalija, Vladimir, Ivanović, Mirjana, Bosnić, Zoran, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Ouhammou, Yassine, editor, Ivanovic, Mirjana, editor, Abelló, Alberto, editor, and Bellatreche, Ladjel, editor

Published
2017
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36. Inquiry as an Entry Point to Equity in the Classroom

Author

Tang, Gail, El Turkey, Houssein, Cilli-Turner, Emily, Savic, Milos, Karakok, Gulden, and Plaxco, David

Abstract

Although many policy documents include equity as part of mathematics education standards and principles, researchers continue to explore means by which equity might be supported in classrooms and at the institutional level. Teaching practices that include opportunities for students to engage in active learning have been proposed to address equity. In this paper, through aligning some characteristics of inquiry put forth by Cook, Murphy and Fukawa-Connelly with Gutiérrez's dimensions of equity, we theoretically explore the ways in which active learning teaching practices that focus on inquiry could support equity in the classroom.

Published
2017
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37. Towards Culture-Sensitive Extensions of CRISs: Gender-Based Researcher Evaluation

Author

Savić, Miloš, Ivanović, Mirjana, Radovanović, Miloš, Surla, Bojana Dimić, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Bellatreche, Ladjel, editor, Pastor, Óscar, editor, Almendros Jiménez, Jesús M., editor, and Aït-Ameur, Yamine, editor

Published
2016
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38. A Digital Game for Undergraduate Calculus

Author

Lee, Yu-Hao, primary, Dunbar, Norah E., additional, Kornelson, Keri, additional, Wilson, Scott N., additional, Ralston, Ryan, additional, Savic, Milos, additional, Stewart, Sepideh, additional, Lennox, Emily Ann, additional, Thompson, William, additional, and Elizondo, Javier, additional

Published
2019
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43. Proof and Proving: Logic, Impasses, and the Relationship to Problem Solving

Author

Savic, Milos

Abstract

Becoming a skillful prover is critical for success in advanced undergraduate and graduate mathematics courses. In this dissertation, I report my investigations of proof and the proving process in three separate studies. In the first study, I examined the amount of logic used in student-constructed proofs to help in the design of transition-to-proof courses. The study had four parts: coding 42 student-constructed proofs from a "proofs course," coding 10 student-constructed proofs from a graduate homological algebra course, interviewing three students proving a theorem, and coding the same 42 student-constructed proofs using "proof frameworks." All four parts were intended to discover the logic in proofs and in the proving process so that designers of transition-to-proof courses can take into consideration the frequency of, and the kind of, logic that occurs in constructing proofs. The second study examined how mathematicians and graduate students recover from proving impasses. I defined impasses, which are colloquially referred to as "getting stuck," as a period of time during the proving process when a prover feels or recognizes that his or her argument has not been progressing fruitfully and that he or she has no new ideas. Using the notes from the "proofs course" on semigroups, and a new data collection technique, six of nine mathematician participants and all five graduate student participants had impasses during the proving of theorems in the notes. I discuss the ways participants got "un-stuck," including incubation, a term from psychology colloquially meaning "taking a break.". Finally, researchers have noted that proving and problem solving are related. In fact, one study by Carlson and Bloom (2005) used the data that they had collected on how mathematicians solve problems to create what they called a Multidimensional Problem-Solving Framework. It occurred to me that the data I had collected in the previous study probably could be analyzed using their framework. Upon closer examination, I found that there were commonalities and differences with the phases and attributes of their framework and those of the proving process. Through these three studies, I hope to add to the existing mathematics education research literature on proof and proving. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Published
2012

49. Abstract OT-39-01: Artificial intelligence supporting cancer patients across Europe - the ASCAPE project for breast cancer patients

Author

Valachis, Antonios, primary, Autexier, Serge, additional, Grau, Imma, additional, Itu, Lucian, additional, Jakotevic, Dusan, additional, Kosmidis, Thanos, additional, Muñoz, Montserrat, additional, Perakis, Konstantinos, additional, Rust, Johannes, additional, Savic, Milos, additional, and Kosmidis, Paris, additional

Published
2021
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