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The complexity of porous structure of building materials
Marko Samec, 2011, doktorska disertacija

Opis: This thesis seeks to establish the link between the structure (in a topological sense) of porous space and charged particle dynamics in porous matter, specifically in constituent elements of sustainable building materials such as clay, cement and soil. The work done is a combination of experimental research and modelling of analysed data using advanced and expanded network models to model pore structure and generalized conductivity model. The main outcome of this doctoral thesis is the demonstration that there is a correlation between the large scale structure of the pore space and the properties of the motion of charged particles through the pore space. This was achieved by conducting two experiments: the structure of pore space of selected porous materials (soil samples, clays, cements, clay-cement mixtures) was investigated using state-of-the-art X-ray computed microtomography, while the dynamics of charged particles in the samples was probed using low-frequency dielectric spectroscopy. The research done and described in the thesis is directed towards the advancement of understanding the transport phenomena and the structure of porous media which is of paramount importance for solving problems in building physics dealing with moist transport in building's envelope, the building-ground interaction, and in transport of contaminants in the vicinity of the repositories where the transfer of moist through soil can be the source of contamination.
Ključne besede: porous matter, clay-water system, hydrating cement, fractional dynamics, dielectric response, X-ray computed tomography, image analysis, complex network
Objavljeno: 11.05.2011; Ogledov: 3071; Prenosov: 111
.pdf Polno besedilo (34,69 MB)

Direct enthalpy exchange between process utilities
Zorka Novak-Pintarič, Peter Glavič, 2002, strokovni članek

Opis: This paper presents an application of the improved pinch methodology by performing a simplified exergy analysis in a real-size ammonia plant. Besides the well known pinch technics like composite curves and grand composite curve, the improved approach with the extended grand composite curve was implemented. The latter presents the most energy intensive units in the process separated from the process background as well as the direct transfer of enthalpy from hot utilities to cold utilities. Based on this presentation the synthesis of modified heat exchanger network was performed which results in considerable decrease of utilities demand.
Ključne besede: chemical engineering, process design, exergy analysis, ammonia plant, pinch methodology, extended hrand composite curve method, enthalpy exchange, distillation column, heat exchanger network
Objavljeno: 10.07.2015; Ogledov: 348; Prenosov: 5
.pdf Polno besedilo (182,17 KB)

Insights into population health management through disease diagnoses networks
Keith Feldman, Gregor Štiglic, Dipanwita Dasgupta, Mark Kricheff, Zoran Obradović, Nitesh Chawla, 2016, izvirni znanstveni članek

Opis: The increasing availability of electronic health care records has provided remarkable progress in the field of population health. In particular the identification of disease risk factors has flourished under the surge of available data. Researchers can now access patient data across a broad range of demographics and geographic locations. Utilizing this Big healthcare data researchers have been able to empirically identify specific high-risk conditions found within differing populations. However to date the majority of studies approached the issue from the top down, focusing on the prevalence of specific diseases within a population. Through our work we demonstrate the power of addressing this issue bottom-up by identifying specifically which diseases are higher-risk for a specific population. In this work we demonstrate that network-based analysis can present a foundation to identify pairs of diagnoses that differentiate across population segments. We provide a case study highlighting differences between high and low income individuals in the United States. This work is particularly valuable when addressing population health management within resource-constrained environments such as community health programs where it can be used to provide insight and resource planning into targeted care for the population served.
Ključne besede: population screening, risk factors, network analysis
Objavljeno: 23.06.2017; Ogledov: 47; Prenosov: 0
.pdf Polno besedilo (743,53 KB)

Link prediction on Twitter
Sanda Martinčić-Ipšić, Edvin Močibob, Matjaž Perc, 2017, izvirni znanstveni članek

Opis: With over 300 million active users, Twitter is among the largest online news and social networking services in existence today. Open access to information on Twitter makes it a valuable source of data for research on social interactions, sentiment analysis, content diffusion, link prediction, and the dynamics behind human collective behaviour in general. Here we use Twitter data to construct co-occurrence language networks based on hashtags and based on all the words in tweets, and we use these networks to study link prediction by means of different methods and evaluation metrics. In addition to using five known methods, we propose two effective weighted similarity measures, and we compare the obtained outcomes in dependence on the selected semantic context of topics on Twitter. We find that hashtag networks yield to a large degree equal results as all-word networks, thus supporting the claim that hashtags alone robustly capture the semantic context of tweets, and as such are useful and suitable for studying the content and categorization. We also introduce ranking diagrams as an efficient tool for the comparison of the performance of different link prediction algorithms across multiple datasets. Our research indicates that successful link prediction algorithms work well in correctly foretelling highly probable links even if the information about a network structure is incomplete, and they do so even if the semantic context is rationalized to hashtags.
Ključne besede: link prediction, data mining, Twitter, network analysis
Objavljeno: 15.09.2017; Ogledov: 60; Prenosov: 0
.pdf Polno besedilo (6,98 MB)

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