1. Lowland forest fragment characteristics and anthropogenic disturbances determine alien plant species richness and compositionMirjana Šipek, Nina Šajna, 2024, original scientific article Abstract: Loss of habitat and biological invasion are the main threats to biodiversity. In intensive agricultural or urban landscapes, forest fragments, even if they are small and isolated represent biodiversity refugia. Environmental variables such as landscape structure, abiotic conditions and anthropogenic disturbance affect the biodiversity of the fragments. In this study, we explored plant species richness in 48 forest fragments embedded in predominantly agricultural landscapes on the alluvial plains of the Mura and Drava rivers in NE Slovenia. We determined several forest fragment characteristics such as perimeter, area, shape complexity, length and proportion of edge shared with adjacent land-cover types and anthropogenic disturbance indicated by the presence of footpaths and waste disposed in fragments. The abiotic condition of these fragments was assessed by Ellenberg indicator values. We built generalized linear models and ordination analyses to assess the importance of environmental variables for the richness and composition of alien plant species and other ecologically meaningful plant groups. Shape complexity had a consistent positive effect on the richness of native and alien plants species. Major drivers of alien plant composition in forest fragments included adjacent land-cover and urbanization level. An increasing proportion of arable land along the forest fragment perimeter negatively affected the richness of alien plants, while the effect of urban areas was positive. Our results confirmed that forest fragments in the rural-urban matrix represent biodiversity refugia and support native plant species; however, they are not resistant to invasions; instead invasion depends on the land-cover type in the surroundings of a given forest fragment.
Keywords: agricultural land, urban area, settlements, fragment size, fragment shape complexity, ornamental plants
Published in DKUM: 29.11.2024; Views: 0; Downloads: 1
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3. Kolmogorov compression complexity may differentiate different schools of Orthodox iconographyDaniel Peptenatu, Ion Andronache, Helmut Ahammer, Richard Taylor, Ioannis Liritzis, Marko Radulovic, Bogdan Ciobanu, Marin Burcea, Matjaž Perc, Tuan D. Pham, 2022, original scientific article Abstract: The complexity in the styles of 1200 Byzantine icons painted between 13th and 16th from Greece, Russia and Romania was investigated through the Kolmogorov algorithmic information theory. The aim was to identify specific quantitative patterns which define the key characteristics of the three different painting schools. Our novel approach using the artificial surface images generated with Inverse FFT and the Midpoint Displacement (MD) algorithms, was validated by comparison of results with eight fractal and non-fractal indices. From the analyzes performed, normalized Kolmogorov compression complexity (KC) proved to be the best solution because it had the best complexity pattern differentiations, is not sensitive to the image size and the least affected by noise. We conclude that normalized KC methodology does offer capability to differentiate the icons within a School and amongst the three Schools.
Keywords: iconography, complexity, Kolmogorov compression, art, physics
Published in DKUM: 15.07.2024; Views: 117; Downloads: 9
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4. Deep learning criminal networksHaroldo V. Ribeiro, Diego D. Lopes, Arthur A. B. Pessa, Alvaro F. Martins, Bruno R. da Cunha, Sebastián Gonçalves, Ervin K. Lenzi, Quentin S. Hanley, Matjaž Perc, 2023, original scientific article Abstract: Recent advances in deep learning methods have enabled researchers to develop and apply algorithms for the analysis and modeling of complex networks. These advances have sparked a surge of interest at the interface between network science and machine learning. Despite this, the use of machine learning methods to investigate criminal networks remains surprisingly scarce. Here, we explore the potential of graph convolutional networks to learn patterns among networked criminals and to predict various properties of criminal networks. Using empirical data from political corruption, criminal police intelligence, and criminal financial networks, we develop a series of deep learning models based on the GraphSAGE framework that are able to recover missing criminal partnerships, distinguish among types of associations, predict the amount of money exchanged among criminal agents, and even anticipate partnerships and recidivism of criminals during the growth dynamics of corruption networks, all with impressive accuracy. Our deep learning models significantly outperform previous shallow learning approaches and produce high-quality embeddings for node and edge properties. Moreover, these models inherit all the advantages of the GraphSAGE framework, including the generalization to unseen nodes and scaling up to large graph structures.
Keywords: organized crime, complexity, crime prediction, GraphSAGE
Published in DKUM: 20.06.2024; Views: 236; Downloads: 9
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6. Systems approach to tourism : a methodology for defining complex tourism systemTadeja Jere Lazanski, 2017, original scientific article Abstract: Background and Purpose: The complexity of the tourism system, as well as modelling in a frame of system dynamics, will be discussed in this paper. The phaenomenon of tourism, which possesses the typical properties of global and local organisations, will be presented as an open complex system with all its elements, and an optimal methodology to explain the relations among them. The approach we want to present is due to its transparency an excellent tool for searching systems solutions and serves also as a strategic decision-making assessment. We will present systems complexity and develop three models of a complex tourism system: the first one will present tourism as an open complex system with its elements, which operate inside of a tourism market area. The elements of this system present subsystems, which relations and interdependencies will be explained with two models: causal-loop diagram and a simulation model in frame of systems dynamics.
Design/methodology/approach: Systems methodology will be shown as the appropriate one, when we discuss complex systems challenges. For illustration, systems approach and systems methodology will be applied to tourism models. With building a qualitative causal-loop diagram we will describe the tourism system complexity in forms of system%s elements relations. Mutual influences among the elements will be presented with positive and negative loops, which forms circles of reinforcement and balance. This will help us to discuss the problem categorically. The final model will follow the causal-loop diagram. This will be a simulation model in a frame of system dynamics as an illustration of the discussed methodology.
Results: The methodology offers the solution of effective and holistic promotion of complex tourism system transformation, which has the potential to go beyond the myth of sustainable tourism and create significant shifts in the approach and acting of the participants (elements of the system) involved. Systems approach brings to tourism and the society, in general, broader dimensions of thinking, the awareness interdependency, interconnectivity, and responsibility for the behaviour of a system, which can be observed by feedback loops.
Conclusions: Findings about meaningfulness of systems thinking presented in the paper, are rarely presented to tourism society systemically and with the aim of designing sustainable complex tourism system. They show new approach, systems awareness and teaches thinking %out of the box%. Consequently, the sustainable behaviour is achieved: tourism supply and demand meet on responsible base and they connect to responsible stakeholders.
Keywords: systems approach, complexity, tourism system, modelling, system dynamics
Published in DKUM: 22.01.2018; Views: 1144; Downloads: 209
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7. Organisational effectiveness and customer satisfactionMilan Ambrož, Martina Praprotnik, 2008, original scientific article Abstract: This paper presents a test of the relationship between organizational culture as a crucial indicator of organizational effectiveness and customer satisfaction using service-unit data from two health resorts. Ensuring survival of the service organisation in the long run requires adaptations which are oriented towards achieving maximum customer satisfaction. This study intended to unveil the effect organisational factors have on customer service orientation from the customer and employee point of view within a two health resort service setting. The finding suggests that when trying to predict the comparative degree which organisational effectiveness factors have in satisfying customers' needs, performance, adaptability and mission can be of the highest importance. Some effects like performance were uniform for employees and customers, while others varied depending on the organisation and the customer or employee group. Furthermore, findings suggest that service performance and organisation mission of the service organisation predict customer satisfaction based on established and proven health services. In this context there is no room for innovation, despite the fact that employees and customers do not share similar views about the impact of organisational effectiveness. Developing an effective service organisation can provide a competitive advantage to the organisation. Critical for the success of the service organisation is that organisational agents have a clear view of the existing organisation effectiveness and a clear view of the customer expectations in this area.
Keywords: organisational effectiveness, customer satisfaction, customer complexity, service orientation, survival, adaptability
Published in DKUM: 04.12.2017; Views: 1638; Downloads: 434
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8. Multiple paradigm research on organisational culture : an introduction of complexity paradigmDan Podjed, 2011, original scientific article Abstract: The author presents multiple paradigm research into the organisational culture of a birdwatching association, where he conducted his ethnographic research. On top of the functionalist, interpretive, radical structuralist and radical humanist paradigms as presented by Gibson Burrell and Gareth Morgan, he applies the fifth paradigm into the analysis of the organisation. The so-called complexity paradigm, which was formed in 1980's based on findings about complex systems and networks that emerged in natural and social sciences, summarizes all other paradigms, integrating them into a coherent unit. According to the author, the approach that exploits the benefits of each previously known paradigm illustrates comprehensively the complexity of organisational cultures, whereas the new paradigm upgrades our previous knowledge on organisations.
Keywords: anthropology, organisational culture, multiple paradigm research, complexity paradigm, ornithological association
Published in DKUM: 04.12.2017; Views: 1081; Downloads: 171
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9. Strong edge geodetic problem in networksPaul Manuel, Sandi Klavžar, Antony Xavier, Andrew Arokiaraj, Elizabeth Thomas, 2017, original scientific article Abstract: Geodesic covering problems form a widely researched topic in graph theory. One such problem is geodetic problem introduced by Harary et al. Here we introduce a variation of the geodetic problem and call it strong edge geodetic problem. We illustrate how this problem is evolved from social transport networks. It is shown that the strong edge geodetic problem is NP-complete. We derive lower and upper bounds for the strong edge geodetic number and demonstrate that these bounds are sharp. We produce exact solutions for trees, block graphs, silicate networks and glued binary trees without randomization.
Keywords: geodetic problem, strong edge geodetic problem, computational complexity, transport networks
Published in DKUM: 03.11.2017; Views: 1194; Downloads: 442
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10. Quantifying soil complexity using network models of soil porous structureMarko Samec, A. Santiago, J. P. Cardenas, R. M. Benito, A. M. Tarquis, Sacha Jon Mooney, Dean Korošak, 2013, original scientific article Abstract: This paper describes an investigation into the properties of spatially embedded complex networks representing the porous architecture of soil systems. We suggest an approach to quantify the complexity of soil pore structure based on the node-node link correlation properties of the networks. We show that the complexity depends on the strength of spatial embedding of the network and that this is related to the transition from a non-compact to compact phase of the network.
Keywords: soil complexity, soil pore networks, complex systems
Published in DKUM: 21.07.2017; Views: 1476; Downloads: 332
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