| 1. |
- Biurrun, Idoia, et al.
(författare)
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Benchmarking plant diversity of Palaearctic grasslands and other open habitats
- 2021
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Ingår i: Journal of Vegetation Science. - Oxford : John Wiley & Sons. - 1100-9233 .- 1654-1103. ; 32:4
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Tidskriftsartikel (refereegranskat)abstract
- Journal of Vegetation Science published by John Wiley & Sons Ltd on behalf of International Association for Vegetation Science.Aims: Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location: Palaearctic biogeographic realm. Methods: We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m2 and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results: Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions: The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology. © 2021 The Authors.
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| 2. |
- Hedman, Åsa, et al.
(författare)
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IEA EBC Annex83 Positive Energy Districts
- 2021
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Ingår i: Buildings. - : MDPI AG. - 2075-5309. ; 11:3
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Tidskriftsartikel (refereegranskat)abstract
- At a global level, the need for energy efficiency and an increased share of renewable energy sources is evident, as is the crucial role of cities due to the rapid urbanization rate. As a consequence of this, the research work related to Positive Energy Districts (PED) has accelerated in recent years. A common shared definition, as well as technological approaches or methodological issues related to PEDs are still unclear in this development and a global scientific discussion is needed. The International Energy Agency’s Energy in Buildings and Communities Programme (IEA EBC) Annex 83 is the main platform for this international scientific debate and research. This paper describes the challenges of PEDs and the issues that are open for discussions and how the Annex 83 is planned and organized to facilitate this and to actively steer the development of PEDs major leaps forward. The main topics of discussion in the PED context are the role and importance of definitions of PEDs, virtual and geographical boundaries in PEDs, the role of different stakeholders, evaluation approaches, and the learnings of realized PED projects.
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| 3. |
- Faramondi, L., et al.
(författare)
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A Hardware-in-the-Loop Water Distribution Testbed Dataset for Cyber-Physical Security Testing
- 2021
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Ingår i: IEEE Access. - 2169-3536. ; 9, s. 122385-1223896
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a dataset to support researchers in the validation process of solutions such as Intrusion Detection Systems (IDS) based on artificial intelligence and machine learning techniques for the detection and categorization of threats in Cyber Physical Systems (CPS). To this end, data were acquired from a hardware-in-the-loop Water Distribution Testbed (WDT) which emulates water flowing between eight tanks via solenoid-valves, pumps, pressure and flow sensors. The testbed is composed of a real subsystem that is virtually connected to a simulated one. The proposed dataset encompasses both physical and network data in order to highlight the consequences of attacks in the physical process as well as in network traffic behaviour. Simulations data are organized in four different acquisitions for a total duration of 2 hours by considering normal scenario and multiple anomalies due to cyber and physical attacks.
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| 4. |
- Faramondi, Luca, et al.
(författare)
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A hybrid behavior- and Bayesian network-based framework for cyber–physical anomaly detection
- 2023
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Ingår i: Computers & electrical engineering. - 0045-7906 .- 1879-0755. ; 112
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Tidskriftsartikel (refereegranskat)abstract
- In recent years, the increasing Internet connectivity and heterogeneity of industrial protocols have been raising the number and nature of cyber-attacks against Industrial Control Systems (ICS). Such cyber-attacks may lead to cyber anomalies and further to the failure of physical components, thus leading to cyber–physical attacks. In this paper, we present a novel unsupervised cyber–physical anomaly detection framework based on a hybrid “multi-formalism” approach that combines the outcomes of multiple unsupervised behavior-based anomaly detectors through a Bayesian network-based probabilistic modeling of the ICS. More precisely, the framework consists of two behavior-based anomaly detection modules that monitor separately and simultaneously the behavior of cyber and physical data acquired from the ICS. The outputs of such modules are filtered and combined through a Bayesian network-based modeling in order to improve the trustworthiness of the detected anomalies and to provide the detection probability of cyber, physical, and cyber–physical anomalies, taking into account possible cascading effects over the cyber–physical process. The outcomes achieved through the implementation of our framework on the hardware-in-the-loop Water Distribution Testbed (WDT) dataset show very high detection performance with a strong ability to reject false positive events and to isolate and localize the anomalies over the cyber–physical process.
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| 5. |
- Faramondi, L., et al.
(författare)
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Evaluating Machine Learning Approaches for Cyber and Physical Anomalies in SCADA Systems
- 2023
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Ingår i: Proc. IEEE Int. Conf. Cyber Security Resilience, CSR. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350311709 ; , s. 412-417
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Konferensbidrag (refereegranskat)abstract
- In recent years, machine learning (ML) techniques have been widely adopted as anomaly-based Intrusion Detection System in order to evaluate cyber and physical attacks against Industrial Control Systems. Nevertheless, a performance comparison of such techniques applied to multiple Cyber-Physical Systems datasets is still missing. In light of this, we propose a comparative study about the performance of four supervised ML-algorithms, Random Forest, k-nearest-Neighbors, Support-Vector-Machine and Naïve-Bayes, applied to three different publicly available datasets from water testbeds. Specifically, we consider three different scenarios where we evaluate: (1) the ability to detect cyber and physical anomalies with respect to the nominal samples, (2) the ability to detect specific types of cyber and physical attacks and (3) the ability to recognize unforeseen attacks without providing any previous knowledge about them. Results show the effectiveness of the ML-techniques in identifying cyber and physical anomalies under some assumptions about their effects on the process dynamics.
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| 6. |
- Graco-Roza, Caio, et al.
(författare)
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Distance decay 2.0 – A global synthesis of taxonomic and functional turnover in ecological communities
- 2022
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Ingår i: Global Ecology and Biogeography. - : Wiley. - 1466-822X .- 1466-8238. ; 31:7, s. 1399-1421
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Tidskriftsartikel (refereegranskat)abstract
- Aim: Understanding the variation in community composition and species abundances (i.e., beta-diversity) is at the heart of community ecology. A common approach to examine beta-diversity is to evaluate directional variation in community composition by measuring the decay in the similarity among pairs of communities along spatial or environmental distance. We provide the first global synthesis of taxonomic and functional distance decay along spatial and environmental distance by analysing 148 datasets comprising different types of organisms and environments.Location: Global.Time period: 1990 to present.Major taxa studied: From diatoms to mammals.Method: We measured the strength of the decay using ranked Mantel tests (Mantel r) and the rate of distance decay as the slope of an exponential fit using generalized linear models. We used null models to test whether functional similarity decays faster or slower than expected given the taxonomic decay along the spatial and environmental distance. We also unveiled the factors driving the rate of decay across the datasets, including latitude, spatial extent, realm and organismal features.Results: Taxonomic distance decay was stronger than functional distance decay along both spatial and environmental distance. Functional distance decay was random given the taxonomic distance decay. The rate of taxonomic and functional spatial distance decay was fastest in the datasets from mid-latitudes. Overall, datasets covering larger spatial extents showed a lower rate of decay along spatial distance but a higher rate of decay along environmental distance. Marine ecosystems had the slowest rate of decay along environmental distances.Main conclusions: In general, taxonomic distance decay is a useful tool for biogeographical research because it reflects dispersal-related factors in addition to species responses to climatic and environmental variables. Moreover, functional distance decay might be a cost-effective option for investigating community changes in heterogeneous environments.
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