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Na voljo sta dva načina iskanja: enostavno in napredno. Enostavno iskanje lahko zajema niz več besed iz naslova, povzetka, ključnih besed, celotnega besedila in avtorja, zaenkrat pa ne omogoča uporabe operatorjev iskanja. Napredno iskanje omogoča omejevanje števila rezultatov iskanja z vnosom iskalnih pojmov različnih kategorij v iskalna okna in uporabo logičnih operatorjev (IN, ALI ter IN NE). V rezultatih iskanja se izpišejo krajši zapisi podatkov o gradivu, ki vsebujejo različne povezave, ki omogočajo vpogled v podroben opis gradiva (povezava iz naslova) ali sprožijo novo iskanje (po avtorjih ali ključnih besedah).

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1611 - 1620 / 2000
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1611.
Atmosphere - vegetation - soil interactions in a climate change context; impact of changing conditions on engineered transport infrastructure slopes in Europe
Anh Minh Tang, P. N. Hughes, T. A. Dijkstra, Amin Askarinejad, Mihael Brenčič, Yu Jun Cui, J. J. Diez, T. Firgi, Beata Gajewska, F. Gentile, G. Grossi, C. Jommi, F. Kehagia, E. Koda, H. W. ter Maat, Stanislav Lenart, S. Lourenco, M. Oliveira, P. Osinski, Sarah Springman, Ross Stirling, D. G. Toll, Ursula J. Van Beek, 2018, izvirni znanstveni članek

Povzetek: In assessing the impact of climate change on infrastructure, it is essential to consider the interactions between the atmosphere, vegetation and the near-surface soil. This paper presents an overview of these processes, focusing on recent advances from the literature and those made by members of COST Action TU1202 - Impacts of climate change on engineered slopes for infrastructure. Climate- and vegetation-driven processes (suction generation, erosion, desiccation cracking, freeze-thaw effects) are expected to change in incidence and severity, which will affect the stability of new and existing infrastructure slopes. This paper identifies the climate- and vegetation-driven processes that are of greatest concern, the suite of known unknowns that require further research, and lists key aspect that should be considered for the design of engineered transport infrastructure slopes in the context of climate change.
Objavljeno v DiRROS: 12.12.2023; Ogledov: 243; Prenosov: 136
.pdf Celotno besedilo (2,29 MB)
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1612.
Heavy metal signature and environmental assessment of nearshore sediments: Port of Koper (Northern Adriatic Sea)
Nastja Rogan Šmuc, Matej Dolenec, Sabina Dolenec, Ana Mladenovič, 2018, izvirni znanstveni članek

Povzetek: Heavy metal abundance and potential environmental risks are reported for surface sediments (n = 21) from the Port of Koper area, Republic of Slovenia. The enrichment factor (EF) indicates minor enrichment in arsenic (As), cadmium (Cd), copper (Cu), molybdenum (Mo), lead (Pb), antimony (Sb), and zinc (Zn), moderately to severely enriched with nickel (Ni). The trace metal chemistries, in the context of sediment quality guidelines (SQG), imply adverse threshold effect concentrations (TEC) and probable effect concentrations (PEC), for Ni only. Sediment sequential leaching experiments demonstrated that the majority of heavy metals were of natural lithogenic origin and low bioavailability. The heavy metals’ potential for “Risk Assessment Code” values exhibited no or low anthropogenic environmental burden, with the exception of Mo.
Ključne besede: port sediments, heavy metals, chemical speciation, risk assessment, Northem Adriatic Sea
Objavljeno v DiRROS: 12.12.2023; Ogledov: 283; Prenosov: 147
.pdf Celotno besedilo (6,88 MB)
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1613.
Corporate Social Responsibility (CSR) in Green and Digital Transition: Legal and Sustainability Issues : scientific conference
2023, druge monografije in druga zaključena dela

Objavljeno v DiRROS: 11.12.2023; Ogledov: 384; Prenosov: 164
.pdf Celotno besedilo (1,89 MB)
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1614.
Preverjanje verjetnostne napovedi sanitarnega poseka smreke zaradi podlubnikov v Sloveniji v 2023
Nikica Ogris, Maarten De Groot, 2023, drugi znanstveni članki

Povzetek: Preverili smo zanesljivost verjetnostne napovedi sanitarnega poseka smreke zaradi podlubnikov v Sloveniji v 2023. Verjetnostni model za napoved sanitarnega poseka smreke zaradi podlubnikov je potrdil visoko zanesljivost (AUC modela = 0,89, AUC napovedi = 0,84). Ugotovili smo optimalni prag za verjetnost sanitarnega poseka, ki ga bomo lahko uporabili pri naslednjih napovedih za bolj jasno določitev območij, kjer se bodo potencialno pojavila žarišča smrekovih podlubnikov. Napoved za leto 2023 smo naredili s pragom 0,30, ki pa se je izkazal za prenizkega, saj je bila kar tretjina modelskih celic lažno pozitivnih. Optimalen prag za verjetnostni model v letu 2023 je bil 0,40. Povprečen optimalen prag v obdobju 2020–2023 je bil 0,45, ki ga predlagamo za izdelavo verjetnostne napovedi v naslednjem letu.
Ključne besede: gozdovi, varstvo gozdov, navadna smreka, Picea abies, sanitarni posek, napoved, ogroženost, model, validacija, zmogljivost, zanesljivost, točnost, natančnost, AUC, občutljivost, specifičnost
Objavljeno v DiRROS: 11.12.2023; Ogledov: 431; Prenosov: 155
.pdf Celotno besedilo (791,14 KB)
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1615.
Šola raka dojk : [strokovno srečanje]
2023, ni določena

Ključne besede: epidemiologija, presejanje, genetsko svetovanje, rehabilitacija, rekonstrukcija, zborniki
Objavljeno v DiRROS: 11.12.2023; Ogledov: 486; Prenosov: 113
.pdf Celotno besedilo (14,08 MB)

1616.
1617.
Using the IUCN environmental impact classification for alien taxa to inform decision-making
Sabrina Kumschick, Sandro Bertolino, Tim M. Blackburn, Giuseppe Brundu, Katie E. Costello, Maarten De Groot, Thomas Evans, Belinda Gallardo, Piero Genovesi, Tanushri Govender, 2023, izvirni znanstveni članek

Povzetek: The Environmental Impact Classification for Alien Taxa (EICAT) is an important tool for biological invasion policy and management and has been adopted as an International Union for Conservation of Nature (IUCN) standard to measure the severity of environmental impacts caused by organisms living outside their native ranges. EICAT has already been incorporated into some national and local decision-making procedures, making it a particularly relevant resource for addressing the impact of non-native species. Recently, some of the underlying conceptual principles of EICAT, particularly those related to the use of the precautionary approach, have been challenged. Although still relatively new, guidelines for the application and interpretation of EICAT will be periodically revisited by the IUCN community, based on scientific evidence, to improve the process. Some of the criticisms recently raised are based on subjectively selected assumptions that cannot be generalized and may harm global efforts to manage biological invasions. EICAT adopts a precautionary principle by considering a species’ impact history elsewhere because some taxa have traits that can make them inherently more harmful. Furthermore, non-native species are often important drivers of biodiversity loss even in the presence of other pressures. Ignoring the precautionary principle when tackling the impacts of non-native species has led to devastating consequences for human well-being, biodiversity, and ecosystems, as well as poor management outcomes, and thus to significant economic costs. EICAT is a relevant tool because it supports prioritization and management of non-native species and meeting and monitoring progress toward the Kunming–Montreal Global Biodiversity Framework (GBF) Target 6.
Ključne besede: biological invasions, evidence synthesis, impact assessment, managing invasive species, precautionary principle
Objavljeno v DiRROS: 11.12.2023; Ogledov: 457; Prenosov: 272
.pdf Celotno besedilo (537,44 KB)
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1618.
1619.
SONAR, a nursing activity dataset with inertial sensors
Orhan Konak, Lucas Liebe, Kirill Postnov, Franz Sauerwald, Hristijan Gjoreski, Mitja Luštrek, Bert Arnrich, 2023, drugi znanstveni članki

Povzetek: Accurate and comprehensive nursing documentation is essential to ensure quality patient care. To streamline this process, we present SONAR, a publicly available dataset of nursing activities recorded using inertial sensors in a nursing home. The dataset includes 14 sensor streams, such as acceleration and angular velocity, and 23 activities recorded by 14 caregivers using five sensors for 61.7 hours. The caregivers wore the sensors as they performed their daily tasks, allowing for continuous monitoring of their activities. We additionally provide machine learning models that recognize the nursing activities given the sensor data. In particular, we present benchmarks for three deep learning model architectures and evaluate their performance using different metrics and sensor locations. Our dataset, which can be used for research on sensor-based human activity recognition in real-world settings, has the potential to improve nursing care by providing valuable insights that can identify areas for improvement, facilitate accurate documentation, and tailor care to specific patient conditions.
Ključne besede: nursing documentation, nursing activities, SONAR, sensors
Objavljeno v DiRROS: 11.12.2023; Ogledov: 315; Prenosov: 166
.pdf Celotno besedilo (1,62 MB)
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1620.
HARE : unifying the human activity recognition engineering workflow
Orhan Konak, Lucas Liebe, Kirill Postnov, Franz Sauerwald, Hristijan Gjoreski, Mitja Luštrek, Bert Arnrich, 2023, izvirni znanstveni članek

Povzetek: Sensor-based human activity recognition is becoming ever more prevalent. The increasing importance of distinguishing human movements, particularly in healthcare, coincides with the advent of increasingly compact sensors. A complex sequence of individual steps currently characterizes the activity recognition pipeline. It involves separate data collection, preparation, and processing steps, resulting in a heterogeneous and fragmented process. To address these challenges, we present a comprehensive framework, HARE, which seamlessly integrates all necessary steps. HARE offers synchronized data collection and labeling, integrated pose estimation for data anonymization, a multimodal classification approach, and a novel method for determining optimal sensor placement to enhance classification results. Additionally, our framework incorporates real-time activity recognition with on-device model adaptation capabilities. To validate the effectiveness of our framework, we conducted extensive evaluations using diverse datasets, including our own collected dataset focusing on nursing activities. Our results show that HARE’s multimodal and on-device trained model outperforms conventional single-modal and offline variants. Furthermore, our vision-based approach for optimal sensor placement yields comparable results to the trained model. Our work advances the field of sensor-based human activity recognition by introducing a comprehensive framework that streamlines data collection and classification while offering a novel method for determining optimal sensor placement.
Ključne besede: human activity recognition, multimodal classification, privacy preservation, real-time classification, sensor placement
Objavljeno v DiRROS: 11.12.2023; Ogledov: 403; Prenosov: 132
.pdf Celotno besedilo (6,40 MB)
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