A case study from the north-eastern Skagerrak region

textProtection of marine areas is important to tackle global environmental challenges humanity faces and manage human activities in a sustainable way. Due to the lack of ecological boundaries in the seas, cross-border collaboration and coordination is essential. However, cross-border collaboration is often lined with challenges, such as the broad array of countries’ institutional designs. This master thesis aims to explore cross-border collaboration, identify challenges and how the collaboration may be affected by the institutional design of two adjacent Nordic marine national parks, Koster Sea in Sweden, and Outer Hvaler in Norway. The study is explorative and qualitative, comparing and analysing the two cases internally, and their interactions, using documents and interviews. A key focus is the countries’ institutional settings. Thus, the Institutional Analysis and Development framework provides an overarching theoretical structure to understand the role of institutions, complemented by a vertical policy hierarchy to unravel formal rules, and mandates on different institutional levels. Moreover, program logic models display conditions to carry out cross-border activities and how the activities are structured from start to finish. The analysis identifies three key challenges: different level priorities; divergent organisational structure and mandate; and degree of allocated resources and capacity. The identified challenges seem closely connected to the institutional design of each country, where internal structural differences seem to cause imbalances in the cross-border collaboration. Possible solutions include determining what cross-border collaboration mean in the specific context, plan for how to collaborate, formalise informal networks and most importantly, allocate resources for collaboration

Multitaper Estimation of the Coherence Spectrum in low SNR

A pseudo coherence estimate using multitapers is presented. The estimate has better localization for sinusoids and is shown to have lower variance for disturbances compared to the usual coherence estimator. This makes it superior in terms of finding coherent frequencies between two sinusoidal signals; even when observed in low SNR. Different sets of multitapers are investigated and the weights of the final coherence estimate are adjusted for a low-biased estimate of a single sinusoid. The proposed method is more computationally efficient than data dependent methods, and does still give comparable results

BEYOND LIKES AND SHARES: THE PRESENCE, CONTENT, COMMUNICATION, AND COLLECTIVE ACTION FRAME OF FAR-RIGHT GROUPS IN NORWAY ON FACEBOOK IN JANUARY 2016 AND AUGUST 2023

openThe strength of far-right groups on social media platforms in Norway has received a lot of attention from scholars and researchers, however, few systematic studies have been carried out on it. One prominent study was published in 2017 by Haanshuus and Jupskås, which compared data sets from March 2015 and January 2016 aiming to map the strength of the presence of far-right groups on Facebook in Norway. This study will compare my own data collection of the same data set and variables used in 2015/2016 by Haanshuss and Jupskås in order to say something about the presence, content, communication, and collective action frame of prominent far-right groups on Facebook in Norway in August 2023, and compare these findings with the ones from January 2016. By conducting a comparative analysis using the data collected in January 2016 and comparing it with my data collection from August 2023, it is possible to reflect on the evolution and development of the type of activism and the collective action frame after six years. It is also worth mentioning that events and circumstances in the span of these six years make for an interesting context to the results. During the data collection done by Haanshuus and Jupskås (2017), the European continent was facing the so-called “refugee crisis”, which made for an interesting context. Since January 2016, Norway has been through a pandemic in Covid-19 which featured protectionist policies and closed borders, a war on the European continent in Russia’s war of aggression against Ukraine, a subsequent energy crisis, and another lethal terrorist attack carried out by a man of mixed ethnicities belonging to the far-right. It is also worth mentioning that regional and communal elections were held in Norway on 11th of September 2023, possibly also impacting the content published by the far-right groups during the month of August. These were also interesting events when analyzing the narratives and main content of far-right groups on Facebook in August 2023. Haanshuus and Jupskås (2017) study concluded that the levels of activity increased, and that the collective action frame was incomplete. However, they pointed out that the narrative of far-right groups on Facebook had changed from Islamophobic to ultra-nationalist when it came to the interpretation of “the problem” (Haanshuus & Jupskås 2017.) The quantitative data that was collected from August 2023 revealed scattered results across the five far-right groups included in this study. Two of the groups, SIAN and Norgesdemokratene, gained less likes per post in August 2023 compared to January 2016, however, the posts in return got more comments and shares, indicating that the audience and followers were more nuanced and engaged in their communication as composing a comment or sharing a post requires more effort than simply pressing like. This also indicates that, in the case of Norgesdemokratene and SIAN, the Facebook-pages were channels for communication rather than simply informational. The Facebook-pages of Pegida and Norsk Folkeparti had an insignificant amount of likes, shares, and comments, however, they were still present in August 2023, albeit with very low levels of activity, and close to zero engagement and communication. The data collected from FMI revealed that, in contrast to January 2016, the Facebook-page of the group seemed to be mostly informational in August 2023, with the highest number of likes, and a drastic decrease of communicative responses from the audience. However, the group was very much still active and present on Facebook. The qualitative analysis, which relied on a content analysis of all the posts published, revealed, similar to January 2016, an incomplete collective action frame, and a scattered interpretation of the biggest “problem” with the society, with some groups leaning towards ultra-nationalist sentiments more than Islamophobia, and vice versa with others

Robust feature representation for classification of bird song syllables

A novel feature set for low-dimensional signal representation, designed for classification or clustering of non-stationary signals with complex variation in time and frequency, is presented. The feature representation of a signal is given by the first left and right singular vectors of its ambiguity spectrum matrix. If the ambiguity matrix is of low rank, most signal information in time direction is captured by the first right singular vector while the signal’s key frequency information is encoded by the first left singular vector. The resemblance of two signals is investigated by means of a suitable similarity assessment of the signals’ respective singular vector pair. Application of multitapers for the calculation of the ambiguity spectrum gives an increased robustness to jitter and background noise and a consequent improvement in performance, as compared to estimation based on the ordinary single Hanning window spectrogram. The suggested feature-based signal compression is applied to a syllable-based analysis of a song from the bird species Great Reed Warbler and evaluated by comparison to manual auditive and/or visual signal classification. The results show that the proposed approach outperforms well-known approaches based on mel-frequency cepstral coefficients and spectrogram cross-correlation

Äldre hemvårdsklienters alkoholbruk : Hemvårdspersonalens syn på äldre och alkohol

I den här studien har jag undersökt hemvårdspersonalens förhållningssätt gentemot äldre och alkohol, hur de uppfattar sin kunskap och roll när det kommer till äldre och alkohol, samt hur de ser på vården av äldre med alkoholproblem i framtiden. Syftet med studien är att skapa kunskap som kan vara till stöd för kommunerna att ge god och jämlik vård inom hemservicen, oberoende om klienterna har alkoholproblem eller inte. Fenomenografi utgör både forskningsansats och analysmetod eftersom det centrala i undersökningen är att studera uppfattningar, eller förhållningssätt som jag använder mig av i denna avhandling. Materialet till undersökningen består av tio (10) halvstrukturerade samtalsintervjuer med hemvårdspersonal från fyra olika kommuner i svenska Kust-Österbotten. Analysen gjordes som en materialbaserad fenomenografisk analys och jag fann sammanlagt sex övergripande beskrivningskategorier av hemvårdspersonalens syn på äldre och alkohol. Gällande personalens förhållningsätt gentemot äldre och alkohol fann jag två huvudkategorier och tretton underkategorier, som ger en mer ingående beskrivning av förhållningssätten, t.ex. att äldre får dricka alkohol så länge det är kontrollerade mängder. Gällande personalens förhållningssätt gentemot kunskap och deras roll när det kommer till äldre och alkohol kunde jag också identifiera två huvudkategorier, men i detta fall tio underkategorier, t.ex. att hemvårdspersonalen anser att de har tillräckligt med kunskap och redskap att ta hand om äldre med alkoholproblem så som det är idag. När det kom till hurudan syn hemvårdspersonalen har på vården av äldre med alkoholproblem i framtiden, fann jag en huvudkategori och fyra underkategorier, t.ex. så tror personalen att antalet äldre med alkoholproblem inom hemservicen bara kommer att öka

Automatic acoustic detection of birds through deep learning : the first bird audio detection challenge

Assessing the presence and abundance of birds is important for monitoring specific species as well as overall ecosystem health. Many birds are most readily detected by their sounds, and thus passive acoustic monitoring is highly appropriate. Yet acoustic monitoring is often held back by practical limitations such as the need for manual configuration, reliance on example sound libraries, low accuracy, low robustness, and limited ability to generalise to novel acoustic conditions. Here we report outcomes from a collaborative data challenge. We present new acoustic monitoring datasets, summarise the machine learning techniques proposed by challenge teams, conduct detailed performance evaluation, and discuss how such approaches to detection can be integrated into remote monitoring projects. Multiple methods were able to attain performance of around 88% AUC (area under the ROC curve), much higher performance than previous general‐purpose methods. With modern machine learning including deep learning, general‐purpose acoustic bird detection can achieve very high retrieval rates in remote monitoring data ̶ with no manual recalibration, and no pre‐training of the detector for the target species or the acoustic conditions in the target environment.</ol

Scaled reassigned spectrograms applied to linear transducer signals

This study evaluates the applicability of scaled reassigned spectrograms (ReSTS) on ultrasound radio frequency data obtained with a clinical linear array ultrasound transducer. The ReSTS's ability to resolve axially closely spaced objects in a phantom is compared to the classical cross-correlation method with respect to the ability to resolve closely spaced objects as individual reflectors using ultrasound pulses with different lengths. The results show that the axial resolution achieved with the ReSTS was superior to the cross-correlation method when the reflected pulses from two objects overlap. A novel B-mode imaging method, facilitating higher image resolution for distinct reflectors, is proposed

Sparse Semi-Parametric Estimation of Harmonic Chirp Signals

In this work, we present a method for estimating the parameters detailing an unknown number of linear, possibly harmonically related, chirp signals, using an iterative sparse reconstruction framework. The proposed method is initiated by a re-weighted group-sparsity approach, followed by an iterative relaxation-based refining step, to allow for high resolution estimates. Numerical simulations illustrate the achievable performance, offering a notable improvement as compared to other recent approaches. The resulting estimates are found to be statistically efficient, achieving the corresponding Cram´er-Rao lower bound

Real-time gas-correlation imaging employing thermal background radiation

Real-time imaging of gas leaks was demonstrated using an IR camera employing outdoor thermal background radiation. Ammonia, ethylene and methane detection was demonstrated in the spectral region 7-13 mu m. Imaging was accomplished using an optical filter and a gas-correlation cell matching the absorption band of the gas. When two gases, such as ammonia and ethylene, are absorbing in the same wavelength region it is possible to isolate one for display by using gas-correlation multispectral imaging. Results from a field test on a leaking gas tanker are presented as QuickTime movies. A detection limit of 200 ppm x meter for ammonia was accomplished in this setup when the temperature difference between the background and the gas was 18 K and the frame rate was 15 Hz. (C) 2000 Optical Society of America

Sparse Semi-Parametric Chirp Estimator

In this work, we present a method for estimating the parameters detailing an unknown number of linear chirp signals, using an iterative sparse reconstruction framework. The proposed method is initiated by a re-weighted Lasso approach, and then use an iterative relaxation-based refining step to allow for high resolution estimates. The resulting estimates are found to be statistically efficient, achieving the Cramér-Rao lower bound. Numerical simulations illustrate the achievable performance, offering a notable improvement as compared to other recent approaches