228 research outputs found
Idrottande elevers dubbla karriärval
No full textInför gymnasiet kan idrottande elever välja att inkorporera sin idrottssatsning i sina kommande gymnasiestudier genom att söka sig till ett Riksidrottsgymnasium (RIG) eller en nationellt godkänd idrottsutbildning (NIU). Dessa idrottsprogram går ut på att maximera möjligheterna till framgångsrika karriärer genom både skolan och idrotten och är en del av Riksidrottsförbundets system för dubbla karriärer. Gymnasievalet för idrottande elever kan därmed betraktas som ett dubbelt karriärval, där eleverna behöver ta ställning till om de vill hantera dubbla karriärer under gymnasietiden.
Syftet med studien var att utveckla en förståelse för idrottande elevers dubbla karriärval utifrån begreppen identitet, upplevd självförmåga och förväntat utfall inom de båda karriärerna. För varje begrepp definierades således en idrottslig dimension och en skolrelaterad dimension. Social Cognitive Career Theory användes som teoretiskt ramverk för karriärbeslut och kombinerades med aktuell forskning på området för att konstruera en relevant forskningsansats. I populationen ingick samtliga niondeklassare på en idrottsgrundskola i Malmö, varav totalt 78 idrottande elever besvarade den digitala enkät som var studiens instrument för datainsamling.
Resultatet visade att den idrottsliga dimensionen av samtliga begrepp varierade i betydande utsträckning med respondenternas beslut att söka idrottsprogram. Regressionsanalys demonstrerade att graden av identifiering med idrottarrollen kunde förutse 92 procent av respondenternas beslut och därmed var den i särklass starkaste prediktorn för beslutet att söka idrottsprogram. Den skolrelaterade dimensionen av begreppen hade inget signifikant samband med beslutet, vilket talade för att det dubbla karriärvalet gjordes oberoende av elevernas relation till skola och studier
Correction: A patient-derived xenograft pre-clinical trial reveals treatment responses and a resistance mechanism to karonudib in metastatic melanoma
No full textOn Pubmed, the name of co-author Roger Olofsson Bagge appeared incorrectly as "Bagge RO" instead of "Olofsson Bagge, Roger". This has been corrected in the PDF and HTML versions
Hyponatremi : ett utforskande i salt
No full textI en tid där begreppet hållbarhet är prioritet i flera frågor får det en att fundera på vad hållbarhet är och betyder. Vi människor kommer antagligen alltid kämpa med frågor om miljö, konsumtion och hållbarhet, i en ständig kamp för balans. Vi omger oss av mer hushållsartiklar än tidigare och har börjat ifrågasätta hur tillverkningsprocessen ser ut av dessa (Roos. 2020). Vi ställer även krav på försäljare och förväntar oss miljömärkta produkter och garantier och pratar oroligt om hållbarhet. I det här projektet vill jag försöka närma mig saltsten som ett alternativt material. Genom praktiska metoder och experiment vill jag belysa fördelar med ett biobaserat material i produktionen av vardagsföremål. Förhoppningsvis kan ett emotionellt värde väckas i mitt experimenterande med saltsten där materialet är med i utvecklingen som en aktiv deltagare. Jag har valt att utforska ett biomaterial och på vad dess hållbarhet kan vara och inte vara. Ett utforskande med saltsten kan hjälpa till att sänka visuella förväntningar men också ge en förståelse till materialet på ett djupare och mer unikt sätt. Jag har valt att arbeta med saltsten eftersom salt förekommer rikligt i naturen och jag vill utforska dess styrkor och svagheter som biomaterial. I mitt sökande följer jag funktionen före formen där formen blir mindre viktig och på så sätt hittar jag nya områden för användandet. I vårt konsumtionssamhälle är ordet hållbarhet på tapeten ofta och en undrar huruvida det på riktigt berör oss. Nya material tillåter oss att handla som aldrig förr med gott samvete men är det hållbart för vår natur? Genom produkter av tillfälliga material kan kanske en balans uppnås där en lika lätt kan bli av med en produkt som att kasta en sten i havet.
Machine Learning for Appearance Grading of Sawn Timber using Cameras and X-ray Computed Tomography
No full textThis doctoral thesis deals with a new approach for the appearance grading of sawn timber adapted to the requirements of modern sawmilling industries and timber market situations. Appearance grading of sawn timber allows wood products to be made with a specific visual style due to wood features such as knots. Identifying and grading sawn timber by its visual style is a holistic-subjective task that is inherently suitable for humans. However, with the ever-increasing demand for a faster and more consistent grading operation, humans have been replaced by automatic systems during the past few decades. However, the human perception of the appearance of sawn timber is not something easily defined coherently and concisely for use in automatic systems, resulting in automatic systems struggling to perform appearance grading using conventional rule-based grading. As shown in this thesis, machine-learning methods can be used to teach an automatic system to perform holistic-subjective grading in a way that emulates manual grading while still performing the fast and consistent grading associated with automatic systems. This thesis introduced machine learning for product-adapted appearance grading of sawn timber and studied the use of machine learning to appearance grade sawn timber according to standardised quality grades, using an X-ray computed tomography (CT) scanner and a camera-based board scanner. In the studies presented in this thesis, measurement data from the CT scan-ner and the board scanner was used to create a set of variables only regarding knots. The variable sets and the grades of the sawn timber were modelled by projection to latent structures (PLS) models. The grade of the sawn timber was determined in three ways; firstly, manual grading according to standard-ised quality grades; secondly, called the product grade, the sawn timber was delivered to a wall-panelling customer, and the grade of the sawn timber was determined by the quality yield at the customer; and thirdly, called the image grade, images were extracted from the board scanner and used to estimate the quality yield of the wall-panelling customer manually. The grading in each scanning system was performed using a machine-learning method and a conventional rule-based approach, and their performances were compared. Seven data sets were collected in the studies presented in this thesis, each with a combination of variable sets from the scanners and quality grades as described above. In each study, one or more PLS models were trained to model the relationship between a variable set and a quality grade and used to predict the quality of the sawn timber. A PLS model predicts a score for each piece of sawn timber, and if that score passes a classification threshold, the model assigns a quality grade. This classification threshold could be tuned manually to introduce a bias in the model and thereby change the sorting outcome. When performing standardised appearance grading of dried sawn timber, both a PLS model and rule-based grading achieved about 80% grading accuracy, while a manual grader agreed to 95% with the PLS model and to 81% with the rule-based grading in a verification test. Furthermore, when performing customer-adapted grading of the standardised grades, a PLS model managed an 84% grading accuracy compared to 64% of the rule-based approach. These results show how a conventional rule-based ap-proach struggled with performing customer-adapted grading compared to a PLS model. When performing standardised grading, however, both meth-ods achieved similar grading accuracy, but only the grading performed by the PLS model could not be significantly distinguished from the targeted standardised grades. Using a PLS model to perform product-adapted grading of dried sawn tim-ber resulted in a grading accuracy of about 70%–80% for di˙erent scenarios. These gradings resulted in a quality yield, pass or fail, of about 80% for the wall-panelling customer. According to the customer, rule-based grad-ing did not yield impressive product-adapted results, and no metric was given. Furthermore, this thesis showed that the image grade was as useful as the product grade for training the PLS models, which greatly simplifies the logistical process of creating a data set for training a product-adapted machine-learning model. Had a traceability method been used to collect the data from the scanners automatically, the image grade would allow for completely software-based data collection, which is very much in line with the industry 4.0 concept. A CT scanner enables the appearance grading of virtual sawn timber in the 3D images of the scanned logs, which allows the logs to be sawn for maxi-mum value or quality yield. The CT scanner was made to perform a primary product-adapted grading using either a PLS model or a rule-based approach. In addition to this primary grading, the CT scanner and board scanner were programmed to perform a small secondary grading by limiting a small set of measurements that the CT scanner could not suÿciently account for. For example, large pith deviations were limited in the CT scanner, and rotten knots were forbidden by the board scanner, as these measurements were associated with a high risk of resulting in poor quality wall panels for the customer. With this setup, a dataset of 300 pieces of virtual sawn timber was studied. Using rule-based primary grading, the sawmill delivered about 200 pieces of sawn timber with a product yield of 77% for the customer, after the board scanner rejected 28 pieces (12%). Then, by controlling the classification threshold of a PLS model to make the primary grading very strict, meaning that the log was sawn to only yield very likely high-quality pieces of sawn timber, the sawmill could deliver 114 pieces of sawn timber with a product yield of 90%, after the board scanner rejected 9 pieces (7%). These results show that a PLS model achieved higher grading accuracy and higher quality yield than a rule-based approach. Furthermore, the classifica-tion threshold of the PLS model allows for easy and intuitive control over the sorting outcome, something that the rule-based approach does not support. This thesis showed that a PLS-based machine-learning model could be used to perform holistic-subjective appearance grading by both a CT scanner and a board scanner, where a rule-based approach struggled in all but the most familiar case of standardised grading. Once a framework for a machine-learning method such as PLS has been implemented, this thesis showed the ease of customising and fine-tuning the grading performance to be in line with customers needs. A customer or product adaptation could conceivably be initiated and finalised completely in software by automatically collecting the data using a traceability method, collecting the reference grades needed for training by grading images of sawn timber, and using the intuitive clas-sification threshold to fine-tune the sorting outcome
Coercive measures and criminality on darknet - An analysis of search warrant and mail delivery control within Swedish law.
No full textProtocol State Fuzzing of EDHOC Implementations Using Register Automata Learning
No full textThis thesis aims to enhance protocol state fuzzing by integrating richer learned models, specifically capturing data flow within security protocols. The goal is to evaluate whether these enhancements lead to more comprehensive models. The key steps include updating the ProtocolState-Fuzzer (PSF) tool to support register automata learning via the RALib API, creating a protocol-specific adaptation for the Ephemeral Diffie-Hellman Over COSE (EDHOC) protocol, and using the adapted tool to learn and analyse models of protocol implementations. Experimental evaluation of four EDHOC protocol implementations demonstrated that while RALib algorithms required significantly longer learning times compared to Mealy machine algorithms, they do indeed produce larger and more comprehensive models. This trade-off between learning time and model complexity revealed that RALib-based models offered more detailed representations, crucial for thorough analysis. The findings underscore the importance of choosing suitable learning algorithms based on the required level of detail. Consequently, this work advances protocol state fuzzing methodologies, enabling the creation and analysis of more intricate state machines, thereby enhancing the testing and analysis of security protocols like EDHOC.Detta projekt syftar till att förbättra protocol state fuzzing genom att integrera rikare inlärda modeller, med fokus på att fånga dataflödet inom säkerhetsprotokoll. Målet är att utvärdera om dessa förbättringar leder till mer omfattande modeller. De viktigaste stegen inkluderar att uppdatera verktyget ProtocolState-Fuzzer (PSF) för att stödja registerautomatinlärning via RALibs API, skapa en protokollspecifik anpassning för Ephemeral Diffie-Hellman Over COSE (EDHOC) protokollet och använda det anpassade verktyget för att analysera modeller av protokollimplementationer. Den experimentella utvärderingen av fyra EDHOC implementationer visade att medan RALib-algoritmer krävde avsevärt längre inlärningstider jämfört med Mealy-maskinalgoritmer, producerade de faktiskt större och mer omfattande modeller. Denna kompromiss mellan inlärningstid och modellkomplexitet visade att RALib-baserade modeller erbjöd mer detaljerade representationer, vilket är avgörande för analys. Resultaten betonar vikten av att välja lämpliga inlärningsalgoritmer baserat på den nödvändiga detaljnivån. Därmed främjar detta arbete metodologier för protocol state fuzzing, möjliggör skapandet och analysen av mer intrikata tillståndsmaskiner, vilket i sin tur förbättrar testningen och analysen av säkerhetsprotokoll som EDHOC
Mass conservative network model for convective net flow in a complex urban geometry
No full textWhen simulating air flows in an urban environment, for e.g. pollutant dispersion investigations, today's main tool is advanced computational fluid dynamics simulations. These simulations take a lot of time and resources to perform, even for small geometries. In some situations, one would like to be able to run approximate simulations, possibly with large geometries, without such a significant investment. The model described in this thesis is a graph network model which have streets and intersections of an urban environment modeled as connections and nodes in a graph. The model uses a pressured pipe model, based on the Darcy-Weisbach equation, to simulate air flow in the network. Such a model requires only rough measurements of the urban geometry and an estimated Darcy's friction factor, to be able to solve the system. Furthermore, using the same rough geometrical parameters, together with shear velocity, the model solves atmospheric exchange rates of the streets. Intersections play a major role when investigating urban dispersion. The way this model deals with dispersion in any complex intersections, represented by single nodes, is by using wind direction variance together with a distribution parameter based on computational fluid dynamics intersection simulations made in Comsol Multiphysics - also present in this paper. Using the simple model described above, I have simulated urban air flows in a complex urban geometry of a part of Paris. This specific geometry has already been investigated by computational fluid dynamics simulations as well as wind tunnel experiments. By comparing the computational fluid dynamics simulation with my model, I have validated its accuracy. 40% and 45% of all streets reach a relative and absolute error below 25% respectively. Directions of the street velocities have been simulated with approximately 90% accuracy - with distinct error indications. Atmospheric exchange rates of the streets are within an order of magnitude accurate, however, showing a systematic error by overestimating the vast majority of the exchange rates. The model could become even better by covering error sources discussed in the discussion section. Excess theory for simulating each of the above-described flows is presented, which might change the results. For example, slightly altering the modeling of the atmospheric exchange rate might fix the overestimation offset we have seen. Potential error sources could be the varying building heights and the streets angle relative the overlaying wind direction. The pressured pipe simulated flows have shown tendencies to be bad at picking up the effects of high/low buildings following low/high buildings, as well as accurately capture the behavior of streets close to perpendicular to the wind direction. Main streets with plenty of exits have been modeled with intersections at each exit, which results in strong flow variation along a street that should have a flow close to constant. Solving main streets like this separately could improve this behavior drastically
Protocol State Fuzzing of EDHOC Implementations Using Register Automata Learning
No full textThis thesis aims to enhance protocol state fuzzing by integrating richer learned models, specifically capturing data flow within security protocols. The goal is to evaluate whether these enhancements lead to more comprehensive models. The key steps include updating the ProtocolState-Fuzzer (PSF) tool to support register automata learning via the RALib API, creating a protocol-specific adaptation for the Ephemeral Diffie-Hellman Over COSE (EDHOC) protocol, and using the adapted tool to learn and analyse models of protocol implementations. Experimental evaluation of four EDHOC protocol implementations demonstrated that while RALib algorithms required significantly longer learning times compared to Mealy machine algorithms, they do indeed produce larger and more comprehensive models. This trade-off between learning time and model complexity revealed that RALib-based models offered more detailed representations, crucial for thorough analysis. The findings underscore the importance of choosing suitable learning algorithms based on the required level of detail. Consequently, this work advances protocol state fuzzing methodologies, enabling the creation and analysis of more intricate state machines, thereby enhancing the testing and analysis of security protocols like EDHOC.Detta projekt syftar till att förbättra protocol state fuzzing genom att integrera rikare inlärda modeller, med fokus på att fånga dataflödet inom säkerhetsprotokoll. Målet är att utvärdera om dessa förbättringar leder till mer omfattande modeller. De viktigaste stegen inkluderar att uppdatera verktyget ProtocolState-Fuzzer (PSF) för att stödja registerautomatinlärning via RALibs API, skapa en protokollspecifik anpassning för Ephemeral Diffie-Hellman Over COSE (EDHOC) protokollet och använda det anpassade verktyget för att analysera modeller av protokollimplementationer. Den experimentella utvärderingen av fyra EDHOC implementationer visade att medan RALib-algoritmer krävde avsevärt längre inlärningstider jämfört med Mealy-maskinalgoritmer, producerade de faktiskt större och mer omfattande modeller. Denna kompromiss mellan inlärningstid och modellkomplexitet visade att RALib-baserade modeller erbjöd mer detaljerade representationer, vilket är avgörande för analys. Resultaten betonar vikten av att välja lämpliga inlärningsalgoritmer baserat på den nödvändiga detaljnivån. Därmed främjar detta arbete metodologier för protocol state fuzzing, möjliggör skapandet och analysen av mer intrikata tillståndsmaskiner, vilket i sin tur förbättrar testningen och analysen av säkerhetsprotokoll som EDHOC
Brytpunkt för samkönad lek : En kvalitativ studie om barns fria utelek ur ett genusperspektiv
No full textSyftet med denna studie är att få en fördjupad förståelse för om det finns någon skillnad mellan flickor och pojkar vad gäller könsöverskridande och åldersblandad utomhuslek, samt på vilket sätt dessa skiljer sig mellan olika förskolor. Den kvalitativa studien har genomförts med stöd av observationer. En observationsmall användes för att strukturera observationerna för att se barnens uppdelningar i den fria uteleken på förskolegårdarna. 15 observationer vid tre förskolor genomfördes där barnens lek dokumenterades utifrån kriterierna ålder och kön. Resultatet visade att den könsöverskridande leken skiljer sig mellan olika förskolor och är av varierande slag vad gäller ålder och kön. Barnen i våra observationer visar ett tydligt intresse för att leka med varandra oberoende av kön eller ålder. Barnen lekte mer köns- och åldersöverskridande då det var många barn som lekte på förskolegården
Herbivores rescue diversity in warming tundra by modulating trait-dependent species losses and gains
No full textClimate warming is altering the diversity of plant communities but it remains unknown which species will be lost or gained under warming, especially considering interactions with other factors such as herbivory and nutrient availability. Here, we experimentally test effects of warming, mammalian herbivory and fertilization on tundra species richness and investigate how plant functional traits affect losses and gains. We show that herbivory reverses the impact of warming on diversity: in the presence of herbivores warming increases species richness through higher species gains and lower losses, while in the absence of herbivores warming causes higher species losses and thus decreases species richness. Herbivores promote gains of short-statured species under warming, while herbivore removal and fertilization increase losses of short-statured and resource-conservative species through light limitation. Our results demonstrate that both rarity and traits forecast species losses and gains, and mammalian herbivores are essential for preventing trait-dependent extinctions and mitigate diversity loss under warming and eutrophication.Correction: Elina Kaarlejärvi, Anu Eskelinen, Johan Olofsson. Author correction: Herbivores rescue diversity in warming tundra by modulating trait-dependent species losses and gains. Nature Communications (vol 8, 423, 2017). DOI: 10.1038/s41467-017-02129-4</p
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