Deformation Properties of Unbound Granular Aggregates

This thesis discusses the resilient and permanent deformation properties of unbound granular aggregates for use in road structures. One of the objectives of the thesis is to identify the influence of the physical properties of the aggregate grains, such as grain size, grain shape, surface texture, mineralogy and mechanical strength through cyclic load triaxial testing. A second objective is to study the effect of water on the deformation properties of materials as well as their frost susceptibility. The third objective is to study the effect of micromechanical properties using a discrete element model (DEM). Deformation in unbound granular materials under cyclic loading is divided into a resilient (recoverable) part and a plastic part that does not recover. The elastic strain represents the denominator in the resilient modulus and the non-recoverable strain results in permanent deformations over time. As the resilient response is non-linear, the resilient deformations may be interpreted using several models for curve fitting. Two of the simplest models are the k-θ model and Uzans model. The interpretation of the permanent deformation behaviour of unbound aggregates is complicated, as there is a need for a failure criterion to define when the material is at a failure stage. Two methods used for interpretation of the permanent deformations are mentioned in Chapter 3 of this thesis; the Shakedown approach and the “Coulomb approach”. Many factors are known to affect the deformation properties in unbound materials. In this thesis the effect of most of these factors is investigated in the six papers. In Chapter 4 the influence of the different factors is discussed on the basis of the results from the papers and findings in the literature. Cyclic load triaxial testing has been the main method to test the deformation properties of the selected unbound materials. This is so far one of the best methods for laboratory simulation of traffic loading. Discrete element modelling is performed to gain a better understanding of the deformation properties of unbound aggregates tested in a triaxial apparatus under cyclic loading. This method provides useful information about the contact mechanics between neighbouring particles and the interaction of the grains. In addition, unbound spherical aggregates have been tested in the laboratory using a triaxial apparatus. The main factors studied in this thesis are the influence of grain shape, grain size distribution, fines content, mineralogy, dry density and water content. Useful information about these key factors has been obtained. However, there is still work to do in order to utilize the conclusions directly in a pavement design system. The dry density, degree of saturation and stress level seem to be key parameters for determining the deformation behaviour, but mineralogy, fines content and grain size distribution are also of importance. Regarding the practical consequences, the results show that mineralogy, fines content and grain size distribution must be given more attention in the pavement design manuals. More effort should also be placed on the compaction control phase in situ, in order to avoid initial rutting in the road structure.PhD i bygg, anlegg og transportPhD in Civil and Transport Engineerin

Binary Classification, Logistic and Nominal Regression: Application to Bank Customer Loyalty Data

Kunder er grunnlaget for enhver forretning sin suksess, og en forretning kan aldri være for takknemlig for sine trofaste kunder. I denne masteroppgaven skal vi finne signifikante forskjeller mellom ulike typer kunder. Ved å gjøre dette kan vi få nyttig kundeinnsikt av passive kunder, og forstå hvorfor kunder velger å gå fra å være aktive til å bli inaktive kunder. Analysene er gjort på kundedatabasen til banken som denne oppgaven er skrevet for. Bankkundene er delt inn i seks grupper, eller kategorier, basert på kundeaktivitet og antall bankprodukter tatt i bruk. Vi betegner kategoriene som A-F, hvor kategori A står for kundene som er mest aktive og kategori F står for kundene som er minst aktive. Vi bruker nominal regresjon til å finne forskjeller i hver av disse kategoriene. Vi fant ut at kunder som har vært i en søkeprosess for lån eller kredittkort hadde en større sannsynlighet for å være en kunde av kategoriene A og B. Vi fant også ut at sannssynligheten for å være kategorisert i F er sterkt redusert hvis kunden er medlem eller ikke-medlem med medlemsbetingelser. I tillegg, sannsynligheten for å være en kunde av kategori A økes kraftig dersom kunden har aktivert eFaktura. La kategoriene A-D være kategoriene med aktive kunder, og kategoriene E-F være kategoriene med inaktive kunder. Vi lager en indikatormodell som forutser hvilke kunder som går fra å være aktive til å bli inaktive i fremtiden. Vi utfører statistiske modellerings- og læringsmetoder, som binær logistisk regresjon, "random forests" og XGBoost, for å oppdage disse kundene. Vi tester også forskjellige modeller basert på modellseleksjonsmetoder som bruker Akaike informasjonskriterium (AIC), lasso regularisering og viktighet av variabler. Modellkvaliteten er evaluert på AUC-verdien på test data. Modellen som presterte best var XGBoost-modellen med alle variablene inkludert. Dermed vil denne modellen bli brukt som indikatormodellen, m.a.o. modellen som skal forutse om en aktiv bankkunde holder seg aktiv eller blir inaktiv i løpet av det kommende året. Vi erfarte at innskuddssaldoen til kunden var den mest signifikante variabelen i denne analysen. Den logistiske regresjonskoeffisienten for denne variabelen er negativ, som betyr at jo høyere innskuddsaldoen er, desto lavere sannsynlighet er det for å bli inaktiv i fremtiden. Antall transaksjoner av kunden og om kunden har lån, er også svært viktige faktorer som spiller inn.Customers are the foundation of any business's success, and a business can never be too grateful for loyal customers. Customer insight is therefore an important key to help sustain loyal and active customers. In this thesis we are going to detect significant differences between different customer types, as well as indicating future inactive customers. Doing so, we will get useful insight about the inactive customers, and perhaps understand why they choose to go from being active to being inactive. The analyses are done on a bank customer database, provided by the bank itself. The bank customers are divided into six groups, or categories, based on customer activity and the number products used. The categories are denoted by A-F, where A contains the most active customers and F contains the least active customers with no products used. We perform nominal regression in order to detect differences between these groups. We experienced that customers that have applied for loan/credit card are more likely to be customers from the categories A and B. Furthermore, we experienced that probability for being in category F is strongly decreased if the customer is a member or a non-member with member benefits. Also, the probability for being in category A is significantly increased if the customers have activated electronical billing. Let the categories A-D relate to the active customers, and the categories E-F relate to the inactive customers. To indicate customers that are going to be inactive in the future, we create an indicator model. We perform statistical modelling and learning methods, such as binary logistic regression, random forests and XGBoost, in order to create this model. We use model selection methods, such as the Akaike Information Criterion (AIC), lasso regularization and variable importance. The performance of a model is evaluated on the AUC value on test data. The model that performed best was the XGBoost model with all the variables included. Thus, this will be used as the indicator for detecting bank customers that are going to be inactive within the next year. We experienced that balance of the customer was clearly the most significant variable, when it comes to being active or inactive in the future. The binary logistic regression coefficient for this variable is negative. Hence, the higher the balance on the deposit account of a customer, the lower is the probability for being inactive in the future. The number of transactions of the customer and if the customer has a loan, are both also very important factors when it comes to being active/inactive in the future

Utilization And Valuation of Open User Communities in High Technology Companies

The context of this study is the AVRfreaks community and Atmel Corporation and we explain how to utilize a community and create a model for calculating the value of a community through two research questions: The practical problem: How to utilize a community? The theoretical problem: How to value a community? High-technology products are debated, criticized and publicly supported by highly skilled, experienced and educated engineers in Internet forums. The engineers form communities with similar interests and compete in having the highest amount of posts and likes from their peers as their only compensation. Meanwhile, in the boardroom, executives ask themselves how they can utilize communities and struggle to understand the return of investment in a community. This study examines existing theories and literature in network theory and community valuation to show how to utilize a community. This study presents a clarification of the community typology in the Introduction and the approach in the study is a generic model for valuation, applied to the functional areas of support and R&D at Atmel. The empirical studies correlate the data from AVRfreaks with Atmels internal data to calibrate the model and provide a valuation of the community. The result of the study finds an annual valuation of AVRfreaks to Atmel to be multi-million dollars in the form of reduced customer support-cost and wider market reach. We find that the application of the model in other industries beyond microcontrollers is possible but further research is required with more calibration to avoid sacrificing precision in the valuation

Lessons learned from Norway:a values-based formulation of inclusive education

Given the numerous conceptual approaches to understanding inclusive education, there is an obvious risk of fragmentation and stagnation in the field. In response, this paper aims to contribute to advancement by going beyond previous work and developing a holistic formulation of inclusive education. Its starting point is that the persistent challenge of offering equal opportunities and full participation for all students in regular schools appears to have complex causal explanations on multiple levels, including the ideological/political, practical, and individual/subjective. This holistic formulation draws on analyses of a) the connections between inclusive education, student diversity and the concept of special educational needs, b) some problematic experiences from Norway, and c) the current state of the field. In this formulation, three core values of inclusion— welcoming communities, combating discriminatory attitudes, and education for all – as articulated in the Salamanca Declaration, are linked to the institutional practice principles of participation, human diversity, and differentiation. The discussion explores these values and their alignment with the principles of inclusive practice and students’ inclusionary outcome in school. Furthermore, the interplay among these values and their corresponding principles of practice principle is illustrated, emphasising the need for awareness when prioritising one over another, both in research and practice

Lessons learned from Norway: a values-based formulation of inclusive education

Given the numerous conceptual approaches to understanding inclusive education, there is an obvious risk of fragmentation and stagnation in the field. In response, this paper aims to contribute to advancement by going beyond previous work and developing a holistic formulation of inclusive education. Its starting point is that the persistent challenge of offering equal opportunities and full participation for all students in regular schools appears to have complex causal explanations on multiple levels, including the ideological/political, practical, and individual/subjective. This holistic formulation draws on analyses of a) the connections between inclusive education, student diversity and the concept of special educational needs, b) some problematic experiences from Norway, and c) the current state of the field. In this formulation, three core values of inclusion— welcoming communities, combating discriminatory attitudes, and education for all – as articulated in the Salamanca Declaration, are linked to the institutional practice principles of participation, human diversity, and differentiation. The discussion explores these values and their alignment with the principles of inclusive practice and students’ inclusionary outcome in school. Furthermore, the interplay among these values and their corresponding principles of practice principle is illustrated, emphasising the need for awareness when prioritising one over another, both in research and practice.publishedVersio

YouTube-ASL: A Large-Scale, Open-Domain American Sign Language-English Parallel Corpus

Machine learning for sign languages is bottlenecked by data. In this paper, we present YouTube-ASL, a large-scale, open-domain corpus of American Sign Language (ASL) videos and accompanying English captions drawn from YouTube. With ~1000 hours of videos and >2500 unique signers, YouTube-ASL is ~3x as large and has ~10x as many unique signers as the largest prior ASL dataset. We train baseline models for ASL to English translation on YouTube-ASL and evaluate them on How2Sign, where we achieve a new finetuned state of the art of 12.39 BLEU and, for the first time, report zero-shot results

Augmenting Poetry Composition with Verse by Verse

We describe Verse by Verse, our experiment in augmenting the creative process of writing poetry with an AI. We have created a group of AI poets, styled after various American classic poets, that are able to offer as suggestions generated lines of verse while a user is composing a poem. In this paper, we describe the underlying system to offer these suggestions. This includes a generative model, which is tasked with generating a large corpus of lines of verse offline and which are then stored in an index, and a dual-encoder model that is tasked with recommending the next possible set of verses from our index given the previous line of verse

Inclusive education for students with challenging behaviour: development of teachers’ beliefs and ideas for adaptations through Lesson Study

This paper explores development in teacher beliefs and ideas for adaptations with respect to students who display challenging behaviour. These students have the same right to inclusive education as other students, but evidence suggest that this still is a partially unsolved issue. The study’s context is an elementary school using Lesson Study as method for professional development over a four-year period. We have used content analysis and compared teacher talk during planning meetings at the beginning and end of the four years. The main findings are increased attention towards student behaviour, increased use of contextual explanations for student behaviour, a marked increase in ideas for adaptations, and ideas changing from exerting external control to engaging students in learning activities. The findings are discussed as to whether they support inclusion and how Lesson Study might have contributed.publishedVersio

Folkehelse og livsmestring i skolen. Hva sier elever om erfaringer med å bestemme selv i læringsaktiviteter? En kvalitativ intervjustudie

Tidligere forskning bekrefter at selvbestemmelse har betydning for elever i skolen, for deres trivsel, indre motivasjon og læringsutbytte. Denne forskningen har i hovedsak kvantitativt design, og vi vet derfor lite om elevenes unike erfaringer gjennom intervju. I denne artikkelen presenteres forskningsfunn fra et skoleutviklingsprosjekt der 150 elever fikk erfare selvbestemmelse i læringsaktiviteter en dag i uken over ett skoleår. 40 elever ble intervjuet med åpne spørsmål om sine erfaringer på godt og vondt. Funnene viste at selvbestemmelse var nye og positive erfaringer for elevene, der opplevelser av frihet og tillit, fri vilje og flyt var fremtredende. Analysene kan tyde på at erfaringene ga elevene opplevelser av å kunne uttrykke «seg selv». Ifølge elevene hadde dette betydning for deres trivsel, innsats og læring i skolehverdagen. Videre reflekterte de over at de utviklet selvstendighet som følge av å skulle bestemme selv; som en kompetanse de var motivert for å lære, der opplevelser av struktur og oversikt syntes som en viktig læringsbetingelse. De beskrev at det fulgte en fremtidsoptimisme med å øve på og å mestre selvstendighet, i form av at de så for seg at de også kunne mestre livet som voksne. Studiens funn viser til at det trengs mer kunnskap om hvordan lærere kan støtte alle skolens elever til selvbestemmelse, som en del av fagfornyelsen og folkehelse og livsmestring (FoL) i skolen.publishedVersio