Crack Analysis Due to Fatigue Load During Subsea Pipeline Installation

Most of the subsea pipelines in Indonesia are installed using the S-Lay method with the pipelay barges equipped with mooring spreads, tensioners, and stinger. During the subsea pipeline installation, static loads occur due to the pipeline configuration from the firing line of the pipelay barge up to the seabed. The pipe will experience axial tension and bending moment in two critical areas: overbend and sagbend. In addition, fatigue loads occur during subsea pipeline installation due to environmental loads (i.e., currents and waves). Defects that are found after welding will grow due to these fatigue loads. Crack analysis with a fracture mechanic approach known as Engineering Critical Assessment (ECA) is carried out by considering the fatigue load due to significant wave height variations for 0.5m, 1.0m, and 1.8m. BS 7910 is used as a standard reference to determine the allowable defects criteria for external and internal flaws. The depth of the defect (a) is simulated from a depth of 1mm – 3mm. The analysis found that the allowable defect length is decreased by 12.7% - 25.0% from a significant wave height of 0.5m to 1.8m for the external surface flaw. While for an internal surface flaw, the allowable defect length is decreased by 5.9% - 13.6% from a significant wave height of 0.5m to 1.8m. These results can be used as a basis for subsea pipeline installation contractors to perform fatigue load sensitivity and optimize the allowable defects based on the actual wave load at the site

Offshore Wind in Maine

80% of U.S. electricity demands are located in coastal states, and the total U.S. offshore wind energy potential is more than twice what the entire country currently uses. Nearly 80% of the U.S. offshore wind resource is located in deepwater, which can be cost effectively harnessed using the University of Maine’s VolturnUS

Lokitiedon visualisointi selaimessa

Työn tarkoituksena oli tehdä TimeToPic Logger-ohjelmaan palvelinkomponentti, jonka tarkoitus on mahdollistaa TimeToPic Logger-ohjelman lokitiedon tarkastelu lähiverkon kautta nettiselaimessa. Näin lokidataan päästään käsiksi esimerkiksi mobiililaitteella. Palvelinkomponentti on Qt-kehitysympäristössä ohjelmoitu luokka, joka sisältää web-palvelimen ja WebSocket-toteutuksen tiedon lähettämistä ja vastaanottamista varten. Komponentin lisäksi tehtiin nettisivu, jonka palvelin lähettää selaimelle sen yhdistäessä palvelimeen. Nettisivu vastaanottaa WebSocket-yhteydellä lokitietoa, ja näyttää sitä muutaman päivittyvän graafisen elementin avulla. Työssä käydään läpi TimeToPic Loggerin toiminta lyhyesti, palvelinkomponentin määrittelyvaatimukset, työssä käytetyt tekniikat ja työkälut, sekä ohjelmakoodin toteutus ja testaus. Lopuksi pohditaan ohjelman jatkokehitysmahdollisuuksia, sekä käydään läpi projektin lopputulokset.The projects goal was to make a web server component for TimeToPic Logger-program that allows viewing the log data from TimeToPic Logger in a browser trough the local network. This way the log data can be for example accessed with a mobile device. The component was a class made in Qt application framework, and it includes a web server and a WebSocket implementation for sending and receiving data. Additionally a web page was made, which the server sends to the browser when it connects. The web page receives log data from a WebSocket connection and shows the data in a few updat-ing graphic elements. This thesis covers a short description of TimeToPic Logger, the components specifica-tions, the techniques and tools used in the work, programming the software and testing it. At the end it ponders the further development of the software and the end results of the project

Ett probabilistiskt inneh ̊ allsbaserat nyhetsrekommenationssystem

Digital content can be created and published in large quantities and at low costs. News publications in particular benefit from being able to reach readers without delay, and because the digital newspaper pages are virtually infinite in size, there is plenty of room for diversity. As the amount of content and variety increase, however, it becomes harder and harder for readers to find relevant news stories. Using knowledge about every news item that has been published and the preferences of readers, news recommender systems provide each user with personalized recommendations. They reduce user effort and make content more accessible and discoverable. In this thesis the development of a news recommender system is explored with the primary target of finding a simple and extensible solution. Using probability theory as a framework, a model of user behavior is iteratively derived through experimentation and validation. It calculates the probability that an item is selected among a set of candidate items. The model consists of several smaller parts, each of which focus on different aspects of what makes news interesting. Some are personalized and adapt to the user’s behavior, while others reflect general usage patterns. There are many challenges involved, and a major one is the cold start problem, which can cause bad results when assumptions are made based on insufficient knowledge. This challenge, and more, define additional requirements on the implementation. By optimizing for minimal mean cross entropy against the empirical selection distribution of several users, accurate and composable models are found. The time and space complexities of the model are low and there is a straight-forward and mathematically sound way to extend the system further. Evaluation metrics such as item coverage and recommendation diversity provide insight into the large scale behavior of the system and confirm the utility of personalization.Digitalt innehåll kan skapas och publiceras i stora mängder och till låga kostnader. Nyhetsförmedlingar i synnerhet kan dra nytta av möjligheten att genast nå läsare och eftersom det digitala pappret är så gott som oändligt finns det rum för mångfald. Men allt som storleken på innehållet och variationen ökar blir det svårare och svårare för läsare att finna relevanta nyheter. Genom att använda kunskap om varje nyhet som publicerats och läsarnas intressen kan ett rekommendationssystem tillgodose varje läsare med personliga rekommendationer. De underlättar användandet och gör innehållet lättillgängligt och enkelt att få en översikt av. I det här diplomarbetet undersöks utvecklandet av ett nyhetsrekommendationssystem vars främsta mål är att finna en enkel lösning som kan utökas. Med sannolikhetslära som grund härleds en modell av användarbeteende genom upprepade experiment och validering. Modellen räknar ut sannolikheten att en nyhet väljs bland en mängd valmöjligheter. Den består av flera mindre delar och var och en av dem fokuserar på olika aspekter av vad som gör nyheter intressanta. En del skräddarsyr resultaten och anpassar sig till användarens beteende och andra speglar allmänna användningsmönster. Det finns många utmaningar varav kallstartsproblemet är viktig, vilken kan leda till odugliga resultat när antaganden görs med otillräcklig information. Denna utmaning bland andra utgör ytterligare krav på implementationen Genom att optimera för minimal medelkorsentropi gentemot flera användares empiriska valdistributioner skapas modeller som ger goda resultat och vilka kan sammanslås. Modellens tids- och rymdkomplexiteter är låga och det finns enkla och matematiskt korrekta sätt att vidare utöka systemet. Utvärderingsmått som täckning och rekommendationsmångfald beskriver modellens storskaliga beteende och bekräftar nyttan av personliga rekommendationer

Public mental health research in Europe:A systematic mapping for the ROAMER project

Background: As part of the ROAMER (ROAdmap for MEntal health Research in Europe) project, aiming to create an integrated European roadmap for mental health research, we set out to map the hitherto unmapped territory of public mental health research in Europe. Methods: Five electronic databases (CINAHL, Health Management, Medline, PsycINFO, Social Services Abstracts) were used for identifying public mental health research articles published between January 2007 and April 2012. The number of publications for each European country in five research domains (i.e. mental health epidemiology, mental health promotion, mental disorder prevention, mental health policy and mental health services) was analysed by population size and gross domestic product (GDP), and mean impact factors were compared. Results: In all, 8143 unique publications were identified. Epidemiology research dominates public mental health research, while promotion, prevention and policy research are scarce. Mental health promotion is the fastest growing research area. Research targeting older adults is under-represented. Publications per capita were highest in northwestern Europe, and similar trends were found also when adjusting the number of publications by GDP per capita. The most widely cited research origins from Italy, Switzerland, the UK, the Nordic countries, the Netherlands, Greece and France. Conclusion: In Europe, public mental health research is currently a matter of the affluent northern and western European countries, and major efforts will be needed to promote public mental health research in south and east Europe. In spite of a smaller public mental health research output, some Mediterranean countries produce highly cited public mental health research

A Latent Factor Analysis of Working Memory Measures Using Large-Scale Data

Working memory (WM) is a key cognitive system that is strongly related to other cognitive domains and relevant for everyday life. However, the structure of WM is yet to be determined. A number of WM models have been put forth especially by factor analytical studies. In broad terms, these models vary by their emphasis on WM contents (e.g., visuospatial, verbal) vs. WM processes (e.g., maintenance, updating) as critical, dissociable elements. Here we conducted confirmatory and exploratory factor analyses on a broad set of WM tasks, half of them numerical-verbal and half of them visuospatial, representing four commonly used task paradigms: simple span, complex span, running memory, and n-back. The tasks were selected to allow the detection of both content-based (visuospatial, numerical-verbal) and process-based (maintenance, updating) divisions. The data were collected online which allowed the recruitment of a large and demographically diverse sample of adults (n = 711). Both factor analytical methods pointed to a clear division according to task content for all paradigms except n-back, while there was no indication for a process-based division. Besides the content-based division, confirmatory factor analyses supported a model that also included a general WM factor. The n-back tasks had the highest loadings on the general factor, suggesting that this factor reflected high-level cognitive resources such as executive functioning and fluid intelligence that are engaged with all WM tasks, and possibly even more so with the n-back. Together with earlier findings that indicate high variability of process-based WM divisions, we conclude that the most robust division of WM is along its contents (visuospatial vs. numerical-verbal), rather than along its hypothetical subprocesses

Vibrator-Assisted Start-Stop Exercises Improve Premature Ejaculation Symptoms: A Randomized Controlled Trial

Premature ejaculation (PE) is associated with decreased quality of life, lower confidence and self-esteem, and higher levels of depression, anxiety, and interpersonal difficulties. Here we investigated the effectiveness of vibrator-assisted start–stop exercises for treatment of PE, and whether the treatment effect could be enhanced by an additional psychobehavioral intervention. Fifty participants with a mean age of 41.7 years were included and randomized into two treatment groups and a waiting list control group. Participants were instructed to perform start–stop exercises while stimulating the penis with a purpose-made vibrator, 3 times a week for 6 weeks. Additionally, participants in one of the treatment groups received additional psychoeducation and performed mindfulness meditation-based body scan exercises three times a week. Data were gathered through online questionnaires before and after treatment, as well as 3 and 6 months after treatment. The interventions reduced PE symptoms with large effect sizes (partial η2 = .20 across the three groups, d [95% CI] = 1.05 [.27, 1.82] and 1.07 [.32, 1.82] for treatment groups compared to waiting list control group). The additional psychobehavioral intervention did not further reduce PE symptoms, but did decrease PE-associated negative symptoms such as levels of sexual distress, anxiety, and depression. No side effects were reported. Vibrator-assisted start–stop exercises can be offered as an adequate treatment option for PE.<br /

Data for "Vibrator-Assisted Start-Stop Exercises Improve Premature Ejaculation Symptoms: A Randomized Controlled Trial"

Data from an intervention study for PE

Tyylitellyn videopelikohtauksen luominen

Opinnäytetyössä tutkittiin, miten toteutetaan tiettyä tyyliä mukaileva välianimaatio videopeliin. Työn toimeksiantajana oli Pixtell Oy. Työssä tehtiin välianimaatio Unreal Engine 5 -kehitysympäristössä. Välianimaation tuli mukailla elokuvaohjaaja Quentin Tarantinon elokuvien tyyliä. Toteutusta varten työssä perehdyttiin Tarantinon elokuvatuotantoon, ja selvitettiin ohjaajan elokuvien tunnuspiirteitä. Työn tuloksena saatiin selvitys tärkeimmistä työvaiheista ja työkaluista, jotka on huomioitava, kun halutaan toteuttaa tiettyä tyyliä mukaileva välianimaatio. Työn tulokset toimivat esimerkkinä aloittelevalle välianimaatioiden tekijälle