Les espèces forestières sont particulières à bien des égards par rapport aux autres espècesdomestiquées. Les arbres forestiers ont de longues phases juvéniles, entrainant de long et couteuxcycles de sélection et nécessitant une sélection en plusieurs étapes indépendantes. Bien que cetteméthode soit efficace du point de vue opérationnel, elle reste couteuse en temps et en ressources,entrainant une dilution de l’intensité et de la précision de sélection. Au vu de ces contraintes,les arbres sont de bons candidats pour la mise en oeuvre de l’évaluation génomique. La sélectiongénomique (SG) repose sur le classement et la sélection d’individus à partir de l’informationcontenu dans leur génome sans utilisé une étape d’évaluation phénotypique et ainsi accélérerle processus de sélection.Ce travail visait à identifier les situations, les critères et les facteursdans lesquelles la SG pourrait être une option réalisable pour le peuplier. Notre étude a montréque les avantages de l’évaluation génomique dépendent du contexte. C’est dans des situationsles moins avantageuse que l’évaluation génomique se montre la plus performante, elle profiteégalement de la densification de l’information génétique de faible à moyenne suite à une étaped’imputation de haute qualité. La sélection génomique pourrait être une option intéressante àstade précoce, où la précision de la sélection est généralement faible et la variabilité génétiqueabondante. Notre travail a également montré qu’il est important d’évaluer les performancesavec des critères alternatifs, comme ceux liés au classement, notamment lorsque ces critèresrépondent au contexte opérationnel du programme d’élevage étudié. / Forest species are unique in many ways compared to other domesticated species. Forest trees have long juvenile phases, leading to long and costly selection cycles and requiring selection in several independent stages. Even if this method is operationally effective, it remains costly in terms of time and resources, resulting in a diluted intensity and accuracy of selection.In view of these constraints, trees are good candidates for the implementation of genomic evaluation. Genomic selection (SG) is based on the classification and selection of individuals from the information contained in their genome without using a phenotypic evaluation step and thus accelerating the selection process, in order to identify the situations, criteria and factors in which SG could be a feasible option for poplar. Our study showed that the benefits of genomic evaluation are context-dependent. Genomic evaluation is most effective in theless-advantageous situations, it also benefits from low to medium density genetic information following a high-quality imputation step. Genomic selection could be an interesting option at an early stage, when the accuracy of selection is generally low and genetic variability is abundant.Our work has also shown that it is important to evaluate performance with alternative criteria,such as those related to ranking, especially when these criteria fit the operational context of the breeding programme under study.

A trans man struggles to stay euphoric on his first day on testosterone in a world where his anxieties and emotional baggage talk back to him. He realizes becoming a self-made man comes with self-made problems. PW for Vimeo Link: DianaSeason2022!

Information retrieval within a company can be referred to as enterprise search. With the use of enterprise search, employees can find the information they need in company internal data. If a business can take advantage of the knowledge within the organization, it can save time and effort, and be a source for innovation and development within the company.  In this project, two open source search engines, Recoll and Apache Solr, are selected, set up, and evaluated based on requirements and needs at the pharmacometric consulting company Pharmetheus AB. A requirement analysis is performed to collect system requirements at the company. Through a literature survey, two candidate search engines are selected. Lastly, a Proof of Concept is performed to demonstrate the feasibility of the search engines at the company. The search tools are evaluated on criteria including indexing performance, search functionality and configurability. This thesis presents assessment questions to be used when evaluating a search tool. It is shown that the indexing time for both Recoll and Apache Solr appears to scale linearly for less than one hundred thousand pdf documents. The benefit of an index is demonstrated when search times for both search engines greatly outperforms the Linux command-line tools grep and find. It is also explained how the strict folder structure and naming conventions at the company can be used in Recoll to only index specific documents and sub-parts of a file share. Furthermore, I demonstrate how the Recoll web GUI can be modified to include functionality for filtering on document type.  The results show that Recoll meets most of the company’s system requirements and for that reason it could serve as an enterprise search engine at the company. However, the search engine lacks support for authentication, something that has to be further investigated and implemented before the system can be put into production.

Data conversion for evolving events in an Event Sourcing System is a complex issue and needs to be maintainable. There are suggested ways handling data conversion today which combine different methods into a framework. However, there is a lack of exploration of different and alternative methods to handle the complicated matter.This thesis explores data conversion with fine-grained events. The purpose is to explore methods and broaden knowledge for handling data conversion while using attribute driven events called fine-grained events. The goal was to build a proof-of-concept that preserves the attributes reliability and availability and can handle data conversion of these specific events.The results found by using fine-grained events are a decrease in terms of system complexity and a proof-of-concept that maintains the desired attributes. / Datakonvertering för utvecklande händelser i ett Event Sourcing System är en komplex fråga som kräver att systemet är enkelt underhållning. Det finns förslag på sätt att hantera datakonvertering idag, vilket kombinerar olika metoder i ett ramverk. Det finns emellertid en brist på undersökning av olika och alternativa metoder för att hantera den komplexa orsaken.Denna avhandling undersöker datakonvertering med finkorniga händelser. Syftet är att utforska metoder och utvidga kunskap för hantering av datakonvertering genom att använda attributdrivna händelser som kallas finkorniga händelser. Målet var att bygga ett proof-of-concept som bevarar egenskaperpålitlighet och tillgängligt och som dessa specifika händelser.även hanterar datakonvertering förResultaten som hittas genom att använda finkorniga händelser är en minskning av systemkomplexiteten och ett bevis på koncept som upprätthåller de önskade egenskaperna.

Internet of Things (IoT) is a phenomenon that involves providing things or objects with sensors and internet connection. The field of IoT is growing rapidly and there are strong incentives for companies to follow the trend to develop and create an IoT. However, the proportion of IoT initiatives considered to be successful has been shown to be low. This study therefore investigates how a project methodology can support a concept development and secure the business value for IoT initiatives. The project methodology developed in this study is named eXtreme PoC Development (XPD). XPD is based on existing project methodologies from literature and interviews from consulting companies within the field in the Stockholm region. It was evaluated by a case study where fault detection in street lighting was investigated and implemented. The evaluation of the methodology highlighted the importance of defining problems and solutions that are anchored in the business value, calculating a potential of an IoT initiative that determines the continuation of a project, involving stakeholders at an early stage and developing a PoC to validate and evaluate a concept with stakeholders. / Internet of Things (IoT) är ett fenomen som innebär att förse saker eller objekt med sensorer och internetförbindelse. Området för IoT är starkt växande och det finns starka incitament hos företag att följa trenden att utveckla och skapa en IoT. Andelen IoT-initiativ som anses vara framgångsrika har däremot visats sig vara låg. Denna studie undersöker hur en projektmetodik kan stödja en konceptutveckling och säkra affärsnyttan för IoT-initiativ. Projektmetodiken som tagits fram i denna studie benämns eXtreme PoC Development (XPD). XPD baseras på befintliga projektmetodiker från litteratur och intervjuer från konsultbolag i Stockholmsregionen. Den utvärderades genom en fallstudie där feldetektering i ljuspunkter i utomhusmiljö undersöktes och implementerades. Utvärderingen av metodiken belyste vikten av att definiera problem och lösningar som är förankrade i affärsnyttan, att beräkna en potential av ett IoT-initiativ som bestämmer ett projekts fortsättning, att involvera intressenter i ett tidigt stadie och att utveckla en PoC för att validera och utvärdera ett koncept med intressenterna.

This thesis presents a PoC for a Machine Learning based Integrated Business Forecasting tool in Integrated Business Planning (mature S&OP) environment for long-term and mid-term transportation volume forecasting for outbound supply flows as a case study.   To achieve this goal, the thesis provides a literature review which ensures the research gap presented by the research questions and scope. Later, the thesis introduces Sales and Operations Planning process, Machine Learning methods used in the study and the case study scope and the corresponding data minning scope. Following a mixed research strategy, a cause effect diagonis is presented and relevant business factors influencing the transportation volumes per lane are identified based on As-Is business process understanding achieved from interviews and internal and external documentations; which is further used to develop a conditional LSTM based machine learning time series forecasting model for transportation volume forecasting for five transportation lanes as PoC. Furthermore, a benchmark evaluation of the developed ML time series forecasting model with two other forecasting models (XGBoost and Extra Trees) is performed for accuracy and robustness performance metrics for long-term transportation volume forecast and also the performance of the developed ML forecasting model for the mid-term forecast is reported.  From the benchmark evaluation the proposed conditional LSTM model is proven to be a better balanced models in terms of maintaining acceptable level of forecasting accuracy and robustness. The Extra Trees model is the most accurate model with least robustness in forecasting across the five transportation lanes due to it’s inability to learn conditionally for each of the five transportation lanes.

Shareholder Registers provide vital information about ownership structures in corporations and are of interest for a diverse set of stakeholders such as the Swedish Companies Registration Office (and its international equivalences), stockholders, the SEC to name a few. Eventhough the information is public and the interest is high, transparency is limited. Blockchain technology offers a unique set of benefits that can help enhance transparency and security in shareholder registers. Therefore, this thesis aims to investigate how shareholder registers can benefit from blockchain technology by implementing a proof-of-concept and conducting a market analysis. The proof of concept consists of a small-scale implementation of a blockchain network with essential functionality meant to simulate a shareholder register. The market analysis was conducted through interviews with executives from several companies. There is good reason to believe blockchain technology has a future in shareholder registers. The decentralied nature of blockchain implies that it can be leveraged to provide security and transparency benefits that contemporary alternatives cannot. The Proof of concept proves that it can be done conceptually and the market analysis shows that there is demand for it that has not been filled by other alternatives. / Aktieböcker lagrar viktig information som berör aktiebolags ägarstrukturer och är av intresse för flertalet intressenter som Bolagsverket, aktieägare och Finansinspektionen för att nämna ett fåtal. Trots att aktieboken är en allmän handling och att intresset för den är så stort präglas aktieböcker av låg transparens. Blockkedjeteknik erbjuder en uppsättning unika egenskaper som kan bidra med ökad transparens och säkerhet för aktieägare. Detta kandidatarbete ämnar därför att undersöka hur blockkedjeteknik kan bidra till att göra aktieböcker bättre i detta avseende genom att genomföra ett koncepttest samt en marknadsanalys. Koncepttestet består av en småskalig implementation av ett blockkedjenätverk med grundläggande funktionalitet menat att simulera en aktiebok. Marknadsanalysen består av intervjuer genomförda med chefer från flera olika aktiebolag. Det finns goda skäl att tro på att blockkedjeteknik har en framtid inom aktieböcker. Blockkedjeteknikens decentraliserade natur medför möjligheter att förbättra säkerhet och transparens hos dagens aktieböcker. Arbetets koncepttest visar att det kan göras rent konceptuellt medan marknadsanalysen visar att det finns en efterfrågan som inte fyllts av andra alternativ.

In today's society we need an emergency communication system to facilitate communication for when disaster strikes. Where the previous attempts only focused on the network communication and were missing a messaging capability between users. This thesis focused on using blockchain technologies and distributed technologies to validate if a messaging application could be built for a LoRaMesh network by using these technologies. This thesis uses the Design science method to create a design and a proof-of-concept messaging application based on the LoRaMesh protocols network constraints. The first step was to gather knowledge about Blockchain technologies and distributed technologies since these were found to be able to complement weaknesses of IoT protocols and their devices. This knowledge was then used to create a design which could then be used to create the proof-of-concept application and a controlled experiment used to validate the solution.  The controlled experiment was executed in two different iterations for a total of 430 test runs. From this controlled experiment quantitative data could be collected and then measured using the statistical analysis method linear regression analysis. The linear regression analysis was used to produce statistical data to validate the design and proof-of-concept application by controlling it against a standard p-value. The results and conclusions of this thesis contributed to new knowledge by showing how Blockchain technologies and distributed technologies can be used to complement each other. To gain a decentralized message application which can be used in an Emergency communication network based on the LoRaMesh protocols network constraints.

Syfte: Den aktuella studien är en metodstudie för att undersöka möjligheten att mäta förändringar i muskeltjocklek med ultraljud. Om detta fungerar kan metoden användas i studier som för närvarande undersöker om muskeltjocklek eller förändringar i muskeltjocklek vid användning är relaterade till orofacial smärta.Material och metod: Tjugotvå friska forskningsindivider undersöktes. Alla forskningsindivider svarade negativt på de tre screeningfrågorna för temporomandibulär dysfunktion. Ultraljudsundersökningen utfördes för att utvärdera massetermuskelns och temporalismuskeln tjocklek (tjockaste delen och på en standardiserad plats för varje muskel) bilateralt som ett surrogatmått för det totala muskelblodflödet i vila och under hopbitning före och efter en tuggövning. Individen skulle tugga tre smaklösa paraffintuggummi med en frekvens av 90 Hz (90 tugg per minut) under 5 minuter. Individen svarade också på tre frågor om muskelsmärta, trötthet och obehag före och efter tuggövningen.Resultat: Vid jämförelse av muskeltjockleken i vila kontra hopbitning, både före och efter tuggövningen, var resultaten att massetermuskeln är tjockare vid hopbitning än vid vila. Resultaten var signifikant för masseter men inte för den temporalis. Resultaten avseende NRS-skalorna, som visade en ökning i värde efter tuggövningen, var enligt den statistiska analysen signifikanta.Slutsats: Denna studie visar att bedömning av muskeltjocklek med ultraljud är möjlig för masseter eftersom metoden kan upptäcka skillnader mellan vila och hopbitning. / Aim: The current study is a proof-of-concept study to investigate the possibility to measure changes in muscle thickness with ultrasound. If this works, the methodology can be used in studies that are currently investigating whether muscle thickness or changes in muscle thickness in use are related to orofacial pain. Materials and method: Twentytwo healthy research individuals were examined. All of the research individuals answered negatively on the three screening questions for temporomandibular disorders. The ultrasound examination was performed to assess masseter and temporal muscle thickness (thickest part at one standardized location for each muscle) bilaterally as a surrogate measure of total muscle blood flow at rest and during clenching before and after a chewing exercise. The subject would chew three paraffin wax taste-less chewing gums at a frequency of 90 Hz (90 chews per minute) for 5.0 minutes. The subject also answered three questions about muscle pain, fatigue and discomfort before and after chewing. Result: When comparing the muscle thickness at rest versus clenching, both before and after the chewing exercise, the results were that the masseter muscle is thicker when clenching than at rest. The difference was significant for the masseter but not for the temporal muscle. The results obtained regarding the NRS-scales, which showed an increase in value after the chewing exercise was according to the statistical analysis significant. Conclusion: This study shows that assessment of muscle thickness with ultrasound is feasible for the masseter muscle since the method is capable of detecting differences between rest and clenching.

<p>Fully homomorphic encryption allows computations to be made on encrypted data without decryption, while preserving data integrity. This feature is desirable in a variety of applications such as banking, search engine and database querying, and some cloud computing services. Despite not knowing the plaintext content of the data, a remote server performing the computation would still be aware of the functions being applied to the data. To address the issue, this thesis proposes a method of encrypting circuits and executing encrypted instructions, by combining fully homomorphic encryption and digital logic theory. We use the classic RISC Archtecture as a foundation of our work, and the result of our algorithm is essentially an encrypted programming language, where a remote server is capable of executing program code that was written and encrypted by a local client.</p> / Master of Science (MS)