Monitoring System for Agrometeorological Application with Voice-Controlled Interface

The objective of this work is to present aspects about the already completed development stages of a monitoring system for agrometeorological application that uses Human-Computer Interface controlled by written and spoken languages. Technologies related to the development of this type of HCI have been increasingly used and are gradually more connected to the most diverse devices and machines including fieldwork uses. This interdisciplinary work is supported by research in the areas of Meteorology, Linguistics, Natural Language Processing (NPL) and Computing using physical prototypes focused on monitoring: automated solar search, unmanned aerial vehicle (UAV), unmanned groundvehicle (UGV), mix of meteorological sensors and the system itself. The steps already completed and interrelated - automated solar tracker, the set of meteorological sensors and the system - show that this type of monitoring has a significant degree of accuracy, low cost and autonomy - it does not depend on the conventional grid and makes small decisions

Offline and online power aware resource allocation algorithms with migration and delay constraints

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/In order to handle advanced mobile broadband services and Internet of Things (IoT), future Internet and 5G networks are expected to leverage the use of network virtualization, be much faster, have greater capacities, provide lower latencies, and significantly be power efficient than current mobile technologies. Therefore, this paper proposes three power aware algorithms for offline, online, and migration applications, solving the resource allocation problem within the frameworks of network function virtualization (NFV) environments in fractions of a second. The proposed algorithms target minimizing the total costs and power consumptions in the physical network through sufficiently allocating the least physical resources to host the demands of the virtual network services, and put into saving mode all other not utilized physical components. Simulations and evaluations of the offline algorithm compared to the state-of-art resulted on lower total costs by 32%. In addition to that, the online algorithm was tested through four different experiments, and the results argued that the overall power consumption of the physical network was highly dependent on the demands’ lifetimes, and the strictness of the required end-to-end delay. Regarding migrations during online, the results concluded that the proposed algorithms would be most effective when applied for maintenance and emergency conditions.Peer ReviewedPreprin

Review of equality statistics

The Equality and Human Rights Commission (EHRC) commissioned this review as part of its remit to map the equalities landscape across England, Scotland and Wales. The report examines the extent to which data are available for the following equality strands: sex; ethnicity / race; disability; religion or belief; age; sexual orientation; and also for socio-economic status (social class). The extent to which statistics are available at different levels of geographic classification (UK, GB, England, Scotland and Wales and regional and local areas within this) is investigated. The report addresses the ten domains of equality identified in the equality measurement framework in the Equalities Review.1 These are: Longevity Physical security Health Education Standard of living Productive and valued activities Individual, family and social life Participation, influence and voice Identity, expression and self-respect Legal securit

New Zealand Working For Families programme: Methodological considerations for evaluating MSD programmes

The methodological review is the second part of the evaluation research commissioned by the Ministry of Social Development (MSD) in 2005 to help in the preparation of the evaluation of the Working for Families (WFF) programme. This review enumerates the key evaluation questions identified by MSD as central to their policy concerns and considers how the features of WFF could affect evaluation. It details the methodological and data requirements that must be addressed in order to meet the four key evaluation objectives, namely: (1) tracking and evaluating the implementation and delivery of WFF (2) identifying changes in entitlement take-up and reasons for it (3) establishing the impact of WFF on employment-related outcomes (4) assessing WFF’s effect on net income and quality of life more generally. The methodological review complements the literature review by reviewing evaluations from around the world that are pertinent to WFF. An overview of evaluation methods is provided, concentrating on particular issues that arise within the WFF context. Section 2 focuses on implementation and delivery. Section 3 covers the issues related to take-up and entitlement and their evaluation. Section 4 discusses the evaluation methodologies that can be used in evaluating programmes such as WFF and introduces the data requirements they entail. Making work pay is the focus of section 5. Finally, section 6 examines hardship and poverty, living standards and wellbeing.

Interpretation methods of CPTU and RCPTU with special focus on soft soils - Assessment between classical approach and data mining techniques

The purpose of the following work is to explain numerous methods of interpretation of CPT (Cone Penetration Test) and to find the most practical one for soft soils. Due to the complex nature of the problem and the needs of acquiring credible results following parameters have been taken into account: pore pressure measurement (CPTU) and resistivity (RCPTU). The present master's thesis focuses on comparison of post-processed results from different interpretation methods with laboratory data. In the beginning most popular approaches for sensitive soils are presented: soil classification charts, undrained shear strength, sensitivity and resistivity measurements from RCPTu. Further, an experimental method of machine learning is explained. Three solutions has been choosen with different classifying algorithms. This ensures separate origin of the calculated results, which should simplify overall analysis of the models. The data mining software called WEKA is used for the calculations. Possible combinations of testing, verification process and modeled soil profiles are presented in the process. All the research is concluded in final comparison of obtained results to laboratory data and most accurate predictions are selected

Application of Digital Twin in Norwegian Oil and Gas Industry

Dei siste ti femten åra har digitale tvillingar blitt implementert i ulike bransjar. Tidlegare forsking indikerer at den globale olje og gass sektoren heng etter andre industriar, som for eksempel produksjonsindustrien. Det er ikkje mykje forsking som er utført på korleis digitale tvillingar blir brukt i den norske olje og gass industrien, men ei spørjeundersøking indikerte at selskapa får positive effektar frå digitale tvillingar i dag. Denne oppgåva ønskjer å undersøke kor moden den norske olje og gass industrien er i bruk av digitale tvillingar. Dette er ein empirisk casestudie som undersøker to av dei norske operatør selskapa frå eit nedanfrå opp perspektiv. Seks intervju er blitt utført. Studien undersøker korleis næringa nyttar digitale tvillingar i praksis. Den undersøker kva element og funksjoner er blitt utvikla, korleis dei er blitt implementert, og i kva grad selskapa oppnår verdi. Videre undersøker oppgåva arkitekturen til dei digitale tvillingane og om dei, slik dei er implementert, er klare for framtidige moglegheiter innanfor maskinlæring. Endeleg diskuterer oppgåva om erfaringane frå olje og gass selskapa kan overførast til fornybarnæringa i Norge. Funn bekreftar at dei to selskapa i studien har utvikla digitale tvillingar nytta i alle livsfasar og i alle delar av organisasjonen. Funn bekreftar også at selskapa er opptatt av kva dei digitale tvillingane skal innehalde av informasjon og har tydlege spesifikasjonar for dette. I tråd med litteratur, indikerer funn at selskapa ikkje er like opptatt av nøyaktigheit og oppløysing i modellane sine, eller at dei skal innehalde regel- og åtferds modellar som definert i litteraturen. Funn indikerer at operativ bruk av digitale tvillingar ikkje er like godt implementert på alle plattformer og felt. Mindre modne digitale tvillingar ser ut til å vere hovudårsak. I følgje litteraturen blir digitale initiativ i olje og gass implementert nedanfrå-opp. Funn tyder på at for selskapa i undersøkinga er dette ikkje tilfelle. Funn tyder på at situasjonen er meir kompleks enn den nemnte spørjeundersøkinga indikerte. Sjølv om undersøkinga viser at selskapa skaper positive effektar frå den digitale tvillingen, er effektane og kostnadar vanskelege å kvantifisere, og det er usikkert om netto effekten er positiv. Funna indikerer og at effektane er lågare når ein digitaliserer gamle plattformer i forhold til nye. Industrien er opptatt av nye moglegheiter innanfor Generativ AI og store språkmodellar. Funn tyder på at dei digitale tvillingane kanskje ikkje er moden for desse teknologiane. Oppgåva konkluderer med at funna i denne studien kan generaliserast og overførast til den norske fornybarnæringa.The last ten to fifteen years, digital twins have been implemented in various industries. Previous research indicate that the global oil and gas sector is lagging compared to other industries, like manufacturing. Not much research has been conducted on how digital twins are used in the Norwegian oil and gas industry. An industry survey indicate that the companies get benefits from digital twins today. This thesis aims to explore how mature the Norwegian oil and gas industry is in its use of digital twins. It is an empirical case study that investigates two Norwegian operator companies from a bottom-up perspective. Six interviews have been conducted to shed light on the topic. The study investigates how digital twins are applied in the operator companies in practice. It examines which elements and functionality have been developed, how they have implemented it, and to what extent the companies gain value from the digital twins. Further, the study explores the basic architecture of the digital twin and whether the models, as they are implemented, are ready for future capabilities within machine learning. Finally, the thesis discusses whether the experience from the oil and gas companies can be adopted by the renewable industry in Norway. Findings confirm that the companies studied have evolved digital twins used in all lifecycles and in all branches of their business. Findings also confirm that the companies are concerned about what their digital twins shall contain and have clear specifications for this. In line with literature, findings indicate that the companies are not that concerned about accuracy and fidelity of their models, nor to include rules- and behavior model as defined in literature. Findings indicate that use of digital twins are not well implemented on all platforms and fields. Lack of mature models seems to be main cause. According to literature digitalization initiatives in oil and gas is implemented bottom-up. Findings suggest that for the companies in the study this is not the case. Findings suggest that the situation is more complex than the mentioned industry survey indicated. The study finds that while the companies gain value from their investment, quantifying benefits and cost is hard, and it is uncertain whether the net value is positive. Findings may also indicate that value creation is lower when digitalizing old platforms then new ones. The industry is concerned with new capabilities within Generative AI and LLM. Findings indicate that their digital twins may not be that well positioned for these technologies. The thesis concludes that the findings may be generalized and adopted to the Norwegian renewable industry

Tool for journalists to edit the text generation logic of an automated journalist

Automated journalism means writing fact-based articles based on structured data using algorithms or software. The advantages of automated journalism are scalability, speed and lower costs. The limitations of it are fluency, quality of writing and limited perception. In this thesis, the different implementation methods of automated journalism were compared. These implementation methods were templates, decision trees, fact ranking method and different machine learning solutions. It was found out that no implementation method was strictly better than others but all had distinct advantages and disadvantages. When selecting an implementation method these factors should be taken into account and weighed. Finnish national broadcasting company Yle’s automated journalist Voitto-robot was discussed. Voitto’s implementation is based on templates and decision trees. While Voitto’s text generation is easily modifiable and transparent due to its implementation method, this was only available to programmers. The decision trees were implemented directly in the code which made them hard to understand and the template files were too complex to be easily edited. In this thesis, a proof-of-concept web application was made to allow journalists and other content creators the possibility to edit the templates and decision trees of Voitto independently. The created software was analysed and it was found that it helped journalists understand the text generation and modify it as they wanted. Even in its proof-of-concept state, it was good enough to be used to automate election reporting for the Finnish parliamentary election of 2019