The aim of this thesis is a complete assessment of the financial situation of a company. Elementary methods of financial analysis are used to evaluate the current state. Proposals are presented in next part of the work. They are designed to improve the financial position of the company and then consolidate the whole economic situation.

Thesis deals with the assessment of the current state of computer network management and information security for a particular company. Analyzes will be foundation for possible change proposals and enhancements to the requirements and economic opportunities of the specific company.

This work deals with software asset management, types of managed software licenses and also the standards that are related to processes of software asset management. There are specified requirements for a system for SAM (Software Asset Management) and also the design of the system. It deals with the description of the system implementation with the chosen implementation environment, followed with testing of this system and evaluation of results.

<p>Underground utilities must comply with the requirements stipulated in utility regulations to ensure their structural integrity and avoid interferences and disruptions of utility services. Noncompliance with the regulations could cause disastrous consequences such as pipeline explosion and pipeline contamination that can lead to hundreds of deaths and huge financial loss. However, the current practice of utility compliance checking relies on manual efforts to examine lengthy textual regulations, interpret them subjectively, and check against massive and heterogeneous utility data. It is time-consuming, costly, and error prone. There remains a critical need for an effective mechanism to help identify the regulatory non-compliances in new utility designs or existing pipelines to limit possible negative impacts. Motivated by this critical need, this research aims to create an intelligent, knowledge-based method to automate the compliance checking for underground utilities. </p> <p>The overarching goal is to build semantic intelligence to enable knowledge-based, automated compliance checking of underground utilities by integrating semantic web technologies, natural language processing (NLP), and domain ontologies. Three specific objectives are: (1) designing an ontology-based framework for integrating massive and heterogeneous utility data for automated compliance checking, (2) creating a semi-automated method for utility ontology development, and (3) devising a semantic NLP approach for interpreting textual utility regulations. Objective 1 establishes the knowledge-based skeleton for utility compliance checking. Objectives 2 and 3 build semantic intelligence into the framework resulted from Objective 1 for improved performance in utility compliance checking. </p> <p>Utility compliance checking is the action that examines geospatial data of utilities and their surroundings against textual utility regulations. The integration of heterogeneous geospatial data of utilities as well as textual data remains a big challenge. Objective 1 is dedicated to addressing this challenge. An ontology-based framework has been designed to integrate heterogeneous data and automate compliance checking through semantic, logic, and spatial reasoning. The framework consists of three key components: (1) four interlinked ontologies that provide the semantic schema to represent heterogeneous data, (2) two data convertors to transform data from proprietary formats into a common and interoperable format, and (3) a reasoning mechanism with spatial extensions for detecting non-compliances. The ontology-based framework was tested on a sample utility database, and the results proved its effectiveness.</p> <p>Two supplementary methods were devised to build the semantic intelligence in the ontology-based framework. The first one is a novel method that integrates the top-down strategy and NLP to address two semantic limitations in existing ontologies for utilities: lack of compatibility with existing utility modeling initiatives and relatively small vocabulary sizes. Specifically, a base ontology is first developed by abstracting the modeling information in CityGML Utility Network ADE through a series of semantic mappings. Then, a novel integrated NLP approach is devised to automatically learn the semantics from domain glossaries. Finally, the semantics learned from the glossaries are incorporated into the base ontology to result in a domain ontology for utility infrastructure. For case demonstration, a glossary of water terms was learned to enrich the base ontology (formalized from the ADE) and the resulting ontology was evaluated to be an accurate, sufficient, and shared conceptualization of the domain. </p> <p>The second one is an ontology- and rule-based NLP approach for automated interpretation of textual regulations on utilities. The approach integrates ontologies to capture both domain and spatial semantics from utility regulations that contain a variety of technical jargons/terms and spatial constraints regarding the location and clearance of utility infrastructure. The semantics are then encoded into pattern-matching rules for extracting the requirements from the regulations. An ontology- and deontic logic-based mechanism have also been integrated to facilitate the semantic and logic-based formalization of utility-specific regulatory knowledge. The proposed approach was tested in interpreting the spatial configuration-related requirements in utility accommodation policies, and results proved it to be an effective means for interpreting utility regulations to ensure the compliance of underground utilities. </p> <p>The main outcome of this research is a novel knowledge-based computational platform with semantic intelligence for regulatory compliance checking of underground utilities, which is also the primary contribution of this research. The knowledge-based computational platform provides a declarative way rather than the otherwise procedural/hard-coding implementation approach to automate the overall process of utility compliance checking, which is expected to replace the conventional costly and time-consuming skill-based practice. Utilizing this computational platform for utility compliance checking will help eliminate non-compliant utility designs at the very early stage and identify non-compliances in existing utility records for timely correction, thus leading to enhanced safety and sustainability of the massive utility infrastructure in the U.S.</p>

The electrical power grid is one of the most important infrastructures in the modernsociety. It supplies industrial and private customers with electricity and supportsother critical infrastructures such as the water supply. Thus, it is significant that the power grid is a reliable system. However, the power system experiences a hugetransition from classical production methods such as coal and nuclear power plantsto distributed renewable energy forms such as wind energy and photovoltaic. This change to a more distributed system challenges the existing power grid as well as the traditional business models of electric utilities. Thus, cost minimization to increase profitability and improvement of the power grid to increase customer satisfactionare in the focus. One approach to increase the reliability of the grid and decrease maintenance costs is a condition-based maintenance approach which requirescondition monitoring techniques. This thesis introduces into failure rate modelling for individual power system components and develops a method to calculate individual failure rates based onthe average failure rate, failure statistics, and condition monitoring data. This approach includes the analysis of failure statistics to identify failure causes and failure locations which are population characteristics but can be utilized to describe the heterogeneity within the population. Thus, the thesis first introduces into the topic of failure analysis and heterogeneity in populations. Different factors are identified and categorized which describe the condition development of a component overtime. Then, the literature within failure rate estimation is reviewed to present the factors which are used within failure rate modelling and to outline the existingmethods which consider the individual. However, limitations are discussed which emphasize the demand for a new approach. Consequently, this thesis introduce intoa new approach for estimating the failure rate for individual components. / <p>QC 20160526</p> / Energiforsk AB risk analysis program

The Turtle Trading Rules was a successful trend-following trading strategy for commodities in the 1980s but has lost recognition in recent days. The strategy revolved around rules for entering and exiting trades as well as position sizing for each trade. The rules was based on the fundamental aim to capture market trends while at the same time maintaining a controlled risk exposure. This thesis aims to revise the Turtle Trading Rules, here applied on major market indexes, and to examine its viability through different financial metrics. This is done by first implementing the aforementioned trading strategy to the indexes, and later by synthesizing market data through Geometric Brownian Motions. The latter primarily to examine how the strategy perform in different financial environments, what market traits favor the strategy, and to complement the previous examination without altering the core principles of the Turtle Trading Rules. The results suggest that the revised rules for major market indexes is not viable. This because of the poor return, the highest achieved 20-year return and average annual return was 25.1 % and 1.4% respectively (without taking trading fees into account). Furthermore, the strategy applied on synthetic data suggests that favorable traits are highly cyclical data with low volatility, which seldom is the case for real financial time series. The results further indicate that the main issue lies in the rules not being able to distinguish noise from actual entry and exit triggers. Moreover, the drawdown further suggest that it is the exit rather than the entry rules that are to blame for the poor performance during the cycle of a trade. / Turtle Trading-reglerna var en framgångsrik trendföljande handelsstrategi för råvaror på 1980- talet men har sedan dess tappat i populäritet. Strategin kretsade kring regler för inträde och utträde ur ordrar samt kring positionsstorleken för varje order. Reglerna byggde på det grundläggande syftet att fånga marknadstrender och samtidigt upprätthålla en kontrollerad riskexponering. Den här avhandlingen syftar till att revidera Turtle Trading-reglerna, som här tillämpas på utvalda marknadsindex, och att undersöka dess lönsamhet genom olika finansiella mått. Detta görs genom att först implementera den tidigare nämnda handelsstrategin till indexen, och senare genom att syntetisera marknadsdata genom geometriska brownska rörelser (Geometric Brownian Motions). Det senare för att i första hand undersöka hur strategin fungerar i olika finansiella miljöer, vilka marknadsdrag som gynnar strategin, och för att komplettera den tidigare granskningen utan att ändra grundprinciperna i Turtle Trading-reglerna. Resultaten tyder på att de reviderade reglerna för marknadsindexen inte är tillräckligt lönsamma. Detta på grund av den låga avkastningen, den högst observerade 20-årsavkastningen och den genomsnittliga årliga avkastningen var 25,1 % respektive 1,4% (utan hänsyn till handelsavgifter). Dessutom antyds när strategin tillämpas på syntetiska data att tydliga cykliska variationer samt låg volatilitet är fördelaktiga egenskaper, vilket sällan är fallet för reella finansiella tidsserier. Resultatet indikerade vidare att grundproblemet ligger i att reglerna inte kan skilja brus i datan från faktiska inträde och exit triggers. Dessutom tyder drawdown-graferna på att det är exit snarare än inträdesreglerna som är orsaken till det dåliga resultatet i utförandet av köp- och säljprocessen.

Just like the rest of society, the use of digital technology has throughout the years become a more crucial part for train companies to improve performance, meet customer demands, improve operation and maintenance processes to increase efficiency and reliability. These solutions have through time developed to become part of a cluster named Digital Asset Management (DAM). A highly relevant segment of DAM is the maintenance and diagnostic segment (M&amp;D) involving solutions such as diagnostic systems, and predictive maintenance. The purpose of this thesis was to investigate what the market of M&amp;D looks like in Sweden given its complex market structure with approximately 40 private train owners. A multi-case study was conducted in which data was collected through eight semi-structured interviews with employees from different key companies in the Swedish railway industry. Based on the interviews, there are several challenges within the digitalization process in the maintenance and diagnostic segment of DAM. These are related to the following: data availability, data analysis and modelling, investments in knowledge and skills, ecosystem perspective and lastly, maintenance optimization. The role of legislation and its impact on the digitalization was studied. The transition to working with a full condition-based strategy is difficult due to the existing challenges. Instead, it is deemed optimal to implement a hybrid strategy consisting both of conventional/time-based maintenance and condition-based maintenance for applicable components given the current state of the industry. / Precis som resten av samhället har användningen av digital teknik under åren blivit en allt viktigare del för tågföretag för att förbättra prestanda, möta kundkrav, förbättra drifts- och underhållsprocesser för att öka effektivitet och tillförlitlighet. Dessa lösningar har med tiden utvecklats och blivit en del av ett kluster som kallas för Digital Asset Management (DAM) eller på svenska, digital tillgångsförvaltning. En central del av DAM är segmentet för underhåll och diagnostik (M&amp;D) som involverar lösningar som diagnostiksystem och prediktivt underhåll. Syftet var att undersöka hur marknaden för M&amp;D ser ut i Sverige med tanke på Sveriges komplexa marknadsstruktur. Data samlades in genom en flerfallstudie från åtta semistrukturerade intervjuer med anställda från olika nyckelföretag inom den svenska järnvägsbranschen. Baserat på intervjuerna att det finns flera utmaningar inom digitaliseringsprocessen inom segmentet för underhåll och diagnostik inom DAM. Utmaningarna är relaterade till följande områden: tillgänglighet av data, dataanalys och modellering, investeringar i kunskap och kompetens, ekosystemperspektiv och slutligen, optimering av underhåll. Lagstiftningens roll visade sig spela en viktig roll. Det konstaterades att övergången till att arbeta med en helt konditionsbaserad strategi är komplext. Med hänsyn till branschens nuvarande tillstånd är det i stället optimalt att implementera en ”hybridstrategi” som består av både konventionellt/tidsbaserat underhåll och konditionsbaserat underhåll för tillämpliga komponenter.

Sveriges kommunala spillvattenledningsnät står idag inför en enorm utmaning, då eftersattunderhåll i kombination med klimatförändringar kommer kräva stora framtida investeringaroch tidskrävande analyser. Detta examensarbete har utförts med målet att förenkla dettastundande förnyelsearbete. Som metod har en enkät utformats, och besvarats av totalt 84kommuner, med syftet att presentera en lägesbild. Vidare har ett artificiellt neuralt nätverkutvecklats, och tillämpats på data från Täby kommun, med syftet att förutspå vilkaspillvattenledningar i ett ledningsnät som har behov av förnyelse. Resultatet visar att det finns ett stort förbättringsbehov i det strategiska förnyelsearbetet.Störst behov, och potential, finns i hantering och insamling av data, där artificiella neuralanätverk kan tillämpas och utnyttjas som ett effektivt och intelligent verktyg. Det artificiellaneurala nätverket som utvecklats, och tillämpats, i detta examensarbete uppnådde en högprecision (93 %), och beräknade att Täby kommun har ca 10-20 spillvattenledningar medoupptäckt förnyelsebehov. Detta bör dock tas med viss reservation pga. bristandedatakvalitet. Avslutningsvis kan konstateras att lösningen för framtidens ledningsförnyelserelateradeproblem och utmaningar, ligger i förmågan att effektivt och intelligent samla in, struktureraoch analysera data om ledningsnäten. Artificiella neurala nätverk är ett verktyg som kanoch bör användas för detta ändamål då man, med hjälp av artificiell intelligens, kan göraprecisa analyser och skapa helhetsbilder över ledningsnät, vilket kan spara bådefinansiella, temporala och personella resurser. / Aging sewer systems and deferred maintenance pose one of the greatest challenges toSwedish municipal infrastructure in the future. This degree project has been completedwith the aim to develop a method with which to sufficiently solve these future challenges,and help decision makers to properly invest in the networks, and optimise the pipe renewalprocess. As a methodology, a survey has been created, and answered by 84representatives from various municipalities and water and waste organisations, in order topresent a deeper understanding of the current situation in Sweden. Furthermore, anartificial neural network has been developed, and trained with data from Täby municipality,with the purpose of predicting which pipes in a sewer network that need to be renewed. The results show that there is a great need for improvement in the strategic renewalplanning. The greatest need, and potential, is found in the collection and processing ofdata, where artificial neural networks can be applied as a highly efficient and intelligenttool, which is proven by the high accuracy (93 %) and strong ability to predict pipes withrenewal needs (ca 10-20 pipes for Täby municipality) that the neural network developedfor this degree project showed. It is, however, important to emphasize that the quality ofthe obtained data from Täby was relatively low, and that the results therefore has to beviewed with some skepticism. It is nevertheless reasonable to assume that artificial intelligence, and more specifically,artificial neural networks, will play an important role in tackling future challenges related tostrategic asset management and renewal planning for underground sewer infrastructure.The main solution lies in the ability to efficiently and intelligently collect, structure, andprocess data, and this is a field where artificial neural networks, as made evident by thisdegree project, certainly have abilities to flourish and contribute to savings in bothfinancial, temporal and human resources.

We have come a long way in the pursuit of reducing our carbon footprint from our way of living, bycontinuously development of batteries and charging infrastructure for electric vehicles to decrease thedemand for fossil fuels, improving the overall energy efficiency and to increase awareness of the problemto the population. One of the industries, that during the last decades has undergone vast improvements,is the development of the airplane engines due to increased emission regulations, for the aviationindustry, and to reduce the costs of air travel. Despite tighter regulations, global impact from travellingby air is increasing due to the explosive increase in number of travels and travellers. In order to copewith the situation, it is of course necessary to further develop fuel and emission effective airplanes, butalso to study the whole chain of emission sources correlated to the air transport industry. So, whilewaiting for improved airplanes there are well known emission effective technologies that can beimplemented already today – implement electric vehicles as support vehicles at airports.Today, and throughout history, most of the focus of air travel has been on the airplane itself. This thesis,that was carried out at KTH Royal Institute of Technology during late spring and autumn 2018, didinstead study the support vehicles used in airports. In this thesis, a generic economic model wasdeveloped in order to estimate the costs involved when replacing traditionally vehicles to suggestedelectrically propelled alternatives. To test and support the development of an economic model, a casestudy has been carried out at Stockholm Arlanda Airport. This case study included a field study to thementioned airport, and in combination with interviews with former employees from one of the groundhandling companies that are currently active in the airport. Raw data was collected over the equipmentand vehicles currently in use. This data was used to describe the vehicles purpose, requirements and toensure that the alternative electric vehicles proposed would offer at least the same performance as thetraditional vehicles. The developed generic economic model was modulated with five stages thatrepresented a selection of input parameters. The collected data became a result in itself and was used asinput to three concurrent theses.The results from the five stages presents the costs during an investment period of between of one tofifteen years. One of the most significant result could be seen from Stage V. This stage showed that thecombined cost to replace all vehicles currently used, with either all new diesel vehicles or electricalternative vehicles, are lower for electric vehicles than for diesel vehicles. Another significant resultcould be seen from the investigation of Stage IV, Stage IV-B, were the model was modulated to representthe case of replacing a vehicle. The results showed that the Letter and Cargo procedures, that travel thefarthest and has the highest fuel consumption of the investigated vehicles, had negative costs throughthe whole investment period. This means that the expenses will always be lower when these vehicles arereplaced. The model was validated through a sensitivity analysis, performed on the discount rates,depreciation rates and as well as costs for battery replacement during the depreciation period. / Vi har kommit långt i vår strävan att minska vårt koldioxidavtryck genom vårat sätt att leva, genom attkontinuerligt utveckla batterier och laddningsinfrastruktur för elfordon med syftet att minskaefterfrågan på fossila bränslen, förbättra den totala energieffektiviteten och öka befolkningensmedvetenhet om problemet. En av de branscher, som under de senaste decennierna har genomgått storaförbättringar, är utvecklingen av flygplansmotorer och regler för flygplan. Men eftersom antaletflygresenärer fortsätter att öka årligen krävs ytterligare arbete för att förbättra den totala effektivitetenoch minska det negativa globala avtrycket från flygresor. Medan väntan på att morgondagens flygplanska utvecklas så finns det teknik som redan kan appliceras idag – elfordon.I dag, och genom historien, har det mesta av all fokus för flygresor varit på flygplanen själva. Dettaexamensarbete, som genomfördes på KTH, Kungliga Tekniska Högskolan, under den senare delen avvåren och hösten 2018, utredde istället de fordon som omger ett flygplan, under den tid flygplanet stårstilla på en flygplats. Under denna uppsats utvecklades en generisk ekonomiskmodell, med syftet attestimera kostnaderna att ersätta och använda elfordon istället för de nuvarande fordonen. För attutveckla den ekonomiska modellen genomfördes en fallstudie på Stockholm Arlanda Airport.Fallstudien innehöll en fältundersökning till den nämnda flygplatsen, och i kombination med intervjuermed tidigare anställda från ett av de marktjänstföretag som är verksamma på flygplatsen, insamladesrådata om vilken utrustning och fordon som vid tillfället användes. Denna data användes för att beskrivafordonens syfte, vilka krav som ställs på fordonen. Detta var för att säkerställa att det valda elfordonetkunde utföra uppgiften. Den utvecklade generiska ekonomiska modellen modulerades med fem steg,som representerade vilka indataparametrar som bör väljas. De insamlade uppgifterna blev ett resultat isig och användes som indata till tre samtidiga avhandlingar.Den generiska modellen resultat presenterade kostnaderna från de fem stegen under en varierandeinvesteringsperiod på ett till femton år. Ett av de viktigaste resultaten var från Steg V, som visade attden sammanlagda kostnaden för att ersätta alla de fordon som för närvarande används, med antingenalla nya dieselfordon eller elektriska alternativa fordon, är lägre för elfordon än för dieselfordon. Detandra betydande resultatet kommer från undersökningen av Steg IV, Steg IV-B. I Steg IV-B moduleradesmodellen i syfte att representera scenariot då ett fordon ska ersättas, där Letter och Cargo procedurernavar de som färdades längst och även har den högsta bränsleförbrukningen utav de undersökta fordonen,hade en negativ kostnad under hela investeringslängden. Detta betyder att kostnaderna alltid är lägre,om fordonet ersätts. Modellen har validerats med hjälp utav en känslighetsanalys som utfördes pådiskonteringsräntan, avskrivningssatsen och kostnader för ersättningsbatterier.

Thesis (MBA.) -- University of Limpopo, 2015 / The Department of Economic Development, Environment and Tourism is mandated to focus on growing the provincial economy, empowering women and youth, on supporting small businesses and co-operatives and improving the lives of the people of the province for the better as indicated in the Limpopo Economic Development, Environment and Tourism Province Budget Vote (2015/16). Economic growth and social wellbeing are closely tied to the ability to protect the natural environment. Mining, electricity generation and agriculture are among the economic activities that have a direct impact on the environment and need to be carried out in a sustainable and responsible manner. Towards this vision, the assets which are furniture, transport, computer hardware and other machinery and equipment need to be managed efficiently and effectively in order to fulfil the needs of society and the departments. These assets represent an enormous value for the owner which is LEDET and for society at large. To grasp the full potential of these assets, a deep and thorough understanding of an asset’s complete lifetime is needed. However, the assets especially physical assets, public buildings and infrastructures are not managed properly and that results in numerous challenges and audit queries that are raised by the Auditor General. The purpose of this study was to investigate the challenges that are facing the asset management unit of Limpopo Department of Economic Development & Tourism (LEDET). Asset Management has been hailed as important in order to enable government to deliver proper services to the citizens of the country. This has encouraged the researcher to undertake the study in order to add more knowledge on the asset management process of the government, looking at the challenges and possible solutions. The need for this study was considered relevant and necessary as government departments and other private sectors face numerous challenges in implementing the asset management. Limpopo Department of Economic Development, Environment and Tourism, as a case study, faces challenges in fulfilling some of its mandate due to lack of support from asset management activities. In terms of its strategic plan, the department seeks to address issues relating to economic growth, the promotion and development of tourism and using environmental management to guide and monitor sustainable development in the province. These challenges have negative implications on the delivery of services to the communities it serves. In this study, the researcher investigated the following: demographic profile of respondents, challenges facing asset management, the impact of asset management on service delivery and lastly the best practice on the implementation of asset management. Data were analysed into themes and revealed communication, training, interpretation of relevant prescripts, limited resources, proper allocation of resources and effective participation of relevant stakeholders as, amongst others, challenges to the process. The study concluded by providing recommendations to management of the Limpopo Department of Economic Development, Environment and Tourism on how to improve the asset management activities to achieve the strategic goals of the department. The recommendations proposed are improved communications with stakeholders, development of asset plan, skills capacity of asset management officials and sourcing the asset information system that integrates with the financial system to provide a reliable asset register. / LEDET (Limpopo Department of Economic Development & Tourism)