Discrepancies in solar irradiation data for Stockholm and Athens

The aim of this study is to evaluate the variation of solar radiation data between different data sources that will be free and available at the Solar Energy Research Center (SERC). The comparison between data sources will be carried out for two locations: Stockholm, Sweden and Athens, Greece. For the desired locations, data is gathered for different tilt angles: 0°, 30°, 45°, 60° facing south. The full dataset is available in two excel files: “Stockholm annual irradiation” and “Athens annual irradiation”. The World Radiation Data Center (WRDC) is defined as a reference for the comparison with other dtaasets, because it has the highest time span recorded for Stockholm (1964–2010) and Athens (1964–1986), in form of average monthly irradiation, expressed in kWh/m2. The indicator defined for the data comparison is the estimated standard deviation. The mean biased error (MBE) and the root mean square error (RMSE) were also used as statistical indicators for the horizontal solar irradiation data. The variation in solar irradiation data is categorized in two categories: natural or inter-annual variability, due to different data sources and lastly due to different calculation models. The inter-annual variation for Stockholm is 140.4kWh/m2 or 14.4% and 124.3kWh/m2 or 8.0% for Athens. The estimated deviation for horizontal solar irradiation is 3.7% for Stockholm and 4.4% Athens. This estimated deviation is respectively equal to 4.5% and 3.6% for Stockholm and Athens at 30° tilt, 5.2% and 4.5% at 45° tilt, 5.9% and 7.0% at 60°. NASA’s SSE, SAM and RETScreen (respectively Satel-light) exhibited the highest deviation from WRDC’s data for Stockholm (respectively Athens). The essential source for variation is notably the difference in horizontal solar irradiation. The variation increases by 1-2% per degree of tilt, using different calculation models, as used in PVSYST and Meteonorm. The location and altitude of the data source did not directly influence the variation with the WRDC data. Further examination is suggested in order to improve the methodology of selecting the location; Examining the functional dependence of ground reflected radiation with ambient temperature; variation of ambient temperature and its impact on different solar energy systems; Im pact of variation in solar irradiation and ambient temperature on system output.

Kravsammanställning samt utvärdering avbildvisningsprogramför diagnostik inom telepatologi : En fallstudiemed SIV-metoden som tillvägagångssätt

De flesta har i sin närhet någon som drabbats av cancer och sjukdomsfallen har ökat genom åren. Den yrkesgrupp som ställer diagnos av denna sjukdom är patologer. Bristen på patologer är idagsläget stor och det finns därför ett behov av att finna effektiva lösningar för att möta denna brist och en ökande mängd patienter. För att digitalisera vävnadsproven som diagnostiseras, scannas dessa in med en glasscanner. Dessa digitala bildfiler kan sedan visas i ett bildvisningsprogram och delas digitalt mellan patologer på distans. Detta begrepp kallas för telepatologi. Studien utgår utifrån följande frågeställningar: Vilka krav är väsentliga och bör ingå i en utvärdering för bildvisningsprogram avsedda för diagnostik inom telepatologi? Vilket bildvisningsprogram är mest lämpat att implementeras i ett webbaserat system baserat på dessa väsentliga krav? Syftet med studien är att undersöka vilka krav som är väsentliga och bör ingå i en utvärdering av bildvisningsprogram avsedda för diagnostik inom telepatologi, samt att utföra en utvärdering av ett urval bildvisningsprogramvaror med hjälp av dessa krav. En fallstudie genomfördes med datainsamlingsmetoderna: intervjuer med två personer från studiens samarbetspartner CGM, Frågeformulär där Sveriges patologer var respondenter samt dokumentstudier för att samla in information gällande bildvisningsprogrammen. Studien tillämpar utvalda delar ur Anders G. Nilssons SIV-metod som tillvägagångsätt för att samla in krav samt för att göra ett urval av bildvisningsprogram som sedan utvärderas gentemot dessa krav. Resultaten av datainsamlingarna analyserades och ledde till ett kravdokument med väsentliga krav.Tre så kallade utslagsgivande faktorer bland dessa krav var att bildvisningsprogrammet måste vara webbaserat utan installation på klient, funktioner för in- och ut-zoomning samt panorering måste finnas. Utvärderingen av utvalda bildvisningsprogram visade slutligen att OpenSlide var mest lämpad att implementeras i ett webbaserat system.

Automating condition monitoring of vegetation on railway trackbeds and embankments

Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.