The purpose of this master thesis is to develop a model to estimate the carbon intensity, i.e the carbon emission relative to economic activity, of publicly traded companies which do not report their carbon emissions. By using statistical and machine learning models, the core of this thesis is to develop and compare different methods and models with regard to accuracy, robustness, and explanatory value when estimating carbon intensity. Both discrete variables, such as the region and sector the company is operating in, and continuous variables, such as revenue and capital expenditures, are used in the estimation. Six methods were compared, two statistically derived and four machine learning methods. The thesis consists of three parts: data preparation, model implementation, and model comparison. The comparison indicates that boosted decision tree is both the most accurate and robust model. Lastly, the strengths and weaknesses of the methodology is discussed, as well as the suitability and legitimacy of the boosted decision tree when estimating carbon intensity. / Syftet med denna masteruppsats är att utveckla en modell som uppskattar koldioxidsintensiteten, det vill säga koldioxidutsläppen i förhållande till ekonomisk aktivitet, hos publika bolag som inte rapporterar sina koldioxidutsläpp. Med hjälp av statistiska och maskininlärningsmodeller kommer stommen i uppsatsen vara att utveckla och jämföra olika metoder och modeller utifrån träffsäkerhet, robusthet och förklaringsvärde vid uppskattning av koldioxidintensitet. Både diskreta och kontinuerliga variabler används vid uppskattningen, till exempel region och sektor som företaget är verksam i, samt omsättning och kapitalinvesteringar. Sex stycken metoder jämfördes, två statistiskt härledda och fyra maskininlärningsmetoder. Arbetet består av tre delar; förberedelse av data, modellutveckling och modelljämförelse, där jämförelsen indikerar att boosted decision tree är den modell som är både mest träffsäker och robust. Slutligen diskuteras styrkor och svagheter med metodiken, samt lämpligheten och tillförlitligheten med att använda ett boosted decision tree för att uppskatta koldioxidintensitet.

Water quality monitoring (WQM) is crucial for managing and protecting riverine ecosystems. There has been a plethora of methods to select the monitoring sites, water quality parameters (WQPs), and monitoring frequencies; however, no standard method or strategy has been accepted for the river systems. Water managers have faced difficulties in adopting appropriate WQM network design methods to their local boundary conditions, monitoring objectives, monitoring costs, and legal regulations. With the elevated cost and time consumption of monitoring, approaches to evaluate and redesign the monitoring networks based on monitoring goal achievements are crucial for water managers. Hence, the overall aim of this thesis is to develop and employ a reliable yet straightforward approach to optimise and quantify the effectiveness of the WQM network in rivers. The objectives are to (i) identify the commonly used methods and the boundary conditions to apply these methods in assessing and designing of WQM networks in rivers; (ii) optimise river WQM network design based on compliance criteria; (iii) optimise river WQM network design based on the trade-offs between information provided by the monitoring network versus the monitoring expenses. A systematic review of the commonly used design methods and their resulting monitoring setups in Chapter 2 shows that multivariate statistical analysis (MVA) is a promising tool to contract the number of monitoring sites and water quality parameters. Most of the reported studies often overlook small streams and trace pollutants such as heavy metals and organic microcontaminants in the analysis. Data availability and expertise’s judgments seem to affect the selection of design methods rather than river size and the extent of the monitoring networks. The commonly found statistical methods are applied to the case study of the Freiberger Mulde (FM) river basin in eastern Germany to optimise its current monitoring network. Chapter 3 dedicates to redesign the monitoring network for compliance monitoring purposes. In Chapter 3, 82 non-biological parameters are initially screened and analysed for their violations to the environmental quality standards. The subsequent result suggests that polycyclic aromatic hydrocarbons, heavy metals, and phosphorus have been the abundant stressors that caused more than 50% of the streams in the FM river basin failing to achieve good status. The proposed approach using hierarchical cluster analysis and weighted violation factor from 22 relevant WQPs allows a reduction of 42 monitoring sites from the current 158 sites. The Mann-Kendall trend test recommends an increase in monitoring frequency of the priority substances by 12 times per annual, and a decrease in the number of sampling events for metals and general physicochemical parameters by quarterly. Overall, the results suggest that the authorities of the Saxony region should develop proper management measures targeting heavy metals and organic micropollutants to be able to achieve good WQ status by 2027 at the latest. In Chapter 4, regularly monitoring parameters with less than 15% of censored data are analysed. A combination of principal component analysis and Pearson’s correlation analysis allows the identification of 14 critical parameters that are responsible for explaining 75.1% of data variability in the FM river basin. Weathering processes, historical mining, wastewater discharges, and seasonality have been the leading causes of water quality variability. Both sampling locations and periods are observed, with the resulting mineral contents vary between locations, and the organic and oxygen content differs depending on the time period that was monitored. The monitoring costs are estimated for one monitoring event and based on laboratory, transportation, and sampling costs. The results show that under the current monitoring-intense conditions, preserving monitoring variables rather than sites seems to be more economical than the opposite practice. The current study provides and employs two statistical approaches to optimise the WQM network for the FM river basin in eastern Germany. The proposed methods can be of interests to other river basins where the historical data are available, and the monitoring costs become a constraint. The presented research also raises some concerns for future research regarding the applications of statistical methods to optimise WQM networks, which are presented in Chapter 5.

Finding economical and environmentally friendly processes to recover heavy metals (HMs) from spent batteries is a research priority to move toward sustainability. Adsorption seems an acceptable procedure to replace the current separation/purification stage of hydrometallurgical techniques. Chitosan is an efficient adsorbent for HM uptake from aqueous solutions. Nevertheless, in practice, chitosan modification is unavoidable to improve its physicochemical properties. Sodium tripolyphosphate is an environmentally benign crosslinker that can be used for chitosan modification. In addition, ion-imprinting technique could potentially enhance the adsorption efficiency and selectivity of crosslinked chitosan. Considering the above, the primary purposes of this research were: investigating the adsorption efficiency of chitosan for heavy metals uptake from synthetic solutions; modifying chitosan by crosslinking alone and combined with ion-imprinting techniques to improve the physicochemical properties as well as adsorption capacity and selectivity of chitosan; evaluating and comparing the adsorption efficiency of modified chitosan beads for the adsorption of Cd(II), Ni(II) and Co(II) in single and multicomponent batch adsorption systems. Chitosan and sodium tripolyphosphate crosslinked chitosan beads were prepared to remove Cd(II) from aqueous solution in the first phase. FTIR and XRD of the synthesized beads showed partial consumption of chitosan amine groups and a decrease in crystallinity of chitosan structure over crosslinking reaction. The isotherm and thermodynamic studies showed that Langmuir isotherm was the best fit to the experimental data of Cd(II) adsorption on crosslinked chitosan and all the adsorption reactions were endothermic and spontaneous. A reduced quadratic model, constructed by the Response Surface Methodology (RSM), indicated that the Cd(II) adsorption uptake of 99.87 (mg/g) was achieved at 55 °C and 2.92 % (w/v) crosslinking degree. Then, chitosan and crosslinked chitosan beads by sodium tripolyphosphate were used for Ni(II) adsorption from aqueous media in the second phase. The BET characterization showed that increasing the crosslinking degree reduced the chitosan beads' surface area and their total pore volume. The Langmuir model described the experimental results best and showed that the maximum adsorption capacity of chitosan (80.00 mg/g) decreased after crosslinking (52.36 mg/g). In addition, a reduced quadratic model with a correlation coefficient of 0.96 was established to correlate the adsorption uptake of Ni(II) with pH and crosslinking degree. In the third phase, the adsorption of Ni(II) and Cd(II) ions from single and binary metal ions solutions onto chitosan and crosslinked chitosan beads was studied. The extended Freundlich model fitted the adsorption equilibrium data in the binary system, implying the existence of preference in the order of Ni(II) > Cd(II). Desorption studies with a mixture of NaCl and H2SO4 were also conducted during this phase, demonstrating a desorption efficiency of greater than 85 %. In the fourth phase, the removal of cadmium from aqueous solution was examined using a novel Cd(II)-imprinted crosslinked chitosan. SEM, FTIR, TGA, and BET characterizations revealed that the ion-imprinted chitosan beads had better physicochemical properties than chitosan beads and superior potential adsorption properties than non-imprinted crosslinked chitosan beads. The isotherm and thermodynamic studies revealed that the Langmuir isotherm fitted the Cd(II) experimental data the best, and the adsorption reactions were spontaneous and endothermic. The kinetics data were also best fitted by the pseudo-second-order equation. Finally, the ion-imprinted crosslinked chitosan beads were employed for the selective adsorption of Cd(II) in a competitive adsorption system of Cd(II)-Ni(II)-Co(II) in phase five. The characterization of the prepared adsorbents was performed using XRD and BET, showing a higher surface area of ion-imprinted crosslinked chitosan than non-imprinted crosslinked chitosan beads. The Extended Langmuir model fitted the experimental results obtained from the multi-component system, indicating that ion-imprinted crosslinked chitosan had a higher total metal uptake with better selectivity toward Cd(II) uptake compared to non-imprinted crosslinked chitosan. Studying the adsorption mechanism in a ternary system showed that the adsorption was governed by chemical binding and ion exchange mechanisms in the ternary system. In conclusion, crosslinking by sodium tripolyphosphate improved chitosan physiochemical properties; however, it resulted in a decrease in HM adsorption uptake. The RSM was used to assess the effect of pH, temperature, and crosslinking degree and optimize the adsorption uptake of chitosan. Also, ion-imprinting was effective in enhancing the adsorption capacity and selectivity of crosslinked chitosan for the ion used as a template (Cd(II)) in preparing ion-imprinted crosslinked chitosan.

Texas has a rich tradition of Early Music ensembles that dates back to 1969. However, there is little reliable information based on statistical data collection and analysis concerning Texas Early Music consumers. Little is known about why they attend Early Music performances or other important factors that affect the Early Music industry. Through the use of an extensive survey and accompanying statistical analysis, this study answers many questions regarding Early Music consumers in the State of Texas. This study collected demographic and psychographic data in January 2020 about the Early Music concert-going public in three major Texas cities - Dallas, Austin, and Houston. Other factors were identified in two primary areas: audience characteristics and ticket pricing practices.

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Laser speckle contrast imaging (LSCI) and its extension, multi-exposure laser speckle contrast imaging (MELSCI) are non-invasive techniques to monitor peripheral blood perfusion. One of the main drawbacks of LSCI and MELSCI in clinical use is that the techniques are sensitive to tissue movement. Moreover, the image background contributes to unnecessary data. The aim of this project was to develop and evaluate different methods to detect local motion artifacts and image backgrounds in LSCI and MELSCI. In this project, three different methods were developed: one using statistical analysis and two using machine learning. The method based on classical statistics was developed in MATLAB with a dataset made up of 1797 frames of 256 x 320 images taken from a recording of a hand where the thumb and middle finger were taking turns making small movements while the middle finger was the subject of three different states made by an occlusion cuff (baseline, occlusion, and reperfusion). The main filter that was used in the first method was the Hampel filter. Furthermore, networks for the machine learning method were developed in Python using the same dataset but with 20,000 small patches extracted from the dataset of sizes 3 x 3 to 21 x 21 pixels. The first machine learning method was based on two-dimensional data patches, hence no time dimension was included, while the second machine learning method used three-dimensional data patches where the time dimension was included (from 1s to 10s). The generation of ground truth for the dataset was manually created frame by frame in a ground truth generation graphical user interface (GUI) in MATLAB. To assess the three methods, the Dice coefficient was used. The statistical method resulted in a Dice coefficient of 0.7557. The highest Dice coefficient for the machine learning method with a 2D dataset was 0.2902 (patch size 13 x 13) and the lowest was 0.2372 (patch size 7 x 7). For the machine learning method with 3D datasets, the patch size of 21 x 21 x 4 resulted in the highest Dice coefficient (0.5173), and the 21 x 21 x 40 model had the lowest Dice coefficient (0.1782). Since the two methods based on temporal data proved to be performing best in this project, one conclusion for further development of an improved model is the usage of temporal data in the training of a model. However, one important difference between the statistical method and the three-dimensional machine learning method is that the statistical method does not handle fast perfusion changes as well as the machine learning method and can not detect image background and static tissue. Therefore, the overall most useful method to further develop is the three-dimensional machine learning method.

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Nationella och internationella kunskapsmätningar i matematik visar likartade resultat för flickor och pojkar. Trots det visar statistiken att flickor erhåller systematiskt högre slutbetyg. Denna studie undersöker huruvida betyg tjänar som likvärdigt mått på kunskap hos flickor och pojkar i gymnasiets matematikämne. Detta görs dels utifrån en kvantitativ ansats och dels utifrån en enkätstudie. Med utgångspunkt i nationell registerdata (SCB) för slutbetyg och resultat på nationella provet undersöks, medelst fyra olika analysmetoder, könsskillnader med avseende på kurs, skolform och län. Studien visar att flickor generellt erhåller högre slutbetyg än pojkar i relation till resultatet på nationella provet, vilket bekräftar tidigare forskning. Vidare påvisar analysen särskilt stora diskrepanser på betygsnivå C och högre; i matematikkurser på yrkesförberedande program; i senare kurser inom samtliga program; i Västernorrlands, Västmanlands, Gotlands och Kalmar län; liksom i fristående skolor. Korrelationsanalys tydliggör hur nationella provet utgör en mindre del av betygsunderlaget för flickor jämfört med pojkar. Dessutom avslöjar analysen ett omvänt samband mellan könsbetingad relativ prestation på nationella provet och avvikelse i slutbetyget. Enkätstudien undersöker bedömningspraktiken hos matematiklärare. Filtrering på lärarens kön, ålder, program och skolform, har tillämpats. Resultatet tyder på systematiska skillnader i bedömningspraktik mellan olika lärarkategorier, vilket innebär att betygssättningen kan brista i likvärdighet. Skillnader har påvisats mellan, i första hand, lärare på yrkesprogram och naturvetenskapliga program, såväl som mellan lärare i kommunala och fristående skolor. Också lärarens kön och ålder tycks ha viss betydelse. Studien avslutas med en diskussion kring möjliga lösningar. / National and international assessments in mathematics show similar results for girls and boys. Despite this, statistics show that girls receive systematically higher final grades. This study examines whether grades serve as an equivalent measure of knowledge of girls and boys in high school mathematics. This is done partly on the basis of a quantitative approach and partly on the basis of a survey. Based on national register data (Statistics Sweden) for final grades and results of national tests, using four different methods of analysis, gender differences with respect to course, school form and county, are examined. The study shows that girls generally get a higher final grade than boys in relation to their results on the national test, confirming previous research. Furthermore, the analysis shows particularly large discrepancies at grade C and higher; in mathematics courses on vocational programs; in later courses within all programs; in V¨asternorrland, V¨astmanland, Gotland and Kalmar County; as well as in independent schools. Correlation analysis clarifies how the national test constitutes a smaller part of the assessment basis for girls compared to boys. The analysis also reveals an inverse relationship between gender dependent relative performance on the national test and the final grade deviation. The survey examines the assessment practice among mathematics teachers. Filtering on the teacher’s gender, age, program and school form has been applied. The result suggests systematic differences in assessment practice between different teacher categories, implying that grades can break in equality. Differences have been shown between, primarily, teachers in vocational programs and science programs, as well as between teachers in municipal and independent schools. Also the teacher’s gender and age seems to be of some importance. The study concludes with a discussion about possible solutions.

This study attempts to analyze the impact of an online educational resource on academic performances among newly arrived immigrant students in Sweden between the grade six to nine in the Swedish school system. The study focuses on the web based educational resource called Studi.se made by Komplementskolan AB.The aim of the study was to investigate the relationship between academic performance and using Studi.se. Another purpose was to see what other factors that can impact academic performances.The study made use of the data mining process, Cross Industry Standard for Data Mining (CRISP-DM), to understand and prepare the data and then create a regression model that is evaluated. The regression model tries predict the dependent variable of grade based on the independent variables of Studi.se activity, gender and years in Swedish schools. The used data set includes the grades in mathematics, physics, chemistry, biology and religion of newly arrived students in Sweden from six municipalities that have access to Studi.se. The data used also includes metrics of the student’s activity on Studi.se.The results show negative correlation between grade and gender of the student across all subjects. In this report, the negative correlation means that female students perform better than male students. Furthermore, there was a positive correlation between number of years a student has been in the same school and their academic grade. The study could not conclude a statistically significant relationship between the activity on Studi.se and the students’ academic grade.Additional explanatory independent variables are needed to make a predictive model as well as investigating alternative regression models other than multiple linear regression. In the sample, a majority of the students have little or no activity on Studi.se despite having free access to the resource through the municipality. / Denna studie analyserar inverkan som digitala läromedel har på skolbetyg bland nyanlända elever i Sverige mellan årskurs sex och nio i det svenska skolsystemet. Studien fokuserar på den webbaserade pedagogisk resursen Studi.se, gjord av Komplementskolan AB.Målet med studien var att undersöka relationen mellan skolresultat och användandet av Studi.se. Ett annat syfte var att undersöka vad för andra faktorer som kan påverka skolresultat.Studien använder sig av datautvinningsprocessen, Cross Industry Standard for Datamining (CRISP-DM), för att förstå, förbereda och analysera datan i form av en regressionsmodell som sedan evalueras. Datasamlingen som används innehåller bland annat skolbetyg i ämnena matematik, fysik, kemi, biologi och religion från sex kommuner som har tillgång till Studi.se. Aktivitet hos eleverna från dessa kommuner på Studi.se hemsidan användes också för studien.Resultaten visar en negativ korrelation mellan betyg och kön hos eleverna i alla ämnena. Den negativa korrelationen betyder i denna rapport att tjejer får bättre betyg i genomsnitt än killar hos urvalet av nyanlända från de sex kommunerna. Dessutom fanns det en positiv korrelation mellan antal år en elev varit i skolan alternativt i svenska skolsystemet och deras betyg. Studien kunde inte säkerställa ett statistisk signifikant resultat mellan aktivitet på Studi.se och elevernas skolresultat.Ett flertal förklarande oberoende variabler behövs för att kunna skapa en prognastisk modell för skolresultat samt bör en undersökning på alternativa regressions modeller förutom linjär multipel regression göras. I studiens urval av nyanlända elever från kommunerna, har majoriteten inte använt eller knappt använt Studi.se även om dessa kommuner haft tillgång till denna resurs.