Choosing the optimal energy system for buildings and districts

The purpose of this master’s thesis was to develop a method to be used in the selection of an optimal energy system for buildings and districts. The term optimal energy system was defined as the energy system which best fulfils the requirements of the stakeholder on whose preferences the energy systems are evaluated. The most influential stakeholder in the process of selecting an energy system was considered to be the district developer. The selection method consisted of several steps: Definition of the district, calculating the energy consumption of the district and buildings within the district, defining suitable energy system alternatives for the district, definition of the comparing criteria, calculating the parameters of the comparing criteria for each energy system alternative and finally using a multi-criteria decision method to rank the alternatives. For the purposes of the selection method, the factors affecting the energy consumption of buildings and districts and technologies enabling the use of renewable energy were reviewed. The key element of the selection method was a multi-criteria decision making method, PROMETHEE II. In order to compare the energy system alternatives with the developed method, the comparing criteria were defined in the study. The criteria included costs, environmental impacts and technological and technical characteristics of the energy systems. Each criterion was given an importance, based on a questionnaire which was sent for the steering groups of two district development projects. The selection method was applied in two case study analyses. The results indicate that the selection method provides a viable and easy way to provide the decision makers alternatives and recommendations regarding the selection of an energy system. Since the comparison is carried out by changing the alternatives into numeric form, the presented selection method was found to exclude any unjustified preferences over certain energy systems alternatives which would affect the selection.

Hankintaprosessin optimaalinen toteutus: Case Medi-IT Oy

Tutkielman tavoitteena on löytää hankintaprosessin optimaalinen toteutustapa tutkimuksen kohdeyritykselle. Tutkielmassa kuvataan kohdeyrityksen hankintaprosessin kulku nykyisellään ja annetaan kehitysehdotuksia. Tutkielmassa pohditaan sitä, mitä osia kohdeyrityksen tulisi hankintaprosessissa suorittaa itse, ja mitä osia puolestaan tulisi ulkoistaa palveluntarjoajille. Tutkielmassa tutkitaan myös ICT-hankintoihin liittyviä erityispiirteitä ja haasteita. Lisäksi tutkielmassa käydään läpi toimittajien vertailussa käytettäviä kriteerejä. Myös hankintalain vaikutusta kohdeyrityksen toimintaan tarkastellaan lyhyesti. Tutkimuksen teoreettinen viitekehys koostuu neljästä teoria-alueesta, jotka ovat: ulkoistaminen, toimittajien luokittelu, toimittajien arviointi ja julkiset hankinnat. Teorian ja empirian välisen vuoropuhelun avulla esitetään ehdotus hankintaprosessin optimaaliseksi toteutustavaksi. Muutoksia ehdotetaan erityisesti toimijoiden väliseen roolijakoon hankintaprosessissa. Työ on luonteeltaan kvalitatiivinen tapaustutkimus. Teoriaosio perustuu kirjallisuuskatsaukseen ja empiriaosio perustuu lähinnä haastatteluihin.

Motivational Influences on Transfer: Dimensions and Boundary Conditions

The focus of this dissertation is the motivational influences on transfer in higher education and professional training contexts. To estimate these motivational influences, the dissertation includes seven individual studies that are structured in two parts. Part I, Dimensions, aims at identifying the dimensionality of motivation to transfer and its structural relations with training-related antecedents and outcomes. Part II, Boundary Conditions, aims at testing the predictive validity of motivation theories used in contemporary training research under different study conditions. Data in this dissertation was gathered from multi-item questionnaires, which were analyzed differently in Part I and Part II. Studies in Part I employed exploratory and confirmatory factor analysis, structural equation modeling, partial least squares (PLS) path modeling, and mediation analysis. Studies in Part II used artifact distribution meta-analysis, (nested) subgroup analysis, and weighted least squares (WLS) multiple regression. Results demonstrate that motivation to transfer can be conceptualized as a three-dimensional construct, including autonomous motivation to transfer, controlled motivation to transfer, and intention to transfer, given a theoretical framework informed by expectancy theory, self-determination theory, and the theory of planned behavior. Results also demonstrate that a range of boundary conditions moderates motivational influences on transfer. To test the predictive validity of expectancy theory, social cognitive theory, and the theory of goal orientations under different study settings, a total of 17 boundary conditions were meta-analyzed, including age; assessment criterion; assessment source; attendance policy; collaboration among trainees; computer support; instruction; instrument used to measure motivation; level of education; publication type; social training context; SS/SMC bias; study setting; survey modality; type of knowledge being trained; use of a control group; and work context. Together, the findings cumulated in this thesis support the basic premise that motivation is centrally important for transfer, but that motivational influences need to be understood from a more differentiated perspective than commonly found in the literature, in order to account for several dimensions and boundary conditions. The results of this dissertation across the seven individual studies are reflected in terms of their implications for theory development and their significance for training evaluation and the design of training environments. Limitations and directions to take in future research are discussed.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

CLASSIFICATION OF FOREST ROADS AND DETERMINATION OF ROUTE USING GEOGRAPHIC INFORMATION SYSTEM

ABSTRACT Geographic Information System (GIS) is an indispensable software tool in forest planning. In forestry transportation, GIS can manage the data on the road network and solve some problems in transportation, such as route planning. Therefore, the aim of this study was to determine the pattern of the road network and define transport routes using GIS technology. The present research was conducted in a forestry company in the state of Minas Gerais, Brazil. The criteria used to classify the pattern of forest roads were horizontal and vertical geometry, and pavement type. In order to determine transport routes, a data Analysis Model Network was created in ArcGIS using an Extension Network Analyst, allowing finding a route shorter in distance and faster. The results showed a predominance of horizontal geometry classes average (3) and bad (4), indicating presence of winding roads. In the case of vertical geometry criterion, the class of highly mountainous relief (4) possessed the greatest extent of roads. Regarding the type of pavement, the occurrence of secondary coating was higher (75%), followed by primary coating (20%) and asphalt pavement (5%). The best route was the one that allowed the transport vehicle travel in a higher specific speed as a function of road pattern found in the study.

Rovakaira Oy:n keskijänniteverkon kehittämissuunnitelma toimitusvarmuuskriteeristön näkökulmasta

Diplomityössä tavoitteena on etsiä teknistaloudellisimmat ratkaisut sekä tutkia niiden vaikutuksia sähkönjakeluverkoston käyttövarmuuteen ja luotettavuuteen toimitusvarmuuskriteeristön näkökulmasta. Lisäksi työssä esitetään uusi tunnusluku kriteeristön ylityksestä aiheutuvan haitan arvostukseen. Merkittävä osa Rovakaira Oy:n keskijänniteverkosta joudutaan uusimaan lähivuosikymmeninä teknistaloudellisen pitoajan täyttyessä. Verkon uusiminen antaa mahdollisuuden toteuttaa verkkoa nykyisiin vaatimuksiin paremmin sopivilla ratkaisuilla. Kehitysvaihtoehtoina vertaillaan johdon tien varteen siirtoa, maastokatkaisijoiden lisäämistä, pienitehoisten ja päättyvien haarajohtojen korvaamista 1 kV tekniikalla sekä pienoissähköaseman kannattavuutta. Työssä tarkastellaan yksityiskohtaisemmin Sodankylän käyttövarmuuden parantamista sähköasemavian aikana ja alueen kuormituksenkasvuun varautumista.

Soybean yield maps using regular and optimized sample with different configurations by simulated annealing

ABSTRACT This study aimed to compare thematic maps of soybean yield for different sampling grids, using geostatistical methods (semivariance function and kriging). The analysis was performed with soybean yield data in t ha-1 in a commercial area with regular grids with distances between points of 25x25 m, 50x50 m, 75x75 m, 100x100 m, with 549, 188, 66 and 44 sampling points respectively; and data obtained by yield monitors. Optimized sampling schemes were also generated with the algorithm called Simulated Annealing, using maximization of the overall accuracy measure as a criterion for optimization. The results showed that sample size and sample density influenced the description of the spatial distribution of soybean yield. When the sample size was increased, there was an increased efficiency of thematic maps used to describe the spatial variability of soybean yield (higher values of accuracy indices and lower values for the sum of squared estimation error). In addition, more accurate maps were obtained, especially considering the optimized sample configurations with 188 and 549 sample points.

Performance Comparison of Behavioral Finance -based Investment Strategies in the Finnish Stock Market 1996-2010

In this thesis traditional investment strategies (value and growth) are compared to modern investment strategies (momentum, contrarian and GARP) in terms of risk, performance and cumulative returns. Strategies are compared during time period reaching from 1996 to 2010 in the Finnish stock market. Used data includes all listed main list stocks, dividends and is adjusted in case of splits, and mergers and acquisitions. Strategies are tested using different holding periods (6, 12 and 36 months) and data is divided into tercile portfolios based on different ranking criteria. Contrarian and growth strategies are the only strategies with improved cumulative returns when longer holding periods are used. Momentum (52-week high price1) and GARP strategies based on short holding period have the best performance and contrarian and growth strategies the worst. Momentum strategies (52-week high price) along with short holding period contrarian strategies (52-week low price2) have the lowest risk. Strategies with the highest risk are both growth strategies and two momentum strategies (52-week low price). The empirical results support the efficiency of momentum, GARP and value strategies. The least efficient strategies are contrarian and growth strategies in terms of risk, performance and cumulative returns. Most strategies outperform the market portfolio in all three measures. 1 Stock ranking criterion (current price/52-week highest price) 2 Stock ranking criterion (current price/52-week lowest price)

Assessing the Environmental Value of Water Treatment Solutions in the Mining Industry

Environmental accountability has become a major source of competitive advantage for industrial companies, because customers consider it as relevant buying criterion. However, in order to leverage their environmental responsibility, industrial suppliers have to be able to demonstrate the environmental value of their products and services, which is also the aim of Kemira, a global water chemistry company considered in this study. The aim of this thesis is to develop a tool which Kemira can use to assess the environmental value of their solutions for the customer companies in mining industry. This study answers to questions on what kinds of methods to assess environmental impacts exist, and what kind of tool could be used to assess the environmental value of Kemira’s water treatment solutions. The environmental impacts of mining activities vary greatly between different mines. Generally the major impacts include the water related issues and wastes. Energy consumption is also a significant environmental aspect. Water related issues include water consumption and impacts in water quality. There are several methods to assess environmental impacts, for example life cycle assessment, eco-efficiency tools, footprint calculations and process simulation. In addition the corresponding financial value may be estimated utilizing monetary assessment methods. Some of the industrial companies considered in the analysis of industry best practices use environmental and sustainability assessments. Based on the theoretical research and conducted interviews, an Excel based tool utilizing reference data on previous customer cases and customer specific test results was considered to be most suitable to assess the environmental value of Kemira’s solutions. The tool can be used to demonstrate the functionality of Kemira’s solutions in customers’ processes, their impacts in other process parameters and their environmental and financial aspects. In the future, the tool may be applied to fit also Kemira’s other segments, not only mining industry.

Is professional recognition in plastic surgery related to activity in research

OBJECTIVE: To evaluate the relation of medical research, with the participation of prominent plastic surgeon in Congress.METHODS: We reviewed the scientific programs of the last 3 Brazilian Congress of Surgery, were selected 21 Brazilian plástic surgeons invited to serve as panelists or speakers in roundtable sessions in the last 3 congresses (Group 1). We randomly selected and paired by other members (associates) of the Brazilian Society of Plastic Surgery, with no participation in congress as speaker (Group 2). We conducted a search for articles published in journals indexed in Medline, Lilacs and SciELO for all doctors selected during the entire academic career and the last 5 years from March 2007 until March 2012. We assessed the research activity through the simple counting of the number of publications in indexed journals for each professional. The number of publications groups was compared.RESULTS: articles produced throughout career: Group 1- 639 articles (average of 30.42 items each). Group 2- 79 articles (mean 3.95 articles each). Difference between medias: p <0.001.CONCLUSION: The results demonstrate that the Brazilian Society of Plastic Surgery seeking professionals with a greater number of publications and journals of higher impact. This approach encourages new members to pursue a higher qualification, and give security to congressmen, they can rely on the existence of a technical criterion in the choice of speakers.

Ultrasonografic changes in the axillary vein of patients with lymphedema after mastectomy

OBJECTIVE: To determine the prevalence of sonographic abnormalities (SA) in the axillary vein of patients with and without post-mastectomy lymphedema. METHODS: We studied a sample of 80 women, divided into two equal groups, with and without lymphedema, with B mode ultrasound, color and pulsed Doppler. The primary variable, SA, is defined as change in the venous diameter, parietal thickening, intraluminal images, compressibility, parietal collapse at inspiration and feature of the axillary venous flow on the operated side. Secondary variables were: stage of lymphedema, surgical technique, number of radio and chemotherapy sessions, limb volume, weight and age. The differences between the proportions in the groups were determined using the Chi-square test and / or Fisher's test. For continuous variables, we used the Mann-Whitney Test. To estimate the magnitude of the associations, we used the prevalence rate of SA in both groups as a measure of frequency, and as a measure of association, the prevalence ratio (PR) obtained as a function of relative risk (RR) and estimated by the test Mantel-Haenszel homogeneity test. We adopted the statistical significance level of 5% (p < 0.05). RESULTS: only the criterion "parietal thickening" was strongly associated with the lymphedema group (p = 0.001). The prevalence of SA was 55% in patients with lymphedema and 17.5% in the group without it, with difference in prevalence of 37.5%. CONCLUSION: the prevalence of SA was higher in patients undergoing mastectomy with lymphedema than in those without lymphedema.

Pricing anomalies in the Finnish stock market

The aim of this thesis is to examine whether the pricing anomalies exists in the Finnish stock markets by comparing the performance of quantile portfolios that are formed on the basis of either individual valuation ratios, composite value measures or combined value and momentum indicators. All the research papers included in the thesis show evidence of value anomalies in the Finnish stock markets. In the first paper, the sample of stocks over the 1991-2006 period is divided into quintile portfolios based on four individual valuation ratios (i.e., E/P, EBITDA/EV, B/P, and S/P) and three hybrids of them (i.e. composite value measures). The results show the superiority of composite value measures as selection criterion for value stocks, particularly when EBITDA/EV is employed as earnings multiple. The main focus of the second paper is on the impact of the holding period length on performance of value strategies. As an extension to the first paper, two more individual ratios (i.e. CF/P and D/P) are included in the comparative analysis. The sample of stocks over 1993- 2008 period is divided into tercile portfolios based on six individual valuation ratios and three hybrids of them. The use of either dividend yield criterion or one of three composite value measures being examined results in best value portfolio performance according to all performance metrics used. Parallel to the findings of many international studies, our results from performance comparisons indicate that for the sample data employed, the yearly reformation of portfolios is not necessarily optimal in order to maximally gain from the value premium. Instead, the value investor may extend his holding period up to 5 years without any decrease in long-term portfolio performance. The same holds also for the results of the third paper that examines the applicability of data envelopment analysis (DEA) method in discriminating the undervalued stocks from overvalued ones. The fourth paper examines the added value of combining price momentum with various value strategies. Taking account of the price momentum improves the performance of value portfolios in most cases. The performance improvement is greatest for value portfolios that are formed on the basis of the 3-composite value measure which consists of D/P, B/P and EBITDA/EV ratios. The risk-adjusted performance can be enhanced further by following 130/30 long-short strategy in which the long position of value winner stocks is leveraged by 30 percentages while simultaneously selling short glamour loser stocks by the same amount. Average return of the long-short position proved to be more than double stock market average coupled with the volatility decrease. The fifth paper offers a new approach to combine value and momentum indicators into a single portfolio-formation criterion using different variants of DEA models. The results throughout the 1994-2010 sample period shows that the top-tercile portfolios outperform both the market portfolio and the corresponding bottom-tercile portfolios. In addition, the middle-tercile portfolios also outperform the comparable bottom-tercile portfolios when DEA models are used as a basis for stock classification criteria. To my knowledge, such strong performance differences have not been reported in earlier peer-reviewed studies that have employed the comparable quantile approach of dividing stocks into portfolios. Consistently with the previous literature, the division of the full sample period into bullish and bearish periods reveals that the top-quantile DEA portfolios lose far less of their value during the bearish conditions than do the corresponding bottom portfolios. The sixth paper extends the sample period employed in the fourth paper by one year (i.e. 1993- 2009) covering also the first years of the recent financial crisis. It contributes to the fourth paper by examining the impact of the stock market conditions on the main results. Consistently with the fifth paper, value portfolios lose much less of their value during bearish conditions than do stocks on average. The inclusion of a momentum criterion somewhat adds value to an investor during bullish conditions, but this added value turns to negative during bearish conditions. During bear market periods some of the value loser portfolios perform even better than their value winner counterparts. Furthermore, the results show that the recent financial crisis has reduced the added value of using combinations of momentum and value indicators as portfolio formation criteria. However, since the stock markets have historically been bullish more often than bearish, the combination of the value and momentum criteria has paid off to the investor despite the fact that its added value during bearish periods is negative, on an average.

Association between Lipid Accumulation Product and Hirsutism in Patients with Polycystic Ovary Syndrome

Objective Polycystic ovary syndrome (PCOS) is the most common endocrine metabolic disorder in women between menarche and menopause. Clinical hyperandrogenism is the most important diagnostic criterion of the syndrome, which manifests as hirsutism in 70% of cases. Hirsute carriers of PCOS have high cardiovascular risk. Lipid accumulation product (LAP) is an index for the evaluation of lipid accumulation in adults and the prediction of cardiovascular risk. The aim of this study was to evaluate the association between LAP and hirsutism in women with PCOS. Methods This was a cross-sectional observational study of a secondary database, which included 263 patients who had visited the Hyperandrogenism Outpatient Clinic from November 2009 to July 2014. The exclusion criteria were patients without Ferriman-Gallwey index (FGI) and/or LAP data. We used the Rotterdam criteria for the diagnosis of PCOS. All patients underwent medical assessment followed by measurement and recording of anthropometric data and the laboratory tests for measurement of the following: thyroid-stimulating hormone, follicle-stimulating hormone, prolactin, total testosterone, sex hormone binding globulin, 17-α-hydroxyprogesterone (follicular phase), glycohemoglobin A1c, and basal insulin. In addition, the subjects underwent lipid profiling and oral glucose tolerance tests. Other laboratory measurements were determined according to clinical criteria. LAP and the homeostatic model assessment index (HOMA-IR) were calculated using the data obtained. We divided patients into two groups: the PCOS group with normal LAP (< 34.5) and the PCOS group with altered LAP (> 34.5) to compare the occurrence of hirsutism. For statistical analysis, we used SPSS Statistics for Windows(r) and Microsoft Excel programs, with descriptive (frequencies, percentages, means, and standard deviations) and comparative analyses (Student's t-test and Chi-square test). We considered relations significant when the p-value was≤0.05. Results LAP was high in most patients (n = 177; 67.3%) and the FGI indicated that 58.5% of the patients (n = 154) had hirsutism. The analysis by LAP quartiles showed a positive correlation (p = 0.04) among patients with a high FGI and an upper quartile LAP (> 79.5) when compared with those with LAP < 29.0 (lower quartile). Conclusion This study demonstrated an association between high LAP and hirsutism. The FGI could represent a simple and low-cost tool to infer an increased cardiovascular risk in women with PCOS.

Impact of Sacrospinous Colpopexy Associated with Anterior Colporrhaphy for the Treatment of Dome Prolapse on all Three Vaginal Compartments

Objective To evaluate the results of sacrospinous colpopexy surgery associated with anterior colporrhaphy for the treatment of women with post-hysterectomy vaginal vault prolapse. Methods This prospective study included 20women with vault prolapse, PelvicOrgan Prolapse Quantification System (POP-Q) stage≥2, treated between January 2003 and February 2006, and evaluated in a follow-up review (more than one year later). Genital prolapse was evaluated qualitatively in stages and quantitatively in centimeters. Prolapse stage < 2 was considered to be the cure criterion. Statistical analysis was performed using the Wilcoxon test (paired samples) to compare the points and stages of prolapse before and after surgery. Results Evaluation of the vaginal vault after one year revealed that 95% of subjects were in stage zero and that 5% were in stage 1. For cystocele, 50% were in stage 1, 10% were in stage 0 (cured) and 40% were in stage 2. For rectocele, three women were in stage 1 (15%), one was in stage 2 (5%) and 16 had no further prolapse. The most frequent complication was pain in the right buttock, with remission of symptoms in all three cases three months after surgery. Conclusions In this retrospective study, the surgical correction of vault prolapse using a sacrospinous ligament fixation technique associatedwith anterior colporrhaphy proved effective in resolving genital prolapse. Despite the low complication rates, there was a high rate of cystocele, which may be caused by posterior vaginal shifting due to either the technique or an overvaluation by the POP-Q system.

Developing raster bands computed from LiDAR to improve forest

This study examines the use of di erent features derived from remotely sensed data in segmentation of forest stands. Surface interpolation methods were applied to LiDAR points in order to represent data in the form of grayscale images. Median and mean shift ltering was applied to the data for noise reduction. The ability of di erent compositions of rasters obtained from LiDAR data and an aerial image to maximize stand homogeneity in the segmentation was evaluated. The quality of forest stand delineations was assessed by the Akaike information criterion. The research was performed in co-operation with Arbonaut Ltd., Joensuu, Finland.