Integration of learning supportive applications into the development of the e-portfolio construction process

The portfolio as a means of demonstrating personal skills has lately been gaining prominence among technology students. This is partially due to the introduction of electronic portfolios, or e-portfolios. As platforms for e-portfolio management with different approaches have been introduced, the learning cycle, traditional portfolio pedagogy, and learner centricity have sometimes been forgotten, and as a result, the tools have been used for the most part as data depositories. The purpose of this thesis is to show how the construction of e-portfolios of IT students can be supported by institutions through the usage of different tools that relate to study advising, teaching, and learning. The construction process is presented as a cycle based on learning theories. Actions related to the various phases of the e-portfolio construction process are supported by the implementation of software applications. To maximize learner-centricity and minimize the intervention of the institution, the evaluated and controlled actions for these practices can be separated from the e-portfolios, leaving the construction of the e-portfolio to students. The main contributions of this thesis are the implemented applications, which can be considered to support the e-portfolio construction by assisting in planning, organizing, and reflecting activities. Eventually, this supports the students in their construction of better and more extensive e-portfolios. The implemented tools include 1) JobSkillSearcher to help students’ recognition of the demands of the ICT industry regarding skills, 2) WebTUTOR to support students’ personal study planning, 3) Learning Styles to determine students' learning styles, and 4) MyPeerReview to provide a platform on which to carry out anonymous peer review processes in courses. The most visible outcome concerning the e-portfolio is its representation, meaning that one can use it to demonstrate personal achievements at the time of seeking a job and gaining employment. Testing the tools and the selected open-source e-portfolio application indicates that the degree of richness of e-portfolio content can be increased by using the implemented applications.

Price spike forecasting in a competitive day-ahead energy market

Electricity price forecasting has become an important area of research in the aftermath of the worldwide deregulation of the power industry that launched competitive electricity markets now embracing all market participants including generation and retail companies, transmission network providers, and market managers. Based on the needs of the market, a variety of approaches forecasting day-ahead electricity prices have been proposed over the last decades. However, most of the existing approaches are reasonably effective for normal range prices but disregard price spike events, which are caused by a number of complex factors and occur during periods of market stress. In the early research, price spikes were truncated before application of the forecasting model to reduce the influence of such observations on the estimation of the model parameters; otherwise, a very large forecast error would be generated on price spike occasions. Electricity price spikes, however, are significant for energy market participants to stay competitive in a market. Accurate price spike forecasting is important for generation companies to strategically bid into the market and to optimally manage their assets; for retailer companies, since they cannot pass the spikes onto final customers, and finally, for market managers to provide better management and planning for the energy market. This doctoral thesis aims at deriving a methodology able to accurately predict not only the day-ahead electricity prices within the normal range but also the price spikes. The Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and its structure is studied in detail. It is almost universally agreed in the forecasting literature that no single method is best in every situation. Since the real-world problems are often complex in nature, no single model is able to capture different patterns equally well. Therefore, a hybrid methodology that enhances the modeling capabilities appears to be a possibly productive strategy for practical use when electricity prices are predicted. The price forecasting methodology is proposed through a hybrid model applied to the price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select the optimal input set of the explanatory variables. The numerical studies show that the proposed methodology has more accurate behavior than all other examined methods most recently applied to case studies of energy markets in different countries. The obtained results can be considered as providing extensive and useful information for participants of the day-ahead energy market, who have limited and uncertain information for price prediction to set up an optimal short-term operation portfolio. Although the focus of this work is primarily on the Finnish price area of Nord Pool Spot, given the result of this work, it is very likely that the same methodology will give good results when forecasting the prices on energy markets of other countries.

Validation and Selection of Transportation Cost Drivers with Advanced Methods

In today's logistics environment, there is a tremendous need for accurate cost information and cost allocation. Companies searching for the proper solution often come across with activity-based costing (ABC) or one of its variations which utilizes cost drivers to allocate the costs of activities to cost objects. In order to allocate the costs accurately and reliably, the selection of appropriate cost drivers is essential in order to get the benefits of the costing system. The purpose of this study is to validate the transportation cost drivers of a Finnish wholesaler company and ultimately select the best possible driver alternatives for the company. The use of cost driver combinations as an alternative is also studied. The study is conducted as a part of case company's applied ABC-project using the statistical research as the main research method supported by a theoretical, literature based method. The main research tools featured in the study include simple and multiple regression analyses, which together with the literature and observations based practicality analysis forms the basis for the advanced methods. The results suggest that the most appropriate cost driver alternatives are the delivery drops and internal delivery weight. The possibility of using cost driver combinations is not suggested as their use doesn't provide substantially better results while increasing the measurement costs, complexity and load of use at the same time. The use of internal freight cost drivers is also questionable as the results indicate weakening trend in the cost allocation capabilities towards the end of the period. Therefore more research towards internal freight cost drivers should be conducted before taking them in use.

Selection of Grids for Weed Mapping

This study aimed to assess the degree of similarity presented by thematic maps generated by different sampling grids of weed plants in a commercial agricultural area of 7.95 hectares. Monocotyledons and dicotyledons were counted on the 2012/2013 and 2013/2014 harvests, before soybean planting, in the fallow period after wheat harvest, in both years. A regular grid of 10 x 10 m was produced to sample the invasive plants, used as reference, and the counting was done in 1 m² of each sample point, totaling 795 samples in each year, compared to regular grids of 30 and 50 m, generated from the data exclusion of the standard grid. Twenty-two composite soil samples were taken at a depth of 0-20 cm to correlate soil properties with weeds occurrence. For the generation of the thematic maps, the Inverse Distance Weighting (IDW) for interpolation was used; when comparing the maps generated from each grid with the reference map, the kappa coefficient was used to assess the loss of quality of the maps as the number of sample points was reduced. It was observed that the map quality loss was lower in 2013 compared to 2012 when the sampling density of the points was reduced. The 30 x 30 m grids have satisfactorily described the infestation data of the dicotyledons and the 50 x 50 m grids have adequately described the monocotyledon weeds infestation, compared to the standard 10 x 10 m grids.

SELECTION OF HERBICIDES TARGETING THE USE IN CROP SYSTEMS CULTIVATED WITH SHOWY CROTALARIA

ABSTRACT The increase in the area planted with Crotalaria spectabilishas occurred by several factors, highlighting the potential to reduce the nematodes, nitrogen fixation and the high production of biomass. By becoming a species sown as a crop, it is necessary to control the weeds that coexist with showy crotalaria. This change in the use of this crop creates the possibility of this specie becoming a weed. The aim of this study was to assess the potential use of herbicides applied in preemergence and postemergence of C.spectabilisfor different purposes (control of volunteer and selectivity plants). Three experiments were installed in a greenhouse (two with herbicides applied in preemergence - in soils with distinct textural categories; and one experiment with herbicides applied in postemergence). The results of the experiments with herbicides applied in preemergence showed that: amicarbazone, atrazine, diuron, metribuzin, prometryn, fomesafen and sulfentrazone showed effectiveness for control of C.spectabilis in clayey soil. Besides these, flumioxazin and isoxaflutole also showed potential to be used in the control of showy crotalaria in soils with loam texture. In relation to the postemergence herbicides, atrazine, diuron, prometryn, flumioxazin, fomesafen, lactofen, saflufenacil, amonio-glufosinate and glyphosate can be used aiming the chemical control of C.spectabilis. Herbicides chlorimuron-ethyl, diclosulan, imazethapyr, pyrithiobac-sodium, trifloxysulfuron-sodium, clomazone, pendimethalin, S-metolachlor and trifluralin applied in preemergence, and imazethapyr, pyrithiobac-sodium, flumiclorac, bentazon and clethodim applied in postemergence caused low levels of injury to C.spectabilis plants, making necessary the development of new searches to ensure the selectivity of these products.

Service paradox in a product oriented company: A service business development case

The master´s thesis had three aims; to develop a service portfolio, to support the management of services through the developed portfolio, and evaluate effects of service differentiation strategy on the future selection of services. The product oriented case company in service paradox is Hilti (Suomi) Oy, which is entering systematic service management era, supported by the late strategic change. Low return on service business investments is referred as service paradox. The project was carried out as a case study, where the primary information source was twenty-one conducted interviews. The theory part focuses on marketing logics, service strategies, and categorization of services. The empirical part contributes in solving the aim related research questions. As a result of the case study a service portfolio was created, next further steps in service management were suggested, and the effect on selection of services by service differentiation strategy was evaluated. The main goal of creating service portfolio contributes to systematic management of services, which required revising at the case company.

Carrier selection and management : A case study on Neste Oil Retail

Service provider selection has been said to be a critical factor in the formation of supply chains. Through successful selection companies can attain competitive advantage, cost savings and more flexible operations. Service provider management is the next crucial step in outsourcing process after the selection has been made. Without proper management companies cannot be sure about the level of service they have bought and they may suffer from service provider's opportunistic behavior. In worst case scenario the buyer company may end up in locked-in situation in which it is totally dependent of the service provider. This thesis studies how the case company conducts its carrier selection process along with the criteria related to it. A model for the final selection is also provided. In addition, case company's carrier management procedures are reflected against recommendations from previous researches. The research was conducted as a qualitative case study on the principal company, Neste Oil Retail. A literature review was made on outsourcing, service provider selection and service provider management. On the basis of the literature review, this thesis ended up recommending Analytic hierarchy process as the preferred model for the carrier selection. Furthermore, Agency theory was seen to be a functional framework for carrier management in this study. Empirical part of this thesis was conducted in the case company by interviewing the key persons in the selection process, making observations and going through documentations related to the subject. According to the results from the study, both carrier selection process as well as carrier management were closely in line with suggestions from literature review. Analytic hierarchy process results revealed that the case company considers service quality as the most important criteria with financial situation and price of service following behind with almost identical weights with each other. Equipment and personnel was seen as the least important selection criterion. Regarding carrier management, the study resulted in the conclusion that the company should consider engaging more in carrier development and working towards beneficial and effective relationships. Otherwise, no major changes were recommended for the case company processes.

Hedge-rahastojen menestyksen pysyvyys ja suhteellinen suoriutuminen sijoittajan näkökulmasta

The purpose of the thesis is to examine the long-term performance persistence and relative performance of hedge funds during bear and bull market periods. Performance metrics applied for fund rankings are raw return, Sharpe ratio, mean variance ratio and strategy distinctiveness index calculated of the original and clustered data correspondingly. Four different length combinations for selection and holding periods are employed. The persistence is examined using decile and quartile portfolio formatting approach and on the basis of Sharpe ratio and SKASR as performance metrics. The relative performance persistence is examined by comparing hedge portfolio returns during varying stock market conditions. The data is gathered from a private database covering 10,789 hedge funds and time horizon is set from January 1990 to December 2012. The results of this thesis suggest that long-term performance persistence of the hedge funds exists. The degree of persistence also depends on the performance metrics employed and length combination of selection and holding periods. The best results of performance persistence were obtained in the decile portfolio analysis on the basis of Sharpe ratio rankings for combination of 12-month selection period and the holding period of equal length. The results also suggest that the best performance persistence occurs in the Event Driven and Multi strategies. Dummy regression analysis shows that a relationship between hedge funds and stock market returns exists. Based on the results, Dedicated Short Bias, Global Macro, Managed Futures and Other strategies perform well during bear market periods. The results also indicate that the Market Neutral strategy is not absolutely market neutral and the Event Driven strategy has the best performance among all hedge strategies.

Creating risk measurement model to project portfolio management in construction company

This thesis was carried out as a case study of a company YIT in order to clarify the sev-erest risks for the company and to build a method for project portfolio evaluation. The target organization creates new living environment by constructing residential buildings, business premises, infrastructure and entire areas worth for EUR 1.9 billion in the year 2013. Company has noted project portfolio management needs more information about the structure of project portfolio and possible influences of market shock situation. With interviews have been evaluated risks with biggest influence and most appropriate metrics to examine. The major risks for the company were evaluated by interviewing the executive staff. At the same time, the most appropriate risk metrics were considered. At the moment sales risk was estimated to have biggest impact on company‟s business. Therefore project port-folio evaluation model was created and three different scenarios for company‟s future were created in order to identify the scale of possible market shock situation. The created model is tested with public and descriptive figures of YIT in a one-year-long market shock and the impact on different metrics was evaluated. Study was conducted using con-structive research methodology. Results indicate that company has notable sales risk in certain sections of business portfolio.

Combined selection in early generation testing of self-pollinated plants

Seven selection indexes based on the phenotypic value of the individual and the mean performance of its family were assessed for their application in breeding of self-pollinated plants. There is no clear superiority from one index to another although some show one or more negative aspects, such as favoring the selection of a top performing plant from an inferior family in detriment of an excellent plant from a superior family

Using the best linear predictor (BLP) in the selection between and among half-sib progenies of the CMS-39 maize population

Data of corn ear production (kg/ha) of 196 half-sib progenies (HSP) of the maize population CMS-39 obtained from experiments carried out in four environments were used to adapt and assess the BLP method (best linear predictor) in comparison with to the selection among and within half-sib progenies (SAWHSP). The 196 HSP of the CMS-39 population developed by the National Center for Maize and Sorghum Research (CNPMS-EMBRAPA) were related through their pedigree with the recombined progenies of the previous selection cycle. The two methodologies used for the selection of the twenty best half-sib progenies, BLP and SAWHSP, led to similar expected genetic gains. There was a tendency in the BLP methodology to select a greater number of related progenies because of the previous generation (pedigree) than the other method. This implies that greater care with the effective size of the population must be taken with this method. The SAWHSP methodology was efficient in isolating the additive genetic variance component from the phenotypic component. The pedigree system, although unnecessary for the routine use of the SAWHSP methodology, allowed the prediction of an increase in the inbreeding of the population in the long term SAWHSP selection when recombination is simultaneous to creation of new progenies.

Working fluid selection and design of small-scale waste heat recovery systems based on organic Rankine cycles

Demand for the use of energy systems, entailing high efficiency as well as availability to harness renewable energy sources, is a key issue in order to tackling the threat of global warming and saving natural resources. Organic Rankine cycle (ORC) technology has been identified as one of the most promising technologies in recovering low-grade heat sources and in harnessing renewable energy sources that cannot be efficiently utilized by means of more conventional power systems. The ORC is based on the working principle of Rankine process, but an organic working fluid is adopted in the cycle instead of steam. This thesis presents numerical and experimental results of the study on the design of small-scale ORCs. Two main applications were selected for the thesis: waste heat re- covery from small-scale diesel engines concentrating on the utilization of the exhaust gas heat and waste heat recovery in large industrial-scale engine power plants considering the utilization of both the high and low temperature heat sources. The main objective of this work was to identify suitable working fluid candidates and to study the process and turbine design methods that can be applied when power plants based on the use of non-conventional working fluids are considered. The computational work included the use of thermodynamic analysis methods and turbine design methods that were based on the use of highly accurate fluid properties. In addition, the design and loss mechanisms in supersonic ORC turbines were studied by means of computational fluid dynamics. The results indicated that the design of ORC is highly influenced by the selection of the working fluid and cycle operational conditions. The results for the turbine designs in- dicated that the working fluid selection should not be based only on the thermodynamic analysis, but requires also considerations on the turbine design. The turbines tend to be fast rotating, entailing small blade heights at the turbine rotor inlet and highly supersonic flow in the turbine flow passages, especially when power systems with low power outputs are designed. The results indicated that the ORC is a potential solution in utilizing waste heat streams both at high and low temperatures and both in micro and larger scale appli- cations.

Osinkosuhteen, osinkotuoton ja omavaraisuusasteen sijoitusstrateginen hyödynnettävyys Suomen osakemarkkinoilla

Tutkielman tavoitteena on selvittää osinkosuhteen, osinkotuoton ja omavaraisuusasteen vaikutus osakkeesta saatavaan kokonaistuottoon Suomenosakemarkkinoilla vuosina 2002–2013. Muuttujien kausaliteettisuhde kokonaistuottoon selvitetään regressioanalyysilla. Portfolioanalyysin avulla tutkitaan valittujen tunnuslukujen toimivuutta sijoitusstrategiana. Tutkimuksessa muodostetaan myös osinkosuhteen ja osinkotuoton yhdistelmänä tunnusluku, jolla pyritään maksimoimaan sijoittajan saama tuotto. Empiiriset tulokset osoittivat, että sijoittaja pystyy saavuttamaan ylituottoja hyödyntämällä edellä mainittuja tunnuslukuja osakevalinnassa. Osinkotuoton ja osakkeen kokonaistuoton välillä havaittiin positiivinen lineaarinen korrelaatio. Portfolioanalyysin perusteella sekä omavaraisuusasteen että osinkosuhteen osalta vaikutus sijoittajan saamaan riskisuhteutettuun kokonaistuottoon on ei-lineaarinen. Valittuja tunnuslukuja ja menetelmiä hyödyntäen sijoittaja saa parhaimman riskisuhteutetun tuoton valitsemalla sijoitussalkkuunsa osakkeita, joiden osinkosuhteen arvo sijoittuu toiseksi ylimpään kvartiiliin sekä osakkeita, joiden osinkotuotto on korkea ja omavaraisuusaste on samanaikaisesti alhainen.

Green supplier selection via Multiple Criteria Data Envelopment Analysis

An appropriate supplier selection and its profound effects on increasing the competitive advantage of companies has been widely discussed in supply chain management (SCM) literature. By raising environmental awareness among companies and industries they attach more importance to sustainable and green activities in selection procedures of raw material providers. The current thesis benefits from data envelopment analysis (DEA) technique to evaluate the relative efficiency of suppliers in the presence of carbon dioxide (CO2) emission for green supplier selection. We incorporate the pollution of suppliers as an undesirable output into DEA. However, to do so, two conventional DEA model problems arise: the lack of the discrimination power among decision making units (DMUs) and flexibility of the inputs and outputs weights. To overcome these limitations, we use multiple criteria DEA (MCDEA) as one alternative. By applying MCDEA the number of suppliers which are identified as efficient will be decreased and will lead to a better ranking and selection of the suppliers. Besides, in order to compare the performance of the suppliers with an ideal supplier, a “virtual” best practice supplier is introduced. The presence of the ideal virtual supplier will also increase the discrimination power of the model for a better ranking of the suppliers. Therefore, a new MCDEA model is proposed to simultaneously handle undesirable outputs and virtual DMU. The developed model is applied for green supplier selection problem. A numerical example illustrates the applicability of the proposed model.