The world is changing, what has been known to work has been put to the test when both the geopolitical and the environmental climate are changing. War, a pandemic, material shortage, financial difficulties and an overall dis- tressed global transportation sector have shown that the ever-more important topic of resilience is crucial to stay relevant in today’s competitive markets. Companies are therefore switching focus towards ensuring sufficient supply chain resilience capabilities to handle these ever-changing situations on the global market.  In this thesis, we focus on how Volvo SML is working with resilience today, and how graph theory and optimisation can be useful tools when analysing a supply chain’s resilience. We made a qualitative analysis by conducting inter- views with employees and comparing our findings with capabilities related to resilience. In addition, we conducted a quantitative analysis by constructing a simulation of the supply chain, comparing two topology metrics and two op- timisation metrics, to analyse the robustness of the aftermarket supply chain.  We analysed the data and summarised the insights gathered from the inter- views using a resilience capability framework. Volvo SML proved to be agile and reactive when dealing with disruptions but is missing some key capabil- ities during the pre-and post-disruption phases. Some areas of improvement we identified were: robustness, collaboration and redundancy. We proved that the simulation is useful when evaluating the robustness of a supply chain, and we showed that a more flexible way of working would improve the overall robustness of Volvo SML’s aftermarket supply chain.

Denna uppsats undersöker om aktiv eller passiv fondförvaltning har presterat bättre under coronapandemin på den svenska fondmarknaden. Med hjälp av Refinitiv Eikon och Morningstar har vi hämtat relevant veckodata för 20 aktivt förvaltade fonder och 12 passivt förvaltade fonder mellan 2020-03-06 och 2022-02-11. Efter noggrann beräkning av de olika prestationsmåtten i Microsoft Excel kan vi konstatera att den passiva förvaltningen presterade bättre under coronapandemin men att detta inte är en garanti för framtida val av fonder under kommande kriser eller ekonomiska chocker. / This thesis examines whether active or passive fund management has performed better during the corona pandemic in the Swedish fund market. With the help of Refinitiv Eikon and Morningstar, we have collected relevant weekly data for 20 actively managed funds and 12 passively managed funds between 2020-03-06 and 2022-02-11. After careful calculation of the various performance measures in Microsoft Excel, we can state that the passive management has performed better during the corona pandemic, but this result is not a guarantee for future fund choices during future crises or economic shocks.

Our brain and nervous system is a vital organ to us, since it is from there our thoughts, personalities, and other mental capacities originate. Within this field of neuroscience a common method of study is to build and run large scale brain simulations where up to hundred thousand neurons are used to produce a model of a brain in three dimensional space. To find all neurites within a specific area is to perform a range query. A vast number of range queries are required when running brain simulations which makes it important that the data structure used to store the simulated neurons is efficient. This study evaluate three common data structures, also called spatial index; the R-tree, Quadtree and R*-tree (Rstar-tree). We test their performance for range queries with regards to execution time, incurred reads, build time, size of data and density of data. The data used is models of a typical neuron so that the characteristics of the data set is preserved. The results show that the R*-tree outperforms the other indices by being significantly more efficient compared to the others, with the R-tree having slightly worse performance than the Quadtree. The time it takes to build the index is to be almost identical for all implementations. / Vår hjärna och nervsystem är ett grundläggande organ för oss. Det är där ifrån våra tankar, personligheter och mentala kapaciteter kommer ifrån. Inom neurovetenskap är en vanlig forskningsmetod att köra storskaliga hjärnsimuleringar där hundratusentals neuroner används för att skapa en modell av hjärnan i 3D. För att hitta alla neuroner inom en viss area används en så kallad intervallfråga. En stor mängd intervallfrågor behövs för hjärnsimuleringar vilket gör det viktigt att datastrukturerna som används för detta är kostnadseffektiva. Denna studie har som mål att jämföra tre stycken vanliga datastrukturer som används för intervallfrågor. Dessa är R-tree, Quadtree och R*-tree. Deras prestanda testas för exekveringstid, antal läsningar, konstruktionstid, samt storlek och densitet på neuroner. För att skapa hjärnsimuleringen används en typisk neuron som standard sådant att dess karakteristiska egenskaper bevaras. Resultaten från studien visar att R*-tree hade den tydligt bästa prestandan för de givna kriterierna, och att Quadtree har en något bättre prestanda än R-tree. Tiden det tar att mata in neuronerna i datastrukturerna är i stort sett densamma.

The modern industry has an increasing demand for simulation software able to help workers and decision-makers visualize the outputs of a specific process in a fast, accurate way. In this report, a comparative study between FACTS (Factory Analyses in ConcepTual phase using Simulation), Plant Simulation, and PSE (Production System Engineering) Toolbox is done regarding their capacity to simulate models with increasing complexity, how accurate they are in their outputs with different optimized buffer allocations, and how well they perform on the task of detecting the bottlenecks of a process. Benchmarking simulation software requires an experimental approach, and for gathering and organizing all the data generated using external programs like MATLAB, C, Excel, and R are used. A high level of automatization is required as otherwise the manual input of data would take too long to be effective.The results conclude on major concordances among FACTS and Plant Simulation as the most used commercial DES (Discrete Event Simulation) software and a more mathematical-theoretical approach coming from PSE Toolbox. The optimization done in the report links to sustainability, with an enhanced TH improving the ecological, social and economic aspects, and to Lean philosophy using lean buffers that smooth and improve the production flow.

In South Africa, legislation dictates that employees must be developed resulting in the need to identify candidate's development capability. As such, it is essential to be able to measure the learning potential of candidates. In practice, cognitive ability has been linked to the complex process of job performance. This study aimed to determine whether learning potential can be used as a predictor of job performance. The Learning Potential Computerised Adaptive Test (LPCAT) was utilised to measure learning potential and job performance was measured through a promotion ratio (taking job knowledge and tenure into account). The moderator variables were investigated. A sample of 135 technical employees was drawn. The data was statistical manipulated reporting various significant relationships confirming the internal reliability of the LPCAT and indicating a strong significant relationship between learning potential and job performance. Variables such as learning potential, job grade and tenure are significant when predicting job performance. / Industrial and Organisational Psychology / MA (Industrial and Organisational Psychology)

<p>Algorithmic trading is an automated process of order execution on electronic stock markets. It can be applied to a broad range of financial instruments, and it is&nbsp; characterized by a signicant investors&#39; control over the execution of his/her orders, with the principal goal of finding the right balance between costs and risk of not (fully) executing an order. As the measurement of execution performance gives information whether best execution is achieved, a signicant number of diffeerent benchmarks is&nbsp; used in practice. The most frequently used are price benchmarks, where some of them are determined before trading (Pre-trade benchmarks), some during the trading&nbsp; day (In-traday benchmarks), and some are determined after the trade (Post-trade benchmarks). The two most dominant are VWAP and Arrival Price, which is along with other pre-trade price benchmarks known as the Implementation Shortfall (IS).</p><p>We introduce Negative Selection as a posteriori measure of the execution algorithm performance. It is based on the concept of Optimal Placement, which represents the ideal order that could be executed in a given time win-dow, where the notion of ideal means that it is an order with the best execution price considering&nbsp; market &nbsp;conditions&nbsp; during the time window. Negative Selection is dened as a difference between vectors of optimal and executed orders, with vectors dened as a quantity of shares at specied price positionsin the order book. It is equal to zero when the order is optimally executed; negative if the order is not (completely) filled, and positive if the order is executed but at an unfavorable price.</p><p>Negative Selection is based on the idea to offer a new, alternative performance measure, which will enable us to find the&nbsp; optimal trajectories and construct optimal execution of an order.</p><p>The first chapter of the thesis includes a list of notation and an overview of denitions and theorems that will be used further in the thesis. Chapters 2 and 3 follow with a&nbsp; theoretical overview of concepts related to market microstructure, basic information regarding benchmarks, and theoretical background of algorithmic trading. Original results are presented in chapters 4 and 5. Chapter 4 includes a construction of optimal placement, definition and properties of Negative Selection. The results regarding the properties of a Negative Selection are given in [35]. Chapter 5 contains the theoretical background for stochastic optimization, a model of the optimal execution formulated as a stochastic optimization problem with regard to Negative Selection, as well as original work on nonmonotone line search method [31], while numerical results are in the last, 6th chapter.</p> / <p>Algoritamsko trgovanje je automatizovani proces izvr&scaron;avanja naloga na elektronskim berzama. Može se primeniti na &scaron;irok spektar nansijskih instrumenata kojima se trguje na berzi i karakteri&scaron;e ga značajna kontrola investitora nad izvr&scaron;avanjem njegovih naloga, pri čemu se teži nalaženju pravog balansa izmedu tro&scaron;ka i rizika u vezi sa izvr&scaron;enjem naloga. S ozirom da se merenjem performasi izvr&scaron;enja naloga određuje da li je postignuto najbolje izvr&scaron;enje, u praksi postoji značajan broj različitih pokazatelja. Najče&scaron;će su to pokazatelji cena, neki od njih se određuju pre trgovanja (eng. Pre-trade), neki u toku trgovanja (eng. Intraday), a neki nakon trgovanja (eng. Post-trade). Dva najdominantnija pokazatelja cena su VWAP i Arrival Price koji je zajedno sa ostalim &quot;pre-trade&quot; pokazateljima cena poznat kao Implementation shortfall (IS).</p><p>Pojam negative selekcije se uvodi kao &quot;post-trade&quot; mera performansi algoritama izvr&scaron;enja, polazeći od pojma optimalnog naloga, koji predstavlja idealni nalog koji se&nbsp; mogao izvrsiti u datom vremenskom intervalu, pri ćemu se pod pojmom &quot;idealni&quot; podrazumeva nalog kojim se postiže najbolja cena u trži&scaron;nim uslovima koji su vladali&nbsp; u toku tog vremenskog intervala. Negativna selekcija se defini&scaron;e kao razlika vektora optimalnog i izvr&scaron;enog naloga, pri čemu su vektori naloga defisani kao količine akcija na odgovarajućim pozicijama cena knjige naloga. Ona je jednaka nuli kada je nalog optimalno izvr&scaron;en; negativna, ako nalog nije (u potpunosti) izvr&scaron;en, a pozitivna ako je nalog izvr&scaron;en, ali po nepovoljnoj ceni.</p><p>Uvođenje mere negativne selekcije zasnovano je na ideji da se ponudi nova, alternativna, mera performansi i da se u odnosu na nju nađe optimalna trajektorija i konstrui&scaron;e optimalno izvr&scaron;enje naloga.</p><p>U prvom poglavlju teze dati su lista notacija kao i pregled definicija i teorema&nbsp; neophodnih za izlaganje materije. Poglavlja 2 i 3 bave se teorijskim pregledom pojmova i literature u vezi sa mikrostrukturom trži&scaron;ta, pokazateljima trgovanja i algoritamskim trgovanjem. Originalni rezultati su predstavljeni u 4. i 5. poglavlju. Poglavlje 4 sadrži konstrukciju optimalnog naloga, definiciju i osobine negativne selekcije. Teorijski i praktični rezultati u vezi sa osobinama negativna selekcije dati su u [35]. Poglavlje 5 sadrži teorijske osnove stohastičke optimizacije, definiciju modela za optimalno izvr&scaron;enje, kao i originalni rad u vezi sa metodom nemonotonog linijskog pretraživanja [31], dok 6. poglavlje sadrži empirijske rezultate.</p>

Aim: The aim of diploma thesis was clinical utility of the Czech version of Canadian Occupational Performance Measure (COPM) in both parts. Utility in performance of activities of daily living and utility in satisfaction with performance of activities of daily living for physically disabled adults persons. Methods: The pre-research consisted of 40 persons with physical disability after stroke. For data collection was used Canadian Occupational Performance Measure, Barthel index and Subjective QUAlity of Life Analysis (SQUALA). Hypotheses were vitrificated by correlation analysis using Spearman's Rank Correlation Coefficient. Results: P-value (p = 0,00001) from the test of dependence of measured values by COPM in performance of activities of daily living and BI was lower than level of significance α = 0,05; 0,00001 < 0,05. P-value from the test of dependence of measured values by COPM in satisfaction with performance of activities of daily living and SQUALA questionnaire was lower than level of significant α = 0,05; 0,041 < 0,05. Conclusion: The results of the statistical analysis did not confirm the independence of the measured values by the Czech version COPM, BI and the SQUALA questionnaire. It was supported the using COPM in both parts, in performance of activities of daily living and in satisfaction...

The generalization abilities of machine learning algorithms often depend on the algorithms’ initialization, parameter settings, training sets, or feature selections. For instance, SVM classifier performance largely relies on whether the selected kernel functions are suitable for real application data. To enhance the performance of individual classifiers, this dissertation proposes classifier fusion models using computational intelligence knowledge to combine different classifiers. The first fusion model called T1FFSVM combines multiple SVM classifiers through constructing a fuzzy logic system. T1FFSVM can be improved by tuning the fuzzy membership functions of linguistic variables using genetic algorithms. The improved model is called GFFSVM. To better handle uncertainties existing in fuzzy MFs and in classification data, T1FFSVM can also be improved by applying type-2 fuzzy logic to construct a type-2 fuzzy classifier fusion model (T2FFSVM). T1FFSVM, GFFSVM, and T2FFSVM use accuracy as a classifier performance measure. AUC (the area under an ROC curve) is proved to be a better classifier performance metric. As a comparison study, AUC-based classifier fusion models are also proposed in the dissertation. The experiments on biomedical datasets demonstrate promising performance of the proposed classifier fusion models comparing with the individual composing classifiers. The proposed classifier fusion models also demonstrate better performance than many existing classifier fusion methods. The dissertation also studies one interesting phenomena in biology domain using machine learning and classifier fusion methods. That is, how protein structures and sequences are related each other. The experiments show that protein segments with similar structures also share similar sequences, which add new insights into the existing knowledge on the relation between protein sequences and structures: similar sequences share high structure similarity, but similar structures may not share high sequence similarity.

In South Africa, legislation dictates that employees must be developed resulting in the need to identify candidate's development capability. As such, it is essential to be able to measure the learning potential of candidates. In practice, cognitive ability has been linked to the complex process of job performance. This study aimed to determine whether learning potential can be used as a predictor of job performance. The Learning Potential Computerised Adaptive Test (LPCAT) was utilised to measure learning potential and job performance was measured through a promotion ratio (taking job knowledge and tenure into account). The moderator variables were investigated. A sample of 135 technical employees was drawn. The data was statistical manipulated reporting various significant relationships confirming the internal reliability of the LPCAT and indicating a strong significant relationship between learning potential and job performance. Variables such as learning potential, job grade and tenure are significant when predicting job performance. / Industrial and Organisational Psychology / MA (Industrial and Organisational Psychology)

Made available in DSpace on 2010-04-20T20:48:35Z (GMT). No. of bitstreams: 3 74548.pdf.jpg: 26566 bytes, checksum: 1363b6015e29349551fc03353232c2f6 (MD5) 74548.pdf: 1970291 bytes, checksum: afaf033a3bee5d623cfb2ac4ccc1cef1 (MD5) 74548.pdf.txt: 340191 bytes, checksum: 0b249196cea065834bc87d775c4ff9ae (MD5) Previous issue date: 2005-09-27T00:00:00Z / A determinação e a mensuração da importância das principais fontes de vantagem competitiva, ainda é um tema em discussão na área de Estratégia. Uma linha de pesquisa, iniciada em meados dos anos 80, tem seu foco principal na determinação e quantificação da importância dos fatores que poderiam explicar as diferenças no desempenho de um grupo de empresas, utilizando a decomposição da variância dos valores do desempenho através das técnicas de Regressão Linear ou de Componentes de Variância. Nesta linha de pesquisa, desenvolveram-se uma série de trabalhos empíricos cujo propósito principal é quantificar, entre outros fatores, qual a importância do setor industrial em que a empresa atua, qual a importância do ano, qual a importância de se fazer parte de um grupo econômico e qual a importância dos fatores idiossincráticos da empresa na explicação do desempenho apresentado em determinados períodos. Dos resultados destes trabalhos surgiram discussões importantes sobre o papel da estratégia corporativa e sobre a importância relativa de tais fatores na determinação da vantagem competitiva. Este trabalho se insere nesta linha de pesquisa, cujo objetivo é, utilizando uma base de dados brasileira muito mais abrangente e completa que os estudos anteriores, quer nacionais e internacionais, primeiramente verificar se a realidade apontada nos estudos internacionais se assemelha à do Brasil. Em segundo lugar, contribuir com um refinamento teórico, refazendo estas análises utilizando modelos lineares mistos, mais apropriados para estes conjuntos de dados, que os modelos de componentes de variância. Em terceiro lugar, utilizando dois tipos de matriz de covariância, verifica se o desempenho de um determinado ano influi no desempenho dos anos imediatamente subseqüentes, verificando, assim, a possível existência de medidas repetidas para a variável ano. Finalmente, analisa se parte da variabilidade do desempenho das empresas brasileiras pode ser atribuído ao fato da empresa se localizar em determinada Unidade da Federação / The delimitation of the main sources of competitive advantage and the quantification of their importance, are still relevant issues in the strategy field of studies. At the middle of the 80´s, a new stream of research emerged, focusing in determining and quantifying the importance of the factors which could explain the differences among the performance of a set of firms, through the decomposition of factors variance using linear regression or variance components. In this set of works, there was developed several empirical researches whose main purpose was to quantify the importance of factors as industrial sector, year, corporate affiliation and idiosyncratic issues in explaining the firm performance. From the results presented in these papers several discussions raised about the hole of corporate strategy and about the relative importance of those factors in the determination of the competitive advantage. The investigation developed in this work, which is aligned with this set of researches, uses a broad and complete data base of Brazilians´ firms, first, to verify if the findings about international firms are similar to Brazilian firms. Second, develop new analysis using linear mixed models, which are theoretically more appropriate for this type of analysis. Third, by the use of two types of covariance matrices, test the existence of repeated measures for the variable year, to verify if the results of performance of a year influence the performance of the subsequent years. Finally, it is analyzed if being established in a specific Brazilian State impacts the firm performance.