The study of Stochastic Local Search (SLS) algorithms is becoming more pivotal these days, due to their vast number of applications in decision making. Prior to the implementation of algorithmic knowledge for decision making, many decisions were made based on manual calculation, on the fly, or even based on guts feeling. Nowadays, such an approach is more rarely seen, especially when the decisions that need to be made are high-risk, cost intensive, or time-consuming. The increasingly often used SLS algorithms are one of the options available to assist the decision making process these days.The work discussed in this thesis concerns the study of SLS algorithms for solving the Quadratic Assignment Problem (QAP), a prominent combinatorial optimization problem, which until today is very hard to solve. Our interest is to study the behavior and performance of SLS algorithms for solving QAP instances of different characteristics, such as size, sparsity, and structure. In this study, we have also proposed new variants of SLS algorithms, inspired by existing, well-performing SLS algorithms for solving the QAP. The new variants of SLS algorithms are then further extended for solving the bi-objective QAP (bQAP).One main focus in this study is to see how the performance of algorithms scales with instance size. We have considered instances that are much larger than the ones usually used in the studies of algorithms for solving the QAP. By understanding how the algorithms perform when the instance size changes, we might be able to solve other problems effectively by considering the similarity in their characteristics to the ones of the QAP, or by seeing common trends in the relative performance of the various available SLS methods. For single objective QAP instances we found that the structure and size of instances do have a significant impact on the performance of SLS algorithms. For example, comparisons between Tabu Search (TS) and Simulated Annealing (SA) on instances with randomly generated matrices show that the overall performance of TS is better than SA, irrespective the size of instances considered. The results on a class of structured instances however show that TS performs well on small-sized instances, while on the larger ones, SA shows better results. In another experiment, Hierarchical Iterated Local Search (HILS) has shown very good results compared to several Iterated Local Search (ILS) variants. This experiment was done on a class of structured instances of size from 100 to 500. An extensive experiment on a class of structured instances of size 30 to 300 using tuned parameter settings shows that population based algorithms perform very well on most of the instance classes considered. SA however, shows very good performance especially on large-sized instances with low sparsity level. For the bQAP, the correlation between the flow matrices does have a strong effect that determines the performance of algorithms for solving them. Hybrid Simulated Annealing (HSA) clearly outperforms Hybrid Iterative Improvement (HII). When compared to Multi Objective Ant Colony Optimization (MOACO) and Strength Pareto Evolutionary Algorithm 2 (SPEA2), HSA shows very good performance, where HSA outperforms MOACO and SPEA2, especially on instances of large size, thus, offering a better scaling behavior. Based the results obtained in this study, it is possible to come up with a general idea on the suitability of SLS algorithms for solving instances with a certain characteristic. Given an unknown QAP instance, one can guess the most suitable algorithm for solving it depending on the type, size, and sparsity of the instance, while for a bQAP instance the most suitable algorithm can be guessed based on its size and correlation between the flow matrices. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

Tourette’s is currently considered a neurodevelopmental genetic disorder. Georges Gilles de la Tourette is given primary credit for the diagnoses of the disorder in the late 1800s. Clear answers have been elusive although modern research and improvements to neuroimaging have enabled the causal factors of Tourette’s Disorder (TD) to be examined with greater scrutiny. Currently, there is no known cure or pharmaceutical treatment that has been proven 100% effective for all patients and symptoms of Tourette’s. Anecdotally, there have been recent media and self-reports of people diagnosed with Tourette’s finding relief from their symptoms through involvement in focus-based activities such as video games, athletic endeavors and musical engagement, albeit little empirical evidence exists on these subjects. The author is seeking empirical data showing the influence of musical engagement on the symptoms of Tourette’s. This research does not focus on the receptive activity of listening to music, but engagement. This performance-based music making or engagement can be described as the body being physically involved in the creation and production of music which comes from such activities as playing a musical instrument or singing. This study seeks to answer the question, “does musical engagement influence the symptoms of Tourette’s?” A self-reported survey instrument was generated to question those claiming to be musicians who have been diagnosed with TD to explore what effect engaging in a musical activity has on their symptoms. Participants’ responses to ten questions were analyzed. The survey apex involved a Likert-type scale asking to what extent these musicians experienced changes in their symptoms. One hundred eighty-three (N = 183) respondents rated their perceptions from one to five where one equaled drastic symptoms increase by engaging in a musical activity and five equaled drastic symptoms decrease. The mean response from the scale was 4.45, clearly showing that these musicians with TD experienced a great deal of relief when engaged in their activity. This study presents evidence and support for research into neurodevelopmental and musical training correlations and a strong case for childhood music education as a means to facilitate this training.

Many econometric analyses of commodity futures over the years have been performed using spot or front month contract prices. Using such daily prices without the consideration of the associated contract traded volumes is slightly erroneous because, in reality, traders will typically trade the ‘most liquid’ contract, that is, the contract with the largest average daily volume (ADV). The reason for this is in order to gain the best price when buying or selling. If this ‘true’ time series is to be considered, a mapping procedure is required to account for the price jumps at the time when a trader trades out of the expiring contract and enters the new front month contract. A key finding was that this effect was significant, irrespective of the size of the price jump, sometimes referred to as basis or roll and also due to the accumulated roll over a number of years corresponding to multiple contracts. It was also found that the mapping procedure has a significant effect on the time series and should hence always be employed if the realistic traded time series is to be considered. Given this phenomenon, algorithmically-traded commodities futures must necessarily employ such time series when creating metrics or considering an econometric analysis. The key findings include the importance of diversification in algorithmically-traded portfolios, utilising the AOM and PSI metrics. The mapping of data sets to create realistic ‘live-traded’ time series was found to be significant, while the optimal day of roll over prior to contract expiry was found to be related to the trading volumes for certain commodities. Other key findings include the causalities and spillovers within the metals sector where various relationships are evident once the results were processed and analysed, both pre and post mapping. Interestingly, the key relationships including bidirectional volatility and shock spillovers between the four key metals existed when the unmapped data was used however, many of the feedbacks within these relationships was lost when the mapped data sets were considered. A significant finding was therefore the consistent differences in findings between mapped and unmapped data sets attributed to the optimisation or favourability of the models (whether econometric or algorithmic). This is due to the unmapped data including roll or basis (which the models are fitted to) taking into account the roll or basis and utilising them in finding relationships between data sets. In the mapped data set (the time series seen by traders) the roll or basis is accounted for and hence the relationships found stand in real-time trading situations. The differences in the results show how the effect of mapping can be significant with unmapped data sets displaying results which will not exist in a real time traded time series.

>Magister Scientiae - MSc / The therapeutic goal of cancer treatment is to trigger selective cell death in cancer cells. To eliminate cancerous cells effectively, the anti–cancer drugs must be targeted to the affected cells. However, anti–cancer drugs are often distributed non–specifically giving rise to systemic toxicities and other adverse effects. Cancer specific peptides are useful cancer targeting agents that can be used for the targeted delivery of anti-cancer drugs. Several cancer targeting peptides and some of their corresponding protein targets have been identified. Previous work investigated the specific binding of five of these peptides (p.C, p.H, p6.1, Frop-1 and p.L) conjugated to fluorescent nanoparticles (quantum dots) to a panel of human cell lines, which included four cancerous cell lines (Caco-2, HeLa, HT29 and HepG2) and one non-cancerous cell line (KMST-6). Flow cytometry showed that the p.L peptide preferentially bind to HT29 cells; suggesting that the expression levels of the target for the p.L peptide are higher in these cells. The objective of this study was to make use of target specific functionalised quantum dots (QDs) to deliver Second mitochondria-derived activator of caspases/ Direct AIP binding protein with low PI (Smac/DIABLO) to HT29 cells with the aim of enhancing the effects of pro-apoptotic drugs. Smac/DIABLO is a pro-apoptotic peptide that is able to interact with inhibitor of apoptosis proteins (IAPs), thereby inducing pro-apoptotic signalling. Methodology: CdSe/ZnS core-shell QDs were synthesised using the one-pot synthesis method. These QDs were characterised using photoluminescence (PL) spectroscopy, high resolution transmission electron microscopy (HR-TEM) and energy dispersive x-ray spectroscopy (EDS). The CdSe/ZnS core-shell QDs were solubilised with L-cysteine (Cys- QDs). The Cys-QDs were bi-conjugated to the p.L peptide and Smac peptide using 1-ethyl-3- (30-dimethylamino) carbodiimide (EDC) chemistry. Cultured HT29 cells were exposed to the 10 | P a g e QD peptide bi-conjugates and fluorescence microscopy was employed to assess targeting and internalisation. The cytotoxicity of the QD peptide bi-conjugates in combinatorial treatment with ceramide was evaluated using the WST-1 Cell Proliferation assay. A commercially available QD with similar chemistry was used to carry out a comparative study to relate the efficiency of the in-house synthesized QD.

Transportation system is one of the key functioning components of the modern society and plays an important role in the circulation of commodity and growth of economy. Transportation system is not only the major influencing factor of the efficiency of large-scale complex industrial logistics, but also closely related to everyone’s daily life. The goals of an ideal transportation system are focused on improving mobility, accessibility, safety, enhancing the coordination of different transportation modals and reducing the impact on the environment, all these activities require sophisticated design and plan that consider different factors, balance tradeoffs and maintaining efficiency. Hence, the design and planning of transportation system are strongly considered to be the most critical problems in transportation research. Transportation system planning and design is a sequential procedure which generally contains two levels: strategic and operational. This dissertation conducts extensive research covering both levels, on the strategic planning level, two network design problems are studied and on the operational level, routing and scheduling problems are analyzed. The main objective of this study is utilizing operations research techniques to generate and provide managerial decision supports in designing reliable and efficient transportation system. Specifically, three practical problems in transportation system design and operations are explored. First, we collaborate with a public transit company to study the bus scheduling problem for a bus fleet with multiples types of vehicles. By considering different cost characteristics, we develop integer program and exact algorithm to efficiently solve the problem. Next, we examine the network design problem in emergency medical service and develop a novel two stage robust optimization framework to deal with uncertainty, then propose an approximate algorithm which is fast and efficient in solving practical instance. Finally, we investigate the major drawback of vehicle sharing program network design problem in previous research and provide a counterintuitive finding that could result in unrealistic solution. A new pessimistic model as well as a customized computational scheme are then introduced. We benchmark the performance of new model with existing model on several prototypical network structures. The results show that our proposed models and solution methods offer powerful decision support tools for decision makers to design, build and maintain efficient and reliable transportation systems.

The main focus of this thesis was to gain a better understanding about the dynamics of risk perception and its influence on people’s evacuation behavior. Another major focus was to improve our knowledge regarding geo-spatial and temporal variations of risk perception and hurricane evacuation behavior. A longitudinal dataset of more than eight hundred households were collected following two major hurricane events, Ivan and Katrina. The longitudinal survey data was geocoded and a geo-spatial database was integrated to it. The geospatial database was composed of distance, elevation and hazard parameters with respect to the respondent’s household location. A set of Bivariate Probit (BP) model suggests that geospatial variables have had significant influences in explaining hurricane risk perception and evacuation behavior during both hurricanes. The findings also indicated that people made their evacuation decision in coherence with their risk perception. In addition, people updated their hurricane evacuation decision in a subsequent similar event.

This thesis covers three different topics. The first part is a pedagogical review of the basic principles and recent advances in nonlinear optics. It was originally written as a chapter for the proceedings of the “International School of Physics (Enrico Fermi)” summer school on Photonics held in June, 2014. It is included to provide some background information about nonlinear optical processes in general, and is particularly relevant for the third part of this thesis which is based on the second-order nonlinear optical process of spontaneous parametric downconversion. The second part is based on original research, and deals with superradiance in plasmonic nanostructures. The process of superradiance, as introduced by Dicke in 1954, entails the shortening of the spontaneous emission lifetime of a collection of N quantum emitters as a consequence of the development of a macroscopic dipole moment. Specifically, the lifetime is shortened by a factor of 1/N, and the linewidth is broadened by a factor of N. Such a linewidth dependence has been previously observed in systems of several plasmonic ‘emitters’. However, a clear physical insight into this phenomenon and how it relates to Dicke superradiance has not been shown yet. In this part, we demonstrate by experiment, simulation, and a simple analytical model that Dicke’s superradiance can indeed be observed in a planar array of plasmonic nanoantennas, with a linewidth that scales linearly with the number of nanoantennas within a square wavelength. The third part is also based on original research, and is based on the scal- ing laws of spontaneous parametric downconversion (SPDC) for a type-I phase- matching configuration. The variation of bi-photon generation rate, heralding efficiency and radiance with parameters such as crystal length, pump focussing and collection waist sizes are examined for collinear and non-collinear emission. The results can be used to maximize the brightness of the SPDC source or increase the heralding efficiency depending on the application.

První část této diplomové práce je zaměřena na vymezení základních aspektů Business Intelligence a její popis, který může být určen k prostudování, jakožto úvod pro jedince této problematiky neznalé. Základní myšlenky a principy jsou vysvětlovány na názorných obrázcích. Ideje zde přednesené ale mohou dále sloužit jako ?jiný? pohled určený k dalšímu uvažování o těchto základních otázkách. Následně se práce zabývá implementací Business Intelligence v organizaci a některými souvislostmi v projektu Business Intelligence. Shrnutí doporučení uváděných v literatuře a nejen z nich vyúsťující návrhy ETL standardů jsou poslední teoretickou částí. Práce je uzavřena dokumentací k projektu Reportingového systému, resp. především části ETL, kterou autor v době psaní textu zpracovával (neveřejná část práce)

Diplomová práce se zabývá využitím aplikační a integrační platformy SAP NetWeaver 7.0 v oblasti business intelligence a data warehousingu. Hlavním cílem a obsahem této práce je(1) Posoudit, zda je společnost SAP schopna díky akvizici firmy Business Objects splnit své cíle (viz kapitola 5.2.1) a vzájemnou integrací business intelligence (BI) nástrojů posílit svou pozici na tomto trhu a odstranit hlavní nedostatky řešení SAP NetWeaver BI (viz kapitola 4.2). (2) Vzájemně, na základě předem zvolených parametrů, porovnat business intelligence nástroje společnosti SAP a Business Objects s konkurenčními produkty firmy Cognos. Na základě porovnání pak vytvořit hodnocení. (3) Zmapovat pozici SAPu na trhu business intelligence řešení a vytvořit vodítko pro konzultanta, který se zajímá o možnosti uplatnění v této oblasti.

The thesis deals with banking data warehouse and the factors which influence their architecture. The goal of the thesis is to analyze the influence by fulfilling the three partial goals -- defining banks' requirements on data warehouses, analyzing a data warehouse in the real banking environment and making a comparison of the Czech banks' data warehouses. First, the thesis briefly introduces elements of business intelligence (BI) and data warehousing. Second, after deducing reasons for BI implementation in commercial banks, the requirements on data warehouse are synthesized and their impacts on the data warehouse architecture are analyzed. Finally, conclusions of the thesis are applied on creation of the survey which enables comparison of the Czech banks' data warehouses. The thesis applies the theory of relationship between BI maturity, requirements on BI and data warehouse architecture and creates a tool for evaluating and comparing the data warehouses of banks with respect to bank's BI maturity and predisposition for a particular architecture. The tool can serve as a basis for a general tool able to compare data warehouses in other branches of economy and can help to better understand relations between organizations' need for information, BI solutions used and underlying data warehouses.