This paper seeks to investigate the current state of market integration among European electricity day-ahead spot prices. We provide reasoning that market integration brings about benefits, such as lower average prices and increased welfare from allocative efficiency. Yet, price convergence leads to higher prices in the low-price market and to lower prices in the high-price market, which creates winners and losers and thus makes the political implementation of market integration cumbersome. In our empirical analysis, we utilize a large sample of hourly spot prices of 25 European markets for the period 01.01.2010-30.06.2015 and combine it with other relevant data such as interconnector capacities and the existence of market coupling. Firstly, empirical results from cointegration analysis indicate that market integration increased from 2010 to 2012 but then declined until 2015, most likely due to increased feed-in from intermittent renewables. Secondly, we empirically assess the speed of adjustment from price shocks and reach the conclusion that the resulting efficiency of integration is rather modest. In general, our findings suggest that integration among European electricity markets has a large potential for improvements from additional capacity investments and further promotion of market coupling. (authors' abstract) / Series: Department of Economics Working Paper Series

Traffic safety at intersections is a particularly difficult phenomenon to study, given the fact that accidents occur randomly in time and space thereby making short-term measurement, assessment and comparison difficult. The EU directive 2008/96/EC introduced road infrastructure safety management, which offers a five layer structure for developing safer road infrastructure has been used to develop tools for accident prediction and black spot management analysis which has been applied in this work to assess the safety level of intersections in Norrköping city in Sweden. Accident data history from STRADA (Swedish Traffic Accident Data Acquisition) and the network demand model for Norrköping city were used to model black spots and predict the expected number of accidents at intersections using PTV Visum Safety tool, after STRADA accident classification was restructured and the Swedish accident prediction model (APM) was configured and tested to work within the tool using the model from the Swedish road administration (SRA). The performance of the default (Swiss) and the Swedish APM was compared and identified locations with the high accident records, predicted accident counts and traffic volumes were audited using qualitative assessment checklist from Street-Audit tool. The results from these methods were analysed, validated and compared. This work provides recommendations on the used quantitative and qualitative methods to prevent accident occurrence at the identified locations.

The filamentous ascomycete fungus Magnaporthe oryzae is a pathogen of over 50 genera of grasses. Two important diseases it can cause are gray leaf spot in Lolium perenne (perennial ryegrass) and blast in Oryza sativa (rice). The telomeres of M. oryzae isolates causing gray leaf spot are highly variable, and can spontaneously change during fungal culture. In this dissertation, it is shown that a rice-infecting isolate is much more stable at the telomeres than an isolate from gray leaf spot. To determine the molecular basis of telomere instability several gray leaf spot isolates telomeres were cloned, which revealed two non-LTR retrotransposons inserted into the telomere repeats. The elements have been termed Magnaporthe oryzae Telomeric Retrotransposons (MoTeRs). These elements do not have poly-A tails common to many other non-LTR retrotransposons, but instead have telomere like sequences at their 5’ end that allow them to insert into telomeres. Intact copies of MoTeRs were restricted to the telomeres of isolates causing gray leaf spot. Surveys for the presence of these elements in M. oryzae showed they were present in several host-specialized forms including gray leaf spot isolates, but were largely absent in the rice blast isolates. The absence of MoTeRs in rice blast isolates, which are relatively stable by comparison, suggested that the telomere instability in gray leaf spot isolates could be due to MoTeRs. Analyzing spontaneous alterations in telomere restriction fragment profiles of asexual progeny revealed that MoTeRs were involved. Expansion and contraction of MoTeR arrays were observed and account for some telomere restriction profile changes. New telomere formation in asexual progeny followed by MoTeR addition was also observed. Based on this evidence, MoTeRs are largely responsible for the high variability of telomere restriction profiles observed in GLS isolates.

The purpose of this research is to study and improve decision accuracy in the real world. Spot price prediction of petroleum products, in a budgeting context, is the task chosen to study prediction accuracy. Prediction accuracy of executives in a multinational oil company is examined. The Brunswik Lens Model framework is used to evaluate prediction accuracy. Predictions of the individuals, the composite group (mathematical average of the individuals), the interacting group, and the environmental model were compared. Predictions of the individuals were obtained through a laboratory experiment in which experts were used as subjects. The subjects were required to make spot price predictions for two petroleum products. Eight predictor variables that were actually used by the subjects in real-world predictions were elicited through an interview process. Data for a 15 month period were used to construct 31 cases for each of the two products. Prediction accuracy was evaluated by comparing predictions with the actual spot prices. Predictions of the composite group were obtained by averaging the predictions of the individuals. Interacting group predictions were obtained ex post from the company's records. The study found the interacting group to be the least accurate. The implication of this finding is that even though an interacting group may be desirable for information synthesis, evaluation, or working toward group consensus, it is undesirable if prediction accuracy is critical. The accuracy of the environmental model was found to be the highest. This suggests that apart from random error, misweighting of cues by individuals and groups affects prediction accuracy. Another implication of this study is that the environmental model can also be used as an additional input in the prediction process to improve accuracy.

<p>Cumulon is a system aimed at simplifying the development and deployment of statistical analysis of big data in public clouds. Cumulon allows users to program in their familiar language of matrices and linear algebra, without worrying about how to map data and computation to specific hardware and cloud software platforms. Given user-specified requirements in terms of time, monetary cost, and risk tolerance, Cumulon automatically makes intelligent decisions on implementation alternatives, execution parameters, as well as hardware provisioning and configuration settings -- such as what type of machines and how many of them to acquire. Cumulon also supports clouds with auction-based markets: it effectively utilizes computing resources whose availability varies according to market conditions, and suggests best bidding strategies for them. Cumulon explores two alternative approaches toward supporting such markets, with different trade-offs between system and optimization complexity. Experimental study is conducted to show the efficiency of Cumulon's execution engine, as well as the optimizer's effectiveness in finding the optimal plan in the vast plan space.</p> / Dissertation

Land cover classification using artificial neural networks Abstract This Diploma thesis deals with automatic classification of the satellite high spatial resolution image in the field of land cover. The first half of the work contains the theoretical information about remote sensing and classification methods. The biggest attention is given to the artificial neural networks. In practical part of Diploma thesis are these methods used for the classification of SPOT satellite image. Keywords: remote sensing, image classification, artificial neural networks, SPOT

The aim of this work is to design automatic detection of spot heights from airborne laser scanning data and its generalization. The first part is about the idea of spot height: the importance of spot heights for altimetry representation on maps and suggestions concerning the scatter of spot heights on maps. In the following part, different approaches for terrain critical points extraction (peaks, depressions, passes) from digital terrain models are described as suitable places for spot heights location. Further, we introduce a description of geomorphological characteristics of these points by which is possible to identify its significance and generalize them. In accordance to analysis of Základní mapa ČR and recommendation for spot heights location described in literature we designed own method of automatic generation and generalization spot heights from digital terrain models. This method were implemented and there is a description of the test data and results on the real data DMR 5G of the algorithm in the end of the work. Powered by TCPDF (www.tcpdf.org)

Title: Application meteorology and historical comparison between weather(meteorological) conditions for yachting and water sports Objectives: To be making maps about windsurfing sports within specific locations. Prove or disprove scientific research about weather conditions changing from 1980 to 2014 years. It's about yachting and water sports at the same locations. Methods: Diploma is descriptive and analytic article. There are methods like research, selections of sources, analysis of information and final synthesis everything knowledge. Results: Description four water ponds for water sports and analytic work with database about weather conditions in the studying locations. Keywords: Meteorology, wind, spot, water sport, yachting.

Title: Use of meteorology and historicalcomparisons atmospheric conditions for yachting and water. Objectives: At work I use two basic methods of research. The method of content analysis and interview. Content analysis, I get the information for the theoretical part of the work, using professional sailing and meteorological publications. Furthermore, the method of non-standardized interview, which I took while visiting Mathematics - Physics Faculty at Charles University, Department of Meteorology and Climatology. Here I have discussed his work with Dr.. Joseph Brechler, PhD. Furthermore, with top windsurfing in the Black foothills and Nechranické dam. Methods: At work I used as a basic research methods method of content analysis and interview. Content analysis, I gained information for the theoretical part, the professional sailing and meteorological publications that deal with the issue. Non-standardized interview method I used when visiting Mathematics - Physics Faculty at Charles University, Department of Meteorology and Climatology. Here I discuss my work with Dr.. Joseph Brechler, PhD., Then Ing. Ružbatský in the foothills of the Black and F.Kasík of Nechranice. For wider acquaintance with the issues I was trying to get other sources of information on various internet portals related to...

In this work, melt pool size in process mapped in power-velocity space for multiple processes and alloys. In the electron beam wire feed and laser powder feed processes, melt pool dimensions are then related to microstructure in the Ti-6Al-4V alloy. In the electron beam wire feed process, work by previous authors that related prior beta grain size to melt pool area is extended and a control scheme is suggested. In the laser powder feed process, in situ thermal imaging is used to monitor melt pool length. Real time melt pool length measurements are used in feedback control to manipulate the resulting microstructure. In laser and electron beam direct metal additive manufacturing, characteristics of the individual melt pool and the resulting final parts are a product of a variety of process parameters. Laser or electron beam spot size is an important input parameter that can affect the size and shape of a melt pool, and has a direct influence on the formation of lack-of-fusion and keyholing porosity. In this work, models are developed to gain a better understanding of the effects of spot size across different alloys and processes. Models are validated through experiments that also span multiple processes and alloys. Methods to expand the usable processing space are demonstrated in the ProX 200 laser powder bed fusion process. In depth knowledge of process parameters can reduce the occurrence of porosity and flaws throughout processing space and allow for the increased use of non-standard parameter sets. Knowledge of the effects of spot size and other process parameters can enable an operator to expand the usable processing space while avoiding the formation of some types of flaws. Based on simulation and experimental results, regions where potential problems may occur are identified and process parameter based solutions are suggested. Methods to expand the usable processing space are demonstrated in the ProX 200 laser powder bed fusion process. In depth knowledge of process parameters can reduce the occurrence of porosity and flaws throughout processing space and allow for the increased use of non-standard parameter sets.