Microstructure characterization of 316L deformed at high strain rates using EBSD

Specimens from split Hopkinson pressure bar experiments, at strain rates between ~ 1000–9000 s− 1 at room temperature and 500 °C, have been studied using electron backscatter diffraction. No significant differences in the microstructures were observed at different strain rates, but were observed for different strains and temperatures. Size distribution for subgrains with boundary misorientations > 2° can be described as a bimodal lognormal area distribution. The distributions were found to change due to deformation. Part of the distribution describing the large subgrains decreased while the distribution for the small subgrains increased. This is in accordance with deformation being heterogeneous and successively spreading into the undeformed part of individual grains. The variation of the average size for the small subgrain distribution varies with strain but not with strain rate in the tested interval. The mean free distance for dislocation slip, interpreted here as the average size of the distribution of small subgrains, displays a variation with plastic strain which is in accordance with the different stages in the stress-strain curves. The rate of deformation hardening in the linear hardening range is accurately calculated using the variation of the small subgrain size with strain.

High-growth firms : Not so vital after all?

High-growth firms have received considerable interest recently since they create most of the new jobs in the economy. The purpose of our paper is to investigate the characteristics of high-growth firms prior to their growth period, and whether these characteristics differ across industries. Using data on a large sample of limited liability firms in Sweden for the period 2007-2010, we find that high-growth firms do not have the characteristics that we typically associate with successful firms. On the contrary, our results indicate that high-growth firms have low profits and a weak financial position. This might explain why studies have found that high-growth firms are seldom capable of sustaining their high growth rates in subsequent periods, and thus question policies that are targeted towards these companies.

Energy efficient and economic renovation of residential buildings with low-temperature heating and air heat recovery

With the building sector accounting for around 40% of the total energy consumption in the EU, energy efficiency in buildings is and continues to be an important issue. Great progress has been made in reducing the energy consumption in new buildings, but the large stock of existing buildings with poor energy performance is probably an even more crucial area of focus. This thesis deals with energy efficiency measures that can be suitable for renovation of existing houses, particularly low-temperature heating systems and ventilation systems with heat recovery. The energy performance, environmental impact and costs are evaluated for a range of system combinations, for small and large houses with various heating demands and for different climates in Europe. The results were derived through simulation with energy calculation tools. Low-temperature heating and air heat recovery were both found to be promising with regard to increasing energy efficiency in European houses. These solutions proved particularly effective in Northern Europe as low-temperature heating and air heat recovery have a greater impact in cold climates and on houses with high heating demands. The performance of heat pumps, both with outdoor air and exhaust air, was seen to improve with low-temperature heating. The choice between an exhaust air heat pump and a ventilation system with heat recovery is likely to depend on case specific conditions, but both choices are more cost-effective and have a lower environmental impact than systems without heat recovery. The advantage of the heat pump is that it can be used all year round, given that it produces DHW. Economic and environmental aspects of energy efficiency measures do not always harmonize. On the one hand, lower costs can sometimes mean larger environmental impact; on the other hand there can be divergence between different environmental aspects. This makes it difficult to define financial subsidies to promote energy efficiency measures.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Are central bank independence reforms necessary for achieving low and stable inflation?

Using data on the occurence of central bank independence (CBI) reforms in 131 countries during 1980-2005, we test whether they were important in reducing inflation and maintaining price stability. CBI reforms are found to have reduced inflation on average 3.31% when countries with historically high inflation rates are included. But countries with lower inflation have reduced it without institutional reforms granting central banks more independence, undermining the theoretical time-inconsistency case for CBI. There is furthermore no evidence that CBI reforms have helped reduce inflation variability.

Determinants and effects of central bank independence reforms

This thesis consists of four empirically oriented papers on central bank independence (CBI) reforms.    Paper [1] is an investigation of why politicians around the world have chosen to give up power to independent central banks, thereby reducing their ability to control the economy. A new data-set, including the possible occurrence of CBI-reforms in 132 countries during 1980-2005, was collected. Politicians in non-OECD countries were more likely to delegate power to independent central banks if their country had been characterized by high variability in inflation and if they faced a high probability of being replaced. No such effects were found for OECD countries.    Paper [2], using a difference-in-difference approach, studies whether CBI reform matters for inflation performance. The analysis is based on a dataset including the possible occurrence of CBI-reforms in 132 countries during the period of 1980-2005. CBI reform is found to have contributed to bringing down inflation in high-inflation countries, but it seems unrelated to inflation performance in low-inflation countries.    Paper [3] investigates whether CBI-reforms are important in reducing inflation and maintaining price stability, using a random-effects random-coefficients model to account for heterogeneity in the effects of CBI-reforms on inflation. CBI-reforms are found to have reduced inflation on average by 3.31 percent, but the effect is only present when countries with historically high inflation rates are included in the sample. Countries with more modest inflation rates have achieved low inflation without institutional reforms that grant central banks more independence, thus undermining the time-inconsistency theory case for CBI. There is furthermore no evidence that CBI-reforms have contributed to lower inflation variability    Paper [4] studies the relationship between CBI and a suggested trade-off between price variability and output variability using data on CBI-levels, and data the on implementation dates of CBI-reforms. The results question the existence of such a trade-off, but indicate that there may still be potential gains in stabilization policy from CBI-reforms.

Simulation study of cascade heat pump for solar combisystems

This paper focuses on the study of cascade heat pump systems in combination with solar thermal for the production of hot water and space heating in single family houses with relatively high heating demand. The system concept was developed by Ratiotherm GmbH and simulated with TRNSYS 17. The basic cascade system uses the heat pump and solar collectors in parallel operation while a further development is the inclusion of an intermediate store that enables the possibility of serial/parallel operation and the use of low temperature solar heat. Parametric studies in terms of compressor size, refrigerant pair and size of intermediate heat exchanger were carried out for the optimization of the basic system. The system configurations were simulated for the complete year and compared to a reference of a solar thermal system combined with an air source heat pump. The results show ~13% savings in electricity use for all three cascade systems compared to the reference. However, the complexity of the systems is different and thus higher capital costs are expected.

Soft computing in biometrics : a pragmatic appraisal

The ever increasing spurt in digital crimes such as image manipulation, image tampering, signature forgery, image forgery, illegal transaction, etc. have hard pressed the demand to combat these forms of criminal activities. In this direction, biometrics - the computer-based validation of a persons' identity is becoming more and more essential particularly for high security systems. The essence of biometrics is the measurement of person’s physiological or behavioral characteristics, it enables authentication of a person’s identity. Biometric-based authentication is also becoming increasingly important in computer-based applications because the amount of sensitive data stored in such systems is growing. The new demands of biometric systems are robustness, high recognition rates, capability to handle imprecision, uncertainties of non-statistical kind and magnanimous flexibility. It is exactly here that, the role of soft computing techniques comes to play. The main aim of this write-up is to present a pragmatic view on applications of soft computing techniques in biometrics and to analyze its impact. It is found that soft computing has already made inroads in terms of individual methods or in combination. Applications of varieties of neural networks top the list followed by fuzzy logic and evolutionary algorithms. In a nutshell, the soft computing paradigms are used for biometric tasks such as feature extraction, dimensionality reduction, pattern identification, pattern mapping and the like.

Pedagogical Methods in Web-Based Language Teaching

This paper presents a research project that is being conducted at Dalarna University in Sweden. The aim is to study the following: 1) The quality of online language education compared with that of campus education, and 2) Advantages and disadvantages of online language education and how the disadvantages might be overcome. The project consists of two parts: pedagogical methods in online language education from the teachers’ point of view and from the students’ point of view. The first part was conducted in 2012 and various characteristics (benefits and difficulties) of online language education were identified. Flexibility and wider opportunities were general benefits, while lack of physical co-presence, difficulty in having lively debates/discussions, and high dropout rates were among the problems. The second part of the project (being conducted in 2014) aims to investigate how students experience online language learning. The goal is to explore alignments and misalignments between teachers’ perspectives and students’ perspectives, and to develop methods to enhance the quality of online education.

Convex Hulls in Image Processing : A Scoping Review

The demands of image processing related systems are robustness, high recognition rates, capability to handle incomplete digital information, and magnanimous flexibility in capturing shape of an object in an image. It is exactly here that, the role of convex hulls comes to play. The objective of this paper is twofold. First, we summarize the state of the art in computational convex hull development for researchers interested in using convex hull image processing to build their intuition, or generate nontrivial models. Secondly, we present several applications involving convex hulls in image processing related tasks. By this, we have striven to show researchers the rich and varied set of applications they can contribute to. This paper also makes a humble effort to enthuse prospective researchers in this area. We hope that the resulting awareness will result in new advances for specific image recognition applications.