Programming and analysing measurement experiments using the PicoCricket system

The aim of this project is to get used to another kind of programming. Since now, I used very complex programming languages to develop applications or even to program microcontrollers, but PicoCricket system is the evidence that we don’t need so complex development tools to get functional devices. PicoCricket system is the clear example of simple programming to make devices work the way we programmed it. There’s an easy but effective way to programs mall devices just saying what we want them to do. We cannot do complex algorithms and mathematical operations but we can program them in a short time. Nowadays, the easier and faster we produce, the more we earn. So the tendency is to develop fast, cheap and easy, and PicoCricket system can do it.

Engendering Group Support Based Foresight for Capital Intensive Manufacturing Industries - Case Paper and Steel Industry Scenarios by 2018

In recent times of global turmoil, the need for uncertainty management has become ever momentous. The need for enhanced foresight especially concerns capital-intensive industries, which need to commit their resources and assets with long-term planning horizons. Scenario planning has been acknowledged to have many virtues - and limitations - concerning the mapping of the future and illustrating the alternative development paths. The present study has been initiated to address both the need of improved foresight in two capital-intensive industries, i.e. the paper and steel industries and the imperfections in the current scenario practice. The research problem has been approached by engendering a problem-solving vehicle, which combines, e.g. elements of generic scenario process, face-to-face group support methods, deductive scenario reasoning and causal mapping into a fully integrated scenario process. The process, called the SAGES scenario framework, has been empirically tested by creating alternative futures for two capital-intensive industries, i.e. the paper and steel industries. Three scenarios for each industry have been engendered together with the identification of the key megatrends, the most important foreign investment determinants, key future drivers and leading indicators for the materialisation of the scenarios. The empirical results revealed a two-fold outlook for the paper industry, while the steel industry future was seen as much more positive. The research found support for utilising group support systems in scenario and strategic planning context with some limitations. Key perceived benefits include high time-efficiency, productivity and lower resource-intensiveness. Group support also seems to enhance participant satisfaction, encourage innovative thinking and provide the users with personalised qualitative scenarios.

Patient education to support self-management of patients with mental illness

This study explores areas which need to be improved to develop the quality of patient education to support self-management of patients with mental illness in psychiatric hospitals. The study was conducted in five phases during the period 2000 – 2007. First, patients‘ (n = 313) satisfaction with patient education were investigated. Second, patients' (n = 51) experiences of patient education were explored. Third, a national survey was conducted to investigate realisation of patient education from the staff (n = 55) viewpoint. Fourth, outcomes of patient education were investigated by evaluating the impacts of different patient education methods on patients‘ (n = 311) attitudes towards medication, knowledge level and importance of information. Fifth, patients‘ (n = 16) perceptions of different patient education methods were explored. Patients reported poor satisfaction with patient education (Phase I), and they have considerable need to receive information during their hospital stay (Phase II). Described by staff, the content of patient education covered almost all informational areas investigated. However, discrepancies related to the realisation of patient education were found. (Phase III.) Evaluation of different patient education methods indicate that patients derived benefits from structured patient education with supportive methods (Phase IV) and patients also perceived that these methods supported their information receiving (Phase V). In order to improve the quality of patient education to support self-management of patients with mental illness patient education should be systematically and individually provided to all patients by using different educational methods. Realisation of this should be ensured by providing written instructions, improving nurses‘ knowledge and skills as well ensuring operating conditions.

Synthesis of quinoxaline 1,4-di-N-oxide derivatives on solid support using room temperature and microwave-assisted solvent-free procedures

We describe the synthesis of 12 new ethyl and methyl quinoxaline-7-carboxylate 1,4-di-N-oxide derivatives on solid supports with room temperature and microwave-assisted solvent-free procedures. Results show that solid supports have good catalytic activity in the formation of quinoxaline 1,4-di-N-oxide derivatives. We found that florisil and montmorillonite KSF and K10 could be used as new, easily available, inexpensive alternatives of catalysts. Additionally, room temperature and microwave-irradiation solvent-free synthesis was more efficient than a conventional procedure (Beirut reaction), reducing reaction time and increasing yield.

Sodium dodecyl sulfate coated γ-alumina support modified by a new Schiff base for solid phase extraction and flame-AAS determination of lead and copper ions

A simple and fast approach for solid phase extraction is herein described, and used to determine trace amounts of Pb2+ and Cu2+ metal ions. The solid phase support is sodium dodecyl sulfate (SDS)-coated γ-alumina modified with bis(2-hydroxy acetophenone)-1,6-hexanediimine (BHAH) ligand. The adsorbed ions were stripped from the solid phase by 6 mL of 4 M nitric acid as eluent. The eluting solution was analyzed by flame atomic absorption spectrometry (FAAS). The sorption recovery of metal ions was investigated with regard to the effects of pH, amount of ligand, γ-alumina and surfactant and the amount and type of eluent. Complexation of BHAH with Pb2+ or Cu2+ ions was examined via spectrophotometry using the HypSpec program. The detection limit for Cu2+ was 7.9 µg L-1 with a relative standard deviation of 1.67%, while that for Pb2+ was 6.4 µg L-1 with a relative standard deviation of 1.64%. A preconcentration factor of 100 was achieved for these ions. The method was successfully applied to determine analyte concentrations in samples of liver, parsley, cabbage, and water.

METHANE DRY REFORMING OVER Ni SUPPORTED ON PINE SAWDUST ACTIVATED CARBON: EFFECTS OF SUPPORT SURFACE PROPERTIES AND METAL LOADING

The influence of metal loading and support surface functional groups (SFG) on methane dry reforming (MDR) over Ni catalysts supported on pine-sawdust derived activated carbon were studied. Using pine sawdust as the catalyst support precursor, the smallest variety and lowest concentration of SFG led to best Ni dispersion and highest catalytic activity, which increased with Ni loading up to 3 Ni atoms nm-2. At higher Ni loading, the formation of large metal aggregates was observed, consistent with a lower "apparen" surface area and a decrease in catalytic activity. The H2/CO ratio rose with increasing reaction temperature, indicating that increasingly important side reactions were taking place in addition to MDR.

A FTIR study of the metal-support interactions and hydrogen spillover on Pd/TiO2 and Ni/TiO2

Nickel and palladium dispersed on titania support were submitted to reductive treatment, under hydrogen, at 200 and 500 ºC. After the reductive thermal treatment the materials were exposed to carbon monoxide (10 Torr) and analyzed in the infrared region. The increasing of the electronic density in the metallic d subshell, produced by the reductive thermal treatment, was monitored by the infrared stretching band shift of carbon monoxide adsorbed and it was interpreted as a consequence of the metal-support interactions. The highest effect was observed for Pd/TiO2 system. From the FTIR spectra was also observed that the hydrogen spillover was stronger on Pd/TiO2 than Ni/TiO2 system.

Early nutritional determinants in cardio-metabolic programming – A prospective randomized controlled dietary intervention study

Western societies have been faced with the fact that overweight, impaired glucose regulation and elevated blood pressure are already prevalent in pediatric populations. This will inevitably mean an increase in later manifestations of cardio-metabolic diseases. The dilemma has been suggested to stem from fetal life and it is surmised that the early nutritional environment plays an important role in the process called programming. The aim of the present study was to characterize early nutritional determinants associating with cardio-metabolic risk factors in fetuses, infants and children. Further, the study was designated to establish whether dietary counseling initiated in early pregnancy can modify this cascade. Healthy mother-child pairs (n=256) participating in a dietary intervention study were followed from early pregnancy to childhood. The intervention included detailed dietary counseling by a nutritionist targeting saturated fat intake in excess of recommendations and fiber consumption below recommendations. Cardio-metabolic programming was studied by characterizing the offspring’s cardio-metabolic risk factors such as over-activation of the autonomic nervous system, elevated blood pressure and adverse metabolic status (e.g. serum high split proinsulin concentration). Fetal cardiac sympathovagal activation was measured during labor. Postnatally, children’s blood pressure was measured at six-month and four-year follow-up visits. Further, infants’ metabolic status was assessed by means of growth and serum biomarkers (32-33 split proinsulin, leptin and adiponectin) at the age of six months. This study proved that fetal cardiac sympathovagal activity was positively associated with maternal pre-pregnancy body mass index indicating adverse cardio-metabolic programming in the offspring. Further, a reduced risk of high split proinsulin in infancy and lower blood pressure in childhood were found in those offspring whose mothers’ weight gain and amount and type of fats in the diet during pregnancy were as recommended. Of note, maternal dietary counseling from early pregnancy onwards could ameliorate the offspring’s metabolic status by reducing the risk of high split proinsulin concentration, although it had no effect on the other cardio-metabolic markers in the offspring. At postnatal period breastfeeding proved to entail benefits in cardio-metabolic programming. Finally, the recommended dietary protein and total fat content in the child’s diet were important nutritional determinants reducing blood pressure at the age of four years. The intrauterine and immediate postnatal period comprise a window of opportunity for interventions aiming to reduce the risk of cardio-metabolic disorders and brings the prospect of achieving health benefits over one generation.

Teaching mathematics and programming : new approaches with empirical evaluation

Programming and mathematics are core areas of computer science (CS) and consequently also important parts of CS education. Introductory instruction in these two topics is, however, not without problems. Studies show that CS students find programming difficult to learn and that teaching mathematical topics to CS novices is challenging. One reason for the latter is the disconnection between mathematics and programming found in many CS curricula, which results in students not seeing the relevance of the subject for their studies. In addition, reports indicate that students' mathematical capability and maturity levels are dropping. The challenges faced when teaching mathematics and programming at CS departments can also be traced back to gaps in students' prior education. In Finland the high school curriculum does not include CS as a subject; instead, focus is on learning to use the computer and its applications as tools. Similarly, many of the mathematics courses emphasize application of formulas, while logic, formalisms and proofs, which are important in CS, are avoided. Consequently, high school graduates are not well prepared for studies in CS. Motivated by these challenges, the goal of the present work is to describe new approaches to teaching mathematics and programming aimed at addressing these issues: Structured derivations is a logic-based approach to teaching mathematics, where formalisms and justifications are made explicit. The aim is to help students become better at communicating their reasoning using mathematical language and logical notation at the same time as they become more confident with formalisms. The Python programming language was originally designed with education in mind, and has a simple syntax compared to many other popular languages. The aim of using it in instruction is to address algorithms and their implementation in a way that allows focus to be put on learning algorithmic thinking and programming instead of on learning a complex syntax. Invariant based programming is a diagrammatic approach to developing programs that are correct by construction. The approach is based on elementary propositional and predicate logic, and makes explicit the underlying mathematical foundations of programming. The aim is also to show how mathematics in general, and logic in particular, can be used to create better programs.

Pilvisovelluskehitys Google App Engine -pilvisovellusalustalla

Tämä Diplomityö keskittyy tutkimaan pilvisovelluskehitystä Google App Engine – pilvisovellusalustalle perustuen kuusi –vaiheiseen vesiputousmalliin sekä tutkimaan Google App Engine -pilvisovellusalustan tarjoamia mahdollisuuksia ja rajoituksia sovelluskehityksen muodossa. Tutkimuksen perusteella kuusi –vaiheinen vesiputousmalli soveltuu pilvisovelluskehitykseen,mikäli vaatimusmäärittely on tarkka jo sovelluskehityksen alkuvaiheessa. Tutkimuksen tuloksena syntyi vaatimusmäärittely MikkoMail –pilvisovellukselle. Vaatimusmäärittelyn pohjalta luotiin MikkoMail –pilvisovellus Google App Engine –pilvisovellusalustalle. Google App Engine –pilvisovellusalusta tukee vain Python- ja Java –ohjelmointikieliä eikä sisällä lainkaan ulkoista tietokantapalveluiden tukea. Tästä syystä Google App Engine -pilvisovellusalusta soveltuu pieniin, keskisuuriin ja pilottiprojektinomaisiin sovelluskehitysprojekteihin.

Applications of graph transformation in tools for domain-specific modeling languages

The use of domain-specific languages (DSLs) has been proposed as an approach to cost-e ectively develop families of software systems in a restricted application domain. Domain-specific languages in combination with the accumulated knowledge and experience of previous implementations, can in turn be used to generate new applications with unique sets of requirements. For this reason, DSLs are considered to be an important approach for software reuse. However, the toolset supporting a particular domain-specific language is also domain-specific and is per definition not reusable. Therefore, creating and maintaining a DSL requires additional resources that could be even larger than the savings associated with using them. As a solution, di erent tool frameworks have been proposed to simplify and reduce the cost of developments of DSLs. Developers of tool support for DSLs need to instantiate, customize or configure the framework for a particular DSL. There are di erent approaches for this. An approach is to use an application programming interface (API) and to extend the basic framework using an imperative programming language. An example of a tools which is based on this approach is Eclipse GEF. Another approach is to configure the framework using declarative languages that are independent of the underlying framework implementation. We believe this second approach can bring important benefits as this brings focus to specifying what should the tool be like instead of writing a program specifying how the tool achieves this functionality. In this thesis we explore this second approach. We use graph transformation as the basic approach to customize a domain-specific modeling (DSM) tool framework. The contributions of this thesis includes a comparison of di erent approaches for defining, representing and interchanging software modeling languages and models and a tool architecture for an open domain-specific modeling framework that e ciently integrates several model transformation components and visual editors. We also present several specific algorithms and tool components for DSM framework. These include an approach for graph query based on region operators and the star operator and an approach for reconciling models and diagrams after executing model transformation programs. We exemplify our approach with two case studies MICAS and EFCO. In these studies we show how our experimental modeling tool framework has been used to define tool environments for domain-specific languages.