First of all the Internet pages presenting C++ Builder teaching material, are studied in the Master’s thesis. Applied themes are stressed the most of which is lacking in those pages. The aim of the work is – to describe the uses of C++ Builder tools that is - components of various format files (*.bmp, *.wmf, *.emf, *.ico, etc.) used to show images, graphic objects in the form of the program, which can show drawings, schemes, drafts; reading and drawing of random sequences, geometrical figures, function, drawing of analytically given functions and data presented by number sequences, the speech signals and other the sound files. Some examples of reading listening and viewing of the different sound files are also presented. The other important for applications subjects, as databases and programming of connections with databases, problem solutions in the form of algorithms, are also described The optimum algorithms “Division in half” and “Golden section” algorithms are realized in C++ Builder.

Evolutionary psychology explains and predicts human behaviour based on its adaptive value. Some apparently non-adaptive behaviours such as humans’ devotion to music can be explained by sexual selection of costly signals, since it takes time and effort to learn to play an instrument well. Here, participants rated pictures of persons of the opposite sex that were said to play a piece of music that was heard while watching each picture. The music performances were either of low, medium, or high level of skill, and a better performance was predicted to lead to higher ratings of partner attractiveness because it is more costly. No effect of the music was found, except that women rated men as less desirable for a long-term relationships when the skill level was high than when it was medium. / Evolutionspsykologiska teorier förklarar och predicerar mänskligt beteende utifrån dess adaptiva värde. Vissa uppenbart icke-adaptiva beteenden, som människans hängivenhet till musik, kan förklaras som sexuell selektion av kostsamma signaler, eftersom det kräver tid och möda att lära sig bemästra ett instrument. Deltagare fick skatta bilder på personer av motsatt kön som påstods spela det musikstycke som hördes medan man tittade på varje bild. Musikutförandet var antingen av låg, medel, eller hög skicklighet, och ett bättre utförande förväntades ge högre skattningar av partnerattraktivitet eftersom det är mer kostsamt. Ingen effekt av musiken förelåg, förutom att kvinnorna skattade män som mindre attraktiva för ett längre förhållande när skicklighetsnivån var hög jämfört med när den var medelhög.

Bakalauro baigiamajame darbe tiriama, ar akcijų rinkos signalizavo apie ekonomikos pokyčius 2000-2012 m. laikotarpiu Baltijos šalyse. Pirmojoje darbo dalyje pateikiami teoriniai ekonominio ciklo ir jo indikatorių aspektai, analizuojamos priežastys, kodėl akcijų rinkos gali būti vadinamos ekonomikos indikatoriais bei išanalizuojami orientuojančio ryšio tarp akcijų rinkų ir ekonominio ciklo moksliniai tyrimai. Antrojoje, tiriamojoje dalyje, siekiama išsiaiškinti ar akcijų rinkos Lietuvoje, Latvijoje ir Estijoje gali būti vadinami orientuojantys ekonomikos ciklo sekos indikatoriais. Tam kad būtų ištirtas šis ryšys, buvo pasirinkti keturi makroekonominiai rodikliai (BVP, neto darbo užmokestis, mažmeninė prekyba, pramoninės produkcijos apimtis) ir grafinės analizės, Grangerio priežastingumo testo bei VAR modelio pagalba šis ryšys buvo tiriamas. Rezultatai parodė, jog tik iš dalies akcijų rinkos yra orientuojantis ekonomikos ciklo sekos indikatorius Baltijos valstybėse, nes reikšmingas ir patikimas ryšys buvo rastas tik su BVP ir pramoninės produkcijos apimtimis. / The thesis investigates if the stock markets signaled about the economic changes for the period of 2000 – 2012 in the Baltic States. In the first part of this work the theoretical overview on economic cycle and its indicator aspects are introduced. What is more, the circumstances why the stock markets can be described as economic indicators are also presented. Moreover, the scientific researches about the orientation links between the stock markets and the economic cycle are analyzed in this final work. The practical part of the work seeks to find out if the stock markets in Lithuania, Latvia and Estonia can be called leading indicators of economic cycle sequence. In order to analyze these relations, four macroeconomic indicators were chosen (GDP, net earnings, retail and volume of industrial production). With the help of graphic analysis, Granger Causality Test and VAR model this relation was analyzed. The results show that the stock markets are just partially leading indicators of economic cycle sequence in the Baltic States because the significant and reliable relation was found only with the volumes GDP and industrial production.

Šiame darbe yra nagrinėjami negęstančių sinusoidžių modeliai. Pagrindinis dėmesys yra skiriamas šių modelių netiesinių parametrų (dažnių) įvertinimui. Darbe pateikti nagrinėjamų parametrų įvertinimo Pisarenko, MUSIC ir Prony metodų rezultatai. Pateiktos išvados apie šių metodų taikymo galimybes ir jų ribotumą. Pateikti sukurtos programinės įrangos, realizuojančios negęstančių sinusoidžių modelių generavimą ir jų parametrų įvertinimą Pisarenko, MUSIC ir Prony metodais, aprašymas ir kodai. / Updamped sinusoidal models are considered in this work. The main attention is given to estimation of nonlinear parameters (correlation and frequencies) of these models. The results of estimation of the considered parameters by Pisarenko, MUSIC and Prony methods are analyzed. The conclusions on possibilities and restrictions of these methods are presented. The description and program codes of the software developed are given. The software is intended for generating of updamped sinusoidal models and estimating by Pisarenko, MUSIC and Prony methods.

Identifying the emergence and development of new technologies has become an essential ability for firms competing in dynamic environments. Nonetheless, current technology intelligence practices are unstructured and vaguely defined. Moreover, the existing literature in future technology studies lacks strong, systematic explanations of what technologies are, where technologies come from, and how new technologies emerge and evolve. The present study builds on Structuration Theory, and proposes the structurational model of emerging technologies (SMET). The SMET suggests not only an ongoing view of technologies as social objects, but also a process for thinking through scientifically the complex, multidimensional and emergent dynamic of social and technological change. The SMET proposes that the emergence and development of a new technology can be tracked by examining systematically and collectively the extent of development of its technology-related social structure – its degree of structuration. The degree of structuration of a technology is an ongoing process instantiated in social practices, and can be observed through visible patterns or specific social outcomes of systemic activity organized in three analytical dimensions: structures of meaning, power, and legitimacy. The SMET assumes that the conceptual initiation of a new technology triggers new patterns of social activity or a signal of technological change; thus, the variation in the slope or trajectory of the degree of structuration of a technology may indicate an early signal of technological change. The SMET sets a foundation for identifying early signals of technological change when it is used on a systematic basis. Empirically, the study conducted an exploratory case study in the Internet industry. The study employed a sequential transformative mixed method procedure, and relied on 77 Internet experts to create retrospectively a systematic and collective interpretation of the Internet industry in the last ten (10) years. The test of hypotheses was based on only seven (7) Internet technologies due to time and instrumental constraints. The results confirm the fundamental relationships among constructs in the model, and support, thus, the SMET. The degree of structuration of a technology is revealed as a process independent of individuals’ participation in the enactment of a technology. Technological outcomes are explained by the extent of development of structures of meaning, power, and legitimacy (i.e., the degree of structuration of a technology). Moreover, influential technological outcomes shape individuals’ perspectives over time – i.e., the structurational effect. Hence, the study not only provides evidence that supports this novel theoretical framework, but also illustrates methodologically how to identify the emergence and development of new technologies. Likewise, the study discusses the implications of these results for technology management practices (e.g., product and technology development, innovation policies, and technology transfer activities). Lastly, the study recognizes limitations and suggests further research avenues.

Increased stress is a continuing problem in our present world. Especiallynegative stress could cause serious health problems if it remainsundiagnosed/misdiagnosed and untreated. In the stress medicine, clinicians’measure blood pressure, ECG, finger temperature and breathing rate during anumber of exercises to diagnose stress-related disorders. One of the physiologicalparameters for quantifying stress levels is the finger temperature that helps theclinicians in diagnosis and treatment of stress. However, in practice, it is difficultand tedious for a clinician to understand, interpret and analyze complex, lengthysequential sensor signals. There are only few experts who are able to diagnose andpredict stress-related problems. A system that can help the clinician in diagnosingstress is important, but the large individual variations make it difficult to build sucha system.This research work has attempted to investigate several artificial Intelligencetechniques to develop an intelligent, integrated sensor system for diagnosis andtreatment plan in the Psychophysiological domain. To diagnose individualsensitivity to stress, case-based reasoning is applied as a core technique to facilitateexperience reuse by retrieving previous similar cases. Further, fuzzy techniques arealso employed and incorporated into the case-based reasoning system to handlevagueness, uncertainty inherently existing in clinicians reasoning process. Thevalidation of the approach is based on close collaboration with experts andmeasurements from twenty four persons used as reference.Thirty nine time series from these 24 persons have been used to evaluate theapproach (in terms of the matching algorithms) and an expert has ranked andestimated similarity which shows a level of performance close to an expert. Theproposed system could be used as an expert for a less experienced clinician or as asecond option for an experienced clinician to their decision making process. / Integrated Personal Health Optimizing System (IPOS)

The human brain consists of a myriad of chemical compounds critical to its functioning. A group of these compounds, collectively known as metabolites, have been a research interest for years because the pathogenesis of neurodegenerative diseases, a tumours classification, the effectiveness of a drug, etc., can be investigated via variations in brain metabolite concentration levels. Nuclear Magnetic Resonance Spectroscopy (NMRS) enables investigators to conduct non-invasive in vivo studies of metabolites in the human brain and the rest of the body. However a number of problems have hindered the usage of NMRS as a clinical diagnostic tool. One is the non-uniqueness of the most widely used analysis methods, i.e. as the parameters and/or prior knowledge data of an analysis method are changed, the results also change. A second problem is the lack of a method that can automatically classify the signal components estimated via signal decomposition based signal analysis methods. Additionally, some of the most widely used analysis methods, by virtue of their algorithms, intrinsically assume the nature of NMRS signals, e.g. stationary, linear, Lorentzian, etc. Hence, this thesis explores a new analysis approach, based on a theoretical and practical understanding of NMRS, that (a) avoids making assumptions about the nature of experimentally acquired NMRS signals, (b) relies on a unique decomposition analysis method, and (c) automatically classifies the estimated peaks of an analysis. Unique decomposition analysis was conducted via the rarely used unique and non-linear signal decomposition method − the Fast Pad´e Transform (FPT). The FPT is compared with the main decomposition based NMRS analysis methods via a detailed mathematical analysis, and a comparative analysis. Automatic classification was conducted via a novel classification method, which is introduced herein, and which is based on quantum mechanical predictions of metabolite NMRS behaviour.

Accurate methods for glottal feature extraction include the use of high-speed video imaging (HSVI). There have been previous attempts to extract these features with the acoustic recording. However, none of these methods compare their results with an objective method, such as HSVI. This thesis tests these acoustic methods against a large diverse population of 46 subjects. Two previously studied acoustic methods, as well as one introduced in this thesis, were compared against two video methods, area and displacement for open quotient (OQ) estimation. The area comparison proved to be somewhat ambiguous and challenging due to thresholding effects. The displacement comparison, which is based on glottal edge tracking, proved to be a more robust comparison method than the area. The first acoustic methods OQ estimate had a relatively small average error of 8.90% and the second method had a relatively large average error of -59.05% compared to the displacement OQ. The newly proposed method had a relatively small error of -13.75% when compared to the displacements OQ. There was some success even though there was relatively high error with the acoustic methods, however, they may be utilized to augment the features collected by HSVI for a more accurate glottal feature estimation.

The European power sector is facing significant challenges related to investments in grid infrastructure and generation capacity. The continued deployment of intermittent renewables also puts pressure on current grid conditions. Smart grids is seen as a cost-efficient way to overcome these challenges through a more efficient use of current capacity. Demand response is a corner-stone in smart grid development,  and is implemented to introduce flexibility on the demand side. Most demand response programs have used dynamic pricing to incentivize consumers to shift consumption from peak to off-peak hours. In Stockholm Royal Seaport, where a sustainable energy system is envisioned, it has been proposed that dynamic pricing should be complemented with an indicator depicting carbon intensity of purchased electricity. This indicator is based on average emissions, which is one of two fundamental perspectives on assessing environmental impacts of electricity consumption.  The aim of this study was to evaluate whether the approach used to quantify carbon intensity in Stockholm Royal Seaport is appropriate in the context of demand response. To achieve this, a literature review has been conducted regarding potential benefits of demand response, power system dynamics and carbon dioxide allocation methods. A quantitative analysis has also been conducted, where the signal proposed for Stockholm Royal Seaport has been modeled under different timeframes. The results show that the CO2-signal in Stockholm Royal Seaport is constructed in such a way that it is largely affected by hydro generation, which in turn makes it correlate negatively with price. As a result, the CO2-signal would counteract many of the predicted long-term benefits of demand response. Furthermore it seems unlikely that the signal would result in significant short-term emission reductions, since hydro generally is used to balance supply and demand in the Swedish and Nordic systems.  Based on the literature review, it was concluded that marginal emissions would be a more appropriate environmental indicator than average emissions. However, it remains a difficulty to construct a day-ahead control signal based on this perspective because of system complexity and lack of data. Historical marginal carbon intensity was nevertheless modeled in this study using a linear regression model. The results indicate that price itself might be a sufficient indicator of marginal emissions. Finally, a model for a signal based on prognoses of intermittent renewable generation is proposed, where the rationale is that consumers should decrease consumption during hours of low renewable generation. This signal was modeled using data on renewable generation from Denmark since corresponding data in Sweden is not yet available. Results show that it would be possible to construct a rather accurate control signal in this way. There are also reasons to believe that demand response based on this type of signal would result in long-term environmental benefits. / Den europeiska energisektorn står inför stora utmaningar, bland annat i form av investeringsbehov i nätinfrastruktur och produktionskapacitet för att säkra framtida leveranssäkerhet. Den fortsatta utbyggnaden av intermittent förnybar kraftproduktion ställer också nya krav på nätet och på aktörernas flexibilitet. Smarta nät ses som ett kostnadseffektivt sätt för att övervinna dessa utmaningar genom en mer effektiv användning av nuvarande kapacitet. En viktig del i detta är efterfrågerespons, som syftar till att minska belastningen på nätet under höglasttimmar genom att i högre grad än tidigare involvera konsumenten. De flesta initiativ inom efterfrågerespons har använt dynamisk prissättning för att uppmuntra konsumenter att flytta konsumtion från höglast- till låglasttimmar. I Norra Djurgårdsstaden, där visionen är att bygga ett hållbart och mer flexibelt energisystem, har det föreslagits att dynamisk prissättning bör kompletteras med en indikator som visar den inköpta elens koldioxidintensitet. Denna indikator är baserad på medelel, vilket är ett av två fundamentala sätt att miljövärdera el. Syftet med denna studie var att utvärdera om den metod som används för att kvantifiera koldioxidintensiteten i Norra Djurgårdsstaden är lämplig i samband med efterfrågerespons. För att uppnå detta har en litteraturstudie genomförts gällande potentiella fördelar med efterfrågerespons, hur kraftsystemet fungerar samt olika metoder för att miljövärdera el. En kvantitativ analys har också genomförts, där CO2-signalen i Norra Djurgårdsstaden har modellerats utifrån olika tidsperspektiv. Resultaten visar att CO2-signalen i Norra Djurgårdsstaden är konstruerad på ett sådant sätt att den till stor del påverkas av vattenkraftens produktionsvariationer, vilket i sin tur gör att signalen generellt rör sig i motsatt riktning mot prissignalen. Resultatet av detta är att CO2-signalen motverkar många av de långsiktiga fördelarna med efterfrågestyrning. Dessutom ter det sig osannolikt att signalen skulle leda till signifikanta utsläppsminskningar på kort sikt, eftersom lasten i Sverige främst balanseras av variationer i vattenkraft. Utifrån litteraturstudien kan man dra slutsatsen att marginalelens koldioxidintensitet skulle vara en lämpligare miljöindikator än genomsnittliga utsläpp i samband med efterfrågestyrning. Det är dock svårt att i praktiken konstruera en styrsignal baserat på detta perspektiv på grund av systemets komplexitet och brist på data. Historiska marginella utsläpp modellerades emellertid med hjälp av linjär regression. Resultaten från detta indikerade att priset kan vara en tillräcklig indikator även för variationerna i koldioxidintensitet utifrån ett marginalperspektiv. Slutligen föreslås en modell för en signal baserad på dagenföreprognoser om intermittent förnybar produktion, där budskapet skulle vara att användaren minskar sin konsumtion under timmar med låg förnybar produktion. Denna signal modellerades med hjälp av uppgifter om förnybar produktion från Danmark eftersom motsvarande uppgifter om Svensk produktion inte finns tillgängliga ännu. Resultaten visar att det skulle vara möjligt att konstruera en relativt träffsäker styrsignal på detta sätt. Det finns också skäl att tro att efterfrågerespons baserat på denna typ av signal skulle leda till miljömässiga fördelar på längre sikt.

In this report we investigate whether an embedded system can be used to determine materials quality by analysing the acoustic resonance frequencies. Through experiments the necessary specifications are established and suitable circuits constructed. Signal analysis is performed by a FFT-based algorithm. We have verified that the system is succesful in detecting the five strongest resonance frequencies and list these in order of amplitude. By using embedded devices, it's possible to lower the cost of purchase as well as power consumption dramatically compared to alternative solutions. / I denna rapport undersöker vi hurvida ett inbyggt system kan användas för att bestämma materialkvalité genom analys av akustiska resonansfrekvenser. Genom experiment fastställs de specifikationer systemet måste ha, varefter lämpliga kretsar konstrueras. Med hjälp av en FFT-baserad algoritm utförs viss signalanalys. Vi har verifierat att systemet framgångsrikt kan detektera de fem starkaste resonansfrekvenserna och lista dessa efter amplitud. Genom användandet av inbyggda system kan energiförbrukningen och inköpskostnaden bli mycket lägre än alternativa lösningar.