MULTIMEDIATIETOPANKKI VERKOSSA

Työ käsittelee multimediatietopankin tietosisällön hallintaa ja kehittämistä. Multimediatietopankki verkossa –projektissa multimediatietopankilla tarkoitetaan vuorovaikutteista ja sisältörikasta liikkuvan ja staattisen kuvan (video, animaatio, valokuvat, 3D, grafiikka), äänten (musiikki ja muut äänet) ja tietokantojen yhdistelmää. Sisällön eri osa-alueet ja vuorovaikutteisuus tukevat kokonaisuutta, jolla on oma viestinnällinen tarkoituksensa. Tätä kokonaistoteutusta levitetään www:n, digitaalitelevision ja mobiililaitteiden välityksellä loppukäyttäjälle. Multimedia- ja matkaviestinteknologioiden nopea kehitys antaa mahdollisuuden kehittää uusia palveluja. Erilaisiin päätelaitteisiin ja vaihteleviin ympäristöihin tarkoitettujen helppokäyttöisten multimedia- ja mobiilipalvelujen kysyntä on jatkuvassa kasvussa. Multimediatietopankkiprojektissa esitetään kuinka multimediapalveluita voidaan toteuttaa integroidussa ympäristössä. Integroidulla ympäristöllä tässä työssä tarkoitetaan Internetin, mobiilien palvelujen, WAP:in, kämmentietokoneen, digitaalisen television sekä uusien multimediakännyköiden käyttöä multimediatietopankin tarjoamien palvelujen välittämisessä. Projekti on jaettu yksittäisiin lukuihin, joissa tarkoituksena on syventää multimediatietopankin yksityiskohtia sisällön tuottamisessa teknologian näkökannalta. Multimediatietokannan toteutuksessa mallinnetaan palvelun sisältö tietokantaan XHTML-muodossa mediaolioiden sisään sekä tallennetaan tietopankin metatietoa multimediarelaatiotietokantaan, josta on mahdollista hakea tietoa minkä tahansa päätelaitteen kyselyjen avulla.Tässä työssä keskitytään multimediatietokannan hallintajärjestelmän tehtäviin ja rakenteeseen, siihen miten multimediadata tallennetaan tietokantaan sekä siihen miten tietokannassa olevaa metatietoa haetaan käyttäen tietokannassa kehitettyjä hakumenetelmiä.

Gamma-ray emission from massive young stellar objects

Context.Massive stars form in dense and massive molecular cores. The exact formation mechanism is unclear, but it is possible that some massive stars are formed by processes similar to those that produce the low-mass stars, with accretion/ejection phenomena occurring at some point of the evolution of the protostar. This picture seems to be supported by the detection of a collimated stellar wind emanating from the massive protostar IRAS 16547-4247. A triple radio source is associated with the protostar: a compact core and two radio lobes. The emission of the southern lobe is clearly non-thermal. Such emission is interpreted as synchrotron radiation produced by relativistic electrons locally accelerated at the termination point of a thermal jet. Since the ambient medium is determined by the properties of the molecular cloud in which the whole system is embedded, we can expect high densities of particles and infrared photons. Because of the confirmed presence of relativistic electrons, inverse Compton and relativistic Bremsstrahlung interactions are unavoidable. Aims.We aim to make quantitative predictions of the spectral energy distribution of the non-thermal spots generated by massive young stellar objects, with emphasis on the particular case of IRAS 16547-4247. Methods.We study the high-energy emission generated by the relativistic electrons which produce the non-thermal radio source in IRAS 16547-4247. We also study the result of proton acceleration at the terminal shock of the thermal jet and make estimates of the secondary gamma rays and electron-positron pairs produced by pion decay. Results.We present spectral energy distributions for the southern lobe of IRAS 16547-4247, for a variety of conditions. We show that high-energy emission might be detectable from this object in the gamma-ray domain. The source may also be detectable in X-rays through long exposures with current X-ray instruments. Conclusions.Gamma-ray telescopes such as GLAST, and even ground-based Cherenkov arrays of new generation can be used to study non-thermal processes occurring during the formation of massive stars.

Roaring lions and chirruping lemurs: How the brain encodes sound objects in space.

The dual-stream model of auditory processing postulates separate processing streams for sound meaning and for sound location. The present review draws on evidence from human behavioral and activation studies as well as from lesion studies to argue for a position-linked representation of sound objects that is distinct both from the position-independent representation within the ventral/What stream and from the explicit sound localization processing within the dorsal/Where stream.

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Shout and Act: an Algorithm for Digital Objects Preservation Inspired from Rescue Robots

We adapt the Shout and Act algorithm to Digital Objects Preservation where agents explore file systems looking for digital objects to be preserved (victims). When they find something they “shout” so that agent mates can hear it. The louder the shout, the urgent or most important the finding is. Louder shouts can also refer to closeness. We perform several experiments to show that this system works very scalably, showing that heterogeneous teams of agents outperform homogeneous ones over a wide range of tasks complexity. The target at-risk documents are MS Office documents (including an RTF file) with Excel content or in Excel format. Thus, an interesting conclusion from the experiments is that fewer heterogeneous (varying skills) agents can equal the performance of many homogeneous (combined super-skilled) agents, implying significant performance increases with lower overall cost growth. Our results impact the design of Digital Objects Preservation teams: a properly designed combination of heterogeneous teams is cheaper and more scalable when confronted with uncertain maps of digital objects that need to be preserved. A cost pyramid is proposed for engineers to use for modeling the most effective agent combinations

Quasi-objects and actors in the web of belief. Formation of a national nuclear waste management system: the case of Finland

Paper presented in ISA RC23 meeting, Gothenburg July 16th 2010

Consistency from the perspective of an experimental systems approach to the sciences and their epistemic objects

It is generally accepted that the development of the modern sciences is rooted in experiment. Yet for a long time, experimentation did not occupy a prominent role, neither in philosophy nor in history of science. With the 'practical turn' in studying the sciences and their history, this has begun to change. This paper is concerned with systems and cultures of experimentation and the consistencies that are generated within such systems and cultures. The first part of the paper exposes the forms of historical and structural coherence that characterize the experimental exploration of epistemic objects. In the second part, a particular experimental culture in the life sciences is briefly described as an example. A survey will be given of what it means and what it takes to analyze biological functions in the test tube.

Performance characteristic of moving average trading rules in the Finnish stock market

The thesis examines the profitability of DMAC trading rules in the Finnish stock market over the 1996-2012 period. It contributes to the existing technical analysis literature by comparing for the first time the performance of DMAC strategies based on individual stock trading portfolios to the performance of index trading strategies based on the trading on the index (OMX Helsinki 25) that consists of the same stocks. Besides, the market frictions including transaction costs and taxes are taken into account, and the results are reported from both institutional and individual investor’s perspective. Performance characteristic of DMAC rules are evaluated by simulating 19,900 different trading strategies in total for two non- overlapping 8-year sub-periods, and decomposing the full-sample-period performance of DMAC trading strategies into distinct bullish- and bearish-period performances. The results show that the best DMAC rules have predictive power on future price trends, and these rules are able to outperform buy-and-hold strategy. Although the performance of the DMAC strategies is highly dependent on the combination of moving average lengths, the best DMAC rules of the first sub-period have also performed well during the latter sub-period in the case of individual stock trading strategies. According to the results, the outperformance of DMAC trading rules over buy-and-hold strategy is mostly attributed to their superiority during the bearish periods, and particularly, during stock market crashes.

Designing a Demand Forecasting Process in the Fast Moving Consumer Goods Context

The purpose of this thesis was to study the design of demand forecasting processes. A literature review in the field of forecasting was conducted, including general forecasting process design, forecasting methods and techniques, the role of human judgment in forecasting and forecasting performance measurement. The purpose of the literature review was to identify the important design choices that an organization aiming to design or re-design their demand forecasting process would have to make. In the empirical part of the study, these choices and the existing knowledge behind them was assessed in a case study where a demand forecasting process was re-designed for a company in the fast moving consumer goods business. The new target process is described, as well as the reasoning behind the design choices made during the re-design process. As a result, the most important design choices are highlighted, as well as their immediate effect on other processes directly tied to the demand forecasting process. Additionally, some new insights on the organizational aspects of demand forecasting processes are explored. The preliminary results indicate that in this case the new process did improve forecasting accuracy, although organizational issues related to the process proved to be more challenging than anticipated.

Probabilistic position and orientation estimation of rigid objects using an RGB-D sensor

The recent emergence of low-cost RGB-D sensors has brought new opportunities for robotics by providing affordable devices that can provide synchronized images with both color and depth information. In this thesis, recent work on pose estimation utilizing RGBD sensors is reviewed. Also, a pose recognition system for rigid objects using RGB-D data is implemented. The implementation uses half-edge primitives extracted from the RGB-D images for pose estimation. The system is based on the probabilistic object representation framework by Detry et al., which utilizes Nonparametric Belief Propagation for pose inference. Experiments are performed on household objects to evaluate the performance and robustness of the system.