A minimal set of coordinates for describing humanoid shoulder motion

The kinematics of the anatomical shoulder are analysed and modelled as a parallel mechanism similar to a Stewart platform. A new method is proposed to describe the shoulder kinematics with minimal coordinates and solve the indeterminacy. The minimal coordinates are defined from bony landmarks and the scapulothoracic kinematic constraints. Independent from one another, they uniquely characterise the shoulder motion. A humanoid mechanism is then proposed with identical kinematic properties. It is then shown how minimal coordinates can be obtained for this mechanism and how the coordinates simplify both the motion-planning task and trajectory-tracking control. Lastly, the coordinates are also shown to have an application in the field of biomechanics where they can be used to model the scapulohumeral rhythm.

Llegint Cinema. Anàlisi de la representació de la malaltia mental en el setè art

El present treball és un estudi sobre l'estigma social en la malaltia mental i la representació d'aquest al cinema. Aquesta anàlisi s'ha portat a terme a partir de dues línies de treball. Per una banda amb l'anàlisi interpretativa de dotze pel·lícules utilitzant els indicadors de 'perillositat'; 'incapacitat per a la vida'; 'incurabilitat'; 'pèrdua de rols socials'; 'por al rebuig i/o por a les relacions socials'; i per l'altra banda a partir d'un grup de discussió, en el qual s'han visionat fragments de cinc pel·lícules amb set estudiants del Grau d'Educació Social de la Universitat de Vic. Dels resultats obtinguts es desprèn que la pel·lícula és un mitjà de comunicació mitjançant el qual els estereotips són usats en favor de l'espectacle, estigmatitzant així les persones diagnosticades de malaltia mental. Aquest és un dels motius que fan valorar el cinema com un recurs educatiu a considerar tant en la formació d'educadors i educadores socials com en els projectes d'intervenció socioeducativa.

Fostering Collaborative Knowledge Building by the Effective Provision of Knowledge about the Discussion Process

Peer-reviewed

Efficient Peer Selection in P2P JXTA-Based Platforms

Peer-reviewed

Security and Privacy in a Ubiquitous Information Screen

We expose the ubiquitous interaction between an information screen and its’ viewers mobile devices, highlights the communication vulnerabilities, suggest mitigation strategies and finally implement these strategies to secure the communication. The screen infers information preferences’ of viewers within its vicinity transparently from their mobile devices over Bluetooth. Backend processing then retrieves up-to-date versions of preferred information from content providers. Retrieved content such as sporting news, weather forecasts, advertisements, stock markets and aviation schedules, are systematically displayed on the screen. To maximise users’ benefit, experience and acceptance, the service is provided with no user interaction at the screen and securely upholding preferences privacy and viewers anonymity. Compelled by the personal nature of mobile devices, their contents privacy, preferences confidentiality, and vulnerabilities imposed by screen, the service’s security is fortified. Fortification is predominantly through efficient cryptographic algorithms inspired by elliptic curves cryptosystems, access control and anonymity mechanisms. These mechanisms are demonstrated to attain set objectives within reasonable performance.

Puhdistetun jäteveden patogeenit ja desinfiointitarve

Turun seudulla kuuden kunnan jätevesien käsittely keskitetään Kakolanmäen kallion sisälle rakennettuun jätevedenpuhdistamoon, joka otetaan käyttöön vuoden 2008 lopulla. Kakolanmäen jätevedenpuhdistamolla on varauduttu tulevaisuudessa kiristyviin lupaehtoihin sekä mahdollisiin puhdistetun jäteveden hygieenistä laatua koskeviin lisämääräyksiin jättämällä tilavaraus puhdistetun jäteveden desinfioimiselle ultraviolettivalolla. Diplomityössä on selvitetty vuoden kestäneessä tutkimusjaksossa 1.9.2006- 31.8.2007 Turun kaupungin keskuspuhdistamolta mereen johdetun puhdistetun jäteveden ja esiselkeytetyn ohitusveden hygieenisen laadun vaihtelua. Jäteveden desinfiointitarvetta on arvioitu tarkastelemalla jätevedenpuhdistamon hygieenistä puhdistustulosta ja jätevesien vaikutusta purkuvesistön hygieeniseen tilaan. Tutkimuksen perusteella virtaama ei vaikuttanut merkittävästi jäteveden ulosteperäisten bakteerien määriin. Sen sijaan jäteveden bakteeripitoisuudet laskivat alhaisissa lämpötiloissa. Lämpötilan vaikutus näkyi selkeämmin esiselkeytetyssä kuin puhdistetussa jätevedessä eli bakteerien poistumiseen aktiivilietevaiheen aikana vaikuttavat muut tekijät. Mitä tehokkaammin aktiivilietevaihe toimi, sitä tehokkaammin myös bakteereja poistui. Taudinaiheuttajabakteerit selvisivät puhdistusprosessista paremmin viileän kauden aikana. Puhdistetun jäteveden hygieeninen laatu ei täyttänyt uimaveden tai kasteluveden laatuvaatimuksia, joten desinfiointitarve olisi perustelua. Jätevesien vaikutus Turun edustan merialueen hygieeniseen tilaan näkyi ajoittain korkeina bakteeripitoisuuksina purkupaikan lähistöllä. Vielä ei ole suoraa näyttöä siitä aiheuttavatko jätevedet purkupaikan lähistön uimarannoilla terveydellisiä riskejä. Jäteveden UV-desinfiointi kannattava toteuttaa vain jos hygieeninen puhdistusvelvoite määrätään. UV-desinfioinnin mitoituksessa Kakolanmäen jätevedenpuhdistamolla tulee ottaa huomioon suurin sallittu hydraulinen painehäviö. Mitoitus voidaan tehdä puhdistamon käyttöönoton jälkeen kun tarvitut prosessimittaustiedot ovat saatavilla.

The Pursuit of Efficient Copyright Licensing : How Some Rights Reserved Attempts to Solve the Problems of All Rights Reserved

This dissertation analyses the growing pool of copyrighted works, which are offered to the public using Creative Commons licensing. The study consist of analysis of the novel licensing system, the licensors, and the changes of the "all rights reserved" —paradigm of copyright law. Copyright law reserves all rights to the creator until seventy years have passed since her demise. Many claim that this endangers communal interests. Quite often the creators are willing to release some rights. This, however, is very difficult to do and needs help of specialized lawyers. The study finds that the innovative Creative Commons licensing scheme is well suited for low value - high volume licensing. It helps to reduce transaction costs on several le¬vels. However, CC licensing is not a "silver bullet". Privacy, moral rights, the problems of license interpretation and license compatibility with other open licenses and collecting societies remain unsolved. The study consists of seven chapters. The first chapter introduces the research topic and research questions. The second and third chapters inspect the Creative Commons licensing scheme's technical, economic and legal aspects. The fourth and fifth chapters examine the incentives of the licensors who use open licenses and describe certain open business models. The sixth chapter studies the role of collecting societies and whether two institutions, Creative Commons and collecting societies can coexist. The final chapter summarizes the findings. The dissertation contributes to the existing literature in several ways. There is a wide range of prior research on open source licensing. However, there is an urgent need for an extensive study of the Creative Commons licensing and its actual and potential impact on the creative ecosystem.

eLab, a Personal Learning Environment for the Green Open Innovation Platform

Open Innovation is a relatively new concept which involves a change of paradigm in the R+D+i processes of companies whose aim is to create new technologies or new processes. If to this change, we add the need for innovation in the new green and sustainability economy, and we set out to create a collaborative platform with a learning space where this can happen, we will be facing an overwhelming challenge which requires the application of intelligent programming technologies and languages at the service of education.The aim of the Green IDI (Green Open Innovation) ¿ Economic development and job creation vector in SMEs, based on the environment and sustainability project is to create a platform where companies and individual researchers can perform open innovation processes in the field of sustainability and the environment.The Green IDI (Green Open Innovation) project is funded under the program INNPACTO by the Ministry of Science and Innovation of Spain and is being developed through a consortium formed by the following institutions: GRUPO ICA; COMPARTIA; GRUPO INTERCOM; CETAQUA and the Instituto de Investigación en Inteligencia Artificial (IIIA) from Consejo Superior de Investigaciones Científicas (CSIC). Also the consortium include FUNDACIÓ PRIVADA BARCELONA DIGITAL; PIMEC and UNIVERSITAT OBERTA DE CATALUNYA (UOC).Sustainability and positive action for the environment are considered the principle vector of economic development for companies. As Nicolás Scoli says (2007) ¿in short, preventing unnecessary consumption and the efficient consumption of resources means producing greater wealth with less. Both effects lead to reduced pollution linked to production and consumption¿.The Spanish Sustainable Development Strategy (EEDS) plan defends consumption and sustainable production linked to social and economic development by adhering to the commitment not to endanger ecosystems and abolishing the idea that economic growth is directly proportional to the deterioration of the environment.Uniting the Open Innovation and New Green Economy concepts leads to the "Green Open Innovation¿ Platform creation project.This article analyses the concept of open innovation and defines the importance of the new green and sustainable economy. Lastly, it proposes the creation of eLab. The eLab is defined as an Open Green Innovation Platform personal and collaborative education space which is fed by the interactions of users and which enables innovation processes based on new green economy concepts to be carried out.The creation of a personal learning environment such as eLab on the Green Open Innovation Platform meets the need to offer a collaborative space where platform users can improve their skills regarding the environment and sustainability based on collaborative synergies through Information and Communication Technologies.

Statistical Optimum Design of Heat Exchangers

The optimal design of a heat exchanger system is based on given model parameters together with given standard ranges for machine design variables. The goals set for minimizing the Life Cycle Cost (LCC) function which represents the price of the saved energy, for maximizing the momentary heat recovery output with given constraints satisfied and taking into account the uncertainty in the models were successfully done. Nondominated Sorting Genetic Algorithm II (NSGA-II) for the design optimization of a system is presented and implemented inMatlab environment. Markov ChainMonte Carlo (MCMC) methods are also used to take into account the uncertainty in themodels. Results show that the price of saved energy can be optimized. A wet heat exchanger is found to be more efficient and beneficial than a dry heat exchanger even though its construction is expensive (160 EUR/m2) compared to the construction of a dry heat exchanger (50 EUR/m2). It has been found that the longer lifetime weights higher CAPEX and lower OPEX and vice versa, and the effect of the uncertainty in the models has been identified in a simplified case of minimizing the area of a dry heat exchanger.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Palvelulogistiikan analysointimenetelmän mallinnus ja ideointi ateriapalvelutoiminnoissa

Ateriapalvelujen tuottamiseen sovellettua palvelulogistiikan tutkimustietoa on julkaistu hyvin rajallisesti eikä aihetta ole kovin laajalti tutkittu liiketoiminnan kehittämisen näkökulmasta. Tämän työn tavoitteena on mallintaa konsultointityöhön sopiva ateriapalvelulogistiikan analysointimenetelmä, jolla voidaan havainnoida ominaisuuksiltaan vastaavia tulevaisuuden asiakasprojekteja. Työssä selvitetään ensin kirjallisuustutkimuksen avulla aiheeseen sekä sen käsittelyyn sopivia tieteellisiä tutkimuksia ja julkaisuja. Aihetta tutkitaan arvon muodostumisen, kustannusvaikutusten sekä toimitusketjun kehittämisen näkökulmista. Lisäksi huomioidaan palvelujen ja palveluprosessien osuus palvelulogistiikan kehittämisessä. PALO -projektin suunnitelmassa kuvatulla tuotanto- ja kustannustehokkaalla keskuskeittiömallilla voidaan saavuttaa massaräätälöinnin etujen lisäksi myös nykytilaa ketterämpi tuotantoketju. Uusi palvelulogistiikkaketju vaikuttaa samalla myös arvoverkkoon sekä asiamuodostumiseen. Uudistusten avulla voidaan mahdollisesti säästää varoja ja samalla vapautuvia resursseja voidaan kohdistaa asiakastyytyväisyyttä lisääviin toimenpiteisiin. Mallinnettava menetelmä on osoittautunut havainnoidussa asiakasprojektissa toimivaksi. Menetelmää voidaan toki edelleen kehittää asiakasprojektien vaatimusten mukaan, mutta työssä on onnistuttu kuvaamaan toimiva menetelmän perusmalli.