CISNE-P: a global scheduling oriented to NOW environments

In this work, we present an integral scheduling system for non-dedicated clusters, termed CISNE-P, which ensures the performance required by the local applications, while simultaneously allocating cluster resources to parallel jobs. Our approach solves the problem efficiently by using a social contract technique. This kind of technique is based on reserving computational resources, preserving a predetermined response time to local users. CISNE-P is a middleware which includes both a previously developed space-sharing job scheduler and a dynamic coscheduling system, a time sharing scheduling component. The experimentation performed in a Linux cluster shows that these two scheduler components are complementary and a good coordination improves global performance significantly. We also compare two different CISNE-P implementations: one developed inside the kernel, and the other entirely implemented in the user space.

Single-trial multisensory memories affect later auditory and visual object discrimination.

Multisensory memory traces established via single-trial exposures can impact subsequent visual object recognition. This impact appears to depend on the meaningfulness of the initial multisensory pairing, implying that multisensory exposures establish distinct object representations that are accessible during later unisensory processing. Multisensory contexts may be particularly effective in influencing auditory discrimination, given the purportedly inferior recognition memory in this sensory modality. The possibility of this generalization and the equivalence of effects when memory discrimination was being performed in the visual vs. auditory modality were at the focus of this study. First, we demonstrate that visual object discrimination is affected by the context of prior multisensory encounters, replicating and extending previous findings by controlling for the probability of multisensory contexts during initial as well as repeated object presentations. Second, we provide the first evidence that single-trial multisensory memories impact subsequent auditory object discrimination. Auditory object discrimination was enhanced when initial presentations entailed semantically congruent multisensory pairs and was impaired after semantically incongruent multisensory encounters, compared to sounds that had been encountered only in a unisensory manner. Third, the impact of single-trial multisensory memories upon unisensory object discrimination was greater when the task was performed in the auditory vs. visual modality. Fourth, there was no evidence for correlation between effects of past multisensory experiences on visual and auditory processing, suggestive of largely independent object processing mechanisms between modalities. We discuss these findings in terms of the conceptual short term memory (CSTM) model and predictive coding. Our results suggest differential recruitment and modulation of conceptual memory networks according to the sensory task at hand.

Web-pohjaisen videoeditorin toteutus ja Object-Relational Mapping

Tässä insinöörityössä esitellään Stadian verkkoviestinnän VIDEOS-hankkeeseen liittyvän web-pohjaisen videoeditorin kehitys ja käytetyt teknologiat. Fooga-nimiseksi nimetty videoeditorin käyttämät tekniikat ovat Ruby, Ruby on Rails, FFmpeg, Mencoder, ImageMagick ja FLVTool2. Ruby on olio-pohjainen skriptikieli, Ruby on Rails on websovelluskehys ja muut tekniikat ovat komentorivipohjaisia työkaluja, jotka tarjoavat tärkeimmät toiminnallisuudet Foogalle. Tavoitteina oli tämän työn yhteydessä ohjelmoida Foogaan perustoiminnallisuudet, jotka mahdollistavat minimaaliset käyttömahdollisuudet kevääseen 2007 mennessä. Kehitystyö jatkuu vuoteen 2009 asti tarjoamalla samalla mahdollisuuden usealle insinöörityölle tekniikan ja liikenteen koulutusohjelmasta. Tämän lisäksi tässä insinöörityössä perehdytään Object-Relational Mapping-tekniikan perusteisiiin ja verrataan Ruby on Railsin ja Javan ORM-ominaisuuksia. Ruby on Railsin osalta esitellään ActiveRecord-luokka ja Javan osalta Hibernate, jonka johdantona on DAO/DTO-sunnittelumalli.

Points to consider for prioritizing clinical genetic testing services: a European consensus process oriented at accountability for reasonableness.

Given the cost constraints of the European health-care systems, criteria are needed to decide which genetic services to fund from the public budgets, if not all can be covered. To ensure that high-priority services are available equitably within and across the European countries, a shared set of prioritization criteria would be desirable. A decision process following the accountability for reasonableness framework was undertaken, including a multidisciplinary EuroGentest/PPPC-ESHG workshop to develop shared prioritization criteria. Resources are currently too limited to fund all the beneficial genetic testing services available in the next decade. Ethically and economically reflected prioritization criteria are needed. Prioritization should be based on considerations of medical benefit, health need and costs. Medical benefit includes evidence of benefit in terms of clinical benefit, benefit of information for important life decisions, benefit for other people apart from the person tested and the patient-specific likelihood of being affected by the condition tested for. It may be subject to a finite time window. Health need includes the severity of the condition tested for and its progression at the time of testing. Further discussion and better evidence is needed before clearly defined recommendations can be made or a prioritization algorithm proposed. To our knowledge, this is the first time a clinical society has initiated a decision process about health-care prioritization on a European level, following the principles of accountability for reasonableness. We provide points to consider to stimulate this debate across the EU and to serve as a reference for improving patient management.

Product information management system design framework for production oriented company

Diplomityössä luodaan viitekehys tuotetiedonhallintajärjestelmän esisuunnittelua varten. Siinä on kolme ulottuvuutta: lisäarvontuotto-, toiminnallisuus- ja ohjelmistoulottuvuus. Viitekehys auttaa- tunnistamaan lisäarvontuottokomponentit, joihin voidaan vaikuttaa tiettyjen ohjelmistoluokkien tarjoamilla tuotetiedonhallintatoiminnallisuuksilla. Viitekehyksen järjestelmäsuunnittelullista näkökulmaa hyödynnetään tutkittavissa yritystapauksissa perustuen laskentamatriisin muotoon mallinnettuihin ulottuvuuksien välisiin suhteisiin. Matriisiin syötetään lisäarvontuotto- ja toiminnallisuuskomponenttien saamat tärkeydet kohdeyrityksessä suoritetussa haastattelututkimuksessa. Matriisin tuotos on tietyn ohjelmiston soveltuvuus kyseisen yrityksen tapauksessa. Soveltuvuus on joukko tunnuslukuja, jotka analysoidaan tulostenkäsittelyvaiheessa. Soveltuvuustulokset avustavat kohdeyritystä sen valitessa lähestymistapaansa tuotetiedonhallintaan - ja kuvaavat esisuunnitellun tuotetiedonhallintajärjestelmän. Viitekehyksen rakentaminen vaatii perinpohjaisen lähestymistavan merkityksellisten lisäarvontuotto- ja toiminnallisuuskomponenttien sekä ohjelmistoluokkien määrittämiseen. Määritystyö perustuu työssä yksityiskohtaisesti laadittujen menetelmien ja komponenttiryhmitysten hyödyntämiselle. Kunkin alueen analysointi mahdollistaa viitekehyksen ja laskentamatriisin rakentamisen yhdenmukaisten määritysten perusteella. Viitekehykselle on ominaista sen muunneltavuus. Nykymuodossaan se soveltuu elektroniikka- ja high-tech yrityksille. Viitekehystä voidaan hyödyntää myös muilla toimialoilla muokkaamalla lisäarvontuottokomponentteja kunkin toimialan intressien mukaisesti. Vastaavasti analysoitava ohjelmisto voidaan valita tapauskohtaisesti. Laskentamatriisi on kuitenkin ensin päivitettävä valitun ohjelmiston kyvykkyyksillä, minkä jälkeen viitekehys voi tuottaa soveltuvuustuloksia kyseiseen yritystapaukseen perustuen

Spontaneous Speech and Emotional Response modeling based on One-class classifier oriented to Alzheimer Disease diagnosis

The purpose of our project is to contribute to earlier diagnosis of AD and better estimates of its severity by using automatic analysis performed through new biomarkers extracted from non-invasive intelligent methods. The methods selected in this case are speech biomarkers oriented to Sponta-neous Speech and Emotional Response Analysis. Thus the main goal of the present work is feature search in Spontaneous Speech oriented to pre-clinical evaluation for the definition of test for AD diagnosis by One-class classifier. One-class classifi-cation problem differs from multi-class classifier in one essen-tial aspect. In one-class classification it is assumed that only information of one of the classes, the target class, is available. In this work we explore the problem of imbalanced datasets that is particularly crucial in applications where the goal is to maximize recognition of the minority class as in medical diag-nosis. The use of information about outlier and Fractal Dimen-sion features improves the system performance.

Foreign-Medical-School Graduates object to the VISA Qualifiying Examination

To the editor; The Visa Qualifying Examination is a two-day test composed of approximately 950 multiple-choice questions conerneing the basic and clinical sciences....

Exploring the relative DNA contribution of first and second object's users on mock touch DNA mixtures

Contact stains recovered at break-in crime scenes are frequently characterized by mixtures of DNA from several persons. Broad knowledge on the relative contribution of DNA left behind by different users overtime is of paramount importance. Such information might help crime investigators to robustly evaluate the possibility of detecting a specific (or known) individual's DNA profile based on the type and history of an object. To address this issue, a contact stain simulation-based protocol was designed. Fourteen volunteers either acting as first or second object's users were recruited. The first user was required to regularly handle/wear 9 different items during an 8-10-day period, whilst the second user for 5, 30 and 120 min, in three independent simulation sessions producing a total of 231 stains. Subsequently, the relative DNA profile contribution of each individual pair was investigated. Preliminary results showed a progressive increase of the percentage contribution of the second user compared to the first. Interestingly, the second user generally became the major DNA contributor when most objects were handled/worn for 120 min, Furthermore, the observation of unexpected additional alleles will then prompt the investigation of indirect DNA transfer events.

Benefits and Limitations of Service Oriented Architecture

In this thesis I examine Service Oriented Architecture (SOA) considering both its positive and negative qualities for business organizations and IT. In SOA, services are loosely coupled and invoked through standard interfaces to enable business process independence from the underlying technology. As an architecture, SOA brings the key benefit of service reuse that may mean anything from simple application reuse to taking advantage of entire business processes across enterprises. SOA also promises interoperability especially by the Web services standards that enable platform independency. Cost efficiency is mainly a result of the savings in IT maintenance and reduced development costs. The most severe limitations of SOA are performance implications and security issues, but the applicability of SOA is also limited. Additional disadvantages of a service oriented approach include problems in data management and complexity questions, and the lack of agreement about SOA and its twofold nature as a business as well as technology approach leads to problematic interpretation of the available information. In this thesis I find the benefits and limitations of SOA for the purpose described above and propose that companies need to consider the decision to implement SOA carefully to determine whether the benefits will outdo the costs in the individual case.

Most and Least Preferred Colours Differ According to Object Context : New Insights from an Unrestricted Colour Range

Humans like some colours and dislike others, but which particular colours and why remains to be understood. Empirical studies on colour preferences generally targeted most preferred colours, but rarely least preferred (disliked) colours. In addition, findings are often based on general colour preferences leaving open the question whether results generalise to specific objects. Here, 88 participants selected the colours they preferred most and least for three context conditions (general, interior walls, t-shirt) using a high-precision colour picker. Participants also indicated whether they associated their colour choice to a valenced object or concept. The chosen colours varied widely between individuals and contexts and so did the reasons for their choices. Consistent patterns also emerged, as most preferred colours in general were more chromatic, while for walls they were lighter and for t-shirts they were darker and less chromatic compared to least preferred colours. This meant that general colour preferences could not explain object specific colour preferences. Measures of the selection process further revealed that, compared to most preferred colours, least preferred colours were chosen more quickly and were less often linked to valenced objects or concepts. The high intra- and inter-individual variability in this and previous reports furthers our understanding that colour preferences are determined by subjective experiences and that most and least preferred colours are not processed equally.

The use of future-oriented knowledge in regional innovation processes: Research on knowledge generation, transfer and conversion

The importance of the regional level in research has risen in the last few decades and a vast literature in the fields of, for instance, evolutionary and institutional economics, network theories, innovations and learning systems, as well as sociology, has focused on regional level questions. Recently the policy makers and regional actors have also began to pay increasing attention to the knowledge economy and its needs, in general, and the connectivity and support structures of regional clusters in particular. Nowadays knowledge is generally considered as the most important source of competitive advantage, but even the most specialised forms of knowledge are becoming a short-lived resource for example due to the accelerating pace of technological change. This emphasizes the need of foresight activities in national, regional and organizational levels and the integration of foresight and innovation activities. In regional setting this development sets great challenges especially in those regions having no university and thus usually very limited resources for research activities. Also the research problem of this dissertation is related to the need to better incorporate the information produced by foresight process to facilitate and to be used in regional practice-based innovation processes. This dissertation is a constructive case study the case being Lahti region and a network facilitating innovation policy adopted in that region. Dissertation consists of a summary and five articles and during the research process a construct or a conceptual model for solving this real life problem has been developed. It is also being implemented as part of the network facilitating innovation policy in the Lahti region.

Using appearance and context for outdoor scene object classification

We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal

Developing a Service-Oriented Software Platform

Tehokkaasti toimiva sähköinen tiedonvälitys yrityksen omien sovellusten välillä sekä sen liikekumppaneiden kanssa on kasvanut merkittäväksi yrityksen kilpailukykyä lisääväksi tekijäksi. Yritysten erilaiset tietojärjestelmät asettavat haasteita tehokkaalle tiedonvälitykselle näiden järjestelmien välillä. Perinteiset EDI teknologioihin perustuvat sähköisen tiedonvälityksen ratkaisut eivät pysty mukautumaan nykyisin nopeasti muuttuviin markkinatilanteisiin. Palvelukeskeiseen arkkitehtuuriin ja Web-palveluihin perustuvat teknologiat mahdollistavat mukautumisen erilaisiin muutoksiin liiketoiminnassa nopeammin ja helpommin. Lisäksi ne nopeuttavat tiedon integrointia erilaisten tietojärjestelmien välillä, koska tiedonvälityksessä käytetään yleisesti hyväksyttyihin standardeihin perustuvia tiedonsiirtoprotokollia sekä tietoformaatteja. Diplomityössä esitellään keskeiset teknologiat ja menetelmät sähköisen tiedonvälityksen toteuttamiseen. Lisäksi työssä vertaillaan erilaisia vaihtoehtoja, joilla sähköinen tiedonvälitys voidaan toteuttaa. Vaihtoehtoina työssä ovat tiedonvälityspalveluiden ostaminen toiselta yritykseltä, olemassa olevan valmiin ohjelmiston hyödyntäminen, tai kokonaan uuden sovellusalustan kehittäminen. Työssä kuvaillaan palvelukeskeisen sovellusalustan toteutus, joka mahdollistaa tehokkaan sekä joustavan tiedonvälityksen sovellusten välillä. Alustan tarjoamien palveluiden päälle voidaan rakentaa erilaisia liiketoimintaa tukevia palveluita, jotka voivat hyödyntää sovellusalustan tarjoamia toiminnallisuuksia. Alustan toteutusta arvioidaan kolmen liiketoimintaskenaarion toteutuksesta saatujen kokemusten perusteella.

Unsupervised visual object categorization

The number of digital images has been increasing exponentially in the last few years. People have problems managing their image collections and finding a specific image. An automatic image categorization system could help them to manage images and find specific images. In this thesis, an unsupervised visual object categorization system was implemented to categorize a set of unknown images. The system is unsupervised, and hence, it does not need known images to train the system which needs to be manually obtained. Therefore, the number of possible categories and images can be huge. The system implemented in the thesis extracts local features from the images. These local features are used to build a codebook. The local features and the codebook are then used to generate a feature vector for an image. Images are categorized based on the feature vectors. The system is able to categorize any given set of images based on the visual appearance of the images. Images that have similar image regions are grouped together in the same category. Thus, for example, images which contain cars are assigned to the same cluster. The unsupervised visual object categorization system can be used in many situations, e.g., in an Internet search engine. The system can categorize images for a user, and the user can then easily find a specific type of image.