Usean näytön hyödyntäminen Windows-ympäristössä

Tässä kandidaatintyössä luodaan kattava katsaus erilaisiin PC-laiteissa toimiviin usean näytön käyttöönottomenetelmiin, joita on olemassa useita ominaisuuksiltaan ja käyttötarkoituksiltaan erilaisia. Työssä perehdytään Windowsin usean näytön tuen historiaan ja sen kehitykseen eri Windows versioiden välillä tuen alkuajoista 1990-luvulta nykyaikaan aina viimeisimpiin Windows käyttöjärjestelmiin asti. Lopuksi tarkastellaan vielä pelien usean näytön tukea ja kuinka hyödyntää useaa näyttöä sellaisissa peleissä, jotka eivät sitä sisäänrakennetusti tue.

Particle Competition and Cooperation in Networks for Semi-Supervised Learning

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Atendimento à norma NBR 12.209/2011 na implantação de uma Estação de Tratamento de Esgotos no município de Guaratinguetá (SP)

The progressive growth of the population and the increase of sewage generated has demanded of society and public policies that, besides the collection network deployment is carried out the treatment and proper disposal of treated sewage in all brazilian municipalities. The aim of this study was to monitor and evaluate the work of implementation of a Sewage Treatment Plant (STP) in Guaratinguetá city of São Paulo state, to identify the compliance with legal requirements and the NBR 12,209/2011. The construction of this ETE met all the requirements of NBR 12209/2011 and benefited a large portion of population with the sewage treatment. Based on the results of this assessment it was concluded that the construction of a STP is relatively simple, differing only on the legal requirements related to the location, area for the construction and materials used in the work. The knowledge generated in this study will assist the public policies in the implementation of STPs in municipalities that do not yet have this basic sanitation

Particle Competition and Cooperation in Networks for Semi-Supervised Learning

Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) semi-supervised classification model is proposed. It employs a combined random-greedy walk of particles, with competition and cooperation mechanisms, to propagate class labels to the whole network. Due to the competition mechanism, the proposed model has a local label spreading fashion, i.e., each particle only visits a portion of nodes potentially belonging to it, while it is not allowed to visit those nodes definitely occupied by particles of other classes. In this way, a "divide-and-conquer" effect is naturally embedded in the model. As a result, the proposed model can achieve a good classification rate while exhibiting low computational complexity order in comparison to other network-based semi-supervised algorithms. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method.

Assessing the gain of biological data integration in gene networks inference

Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

Networking: the "making of" social networks. A closer look at the process and antecedents of some resourcing-oriented behaviors in organizations.

Social networks are one of the “hot” themes in people’s life and contemporary social research. Considering our “embeddedness” in a thick web of social relations is a study perspective that could unveil a number of explanations of how people may manage their personal and social resources. Looking at people’s behaviors of building and managing their social networks, seems to be an effective way to find some possible rationalization about how to help people getting the best from their resources . The main aim of this dissertation is to give a closer look at the role of networking behaviors. Antecedents, motivations, different steps and measures about networking behaviors and outcomes are analyzed and discussed. Results seem to confirm, in a different setting and time perspective, that networking behaviors include different types and goals that change over time. Effects of networking behaviors seem to find empirical confirmation through social network analysis methods. Both personality and situational self-efficacy seem to predict networking behaviors. Different types of motivational drivers seem to be related to diverse networking behaviors.

Shifted Coupling of EEG Driving Frequencies and fMRI Resting State Networks in Schizophrenia Spectrum Disorders

INTRODUCTION: The cerebral resting state in schizophrenia is altered, as has been demonstrated separately by electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state networks (RSNs). Previous simultaneous EEG/fMRI findings in healthy controls suggest that a consistent spatiotemporal coupling between neural oscillations (EEG frequency correlates) and RSN activity is necessary to organize cognitive processes optimally. We hypothesized that this coupling is disorganized in schizophrenia and related psychotic disorders, in particular regarding higher cognitive RSNs such as the default-mode (DMN) and left-working-memory network (LWMN). METHODS: Resting state was investigated in eleven patients with a schizophrenia spectrum disorder (n = 11) and matched healthy controls (n = 11) using simultaneous EEG/fMRI. The temporal association of each RSN to topographic spectral changes in the EEG was assessed by creating Covariance Maps. Group differences within, and group similarities across frequencies were estimated for the Covariance Maps. RESULTS: The coupling of EEG frequency bands to the DMN and the LWMN respectively, displayed significant similarities that were shifted towards lower EEG frequencies in patients compared to healthy controls. CONCLUSIONS: By combining EEG and fMRI, each measuring different properties of the same pathophysiology, an aberrant relationship between EEG frequencies and altered RSNs was observed in patients. RSNs of patients were related to lower EEG frequencies, indicating functional alterations of the spatiotemporal coupling. SIGNIFICANCE: The finding of a deviant and shifted coupling between RSNs and related EEG frequencies in patients with a schizophrenia spectrum disorder is significant, as it might indicate how failures in the processing of internal and external stimuli, as commonly seen during this symptomatology (i.e. thought disorders, hallucinations), arise.

Demo -- Closer to Cloud-RAN: RAN as a Service

Commoditization and virtualization of wireless networks are changing the economics of mobile networks to help network providers (e.g., MNO, MVNO) move from proprietary and bespoke hardware and software platforms toward an open, cost-effective, and flexible cellular ecosystem. In addition, rich and innovative local services can be efficiently created through cloudification by leveraging the existing infrastructure. In this work, we present RANaaS, which is a cloudified radio access network delivered as a service. RANaaS provides the service life-cycle of an ondemand, elastic, and pay as you go 3GPP RAN instantiated on top of the cloud infrastructure. We demonstrate an example of realtime cloudified LTE network deployment using the OpenAirInterface LTE implementation and OpenStack running on commodity hardware as well as the flexibility and performance of the platform developed.

On the economics of energy consumption in 4G networks: the case of Spain

Reducing energy consumption is one of the main challenges in most countries. For example, European Member States agreed to reduce greenhouse gas (GHG) emissions by 20% in 2020 compared to 1990 levels (EC 2008). Considering each sector separately, ICTs account nowadays for 2% of total carbon emissions. This percentage will increase as the demand of communication services and applications steps up. At the same time, the expected evolution of ICT-based developments - smart buildings, smart grids and smart transportation systems among others - could result in the creation of energy-saving opportunities leading to global emission reductions (Labouze et al. 2008), although the amount of these savings is under debate (Falch 2010). The main development required in telecommunication networks ?one of the three major blocks of energy consumption in ICTs together with data centers and consumer equipment (Sutherland 2009) ? is the evolution of existing infrastructures into ultra-broadband networks, the so-called Next Generation Networks (NGN). Fourth generation (4G) mobile communications are the technology of choice to complete -or supplement- the ubiquitous deployment of NGN. The risk and opportunities involved in NGN roll-out are currently in the forefront of the economic and policy debate. However, the issue of which is the role of energy consumption in 4G networks seems absent, despite the fact that the economic impact of energy consumption arises as a key element in the cost analysis of this type of networks. Precisely, the aim of this research is to provide deeper insight on the energy consumption involved in the usage of a 4G network, its relationship with network main design features, and the general economic impact this would have in the capital and operational expenditures related with network deployment and usage.

Providing 30Mbit/s to Spain’s final third. -A techno-economic assessment.

Since the Digital Agenda for Europe released the Europe2020 flagship, Member States are looking for ways of fulfilling their agreed commitments to fast and ultrafast internet deployment. However, Europe is not a homogenous reality. The economic, geographic, social and demographic features of each country make it a highly diverse region to develop best practices over Next Generation Access Networks (NGAN) deployments. There are special concerns about NGAN deployments for “the final third”, as referred to the last 25% of the country’s population who, usually, live in rural areas. This paper assesses, through a techno-economic analysis, the access cost of providing over 30 Mbps broadband for the final third of Spain`s population in municipalities, which are classified into area types, referred to as geotypes. Fixed and mobile technologies are compared in order to determine which is the most cost-effective technology for each geotype. The demographic limit for fixed networks (cable, fibre and copper) is also discussed. The assessment focuses on the supply side and the results show the access network cost only. The research completes a previous published assessment (Techno-economic analysis of next generation access networks roll-out. The case of platform competition, regulation and public policy in Spain) by including the LTE scenario. The LTE scenario is dimensioned to provide 30 Mbps (best effort) broadband, considering a network take-up of 25%. The Rocket techno-economic model is used to assess a ten-year study period deployment. Nevertheless, the deployment must start in 2014 and be completed by 2020, in order to fulfil the Digital Agenda’s goals. The feasibility of the deployment is defined as the ability to recoup the investment at the end of the study period. This ability is highly related to network take-up and, therefore, to service adoption. Network deployment in each geotype is compared with the cost of the deployment in the Urban geotype and broadband expected penetration rates for clarity and simplicity. Debating the cost-effective deployments for each geotype, while addressing the Digital Agenda’s goals regarding fast and ultrafast internet, is the main purpose of this paper. At the end of the last year, the independent Spanish regulation agency released the Spain broadband coverage report at the first half of 2013. This document claimed that 59% and 52% of Spain’s population was already covered by NGAN capable of providing 30 Mbps and 100 Mbps broadband respectively. HFC, with 47% of population coverage, and FTTH, with 14%, were considered as a 100 Mbps capable NGAN. Meanwhile VDSL, with 12% of the population covered, was the only NGAN network considered for the 30 Mbps segment. Despite not being an NGAN, the 99% population coverage of HSPA networks was also noted in the report. Since mobile operators are also required to provide 30 Mbps broadband to 90% of the population in rural areas by the end of 2020, mobile networks will play a significant role on the achievement of the 30 Mbps goal in Spain’s final third. The assessment indicates the cost of the deployment per cumulative households coverage with 4 different NGANs: FTTH, HFC, VDSL and LTE. Research shows that an investment ranging from €2,700 (VDSL) to €5,400 (HFC) million will be needed to cover the first half of the population with any fixed technology assessed. The results state that at least €3,000 million will be required to cover these areas with the least expensive technology (LTE). However, if we consider the throughput that fixed networks could provide and achievement of the Digital Agenda’s objectives, fixed network deployments are recommended for up to 90% of the population. Fibre and cable deployments could cover up to a maximum of 88% of the Spanish population cost efficiently. As there are some concerns about the service adoption, we recommend VDSL and mobile network deployments for the final third of the population. Despite LTE being able to provide the most economical roll-out, VDSL could also provide 50 Mbps from 75% to 90% of the Spanish population cost efficiently. For this population gap, facility based competition between VDSL providers and LTE providers must be encouraged. Regarding 90% to 98.5% of the Spanish population, LTE deployment is the most appropriate. Since costumers in less populated the municipalities are more sensitive to the cost of the service, we consider that a single network deployment could be most appropriate. Finally, it has become clear that it is not possible to deliver 30Mbps to the final 1.5% of the population cost-efficiently and adoption predictions are not optimistic either. As there are other broadband alternatives able to deliver up to 20 Mbps, in the authors’ opinion, it is not necessary to cover the extreme rural areas, where public financing would be required.

Resilient Wireless Sensor Networks Using Topology Control: A Review

Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs.

QSAR e dinâmica molecular no estudo de sistemas biomoleculares: predição da atividade biológica de antagonistas do receptor sigma-1 e simulações de bicamadas lipídicas

Diferentes abordagens teóricas têm sido utilizadas em estudos de sistemas biomoleculares com o objetivo de contribuir com o tratamento de diversas doenças. Para a dor neuropática, por exemplo, o estudo de compostos que interagem com o receptor sigma-1 (Sig-1R) pode elucidar os principais fatores associados à atividade biológica dos mesmos. Nesse propósito, estudos de Relações Quantitativas Estrutura-Atividade (QSAR) utilizando os métodos de regressão por Mínimos Quadrados Parciais (PLS) e Rede Neural Artificial (ANN) foram aplicados a 64 antagonistas do Sig-1R pertencentes à classe de 1-arilpirazóis. Modelos PLS e ANN foram utilizados com o objetivo de descrever comportamentos lineares e não lineares, respectivamente, entre um conjunto de descritores e a atividade biológica dos compostos selecionados. O modelo PLS foi obtido com 51 compostos no conjunto treinamento e 13 compostos no conjunto teste (r² = 0,768, q² = 0,684 e r²teste = 0,785). Testes de leave-N-out, randomização da atividade biológica e detecção de outliers confirmaram a robustez e estabilidade dos modelos e mostraram que os mesmos não foram obtidos por correlações ao acaso. Modelos também foram gerados a partir da Rede Neural Artificial Perceptron de Multicamadas (MLP-ANN), sendo que a arquitetura 6-12-1, treinada com as funções de transferência tansig-tansig, apresentou a melhor resposta para a predição da atividade biológica dos compostos (r²treinamento = 0,891, r²validação = 0,852 e r²teste = 0,793). Outra abordagem foi utilizada para simular o ambiente de membranas sinápticas utilizando bicamadas lipídicas compostas por POPC, DOPE, POPS e colesterol. Os estudos de dinâmica molecular desenvolvidos mostraram que altas concentrações de colesterol induzem redução da área por lipídeo e difusão lateral e aumento na espessura da membrana e nos valores de parâmetro de ordem causados pelo ordenamento das cadeias acil dos fosfolipídeos. As bicamadas lipídicas obtidas podem ser usadas para simular interações entre lipídeos e pequenas moléculas ou proteínas contribuindo para as pesquisas associadas a doenças como Alzheimer e Parkinson. As abordagens usadas nessa tese são essenciais para o desenvolvimento de novas pesquisas em Química Medicinal Computacional.

A educação permanente em saúde para a institucionalização de uma rede-rizoma

Esta dissertação é resultado de uma pesquisa-intervenção cuja produção de dados ocorreu com o Grupo Condutor Regional da Rede Cegonha (GCR) no DRS III de Araraquara - SP, parte do Projeto de Pesquisa para o Sistema Único de Saúde (PPSUS): O processo de implantação da rede de atenção à saúde materno infantil no DRS III de Araraquara: a atenção básica como ordenadora da atenção em rede. Nosso objetivo foi compreender este coletivo como espaço de Educação Permanente em Saúde (EPS) para a institucionalização dessa Rede, e também caracterizar a EPS no território de abrangência deste DRS, compreender suas fragilidades-potencialidades e também os processos de EPS produzidos no interior do GCR para a implementação da Rede Cegonha (RC), diante de desafios como a redução da morbimortalidade materno infantil e o atendimento integral e humanizado a mulheres e crianças. Esta pesquisa qualitativa compreendeu a análise de documentos e a pesquisa-intervenção, utilizando método cartográfico, e a produção dos dados ocorreu no ano de 2014 com os integrantes do GCR e outros pesquisadores PPSUS. As análises tiveram como referenciais o Processo de Trabalho em Saúde e conceitos do movimento institucionalista, das correntes da Análise Institucional e da Esquizoanálise. Esta pesquisa de cunho cartográfico explorou o contexto sócio-histórico da EPS e da RC no DRS III e paisagens que compõem o mapa do aprendizado no que chamamos Rede-rizoma, entremeadas por análises de implicações e aprendizados na experiência, tanto de construção da pesquisa como da RC. Nos planos do rizoma houve momentos de aprendizado significativo, ecos nos municípios, interferências da pesquisa-intervenção, dentre outros componentes de tessitura da rede que envolveram seus atores, seus pontos de conexão, de tensão, de apoio. Nesse emaranhado quente e frio, interessou-nos explorar as singularidades do encontro e os movimentos de forças instituintes e do instituído com o compromisso de entender a EPS como ferramenta de trabalho para a institucionalização da RC. Percebemos a existência de microprocessos de institucionalização disparados no cotidiano do GCR, caracteristicamente paralisantes e mobilizadores, como a importância da participação social, ainda tímida, as tensões com a imobilidade municipal, as fragilidades-potencialidades dos recursos humanos e financeiros, e também resultados que refletem em alargamento e participação de novos atores, cooperação intermunicipal, fortalecimento dos Grupos Condutores Municipais da rede cegonha e uma gestão estadual disposta a deflagrar processos de formação participativos. Trata-se de movimentos que se revelaram em implicações de múltiplas bifurcações e em processos de EPS que se fazem de forma mutante, conformando a rede-rizoma

Low-cost interrogation of optical fibre Bragg grating sensors

Through the application of novel signal processing techniques we are able to measure physical measurands with both high accuracy and low noise susceptibility. The first interrogation scheme is based upon a CCD spectrometer. We compare different algorithms for resolving the Bragg wavelength from a low resolution discrete representation of the reflected spectrum, and present optimal processing methods for providing a high integrity measurement from the reflection image. Our second sensing scheme uses a novel network of sensors to measure the distributive strain response of a mechanical system. Using neural network processing methods we demonstrate the measurement capabilities of a scalable low-cost fibre Bragg grating sensor network. This network has been shown to be comparable with the performance of existing fibre Bragg grating sensing techniques, at a greatly reduced implementation cost.

Disruption prediction at JET [Joint European Torus]

The sudden loss of the plasma magnetic confinement, known as disruption, is one of the major issue in a nuclear fusion machine as JET (Joint European Torus), Disruptions pose very serious problems to the safety of the machine. The energy stored in the plasma is released to the machine structure in few milliseconds resulting in forces that at JET reach several Mega Newtons. The problem is even more severe in the nuclear fusion power station where the forces are in the order of one hundred Mega Newtons. The events that occur during a disruption are still not well understood even if some mechanisms that can lead to a disruption have been identified and can be used to predict them. Unfortunately it is always a combination of these events that generates a disruption and therefore it is not possible to use simple algorithms to predict it. This thesis analyses the possibility of using neural network algorithms to predict plasma disruptions in real time. This involves the determination of plasma parameters every few milliseconds. A plasma boundary reconstruction algorithm, XLOC, has been developed in collaboration with Dr. D. Ollrien and Dr. J. Ellis capable of determining the plasma wall/distance every 2 milliseconds. The XLOC output has been used to develop a multilayer perceptron network to determine plasma parameters as ?i and q? with which a machine operational space has been experimentally defined. If the limits of this operational space are breached the disruption probability increases considerably. Another approach for prediction disruptions is to use neural network classification methods to define the JET operational space. Two methods have been studied. The first method uses a multilayer perceptron network with softmax activation function for the output layer. This method can be used for classifying the input patterns in various classes. In this case the plasma input patterns have been divided between disrupting and safe patterns, giving the possibility of assigning a disruption probability to every plasma input pattern. The second method determines the novelty of an input pattern by calculating the probability density distribution of successful plasma patterns that have been run at JET. The density distribution is represented as a mixture distribution, and its parameters arc determined using the Expectation-Maximisation method. If the dataset, used to determine the distribution parameters, covers sufficiently well the machine operational space. Then, the patterns flagged as novel can be regarded as patterns belonging to a disrupting plasma. Together with these methods, a network has been designed to predict the vertical forces, that a disruption can cause, in order to avoid that too dangerous plasma configurations are run. This network can be run before the pulse using the pre-programmed plasma configuration or on line becoming a tool that allows to stop dangerous plasma configuration. All these methods have been implemented in real time on a dual Pentium Pro based machine. The Disruption Prediction and Prevention System has shown that internal plasma parameters can be determined on-line with a good accuracy. Also the disruption detection algorithms showed promising results considering the fact that JET is an experimental machine where always new plasma configurations are tested trying to improve its performances.