884 resultados para Connectivity,Connected Car,Big Data,KPI
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Anders Söderbäckin esitys Kirjastoverkkopäivillä 26.10.2011 Helsingissä.
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SStrong evidence suggests that the climate is changing and that these changes are largely caused by human activities. A consensus exists among researchers that human activity is causing global warming and that actions to mitigate global warming need to be taken swiftly. The transportation sector, which relies heavily on fossil fuel burning and primarily oil, is one of the big contributors to air pollution problems at local, regional and global levels. It is the fastest growing source of greenhouse gas emissions and is estimated to be responsible for nearly a quarter of global energyrelated carbon dioxide emissions. Car sharing is a mobility solution encouraging its users to decrease private car usage in favour of communal transit and environmental goals. The idea of car sharing originates from the aspiration to decrease personal car ownership and to reduce vehicle distance travelled. This thesis seeks to complement the understanding of Finnish car sharing users and their usage through better categorization. Through better categorization and segmentation of Finnish car sharing users the thesis seeks to provide information for improved marketing insight. Research is done on the demographic and behavioural characteristics of Finnish car sharing users and they are compared with international findings about the characteristics of International car sharing users. The main research problem is Are Finnish car sharing users similar to international ones? A theoretical research framework on the determinants of individual car sharing usage is built based on international research about demographic and behaviouristic characteristics. After this a quantitative survey is performed to the customers of a Finnish car sharing organization. The data analysed in the thesis consist out of 532 answers received from the car sharing organizations customers. The data is analysed with descriptive and other exploratory methods, which create an understanding of Finnish car sharing users. At the end of the analysis the demographic and behavioural characteristics of Finnish car sharing users are compared with international ones. The research findings of the thesis indicate that the demographic and behavioural characteristics of Finnish car sharing usage largely follow those of their international counterparts. Thanks to the thesis results the car sharing organization is able to better target their customers through improved marketing insight.
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List of topics and Slides which summarise legal perspectives with suggested methods on how to revise for the exam
Big Decisions and Sparse Data: Adapting Scientific Publishing to the Needs of Practical Conservation
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The biggest challenge in conservation biology is breaking down the gap between research and practical management. A major obstacle is the fact that many researchers are unwilling to tackle projects likely to produce sparse or messy data because the results would be difficult to publish in refereed journals. The obvious solution to sparse data is to build up results from multiple studies. Consequently, we suggest that there needs to be greater emphasis in conservation biology on publishing papers that can be built on by subsequent research rather than on papers that produce clear results individually. This building approach requires: (1) a stronger theoretical framework, in which researchers attempt to anticipate models that will be relevant in future studies and incorporate expected differences among studies into those models; (2) use of modern methods for model selection and multi-model inference, and publication of parameter estimates under a range of plausible models; (3) explicit incorporation of prior information into each case study; and (4) planning management treatments in an adaptive framework that considers treatments applied in other studies. We encourage journals to publish papers that promote this building approach rather than expecting papers to conform to traditional standards of rigor as stand-alone papers, and believe that this shift in publishing philosophy would better encourage researchers to tackle the most urgent conservation problems.
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The General Election for the 56th United Kingdom Parliament was held on 7 May 2015. Tweets related to UK politics, not only those with the specific hashtag ”#GE2015”, have been collected in the period between March 1 and May 31, 2015. The resulting dataset contains over 28 million tweets for a total of 118 GB in uncompressed format or 15 GB in compressed format. This study describes the method that was used to collect the tweets and presents some analysis, including a political sentiment index, and outlines interesting research directions on Big Social Data based on Twitter microblogging.
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It is known that large fragment sizes and high connectivity levels are key components for maintaining species in fragments; however, their relative effects are poorly understood, especially in tropical areas. In order to test these effects, we built models for explaining understory birds occurrence in a fragmented Atlantic Rain Forest landscape with intermediate habitat cover (3%). Data from over 9000 mist-net hours from 17 fragments differing in size (2-175 ha) and connectivity (considering corridor linkages and distance to nearby fragments) were ranked under a model selection approach. A total 1293 individuals of 62 species were recorded. Species richness, abundance and compositional variation were mainly affected by connectivity indices that consider the capacity of species to use corridors and/or to cross short distances up to 30 m through the matrix. Bird functional groups were differently affected by area and connectivity: while terrestrial insectivores, omnivores and frugivores were affected by both area and connectivity, the other groups (understory insectivores, nectarivores, and others) were affected only by connectivity. In the studied landscape, well connected fragments can sustain an elevated number of species and individuals. Connectivity gives the opportunity for individuals to use multiple fragments, reducing the influence of fragment size. While preserving large fragments is a conservation target worldwide and should continue to be, our results indicated that connectivity between fragments can enhance the area functionally connected and is beneficial to all functional groups and therefore should be a conservation priority. (C) 2008 Elsevier Ltd. All rights reserved.
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In the present study, we propose a theoretical graph procedure to investigate multiple pathways in brain functional networks. By taking into account all the possible paths consisting of h links between the nodes pairs of the network, we measured the global network redundancy R (h) as the number of parallel paths and the global network permeability P (h) as the probability to get connected. We used this procedure to investigate the structural and dynamical changes in the cortical networks estimated from a dataset of high-resolution EEG signals in a group of spinal cord injured (SCI) patients during the attempt of foot movement. In the light of a statistical contrast with a healthy population, the permeability index P (h) of the SCI networks increased significantly (P < 0.01) in the Theta frequency band (3-6 Hz) for distances h ranging from 2 to 4. On the contrary, no significant differences were found between the two populations for the redundancy index R (h) . The most significant changes in the brain functional network of SCI patients occurred mainly in the lower spectral contents. These changes were related to an improved propagation of communication between the closest cortical areas rather than to a different level of redundancy. This evidence strengthens the hypothesis of the need for a higher functional interaction among the closest ROIs as a mechanism to compensate the lack of feedback from the peripheral nerves to the sensomotor areas.
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In the last 10 years the number of mobile devices has grown rapidly. Each person usually brings at least two personal devices and researchers says that in a near future this number could raise up to ten devices per person. Moreover, all the devices are becoming more integrated to our life than in the past, therefore the amount of data exchanged increases accordingly to the improvement of people's lifestyle. This is what researchers call Internet of Things. Thus, in the future there will be more than 60 billions of nodes and the current infrastructure is not ready to keep track of all the exchanges of data between them. Therefore, infrastructure improvements have been proposed in the last years, like MobileIP and HIP in order to facilitate the exchange of packets in mobility, however none of them have been optimized for the purpose. In the last years, researchers from Mid Sweden University created The MediaSense Framework. Initially, this framework was based on the Chord protocol in order to route packets in a big network, but the most important change has been the introduction of PGrids in order to create the Overlay and the persistence. Thanks to this technology, a lookup in the trie takes up to 0.5*log(N), where N is the total number of nodes in the network. This result could be improved by further optimizations on the management of the nodes, for example by the dynamic creation of groups of nodes. Moreover, since the nodes move, an underlaying support for connectivity management is needed. SCTP has been selected as one of the most promising upcoming standards for simultaneous multiple connection's management.
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Independent component analysis (ICA) or seed based approaches (SBA) in functional magnetic resonance imaging blood oxygenation level dependent (BOLD) data became widely applied tools to identify functionally connected, large scale brain networks. Differences between task conditions as well as specific alterations of the networks in patients as compared to healthy controls were reported. However, BOLD lacks the possibility of quantifying absolute network metabolic activity, which is of particular interest in the case of pathological alterations. In contrast, arterial spin labeling (ASL) techniques allow quantifying absolute cerebral blood flow (CBF) in rest and in task-related conditions. In this study, we explored the ability of identifying networks in ASL data using ICA and to quantify network activity in terms of absolute CBF values. Moreover, we compared the results to SBA and performed a test-retest analysis. Twelve healthy young subjects performed a fingertapping block-design experiment. During the task pseudo-continuous ASL was measured. After CBF quantification the individual datasets were concatenated and subjected to the ICA algorithm. ICA proved capable to identify the somato-motor and the default mode network. Moreover, absolute network CBF within the separate networks during either condition could be quantified. We could demonstrate that using ICA and SBA functional connectivity analysis is feasible and robust in ASL-CBF data. CBF functional connectivity is a novel approach that opens a new strategy to evaluate differences of network activity in terms of absolute network CBF and thus allows quantifying inter-individual differences in the resting state and task-related activations and deactivations.
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This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC), an initiative to collect unique longitudinal smartphone dataset for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC, describe the specific datasets used in each of them, discuss the key design and implementation aspects introduced in order to generate privacy-preserving and scientifically relevant mobile data resources for wider use by the research community, and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.
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Sensory rhodopsin I (SRI) in Halobacterium salinarum acts as a receptor for single-quantum attractant and two-quantum repellent phototaxis, transmitting light stimuli via its bound transducer HtrI. Signal-inverting mutations in the SRI-HtrI complex reverse the single-quantum response from attractant to repellent. Fast intramolecular charge movements reported here reveal that the unphotolyzed SRI-HtrI complex exists in two conformational states, which differ by their connection of the retinylidene Schiff base in the SRI photoactive site to inner or outer half-channels. In single-quantum photochemical reactions, the conformer with the Schiff base connected to the cytoplasmic (CP) half-channel generates an attractant signal, whereas the conformer with the Schiff base connected to the extracellular (EC) half-channel generates a repellent signal. In the wild-type complex the conformer equilibrium is poised strongly in favor of that with CP-accessible Schiff base. Signal-inverting mutations shift the equilibrium in favor of the EC-accessible Schiff base form, and suppressor mutations shift the equilibrium back toward the CP-accessible Schiff base form, restoring the wild-type phenotype. Our data show that the sign of the behavioral response directly correlates with the state of the connectivity switch, not with the direction of proton movements or changes in acceptor pK(a). These findings identify a shared fundamental process in the mechanisms of transport and signaling by the rhodopsin family. Furthermore, the effects of mutations in the HtrI subunit of the complex on SRI Schiff base connectivity indicate that the two proteins are tightly coupled to form a single unit that undergoes a concerted conformational transition.
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Resting-state functional connectivity (FC) fMRI (rs-fcMRI) offers an appealing approach to mapping the brain's intrinsic functional organization. Blood oxygen level dependent (BOLD) and arterial spin labeling (ASL) are the two main rs-fcMRI approaches to assess alterations in brain networks associated with individual differences, behavior and psychopathology. While the BOLD signal is stronger with a higher temporal resolution, ASL provides quantitative, direct measures of the physiology and metabolism of specific networks. This study systematically investigated the similarity and reliability of resting brain networks (RBNs) in BOLD and ASL. A 2×2×2 factorial design was employed where each subject underwent repeated BOLD and ASL rs-fcMRI scans on two occasions on two MRI scanners respectively. Both independent and joint FC analyses revealed common RBNs in ASL and BOLD rs-fcMRI with a moderate to high level of spatial overlap, verified by Dice Similarity Coefficients. Test-retest analyses indicated more reliable spatial network patterns in BOLD (average modal Intraclass Correlation Coefficients: 0.905±0.033 between-sessions; 0.885±0.052 between-scanners) than ASL (0.545±0.048; 0.575±0.059). Nevertheless, ASL provided highly reproducible (0.955±0.021; 0.970±0.011) network-specific CBF measurements. Moreover, we observed positive correlations between regional CBF and FC in core areas of all RBNs indicating a relationship between network connectivity and its baseline metabolism. Taken together, the combination of ASL and BOLD rs-fcMRI provides a powerful tool for characterizing the spatiotemporal and quantitative properties of RBNs. These findings pave the way for future BOLD and ASL rs-fcMRI studies in clinical populations that are carried out across time and scanners.