829 resultados para Multi-classifier systems


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The main aim of this article is to shed light on the extent to which differences in higher education participation between people with and without a migrant background of low/higher social origin can be explained by two macro-level characteristics of national educational institutions: stratification of the secondary school system and provision of alternative access to higher education. General assumptions are that people with a migrant background of low social origin benefit in low-stratified secondary school systems and in systems that provide alternative access to institutions of higher education more than their native peers in the same social stratum, owing to primary and secondary effects of migrant background. Database is a pooled dataset of the five waves of the European Social Survey. Results of logistic multi-level analyses indicate that a low-stratified secondary school system improves the probability of people with a migrant background/low social origin attaining a higher education degree. On the other hand, a stratified secondary school system reduces their chances regarding this educational stage. The provision of alternative access to an institution of higher education improves their likelihood of becoming higher education graduates.

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In Germany's compensatory mixed electoral system, alternative electoral routes lead into parliament. We study the relationship between candidates' electoral situations across both tiers and policy representation, fully accounting for candidate, party and district preferences in a multi-actor constellation and the exact electoral incentives for candidates to represent either the party or the district. The results (2009 Bundestag election data) yield evidence of an interactive effect of closeness of the district race and list safety on candidates' positioning between their party and constituency.

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Software corpora facilitate reproducibility of analyses, however, static analysis for an entire corpus still requires considerable effort, often duplicated unnecessarily by multiple users. Moreover, most corpora are designed for single languages increasing the effort for cross-language analysis. To address these aspects we propose Pangea, an infrastructure allowing fast development of static analyses on multi-language corpora. Pangea uses language-independent meta-models stored as object model snapshots that can be directly loaded into memory and queried without any parsing overhead. To reduce the effort of performing static analyses, Pangea provides out-of-the box support for: creating and refining analyses in a dedicated environment, deploying an analysis on an entire corpus, using a runner that supports parallel execution, and exporting results in various formats. In this tool demonstration we introduce Pangea and provide several usage scenarios that illustrate how it reduces the cost of analysis.

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Superresolution from plenoptic cameras or camera arrays is usually treated similarly to superresolution from video streams. However, the transformation between the low-resolution views can be determined precisely from camera geometry and parallax. Furthermore, as each low-resolution image originates from a unique physical camera, its sampling properties can also be unique. We exploit this option with a custom design of either the optics or the sensor pixels. This design makes sure that the sampling matrix of the complete system is always well-formed, enabling robust and high-resolution image reconstruction. We show that simply changing the pixel aspect ratio from square to anamorphic is sufficient to achieve that goal, as long as each camera has a unique aspect ratio. We support this claim with theoretical analysis and image reconstruction of real images. We derive the optimal aspect ratios for sets of 2 or 4 cameras. Finally, we verify our solution with a camera system using an anamorphic lens.

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The Multi-GNSS Experiment (MGEX) of the International GNSS Service (IGS) aims at the data collection and analysis of all available satellite navigation systems. In particular the new global and regional satellite navigation systems are of interest, i.e., the European Galileo, the Chinese BeiDou, the Japanese QZSS as well as satellite based augmentation systems. This article analyzes the orbit and clock quality of the Galileo products of four MGEX analysis centers for a common time period of 20 weeks. Orbit comparisons of the individual analysis centers have a consistency at the 5–30 cm level. Day boundary discontinuities range from 4 to 28 cm whereas 2-day orbit fit RMS values vary between 1 and 7 cm. The accuracy evaluated by satellite laser ranging residuals is on the one decimeter level with a systematic bias of about −5 cm for all analysis centers. In addition, systematic errors on the decimeter level related to solar radiation pressure mismodeling are present in all orbit products. Due to the correlation of radial orbit errors with the clock parameters, these errors are also visible as a bump in the Allan deviation of the Galileo satellite clocks at the orbital frequency.

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The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.

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The north-eastern escarpment of Madagascar harbours the island’s last remaining large-scale humid forest massifs surrounded by a small-scale agricultural mosaic. There is high deforestation, commonly thought to be caused by shifting cultivation practiced by local land users to produce upland rice. However, little is known about the dynamics between forest and shifting cultivation systems at a regional level. Our study presents a first attempt to quantify changes in the extent of forest and different agricultural land cover classes, and to identify the main dynamics of land cover change for two intervals, 1995–2005 and 2005–2011. Over the 16-year study period, the speed of forest loss increased, the total area of upland rice production remained almost stable, and the area of irrigated rice fields slightly increased. While our findings seem to confirm a general trend of land use intensification, deforestation through shifting cultivation is still on the rise. Deforestation mostly affects the small forest fragments interspersed in the agricultural mosaic and is slowly leading to a homogenization of the landscape. These findings have important implications for future interventions to slow forest loss in the region, as the processes of agricultural expansion through shifting cultivation versus intensified land use cannot per se be considered mutually exclusive.

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This book attempts to synthesize research that contributes to a better understanding of how to reach sustainable business value through information systems (IS) outsourcing. Important topics in this realm are how IS outsourcing can contribute to innovation, how it can be dynamically governed, how to cope with its increasing complexity through multi-vendor arrangements, how service quality standards can be met, how corporate social responsibility can be upheld and how to cope with increasing demands of internationalization and new sourcing models, such as crowdsourcing and platform-based cooperation. These issues are viewed from either the client or vendor perspective, or both. The book should be of interest to all academics and students in the fields of Information Systems, Management and Organization as well as corporate executives and professionals who seek a more profound analysis and understanding of the underlying factors and mechanisms of outsourcing.

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Information-centric networking (ICN) addresses drawbacks of the Internet protocol, namely scalability and security. ICN is a promising approach for wireless communication because it enables seamless mobile communication, where intermediate or source nodes may change, as well as quick recovery from collisions. In this work, we study wireless multi-hop communication in Content-Centric Networking (CCN), which is a popular ICN architecture. We propose to use two broadcast faces that can be used in alternating order along the path to support multi-hop communication between any nodes in the network. By slightly modifying CCN, we can reduce the number of duplicate Interests by 93.4 % and the number of collisions by 61.4 %. Furthermore, we describe and evaluate different strategies for prefix registration based on overhearing. Strategies that configure prefixes only on one of the two faces can result in at least 27.3 % faster data transmissions.

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Most commercial project management software packages include planning methods to devise schedules for resource-constrained projects. As it is proprietary information of the software vendors which planning methods are implemented, the question arises how the software packages differ in quality with respect to their resource-allocation capabilities. We experimentally evaluate the resource-allocation capabilities of eight recent software packages by using 1,560 instances with 30, 60, and 120 activities of the well-known PSPLIB library. In some of the analyzed packages, the user may influence the resource allocation by means of multi-level priority rules, whereas in other packages, only few options can be chosen. We study the impact of various complexity parameters and priority rules on the project duration obtained by the software packages. The results indicate that the resource-allocation capabilities of these packages differ significantly. In general, the relative gap between the packages gets larger with increasing resource scarcity and with increasing number of activities. Moreover, the selection of the priority rule has a considerable impact on the project duration. Surprisingly, when selecting a priority rule in the packages where it is possible, both the mean and the variance of the project duration are in general worse than for the packages which do not offer the selection of a priority rule.

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Spurred by the consumer market, companies increasingly deploy smartphones or tablet computers in their operations. However, unlike private users, companies typically struggle to cover their needs with existing applications, and therefore expand mobile software platforms through customized applications from multiple software vendors. Companies thereby combine the concepts of multi-sourcing and software platform ecosystems in a novel platform-based multi-sourcing setting. This implies, however, the clash of two different approaches towards the coordination of the underlying one-to-many inter-organizational relationships. So far, however, little is known about impacts of merging coordination approaches. Relying on convention theory, we addresses this gap by analyzing a platform-based multi-sourcing project between a client and six software vendors, that develop twenty-three custom-made applications on a common platform (Android). In doing so, we aim to understand how unequal coordination approaches merge, and whether and for what reason particular coordination mechanisms, design decisions, or practices disappear, while new ones emerge.

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Information-centric networking (ICN) is a promising approach for wireless communication because users can exploit the broadcast nature of the wireless medium to quickly find desired content at nearby nodes. However, wireless multi-hop communication is prone to collisions and it is crucial to quickly detect and react to them to optimize transmission times and a void spurious retransmissions. Several adaptive retransmission timers have been used in related ICN literature but they have not been compared and evaluated in wireless multi-hop environments. In this work, we evaluate existing algorithms in wireless multi-hop communication. We find that existing algorithms are not optimized for wireless communication but slight modificati ons can result in considerably better performance without increasing the number of transmitted Interests.

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Soils provide us with over 90% of all human food, livestock feed, fibre and fuel on Earth. Soils, however, have more than just productive functions. The key challenge in coming years will be to address the diverse and potentially conflicting demands now being made by human societies and other forms of life, while ensuring that future generations have the same potential to use soils and land of comparable quality. In a multi-level stakeholder approach, down-to-earth action will have to be supplemented with measures at various levels, from households to communities, and from national policies to international conventions. Knowledge systems, both indigenous and scientific, and related research and learning processes must play a central role. Ongoing action can be enhanced through a critical assessment of the impact of past achievements, and through better cooperation between people and institutions.

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Abstract Information-centric networking (ICN) offers new perspectives on mobile ad-hoc communication because routing is based on names but not on endpoint identifiers. Since every content object has a unique name and is signed, authentic content can be stored and cached by any node. If connectivity to a content source breaks, it is not necessarily required to build a new path to the same source but content can also be retrieved from a closer node that provides the same content copy. For example, in case of collisions, retransmissions do not need to be performed over the entire path but due to caching only over the link where the collision occurred. Furthermore, multiple requests can be aggregated to improve scalability of wireless multi-hop communication. In this work, we base our investigations on Content-Centric Networking (CCN), which is a popular {ICN} architecture. While related works in wireless {CCN} communication are based on broadcast communication exclusively, we show that this is not needed for efficient mobile ad-hoc communication. With Dynamic Unicast requesters can build unicast paths to content sources after they have been identified via broadcast. We have implemented Dynamic Unicast in CCNx, which provides a reference implementation of the {CCN} concepts, and performed extensive evaluations in diverse mobile scenarios using NS3-DCE, the direct code execution framework for the {NS3} network simulator. Our evaluations show that Dynamic Unicast can result in more efficient communication than broadcast communication, but still supports all {CCN} advantages such as caching, scalability and implicit content discovery.