BM25 is probably the most well known term weighting model in Information Retrieval. It has, depending on the formula variant at hand, 2 or 3 parameters (k1, b, and k3). This paper addresses b-the document length norma...
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In this work we investigate an infrared structured light pro-totype which is intended for 3D reconstruction in resource-restricted mobile applications. We explore the constraints on working range and pattern resolutio...
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ISBN:
(纸本)9781450334938
In this work we investigate an infrared structured light pro-totype which is intended for 3D reconstruction in resource-restricted mobile applications. We explore the constraints on working range and pattern resolution that are imposed by the low-light property of our single-shot set-up. While focusing on the most light-sensitive steps of the decoding workow, we suggest adaptations of image rectification and pattern generation and segmentation algorithms that are tailored to the specific spatial and radiometric requirements of our system. Copyright 2015 ACM.
The advent of the Internet of Things (IoT) is driving several technological trends. The first trend is an increased level of integration between edge devices and commodity computers. This trend, in conjunction with lo...
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ISBN:
(纸本)9781509033232
The advent of the Internet of Things (IoT) is driving several technological trends. The first trend is an increased level of integration between edge devices and commodity computers. This trend, in conjunction with low power-devices, energy harvesting, and improved battery technology, is enabling the next generation of information technology (IT) innovation: city-scale smart systems. These types of IoT systems can operate at multiple time-scales, ranging from closed-loop control requiring strict real-time decision and actuation to near real-time operation with humans-in-the-loop, as well as to long-term analysis, planning, and decision-making.
Mobile business applications such as mobile shopping have experienced a major upswing in recent years. In order to respond appropriately to the high and still increasing demands of consumers, traders make use of mobil...
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Research databases are an important building block in eScience and computational science investigations. For enabling reproducible research, an approach is needed which supports the identification and citation of the ...
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Research databases are an important building block in eScience and computational science investigations. For enabling reproducible research, an approach is needed which supports the identification and citation of the exact data (sub)sets utilized in experiments. While this itself is a challenge, in many cases the data stored in databases is sensitive and needs to be protected. Due to the increasing complexity of eScience investigations, data is often integrated from different sources, potentially stemming from competing data owners. In order to achieve the research goals, the data needs to be combined and analysed as a whole. As data owners of such sources may have potential conflicts of interest in certain aspects, a mechanism is needed which prevents the retrieval and or recombination of privacy related data while still full access to own data must be granted at all times.
Monitoring ultrascale systems such as Clouds requires collecting enormous amount of data by periodically reading metric values from a system. Current approaches tend to select a static frequency for sampling monitorin...
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Monitoring ultrascale systems such as Clouds requires collecting enormous amount of data by periodically reading metric values from a system. Current approaches tend to select a static frequency for sampling monitoring data. On one hand, over-sampling the data by collecting it at high frequencies results in data redundancy during steady runs of the system. On the other hand, under-sampling with low monitoring frequencies results in information loss during volatile behaviour of the system as data is significantly diluted. Therefore, choosing an optimal monitoring frequency represents a challenging research issue. In this paper, we propose a dynamic monitoring frequency algorithm for collecting monitoring data from ultrascale systems such as Clouds. The algorithm deterministically reduces data velocity by self-adapting the monitoring frequency to the volatility of data being collected. Consequently, it collects less data due to fewer readings, while keeping the same data value as the equivalent static monitoring frequency. The proposed approach is evaluated using Google traces where it is able to reduce the velocity of monitoring data by up to 85% without diluting information quality.
Patents, archived as large collections of semi-structured text documents, contain valuable information about historical trends and current states of R&D fields, as well as performances of single inventors and comp...
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ISBN:
(纸本)9789897580888
Patents, archived as large collections of semi-structured text documents, contain valuable information about historical trends and current states of R&D fields, as well as performances of single inventors and companies. Specific methods are needed to unlock this information and enable its insightful analysis by investors, executives, funding agencies, and policy makers. In this position paper, we propose an approach based on modelling patent repositories as multivariate temporal networks, and examining them by the means of specific visual analytics methods. We illustrate the potential of our approach by discussing two use-cases: the determination of emerging research fields in general and within companies, as well as the identification of inventors characterized by different temporal paths of productivity.
Due to recent developments of low-cost image sensors and high-performance embedded processing hardware, future cars and automotive systems will increasingly use binocular stereo vision for environmental perception. Ho...
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Due to recent developments of low-cost image sensors and high-performance embedded processing hardware, future cars and automotive systems will increasingly use binocular stereo vision for environmental perception. However, research and development in stereo vision is still ongoing since there are many challenges unsolved. In this paper, we propose a fast and accurate stereo matching algorithm, designed for automotive applications. It convincingly handles real-world scenes containing complex, textureless, and slanted surfaces. To achieve that, we propose an improved PatchMatch stereo algorithm that combines a census-based cost function with Semi-Global Matching optimization integrated in a cross-scale fusion processing scheme. To further accelerate the algorithm, we propose a novel enhancement approach for PatchMatch-based approximation which allows us to skip the random search or at least significantly reduce the number of iterations. Our method is ranked in the upper third of the KITTI benchmark and among the top performers in terms of processing time.
Clinical practice guidelines aim at raising the quality of healthcare. They are written in a narrative style and have to be translated into a computer-interpretable guideline (CIG) to be usable in a clinical software ...
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