2,858 research outputs found

    Constructing a no-reference H.264/AVC bitstream-based video quality metric using genetic programming-based symbolic regression

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    In order to ensure optimal quality of experience toward end users during video streaming, automatic video quality assessment becomes an important field-of-interest to video service providers. Objective video quality metrics try to estimate perceived quality with high accuracy and in an automated manner. In traditional approaches, these metrics model the complex properties of the human visual system. More recently, however, it has been shown that machine learning approaches can also yield competitive results. In this paper, we present a novel no-reference bitstream-based objective video quality metric that is constructed by genetic programming-based symbolic regression. A key benefit of this approach is that it calculates reliable white-box models that allow us to determine the importance of the parameters. Additionally, these models can provide human insight into the underlying principles of subjective video quality assessment. Numerical results show that perceived quality can be modeled with high accuracy using only parameters extracted from the received video bitstream

    Measuring the software process and product: Lessons learned in the SEL

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    The software development process and product can and should be measured. The software measurement process at the Software Engineering Laboratory (SEL) has taught a major lesson: develop a goal-driven paradigm (also characterized as a goal/question/metric paradigm) for data collection. Project analysis under this paradigm leads to a design for evaluating and improving the methodology of software development and maintenance

    Compressor and fan wake characteristics

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    A triaxial probe and a rotating conventional probe, mounted on a traverse gear operated by two step motors were used to measure the mean velocities and turbulence quantities across a rotor wake at various radial locations and downstream stations. The data obtained was used in an analytical model developed to study how rotor flow and blade parameters and turbulence properties such as energy, velocity correlations, and length scale affect the rotor wake characteristics and its diffusion properties. The model, includes three dimensional attributes, can be used in predicting the discrete as well as broadband noise generated in a fan rotor, as well as in evaluating the aerodynamic losses, efficiency and optimum spacing between a rotor and stator in turbomachinery

    Complexity in financial market. Modeling psychological behavior in agent-based models and order book models

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    The fundamental idea developed throughout this work is the introduction of new metrics in Social Sciences (Economics, Finance, opinion dynamics, etc). The concept of metric, that is the concept of measure, is usually neglected by mainstream theories of Economics and Finance. Financial Markets are the natural starting point of such an approach to Social Sciences because a systematic approach can be undertaken and the methods of Physics has shown to be very effective. In fact since a decade there exists a very huge amount of high frequency data from stock exchanges which permit to perform experimental procedures as in Natural Sciences. Financial markets appear as a perfect playground where models can be tested and where repeatability of empirical evidences are well-established features differently from, for instance, Macro-Economy and Micro-Economy. Thus Finance has been the first point of contact for the interdisciplinary application of methods and tools deriving from Physics and it has been also the starting point of this work. We investigated the origin of the so-called Stylized Facts of financial markets (i.e. the statistical properties of financial time series) in the framework of agent-based models. We found that Stylized Facts can be interpreted as a finite size effect in terms of the number of effectively independent agents (i.e. strategy) which results to be a key variable to understand the self-organization of financial markets. As a second issue we focused our attention on the order book dynamics both from a theoretical and a data oriented point of view. We developed a zero intelligence model in order to investigate the role of vanishing liquidity in the price response to incoming orders. Within the framework of this model we have analyzed the effect of the introduction of strategies pointing out that simple strategic behaviors can explain bursts of intermittency and long memory effects. On the other hand we quantitatively showed that there exists a feedback effect in markets called self-fulfilling prophecy which is the mechanism through which technical trading can exist and work. This feature is a very interesting quantitative evidence of a self-reinforcement of agents’ belief. Last but not least nowadays we live in a computerized and networked society where many of our actions leave a digital trace and affect other people’s actions. This has lead to the emergence of a new data-driven research field. In this work we highlighted how non financial data can be used to track financial activity, in detail we investigate query log volumes, i.e. the volumes of searches for a specific query done by users in a search engine, as a proxy for trading volumes and we find that users’ activity on Yahoo! search engine anticipates trading volume by one-two days. Differently from Finance, Economics is far from being an ideal candidate to export the methodology of Natural Sciences because of the lack of empirical data since controlled (and repeatable) experiments are totally artificial while real experiments are almost incontrollable and non repeatable due to a high degree of non stationarity of economical systems. However, the application of method deriving from complexity to the Economics of Growth is one of the more important achievement of the work here developed. The basic idea is to study the network defined by international trade flows and introduce a (non-monetary) metric to measure the complexity and the competitiveness of countries’ productive system. In addition we are able to define a metric for products’ quality which overcomes traditional economic measure for the quality of products given in terms of hours of qualified labour needed to produce a good. The method developed provides some impressive results in predicting economical growth of countries and offers many opportunities of improvements and generalizations

    Why Performance Information Use Requires a Managerial Identity: Evidence from the Field of Human Services

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    Previous research suggests that civil servants can perceive their role differently and that these differing perceptions also influence their responses to managerial reform programs. Yet there is little research examining how different role perceptions influence the application of performance measurement. Using survey data from 742 human service organizations in Switzerland, the present study addresses this gap by investigating how professional and managerial role identities affect managers’ use of performance information. The results support the hypotheses that role identities indirectly influence the application of performance information through the effects on role conflict that may occur when managerial professionals measure the performance of their organizations. A lack of resources, stringent political control, and poor information quality are also found to be associated with role conflict and a limited use of performance information
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