4,649 research outputs found
Predictability of stock returns using financial statement information: Evidence on semi-strong efficiency of emerging Greek stock market
This article examines the predictability of stock returns in the Athens Stock
Exchange (ASE) during 1993 to 2006 by using accounting information. Using panel
data analysis, this article concludes that the selected set of financial ratios
contains significant information for predicting the cross-section of stock
returns. Results indicate that portfolios selected on the basis of financial
ratios produce higher than average returns, suggesting that the emerging Greek
market does not fully incorporate accounting information into stock prices and
hence it is not semi-strong efficient
Grand Challenges of Traceability: The Next Ten Years
In 2007, the software and systems traceability community met at the first
Natural Bridge symposium on the Grand Challenges of Traceability to establish
and address research goals for achieving effective, trustworthy, and ubiquitous
traceability. Ten years later, in 2017, the community came together to evaluate
a decade of progress towards achieving these goals. These proceedings document
some of that progress. They include a series of short position papers,
representing current work in the community organized across four process axes
of traceability practice. The sessions covered topics from Trace Strategizing,
Trace Link Creation and Evolution, Trace Link Usage, real-world applications of
Traceability, and Traceability Datasets and benchmarks. Two breakout groups
focused on the importance of creating and sharing traceability datasets within
the research community, and discussed challenges related to the adoption of
tracing techniques in industrial practice. Members of the research community
are engaged in many active, ongoing, and impactful research projects. Our hope
is that ten years from now we will be able to look back at a productive decade
of research and claim that we have achieved the overarching Grand Challenge of
Traceability, which seeks for traceability to be always present, built into the
engineering process, and for it to have "effectively disappeared without a
trace". We hope that others will see the potential that traceability has for
empowering software and systems engineers to develop higher-quality products at
increasing levels of complexity and scale, and that they will join the active
community of Software and Systems traceability researchers as we move forward
into the next decade of research
Performance tuning of a smartphone-based overtaking assistant
ITS solutions suffer from the slow pace of adoption by manufacturers despite the interest shown by both consumers and industry. Our goal is to develop ITS applications using already available technologies to make them affordable, quick to deploy, and easy to adopt. In this paper we introduce EYES, an overtaking assistance solution that provides drivers with a real-time video feed from the vehicle located just in front. Our application thus provides a better view of the road ahead, and of any vehicles travelling in the opposite direction, being especially useful when the front view of the driver is blocked by large vehicles. We evaluated our application using the MJPEG video encoding format, and have determined the most effective resolution and JPEG quality choice for our case. Experimental results from the tests performed with the application in both indoor and outdoor scenarios, allow us to be optimistic about the effectiveness and applicability of smartphones in providing overtaking assistance based on video streaming in vehicular networks
Determining the relative position of vehicles considering bidirectional traffic scenarios in VANETS
Researchers pertaining to both academia and industry have shown strong interest in developing and improving the existing critical ITS solutions. In some of the existing solutions, specially the ones that aim at providing context aware services, the knowledge of relative positioning of one node by other nodes becomes crucial. In this paper we explore, apart from the conventional use of GPS data, the applicability of image processing to aid in determining the relative positions of nodes in a vehicular network. Experiments conducted show that both the use of location information and image processing works well and can be deployed depending on the requirement of the application. Our experiments show that the results that used location information were affected by GPS errors, while the use of image processing, although producing more accurate results, require significantly more processing power
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