University of Piraeus

About: University of Piraeus is a education organization based out in Piraeus, Attiki, Greece. It is known for research contribution in the topics: Context (language use) & Computer science. The organization has 1731 authors who have published 6209 publications receiving 106699 citations.

Effective software-based self-test strategies for on-line periodic testing of embedded processors

Abstract: Software-based self-test (SBST) strategies are particularly useful for periodic testing of deeply embedded processors in low-cost embedded systems that do not require immediate detection of errors and cannot afford the well-known hardware, software, or time redundancy mechanisms. In this paper, first, we identify the stringent characteristics of an SBST test program to be suitable for on-line periodic testing. Then, we introduce a new SBST methodology with a new classification scheme for processor components. After that, we analyze the self-test routine code styles for the three more effective test pattern generation (TPG) strategies in order to select the most effective self-test routine for on-line periodic testing of a component under test. Finally, we demonstrate the effectiveness of the proposed SBST methodology for on-line periodic testing by presenting experimental results for a RISC pipeline processor.

Assessing n-order dependencies between critical infrastructures

Abstract: The protection of critical infrastructures (CI) is a complex task, since it involves the assessment of both internal and external security risk. In the recent literature, methodologies have been proposed that can be used to identify organisation-wise security threats, or even first-order dependency risk (i.e., risk deriving from direct dependencies). However, there is a lack of work in the area of multi-order dependencies, i.e., assessing the cumulative effects of a single incident, on infrastructures that are connected indirectly. In this paper, we propose a method to identify and assess multi-order dependencies. Based on previous work, we utilise existing first-order dependency graphs, in order to assess the effect of a disruption to consequent infrastructures. In this way, it may be possible to identify and prevent security threats of very high impact from a macroscopic view, which would be hard to identify if we only examine first-order dependencies. We also present a scenario, which provides some evidence on the applicability of the proposed approach.

Bank dividends, risk, and regulatory regimes.

Abstract: This paper investigates the relation between bank dividends and bank risk over the period 1984–2011, and assesses the existence of risk-taking and risk-shifting in the US commercial banking sector subject to regulatory regime changes. The introduction of PCA in 1992 and TARP in 2008 constitute significant regulatory regime changes, and provide the necessary framework to explore whether regime-dependent risk-shifting or risk-taking is present. We find strong evidence of risk-shifting and risk-taking over the post-PCA regime spanning the period 1992–2008. We interpret this evidence as indication of ineffectiveness of PCA in controlling risk-taking and risk-shifting. The finding of risk-taking just prior to the recent financial crisis suggests that risk-taking may be a factor contributing to this crisis. As risk-taking and risk-shifting are important aspects of bank behavior ( Basel Committee on Banking Supervision, 2009 ), these results are of interest to bank regulators and important to Basel III.

Causality between energy consumption and GDP in the U.S.: evidence from wavelet analysis

Abstract: This study investigates the dynamic causal relationship between energy consumption and economic growth in the U.S. at different time scales. The main novelty of the study is that this paper complements the existing studies on the nexus between energy consumption and economic growth by employing the wavelet transformation to obtain different time scales in order to investigate causality between energy consumption and economic growth. This method is first developed by Ramsey and Lampart. Their approach consists of first decomposing the series into time scales by wavelet filters and testing causality of each time scale with the pertinent time scale of the other series separately. The data span from 1973q1 to 2012q1 on a quarterly basis. The main empirical insight is that the causal relationship is stronger at finer time scales, whereas the relationship is less and less apparent at longer time horizons. The results indicate that energy consumption causes economic growth, while the reverse is not true at the original frequency of the data. At the very finest scale the same result arises. However, at coarser scales feedback is observed. In particular, at intermediate time scales the evidence indicates that energy consumption causes economic growth, while the reverse is also true. These empirical findings are expected to be of high importance in terms of the effective design and implementation of energy and environmental policies, especially when a number of countries in the pursuit of high economic growth targets do not pay any serious attention on environmental issues.

The Greek Implied Volatility Index: Construction and Properties

Abstract: There is a growing literature on implied volatility indices in developed markets. However, no research has been conducted in the context of emerging markets. In this paper, an implied volatility index (GVIX) is constructed for the fast developing Greek derivatives market. Next, the properties of GVIX are explored. In line with earlier results, GVIX can be interpreted as a gauge of the investor's sentiment. In addition, we find that the underlying market can forecast the future movements of GVIX. However, the reverse relationship does not hold. Finally, a contemporaneous spillover between GVIX, and the US volatility indices VXO and VXN is detected.