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.

Predictability of stock returns using financial statement information: evidence on semi-strong efficiency of emerging Greek stock market

Abstract: 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.

Competition and price asymmetries in the Greek oil sector: an empirical analysis on gasoline market

Abstract: This article attempts to investigate the issue of asymmetries in the transmission of shocks to input prices and exchange rate onto the wholesale and retail price of gasoline respectively. For this purpose, we utilise the error-correction methodology in the Greek gasoline market. The sample consists of monthly data covering the period of January 1988 to June 2006. We also try to analyse by using impulse response functions the effect of competition on the dynamic adjustment of gasoline price to which has been paid scant attention in the past. The results favour the common perception that retail gasoline prices respond asymmetrically to cost increases and decreases both in the long and the short-run. At the wholesale segment, there is a symmetric response of the spot prices of gasoline towards the adjustment to the short-run responses of the exchange rate. Lastly, after the deregulation, wholesale prices of gasoline tend to gradually restore equilibrium triggered by a price shock compared to the regulated period.

Cryptography Goes to the Cloud

Abstract: In this paper we identify some areas where cryptography can help a rapid adoption of cloud computing. Although secure storage has already captured the attention of many cloud providers, offering a higher level of protection for their customer’s data, we think that more advanced techniques such as searchable encryption and secure outsourced computation will become popular in the near future, opening the doors of the Cloud to customers with higher security requirements.

A Knowledge-Based Approach to Online Fault Diagnosis of FET Biosensors

Abstract: Real-time diagnosis of insulator-semiconductor field-effect transistor (ISFET)-based biosensor systems aims at promptly correcting errors caused by insufficient function; insufficiency is judged by the operational behavior of the sensor, i.e., the data that it produces. Ultimately, a complete failure of the system (i.e., a “dead” sensor) should easily be recognized. Much more difficult is the recognition of a gradual malfunction of this complex system, which may be attributed to faults or failures in one or more of its subsystems. Evidently, the identification of the possible fault modes and their symptoms requires in-depth knowledge of sensor's design and operation, both from the biochemical and electrical/electronic points of view, along with tackling uncertain, incomplete, or imprecise information. In this paper, a novel real-time diagnostic expert scheme for field-effect transistor (FET)-based biosensing is proposed. This paper 1) investigates the causes of sensor misfunction by means of fault tree analysis (FTA) relying on fuzzy reasoning to account for uncertainty and 2) proposes a computer-aided method for diagnosing biosensor failure during operation through an algorithmic procedure that is based on a nested loop mechanism. The tree (dendritic) structure (built using the information provided by the biosensor components and their intrarelations/interrelations on a surface- and a deep-knowledge level) serves as the knowledge base (KB), and the fuzzy-rules-based decision mechanism is the inference engine for fault detection and isolation.

Baquara: A Holistic Ontological Framework for Movement Analysis Using Linked Data

Abstract: Movement understanding frequently requires further information and knowledge than what can be obtained from bare spatio-temporal traces. Despite recent progress in trajectory data management, there is still a gap between the spatio-temporal aspects and the semantics involved. This gap hinders trajectory analysis benefiting from growing collections of linked data, with well-defined and widely agreed semantics, already available on the Web. This article introduces Baquara, an ontology with rich constructs, associated with a system architecture and an approach to narrow this gap. The Baquara ontology functions as a conceptual framework for semantic enrichment of movement data with annotations based on linked data. The proposed architecture and approach reveal new possibilities for trajectory analysis, using database management systems and triple stores extended with spatial data and operators. The viability of the proposal and the expressiveness of the Baquara ontology and enabled queries are investigated in a case study using real sets of trajectories and linked data.