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.

Estimator Choice and Fisher's Paradox: A Monte Carlo Study

Abstract: This paper argues that Fisher's paradox can be explained away in terms of estimator choice. We analyse by means of Monte Carlo experiments the small sample properties of a large set of estimators (including virtually all available single-equation estimators), and compute the critical values based on the empirical distributions of the t-statistics, for a variety of Data Generation Processes (DGPs), allowing for structural breaks, ARCH effects etc. We show that precisely the estimators most commonly used in the literature, namely OLS, Dynamic OLS (DOLS) and non-prewhitened FMLS, have the worst performance in small samples, and produce rejections of the Fisher hypothesis. If one employs the estimators with the most desirable properties (i.e., the smallest downward bias and the minimum shift in the distribution of the associated t-statistics), or if one uses the empirical critical values, the evidence based on US data is strongly supportive of the Fisher relation, consistently with many theoretical m...

Preamble-based channel estimation in MIMO-OFDM/OQAM systems

Abstract: Filter bank-based multicarrier modulation (FBMC) using offset quadrature amplitude modulation (OQAM), known as OFDM/OQAM (or FBMC/OQAM), provides an attractive alternative to the conventional cyclic prefix-based orthogonal frequency division multiplexing (CP-OFDM), especially in terms of increased robustness to frequency offset and Doppler spread, and high bandwidth efficiency. It suffers, however, from an inherent (intrinsic) imaginary inter-carrier/inter-symbol interference that complicates signal processing tasks such as channel estimation (CE). Recently, the so-called interference approximation method (IAM) was proposed for preamble-based CE in single-input single-output (SISO) systems. It relies on the knowledge of the pilot's neighborhood to approximate this interference and constructively exploit it in simplifying CE and improving its performance. A number of IAM preambles have been proposed, with varying CE performance. This paper is concerned with the application of the IAM idea in multi-input multi-output (MIMO) systems. The most prominent IAM variants are considered and their MIMO extensions with their relative advantages and practical issues are investigated. The IAM preambles are compared, with each other and with CP-OFDM, via simulations in both mildly and highly frequency-selective channels.

An efficient ant colony optimization system for the manufacturing cells formation problem

Abstract: An ant colony optimization (ACO) scheme for the manufacturing cells design problem is proposed, which uses a tight eigenvalue-based bound to guide and accelerate the search. This feature is combined with a good initialization procedure and with ideas from successful ACO implementations in other areas, to achieve efficiency and reliability with the minimum structure and set of parameters. The resulting algorithm produces most promising results for medium to large size problems, with negligible computational effort.

Trajectory Compression under Network Constraints

Abstract: The wide usage of location aware devices, such as GPS-enabled cellphones or PDAs, generates vast volumes of spatiotemporal streams modeling objects movements, raising management challenges, such as efficient storage and querying. Therefore, compression techniques are inevitable also in the field of moving object databases. Moreover, due to erroneous measurements from GPS devices, the problem of matching the location recordings with the underlying traffic network has recently gained the attention of the research community. So far, the proposed compression techniques are not designed for network constrained moving objects, while map matching algorithms do not consider compression issues. In this paper, we propose solutions tackling the combined, map matched trajectory compression problem, the efficiency of which is demonstrated through an experimental evaluation using a real trajectory dataset.