Charting of geoelectric potential signal dynamics via geometrical techniques and its possible relation to significant earthquakes in Western Greece

An exploratory data analysis (EDA) framework was developed in order to investigate the presence of possible correlations in the long-term geoelectric potential (LTGP) signal, prior to significant seismic events in Western Greece. Experimental data, which had been collected continuously within a 6-year period (1998–2003) at the earthquake signal-acquisition center of the University of Patras Seismological Laboratory (UPSL), were studied. The multidimensional scaling (MDS) technique was used to detect putative clustering tendencies in the ensemble of time-series (TS) segments that could indicate the existence of a possible correlation between the geoelectric signal structure and the impending seismic activity. The end result is a 2-dimensional point diagram with the geometry reflecting important signal characteristics, directly related with the underlying seismic events. In addition, the “appending technique”, a well-suited data analysis methodology was incorporated as a means of relating any other TS segment directly with the pre-computed, via the MDS, point diagram. Using the proposed EDA framework, we examined the presence of similar temporal patterns in the recorded geoelectric TS field, 10 days before the occurrence of the major earthquakes. The presented experimental results indicated clearly the validity of the introduced approach and, further, motivated the use of such advanced visualization schemes for charting precursor trends of significance seismicity.     

Drought Severity Assessment Based on Bivariate Probability Analysis

Conventionally drought severity is assessed based on drought indices. Recently the Reconnaissance Drought Index (RDI) was proposed to assess drought severity based on the precipitation to potential evapotranspiration ratio (P/PET). In this paper RDI is studied as a bivariate index under a set of assumptions and simplifications. The paper presents a simple computational procedure for estimating the P/PET ratio for selected reference periods varying from 3 to 12 months, for any return period of drought. Alternatively, based on this procedure, the severity of any drought episode is rationally assessed. A bivariate probability analysis is employed based on the assumption that P and PET values are normally distributed and often negatively correlated. Examples for the application of the proposed procedure are presented using data from several meteorological stations in Greece. It is shown that the assumption of normality of both P and PET holds for long periods at all examined stations.     

Mytilene E-guide: a multiplatform mobile application tourist guide exemplar

This paper introduces an approach of enhancing the tourism experience by incorporating a tool that adopts a “web-to-mobile” model into tourism websites that allows for the adaptation of personalized tourism web content to be transferred to a mobile application hosted at users’ mobile device. These applications upon installation to mobile devices allow for browsing of adapted multimedia content with no requirement for constant network connection. Furthermore so we convey the development experiences of a multiplatform mobile tourist guide aimed at producing a personalized mobile guide application used in both an online and offline modes offering services to tourists such as a personal profiling-based recommendation system, a commenting system and location-based services. This paper focuses on the design, implementation and usability case study of a Multi-Platform Tourist Guide system for the Municipal Council of Mytilene, Greece.     

On the discovery of subsumption relations for the alignment of ontologies

For the effective alignment of ontologies, the subsumption mappings between the elements of the source and target ontologies play a crucial role, as much as equivalence mappings do. This paper presents the “Classification-Based Learning of Subsumption Relations” (CSR) method for the alignment of ontologies. Given a pair of two ontologies, the objective of CSR is to learn patterns of features that provide evidence for the subsumption relation among concepts, and thus, decide whether a pair of concepts from these ontologies is related via a subsumption relation. This is achieved by means of a classification task, using state of the art supervised machine learning methods. The paper describes thoroughly the method, provides experimental results over an extended version of benchmarking series of both artificially created and real world cases, and discusses the potential of the method.     

Intelligent Network Provisioning for Dynamically Downloadable Applications in Beyond 3G Mobile Networks

Mobile communications beyond 3G will integrate different (but complementary) access technologies into a common platform to deliver value-added services and multimedia content in an optimum way. However, the numerous possible configurations of mobile networks complicated the dynamic deployment of mobile applications. Therefore, research is intensely seeking a service provisioning framework that is technology-independent, supports multiple wireless network technologies, and can interwork high-level service management tasks to network management operations. This paper presents an open value chain paradigm, a model for downloadable applications and a mediating platform for service provisioning in beyond 3G mobile settings. Furthermore, we introduce mechanisms that support a coupled interaction between service deployment and network configuration operations, focusing on the dynamic provisioning of QoS state to data path devices according to the requirements of dynamically downloadable mobile value-added services (VAS).

The history and development of the helium ion microscope

The helium ion microscope has recently emerged as a commercially available instrument. However, its roots go back more than 60 years to the development of the field ion microscope in Berlin, first reported in 1951. Over the intervening years, numerous researchers have pursued the development of a gas field ionization source with the goal of producing a suitable source for an ion microscope. This proved to be an elusive goal until early in this century when a number of discoveries led to a successful source, and shortly thereafter, an instrument fully able to exploit its advantages. Many individuals and many technical advances have come together to make this new class of microscope. The long history of this quest is reviewed along with the recent advances that led to the achievement of this milestone. A brief summary of the current status of the technology and its applications are given.     

Chemical investigation and antimicrobial properties of mastic water and its major constituents

Mastic water is a commercial flavouring obtained during the steam distillation of mastic resin (the resin of Pistacia lentiscus var. chia) for the production of mastic oil. The mastic water extracts were analysed by GC−MS. The major compounds identified were verbenone, α-terpineol, linalool and trans-pinocarveol. Overall the composition was found to be very different from that of mastic oil. Additional GC−MS revealed the enantiomeric ratio of the chiral constituents of mastic water. The antimicrobial activity of mastic water extract, as well as that of its major constituents, was examined against Escherichia coli, Staphylococcus aureus and Candida spp. including ATCC wild clinical and food-borne strains. Linalool and α-terpineol were found to be the most potent antimicrobial constituents. Finally the stability of mastic water at different temperatures was studied, showing no change in the GC−MS profile of the organic extract for a period of 4 months at storage temperatures up to 4 °C.     

Segmentation of color images using multiscale clustering and graph theoretic region synthesis

A multiresolution color image segmentation approach is presented that incorporates the main principles of region-based segmentation and cluster-analysis approaches. The contribution of This work may be divided into two parts. In the first part, a multiscale dissimilarity measure is proposed that makes use of a feature transformation operation to measure the interregion relations with respect to their proximity to the main clusters of the image. As a part of this process, an original approach is also presented to generate a multiscale representation of the image information using nonparametric clustering. In the second part, a graph theoretic algorithm is proposed to synthesize regions and produce the final segmentation results. The latter algorithm emerged from a brief analysis of fuzzy similarity relations in the context of clustering algorithms. This analysis indicates that the segmentation methods in general may be formulated sufficiently and concisely by means of similarity relations theory. The proposed scheme produces satisfying results and its efficiency is indicated by comparing it with: 1) the single scale version of dissimilarity measure and 2) several earlier graph theoretic merging approaches proposed in the literature. Finally, the multiscale processing and region-synthesis properties validate our method for applications, such as object recognition, image retrieval, and emulation of human visual perception.     

Framestore system for map displays

The map displays project was undertaken to investigate techniques for the storage and display of geographical maps and related information and to develop the hardware and software required for a complete working system. Initially most of the project was concerned with the design of graphics hardware to be interfaced to a DEC LSI-11/03 micro-computer which was the main supply of computing power for the project. The development of one of the pieces of specialized hardware, the framestore display, is described.