A Multiagent Platform for Ubiquitous Service Provision

The Virtual Home Environment is very important in contemporary mobile telecommunications infrastructure as it caters for the ubiquitous provision of services irrespective of network, location and user device. The universality of systems like Universal Mobile Telecommunications System and wi-fi increases the need for the rapid introduction of efficient VHE schemes. In this paper, we study the adoption of Mobile Agents for handling the VHE functionality. Mobile agents are nicely harmonized with the broader idea of VHE as they allow the autonomous execution of tasks by components that roam from node to node and network to network. We present the detailed modeling of a VHE provisioning architecture and investigate its suitability for different use cases and technical options (e.g., end user devices). The adoption of mobile agents for the ubiquitous provision of telecommunication services is quite promising in terms of efficiency. Through a series of experiments we quantify the performance benefits stemming from the adoption of mobile agents in contrast to conventional service provisioning schemes.     

Flood forecasting in transboundary catchments using the Open Modeling Interface

Using satellite data for flood forecasting in catchments located in mid-latitudes is challenging to engineers and model developers, in no small part due to the plethora of data sets that need to be retrieved, combined, calibrated and used for simulation in real time. The differences between the various satellite rainfall data products and the continuous improvement in their quantity and quality render the development of a single software tool, able to read and process all the different data sets, particularly difficult. Even if such an endeavour was undertaken, the degree of flexibility and extensibility that such a tool would require to accommodate future versions of data sets, available in different file formats as well as different temporal and spatial resolution should not be underestimated. This paper describes the development of a flood forecasting system that addresses this issue through a modular architecture based on the use of the Open Modeling Interface (OpenMI) standard, which facilitates the interaction between a number of separate software components. It is suggested that this approach greatly simplifies programming and debugging and eliminates the need to create spatial and temporal transformation functions without significantly compromising the overall execution speed. The approach and system were tested for forecasting flood events within a particularly challenging transboundary catchment, the Evros catchment, extending between Greece, Bulgaria and Turkey. The system uses two sets of data sources, as an example (NASA’s TRMM 3B42 and 3B42RT satellite data sets) to forecast flooding in the Evros catchment. Results indicate that OpenMI greatly facilitates the complex interaction of various software components and considerably increases the flexibility and extensibility of the overall system and hence its operational value and sustainability.     

Low bit depth representation motion estimation algorithms: a comparative study

A comparative study of low complexity motion estimation algorithms is presented. The algorithms included in the study are the 1-bit transform, the 2-bit transform, the constrained 1-bit transform and the multiplication free 1-bit transform which are using different motion estimation strategies compared to standard exhaustive search algorithm-mean absolute difference or similar combinations. These techniques provide better performance in terms of computational load compared to traditional algorithms. Although the accuracy of motion compensation is only slightly lower comparing to the other techniques, results in terms of objective quality (peak signal-to-noise ratio) and entropy are comparable. This fact, nominates them as suitable candidates for inclusion in embedded devices applications where lower complexity translates to lower power consumption and consequently improved device autonomy.     

The role of a “make” or internal human resource management system in Spanish manufacturing companies: Empirical evidence

The combined study of the literature about human resource management and the resource‐based view of the firm and organizational learning provides an analysis framework useful for understanding how strategic human resource management systems contribute to the creation and development of a sustained competitive advantage for the firm. This article has two major aims. First, it provides a conceptual framework linking simultaneously three theoretical blocks: (a) human resource management, (b) organizational learning and knowledge management, and (c) sustained competitive advantage. Second, the article builds a causal model and tests it with a sample of Spanish firms from the manufacturing industry using structural equation modeling (SEM). After the performance of a cluster analysis, a group of 72 learning firms is identified and used to test the model. Finally, major conclusions and implications for management are drawn and further avenues for research are suggested. © 2008 Wiley Periodicals, Inc.     

Investigation of the Equivalence of National Dew-Point Temperature Realizations in the ?50?°C to +?20?°C Range

In the field of humidity quantities, the first CIPM key comparison, CCT-K6 is at its end. The corresponding European regional key comparison, EUROMET.T-K6, was completed in early 2008, about 4?years after the starting initial measurements in the project. In total, 24 NMIs from different countries took part in the comparison. This number includes 22 EURAMET countries, and Russia and South Africa. The comparison covered the dew-point temperature range from ?50?°C to +20?°C. It was carried out in three parallel loops, each with two chilled mirror hygrometers as transfer standards in each loop. The comparison scheme was designed to ensure high quality results with evenly spread workload for the participants. It is shown that the standard uncertainty due to the long-term instability was smaller than 0.008?°C in all loops. The standard uncertainties due to links between the loops were found to be smaller than 0.025?°C at ?50?°C and 0.010?°C elsewhere. Conclusions on the equivalence of the dew-point temperature standards are drawn on the basis of calculated bilateral degrees of equivalence and deviations from the EURAMET comparison reference values (ERV). Taking into account 16 different primary dew-point realizations and 8 secondary realizations, the results demonstrate the equivalence of a large number of laboratories at an uncertainty level that is better than achieved in other multilateral comparisons so far in the humidity field.     

Nonlinearities in regional economic growth and convergence: the role of entrepreneurship in the European union regions

Nonlinearities have been identified in recent literature on growth and convergence at the cross-country level and they have been associated with a number of variables of interest such as initial conditions and human capital accumulation. This research takes the analysis at the regional level within a European context while focusing on entrepreneurship and, using semiparametric regression techniques, provides evidence for nonlinear effects of the base-year income per capita on growth suggesting that convergence may be a phenomenon restricted to particular income bands. Entrepreneurship has a positive effect on regional growth and no serious departures from linearity are detected, while evidence for an almost L-shaped relationship between income per capita levels and self-employment rates was produced. A quality-adjusted proxy for human capital stock was found to be a positive and significant determinant of economic growth across European regions but, again, no departures for linearity were detected for this effect.     

Applied data science in patient-centric healthcare: Adaptive analytic systems for empowering physicians and patients

We define the emerging research field of applied data science as the knowledge discovery process in which analytic systems are designed and evaluated to improve the daily practices of domain experts. We investigate adaptive analytic systems as a novel research perspective of the three intertwining aspects within the knowledge discovery process in healthcare: domain and data understanding for physician- and patient-centric healthcare, data preprocessing and modelling using natural language processing and (big) data analytic techniques, and model evaluation and knowledge deployment through information infrastructures. We align these knowledge discovery aspects with the design science research steps of problem investigation, treatment design, and treatment validation, respectively. We note that the adaptive component in healthcare system prototypes may translate to data-driven personalisation aspects including personalised medicine. We explore how applied data science for patient-centric healthcare can thus empower physicians and patients to more effectively and efficiently improve healthcare. We propose meta-algorithmic modelling as a solution-oriented design science research framework in alignment with the knowledge discovery process to address the three key dilemmas in the emerging “post-algorithmic era” of data science: depth versus breadth, selection versus configuration, and accuracy versus transparency.     

Ethylene epoxidation on Ag catalysts supported on non-porous, microporous and mesoporous silicates

The ethylene epoxidation activity of Ag catalysts supported on non-porous SiO₂, microporous silicalite zeolite and mesoporous MCM-41 and HMS silicates was investigated in the present study in comparison to conventional low surface area -Al₂O₃ based catalysts. The MCM-41 and HMS based catalysts exhibited similar ethylene conversion activity and ethylene oxide (EO) selectivity with the SiO₂ and -Al₂O₃ based catalysts at relatively lower temperatures (up to 230 °C), whereas their activity and selectivity decreased significantly at higher temperatures (≥300 °C). The silicalite based catalyst was highly active for a wide temperature range, similar to the SiO₂ and -Al₂O₃ based catalysts, but it was the less selective amongst all catalysts tested. High loadings of Ag particles (up to ca. 40 wt.%) with medium crystallites size (20–55 nm) could be achieved on the mesoporous materials resulting in very active epoxidation catalysts. The HMS-type silicate with the 3D network of wormhole-like framework mesopores (with average diameter of 3.5 nm), in combination with a high-textural (interparticle) porosity, appeared to be the most promising mesoporous support.     

Data hiding based on image texture classification

In this paper, a new pattern-based fragile, semi-blind, spatial domain data hiding scheme is proposed. The Local Binary Pattern texture classification approach is used, in order to transparently and securely embed secret data into an image. Pixel values are modified in such a way that the texture satisfies the message requirements. The method is thoroughly studied and compared to other techniques in spatial domain in terms of capacity and image quality. The scheme performs well in images with smooth areas and can be used for authentication, tamper proofing, and secret communications.