Comments on "On the relationship between fractal dimension and the performance of multi-resonant dipole antennas using Koch curves"

Comentaris referits a l'article següent: K. J. Vinoy, J. K. Abraham, and V. K. Varadan, “On the relationshipbetween fractal dimension and the performance of multi-resonant dipoleantennas using Koch curves,” IEEE Transactions on Antennas and Propagation, 2003, vol. 51, p. 2296–2303.

Blind channel estimation and data detection using hidden Markov models theory

In this correspondence, we propose applying the hiddenMarkov models (HMM) theory to the problem of blind channel estimationand data detection. The Baum–Welch (BW) algorithm, which is able toestimate all the parameters of the model, is enriched by introducingsome linear constraints emerging from a linear FIR hypothesis on thechannel. Additionally, a version of the algorithm that is suitable for timevaryingchannels is also presented. Performance is analyzed in a GSMenvironment using standard test channels and is found to be close to thatobtained with a nonblind receiver.

Average performance analysis of circular and hyperbolic geolocation

A comparative performance analysis of four geolocation methods in terms of their theoretical root mean square positioning errors is provided. Comparison is established in two different ways: strict and average. In the strict type, methods are examined for a particular geometric configuration of base stations(BSs) with respect to mobile position, which determines a givennoise profile affecting the respective time-of-arrival (TOA) or timedifference-of-arrival (TDOA) estimates. In the average type, methodsare evaluated in terms of the expected covariance matrix ofthe position error over an ensemble of random geometries, so thatcomparison is geometry independent. Exact semianalytical equationsand associated lower bounds (depending solely on the noiseprofile) are obtained for the average covariance matrix of the positionerror in terms of the so-called information matrix specific toeach geolocation method. Statistical channel models inferred fromfield trials are used to define realistic prior probabilities for therandom geometries. A final evaluation provides extensive resultsrelating the expected position error to channel model parametersand the number of base stations.

Monitoring bank performance in the presence of risk

This paper proposes a managerial control tool that integrates risk in efficiency scores. Building on existing efficiency specifications, our proposal reflects the real banking technology and accurately models the relationship between desirable and undesirable outputs. Specifically, the undesirable output is defined as non-performing loans to capture credit risk, and is linked only to the relevant dimension of the output set. We empirically illustrate how our efficiency measure functions for managerial control purposes. The application considers a unique dataset of Costa Rican banks during 1998-2012. Efficiency scores? implications are mostly discussed at bank-level, and their interpretations are enhanced by using accounting ratios. We also show the usefulness of our tool for corporate governance by examining performance changes around executive turnover. Results confirm that appointing CEOs from outside the bank significantly improves performance, thus suggesting the potential benefits of new organisational practices.

Forecasting tourism demand to Catalonia: neural networks vs. time series models

The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more accurate forecasts of tourismdemand at the destination level due to the constant growth of world tourism, has lead us to evaluate the forecasting performance of neural modelling relative to that of time seriesmethods at a regional level. Seasonality and volatility are important features of tourism data, which makes it a particularly favourable context in which to compare the forecasting performance of linear models to that of nonlinear alternative approaches. Pre-processed official statistical data of overnight stays and tourist arrivals fromall the different countries of origin to Catalonia from 2001 to 2009 is used in the study. When comparing the forecasting accuracy of the different techniques for different time horizons, autoregressive integrated moving average models outperform self-exciting threshold autoregressions and artificial neural network models, especially for shorter horizons. These results suggest that the there is a trade-off between the degree of pre-processing and the accuracy of the forecasts obtained with neural networks, which are more suitable in the presence of nonlinearity in the data. In spite of the significant differences between countries, which can be explained by different patterns of consumer behaviour,we also find that forecasts of tourist arrivals aremore accurate than forecasts of overnight stays.

Forecasting coal resources and reserves in heterogeneous coal zones using 3D facies models (As Pontes Basin, NW Spain)

Forecasting coal resources and reserves is critical for coal mine development. Thickness maps are commonly used for assessing coal resources and reserves; however they are limited for capturing coal splitting effects in thick and heterogeneous coal zones. As an alternative, three-dimensional geostatistical methods are used to populate facies distributionwithin a densely drilled heterogeneous coal zone in the As Pontes Basin (NWSpain). Coal distribution in this zone is mainly characterized by coal-dominated areas in the central parts of the basin interfingering with terrigenous-dominated alluvial fan zones at the margins. The three-dimensional models obtained are applied to forecast coal resources and reserves. Predictions using subsets of the entire dataset are also generated to understand the performance of methods under limited data constraints. Three-dimensional facies interpolation methods tend to overestimate coal resources and reserves due to interpolation smoothing. Facies simulation methods yield similar resource predictions than conventional thickness map approximations. Reserves predicted by facies simulation methods are mainly influenced by: a) the specific coal proportion threshold used to determine if a block can be recovered or not, and b) the capability of the modelling strategy to reproduce areal trends in coal proportions and splitting between coal-dominated and terrigenousdominated areas of the basin. Reserves predictions differ between the simulation methods, even with dense conditioning datasets. Simulation methods can be ranked according to the correlation of their outputs with predictions from the directly interpolated coal proportion maps: a) with low-density datasets sequential indicator simulation with trends yields the best correlation, b) with high-density datasets sequential indicator simulation with post-processing yields the best correlation, because the areal trends are provided implicitly by the dense conditioning data.

Mixed and Hybrid Models of Public Service Delivery

This symposium presents research from different contexts to improve our collective understanding of a variety of aspects of mixed forms of service delivery, be they mixed contracting at the level of the market (which is more common in the U.S.), or mixed management and ownership at the level of the firm (which is more common in Europe). The articles included in this special symposium examine the factors that give rise to mixed forms of service delivery (e.g., economic and fiscal stress, regulatory flexibility, geography, management) and how these factors impact their design and operation. Articles also explore the performance of mixed forms of service delivery relative to more conventional arrangements like contracted or direct service delivery. The articles contribute to a better theoretical and conceptual understanding of mixed/hybrid forms of services delivery.

Evidence on the role of ownership structure on firms' innovative performance

Based on the Knowledge Production Function framework given by Griliches -1979-, we slightly modify it so that the innovative output depends upon a set of factors related to the firm internal characteristics and are influenced by the environment. Specifically, regarding the firm internal determinants the effect of the concentration of the ownership, the composition of the boards of directors and the effect of the nature of the ownership (foreign and public) are analyzed. Additionally, in order to capture the determinants of the environment in which the firm operates other variables concerning the internationalization of market, the agglomeration economies and the regional knowledge externalities are also considered. In order to assess the impact of these determinants on the number of patents and models of use awarded by the firm, the discreteness of the latter variable has to be taken into account. We apply Poisson and Negative Binomial models for a more comprehensive evaluation of the hypothesis in a panel of Spanish manufacturing firms. The results show patenting activity is positively favoured by being located in an environment with a high innovative activity, due to the existence of knowledge spillovers and agglomeration economies.

Earnings quality and performance in the banking industry: a profit frontier approach

The analysis of efficiency and productivity in banking has received a great deal of attention for almost three decades now. However, most of the literature to date has not explicitly accounted for risk when measuring efficiency. We propose an analysis of profit efficiency taking into account how the inclusion of a variety of bank risk measures might bias efficiency scores. Our measures of risk are partly inspired by the literature on earnings management and earnings quality, keeping in mind that loan loss provisions, as a generally accepted proxy for risk, can be adjusted to manage earnings and regulatory capital. We also consider some variants of traditional models of profit efficiency where different regimes are stipulated so that financial institutions can be evaluated in different dimensions—i.e., prices, quantities, or prices and quantities simultaneously. We perform this analysis on the Spanish banking industry, whose institutions have been deeply affected by the current international financial crisis, and where re-regulation is taking place. Our results can be explored in multiple dimensions but, in general, they indicate that the impact of earnings management on profit efficiency is of less magnitude than what might a priori be expected, and that on the whole, savings banks have performed less well than commercial banks. However, savings banks are adapting to the new regulatory scenario and rapidly catching up with commercial banks, especially in some dimensions of performance.

Comparative performance of the stable isotope signatures of carbon, nitrogen and oxygen in assessing early vigour and grain yield in durum wheat

The present paper studied the performance of the stable isotope signatures of carbon (δ13C), nitrogen (δ15N) and oxygen (δ18O) in plants when used to assess early vigour and grain yield (GY) in durum wheat growing under mild and moderate Mediterranean stress conditions. A collection of 114 recombinant inbred lines was grown under rainfed (RF) and supplementary irrigation (IR) conditions. Broad sense heritabilities (H2) for GY and harvest index (HI) were higher under RF conditions than under IR. Broad sense heritabilities for δ13C were always above 0·60, regardless of the plant part studied, with similar values for IR and RF trials. Some of the largest genetic correlations with GY were those shown by the δ13C content of the flag leaf blade and mature grains. Under both water treatments, mature grains showed the highest negative correlations between δ13C and GY across genotypes. Flag leaf δ13C was negatively correlated with GY only under RF conditions. The δ13C in seedlings was negatively correlated, under IR conditions only, with GY but also with early vigour. The sources of variation in early vigour were studied by stepwise analysis using the stable isotope signatures measured in seedlings. The δ13C was able to explain almost 0·20 of this variation under RF, but up to 0·30 under IR. In addition, nitrogen concentration in seedlings accounted for another 0·05 of variation, increasing the amount explained to 0·35. The sources of variation in GY were also studied through stable isotope signatures and biomass of different plant parts: δ13C was always the first parameter to appear in the models for both water conditions, explaining c. 0·20 of the variation. The second parameter (δ15N or N concentration of grain, or biomass at maturity) depended on the water conditions and the plant tissue being analysed. Oxygen isotope composition (δ18O) was only able to explain a small amount of the variation in GY. In this regard, despite the known and previously described value of δ13C as a tool in breeding, δ15N is confirmed as an additional tool in the present study. Oxygen isotope composition does not seem to offer any potential, at least under the conditions of the present study.

Bowing the violin : a case study for auditory-motor pattern modelling in the context of music performance

This project addresses methodological and technological challenges in the development of multi-modal data acquisition and analysis methods for the representation of instrumental playing technique in music performance through auditory-motor patterning models. The case study is violin playing: a multi-modal database of violin performances has been constructed by recording different musicians while playing short exercises on different violins. The exercise set and recording protocol have been designed to sample the space defined by dynamics (from piano to forte) and tone (from sul tasto to sul ponticello), for each bow stroke type being played on each of the four strings (three different pitches per string) at two different tempi. The data, containing audio, video, and motion capture streams, has been processed and segmented to facilitate upcoming analyses. From the acquired motion data, the positions of the instrument string ends and the bow hair ribbon ends are tracked and processed to obtain a number of bowing descriptors suited for a detailed description and analysis of the bow motion patterns taking place during performance. Likewise, a number of sound perceptual attributes are computed from the audio streams. Besides the methodology and the implementation of a number of data acquisition tools, this project introduces preliminary results from analyzing bowing technique on a multi-modal violin performance database that is unique in its class. A further contribution of this project is the data itself, which will be made available to the scientific community through the repovizz platform.