Financial Regulation and Transparency of Information: first steps on new land

This article examines the relationship between the level of regulation and transparency of financial institutions from 37 countries and the impacts of the subprime crisis on the stock market, through a regulation and transparency index. Furthermore, with the objective of detecting reasons for the success of some emerging economies in avoiding the crisis, empirical evidence for the presence of market discipline in the Brazilian banking industry is shown. The results are that a higher degree of regulation and transparency is related to higher returns and lower volatility in the stock market during the subprime crisis. Moreover, one of the main reasons for the apparent success of the Brazilian case in facing the crisis is the combination of a strong regulation of the financial system and the presence of market discipline.

Computer Aided Aroma Design. I. Molecular knowledge framework

Computer Aided Aroma Design (CAAD) is likely to become a hot issue as the REACH EC document targets many aroma compounds to require substitution. The two crucial steps in CAMD are the generation of candidate molecules and the estimation of properties, which can be difficult when complex molecular structures like odours are sought and when their odour quality are definitely subjective whereas their odour intensity are partly subjective as stated in Rossitier’s review (1996). In part I, provided that classification rules like those presented in part II exist to assess the odour quality, the CAAD methodology presented proceeds with a multilevel approach matched by a versatile and novel molecular framework. It can distinguish the infinitesimal chemical structure differences, like in isomers, that are responsible for different odour quality and intensity. Besides, its chemical graph concepts are well suited for genetic algorithm sampling techniques used for an efficient screening of large molecules such as aroma. Finally, an input/output XML format based on the aggregation of CML and ThermoML enables to store the molecular classes but also any subjective or objective property values computed during the CAAD process

An Overview of Computational Approaches for Interpretation Analysis

It is said that beauty is in the eye of the beholder. But how exactly can we characterize such discrepancies in interpretation? For example, are there any specific features of an image that makes person A regard an image as beautiful while person B finds the same image displeasing? Such questions ultimately aim at explaining our individual ways of interpretation, an intention that has been of fundamental importance to the social sciences from the beginning. More recently, advances in computer science brought up two related questions: First, can computational tools be adopted for analyzing ways of interpretation? Second, what if the "beholder" is a computer model, i.e., how can we explain a computer model's point of view? Numerous efforts have been made regarding both of these points, while many existing approaches focus on particular aspects and are still rather separate. With this paper, in order to connect these approaches we introduce a theoretical framework for analyzing interpretation, which is applicable to interpretation of both human beings and computer models. We give an overview of relevant computational approaches from various fields, and discuss the most common and promising application areas. The focus of this paper lies on interpretation of text and image data, while many of the presented approaches are applicable to other types of data as well.Comment: Preprint submitted to Digital Signal Processin

Applying the structural equation model rule-based fuzzy system with genetic algorithm for trading in currency market

The present study uses the structural equation model (SEM) to analyze the correlations between various economic indices pertaining to latent variables, such as the New Taiwan Dollar (NTD) value, the United States Dollar (USD) value, and USD index. In addition, a risk factor of volatility of currency returns is considered to develop a risk-controllable fuzzy inference system. The rational and linguistic knowledge-based fuzzy rules are established based on the SEM model and then optimized using the genetic algorithm. The empirical results reveal that the fuzzy logic trading system using the SEM indeed outperforms the buy-and-hold strategy. Moreover, when considering the risk factor of currency volatility, the performance appears significantly better. Remarkably, the trading strategy is apparently affected when the USD value or the volatility of currency returns shifts into either a higher or lower state.Knowledge-based Systems, Fuzzy Sets, Structural Equation Model (SEM), Genetic Algorithm (GA), Currency Volatility

Evolutionary Computation and QSAR Research

[Abstract] The successful high throughput screening of molecule libraries for a specific biological property is one of the main improvements in drug discovery. The virtual molecular filtering and screening relies greatly on quantitative structure-activity relationship (QSAR) analysis, a mathematical model that correlates the activity of a molecule with molecular descriptors. QSAR models have the potential to reduce the costly failure of drug candidates in advanced (clinical) stages by filtering combinatorial libraries, eliminating candidates with a predicted toxic effect and poor pharmacokinetic profiles, and reducing the number of experiments. To obtain a predictive and reliable QSAR model, scientists use methods from various fields such as molecular modeling, pattern recognition, machine learning or artificial intelligence. QSAR modeling relies on three main steps: molecular structure codification into molecular descriptors, selection of relevant variables in the context of the analyzed activity, and search of the optimal mathematical model that correlates the molecular descriptors with a specific activity. Since a variety of techniques from statistics and artificial intelligence can aid variable selection and model building steps, this review focuses on the evolutionary computation methods supporting these tasks. Thus, this review explains the basic of the genetic algorithms and genetic programming as evolutionary computation approaches, the selection methods for high-dimensional data in QSAR, the methods to build QSAR models, the current evolutionary feature selection methods and applications in QSAR and the future trend on the joint or multi-task feature selection methods.Instituto de Salud Carlos III, PIO52048Instituto de Salud Carlos III, RD07/0067/0005Ministerio de Industria, Comercio y Turismo; TSI-020110-2009-53)Galicia. Consellería de Economía e Industria; 10SIN105004P

Construct Validity of Dimensions of Adaptive Behavior: A Multitrait-Multimethod Evaluation.

The construct validity of four dimensions of adaptive and maladaptive behavior was investigated using the multitrait-multimethod matrix procedure of Campbell and Fiske (1959). Measures off our traits cognitive competence, social competence, social maladaption, and personal maladaption were obtained on a sample of 157 persons with moderate, severe, or profound mental retardation using each of three methods of measurement-standardized assessment instrument, day shift staff ratings, and evening shift staff ratings. Applying the Campbell and Fiske rules of thumb and recently proposed structural equation modeling techniques to the data demonstrated strong convergent validity, clear discriminant validity, and only moderate levels of method variance in the observed measures. implications of the results for the assessment of adaptive behavior and its dimensional structure were discussed

Pan-sharpening Using Spatial-frequency Method

Over the years, researchers have formulated various techniques for pan sharpening that attempt to minimize the spectral distortion, i.e., retain the maximum spectral fidelity of the MS images. On the other hand, if the use of the PAN-sharpened image is just to produce maps for better visual interpretation, then the spectral distortion is not of much concern, as the goal is to produce images with high contrast. To solve the color distortion problem, methods based on spatial frequency domain have been introduced and have demonstrated superior performance in terms of producing high spectral fidelity pan-sharpened images over spatial-scale methods