Classification of Chenopodium Genus Populations and Species Based on Continuous and Categorical Variables

2000 Mathematics Subject Classification: 62P10, 62H30The estimation of statistical distance between populations arises in many multivariate analysis techniques. Whereas distance measures for continuous data are well developed, those for mixed discrete and continuous data are less so because of the lack of a standard model for such data. Such mixture of variables arise frequently in the field of medicine, biometry, psychology, econometrics and only comparatively few models have been developed for evaluating distance between populations. The subject of our study were data in the field of botany. The aim of the presented investigation was to apply methods for analysis of dissimilarity between 44 populations of 13 species of Ghenopodium genus,presented by 15 variables - 10 continuous and 5 categorical. The previously developed by another authors distance measures between populations presented by mixed attributes turned out not appropriate for the available data of Chenopodium genus. F or that reason a specific distance measures were applied. The matrices with distances between populations and species were used as input for Hierarchical Cluster Analysis to explore the taxonomic structure of the Chenopodium genus

Perceived Diversity of Complex Environmental Systems: Multidimensional Measurement and Synthetic Indicators

The general attitude towards the sustainable management of environmental resources is evolving towards the implementation of ‘participatory’ (as opposed to the classical ‘command and control’) and, especially at local scale, ‘bottom up’ (as opposed to the classical ‘top down’) approaches. This progress pushes a major interest in the development and application of methodologies able to ‘discover’ and ‘measure’ how environmental systems tend to be perceived by the different Stakeholders. Due to the ‘nature’ of the investigated systems, often too ‘complex’ to be treated through a classical deterministic approach, as typical for ‘hard’ physical/mathematical sciences, any ‘measurement’ has necessarily to be multidimensional. In the present report an approach, more typical of ‘soft’ social sciences, is presented and applied to the analysis of the sustainable management of water resources in seven Southern and Eastern Mediterranean Watersheds. The methodology is based on the development and analysis (explorative factor analysis, multidimensional scaling) of a questionnaire and is aimed at the ‘discovery’ and ‘measurement’ of a latent multidimensional ‘underlying structure’ (‘conceptual map’). It is the opinion of the authors, that the identification of a set of ‘consistent’, ‘independent’, ‘bottom up’ and ‘shared’ synthetic indicators (aggregated indices) could be strongly facilitated by the interpretation of the dimensions of the emerging ‘underlying structure’.Participative Approach, Cognitive Map, Factor Analysis, Indicators of Sustainability, Sustainable Water, Management

A new synthesis procedure for TOPSIS based on AHP

Vega et al. [1] analyzed the influence of the attributes’ dependence when ranking a set of alternatives in a multicriteria decision making problem with TOPSIS. They also proposed the use of the Mahalanobis distance to incorporate the correlations among the attributes in TOPSIS. Even in those situations for which dependence among attributes is very slight, the results obtained for the Mahalanobis distance are significantly different from those obtained with the Euclidean distance, traditionally used in TOPSIS, and also from results obtained using any other distance of the Minkowsky family. This raises serious doubts regarding the selection of the distance that should be employed in each case. To deal with the problem of the attributes’ dependence and the question of the selection of the most appropriate distance measure, this paper proposes to use a new method for synthesizing the distances to the ideal and the anti-ideal in TOPSIS. The new procedure is based on the Analytic Hierarchy Process and is able to capture the relative importance of both distances in the context given by the measure that is considered; it also provides rankings, which are closer to the distances employed in TOPSIS, regardless of the dependence among the attributes. The new technique has been applied to the illustrative example employed in Vega et al. [1]

An Evolutionary Learning Approach for Adaptive Negotiation Agents

Developing effective and efficient negotiation mechanisms for real-world applications such as e-Business is challenging since negotiations in such a context are characterised by combinatorially complex negotiation spaces, tough deadlines, very limited information about the opponents, and volatile negotiator preferences. Accordingly, practical negotiation systems should be empowered by effective learning mechanisms to acquire dynamic domain knowledge from the possibly changing negotiation contexts. This paper illustrates our adaptive negotiation agents which are underpinned by robust evolutionary learning mechanisms to deal with complex and dynamic negotiation contexts. Our experimental results show that GA-based adaptive negotiation agents outperform a theoretically optimal negotiation mechanism which guarantees Pareto optimal. Our research work opens the door to the development of practical negotiation systems for real-world applications

Approximation of the Value of an Asset Inscribed on the List of Intangible Cultural Heritage of UNESCO: Estimation of a Hedonic Price Model for the Fiesta of the Patios in Cordoba

The city of Cordoba (Spain) stands out due to the fact that it has different inscriptions both in the List of World Heritage Sites and the List of Intangible Cultural Heritage (LICH) of UNESCO. In 2012 the Fiesta of the Patios was inscribed on the LICH. Currently, this event held during two weeks in May involves visits by the public to traditional dwellings. This event is becoming a magnet for tourists from outside the city and has established itself as a further tourist attraction, with the risk that it may lose part of its authenticity. This paper aims to use the hedonic price methodology to examine the externalities deriving from the “Fiesta” in order to verify whether the possible benefits/disadvantages of its existence are capitalised in real estate prices and quantify these effects. The results indicate that the “Fiesta” constitutes an added value for housing properties.JEL Codes - L83; Z30; A1

Stocking density and its influence on shape of Senegalese sole adults

Peer Reviewe

Exclusive lasso-based k-nearest-neighbor classification

Conventionally, the k nearest-neighbor (kNN) classification is implemented with the use of the Euclidean distance-based measures, which are mainly the one-to-one similarity relationships such as to lose the connections between different samples. As a strategy to alleviate this issue, the coefficients coded by sparse representation have played a role of similarity gauger for nearest-neighbor classification as well. Although SR coefficients enjoy remarkable discrimination nature as a one-to-many relationship, it carries out variable selection at the individual level so that possible inherent group structure is ignored. In order to make the most of information implied in the group structure, this paper employs the exclusive lasso strategy to perform the similarity evaluation in two novel nearest-neighbor classification methods. Experimental results on both benchmark data sets and the face recognition problem demonstrate that the EL-based kNN method outperforms certain state-of-the-art classification techniques and existing representation-based nearest-neighbor approaches, in terms of both the size of feature reduction and the classification accuracy

A Comparison Study of the Differential Functioning of Tests Statistic and a New Mahalanobis Distance-Based Statistic For Pre-Screening Item Response Theory Models

The Differential Test Functioning (DTF) statistic, with the Item Parameter Replication (IPR) procedure, can measure Differential Item Functioning (DIF) within the Differential Functioning of Items and Tests (DFIT) framework for Item Response Theory (IRT) models. However, it comes with many practical costs and theoretical assumptions. In some reasonably anticipated circumstances, the DTF statistic cannot be evaluated easily, and DFIT analysis consequentially remains beyond the scope of impacted IRT models. A straightforward, diagnostic statistic would add value to typical IRT model fitting. It was hypothesized that a statistic based on Mahalanobis distances and standard errors of an IRT model could perform as a reliable flag for likely DIF. To test this hypothesis, a Monte Carlo simulation study compared the performance of the traditional DTF measure to the new statistic. Although easy to calculate, the statistic proved unproductive in flagging models with DIF present. Related performance analysis and recommendations were provided