Do Social Relations Affect Economic Welfare? A Microeconomic Empirical Analysis

Over the last few years, many studies have shown that social networks affect the socioeconomic development. This paper presents evidence, through the Italian microdata representative of the entire Italian population, that the quality and quantity of interpersonal relations of agents can increase their economic welfare. Two proxies of interpersonal relations at an individual level are considered: a proxy for the density and one for the quality of network structure of personal contacts. Both seem to have a positive effect on the level of household economic welfare of agents. This result proves robust to the inclusion of a variety of control variables and to the use of different econometric methods.Networks, Social Interactions, Household Economic Welfare, Microdata, Fuzzy Logic

A COMPREHENSIVE GEOSPATIAL KNOWLEDGE DISCOVERY FRAMEWORK FOR SPATIAL ASSOCIATION RULE MINING

Continuous advances in modern data collection techniques help spatial scientists gain access to massive and high-resolution spatial and spatio-temporal data. Thus there is an urgent need to develop effective and efficient methods seeking to find unknown and useful information embedded in big-data datasets of unprecedentedly large size (e.g., millions of observations), high dimensionality (e.g., hundreds of variables), and complexity (e.g., heterogeneous data sources, space–time dynamics, multivariate connections, explicit and implicit spatial relations and interactions). Responding to this line of development, this research focuses on the utilization of the association rule (AR) mining technique for a geospatial knowledge discovery process. Prior attempts have sidestepped the complexity of the spatial dependence structure embedded in the studied phenomenon. Thus, adopting association rule mining in spatial analysis is rather problematic. Interestingly, a very similar predicament afflicts spatial regression analysis with a spatial weight matrix that would be assigned a priori, without validation on the specific domain of application. Besides, a dependable geospatial knowledge discovery process necessitates algorithms supporting automatic and robust but accurate procedures for the evaluation of mined results. Surprisingly, this has received little attention in the context of spatial association rule mining. To remedy the existing deficiencies mentioned above, the foremost goal for this research is to construct a comprehensive geospatial knowledge discovery framework using spatial association rule mining for the detection of spatial patterns embedded in geospatial databases and to demonstrate its application within the domain of crime analysis. It is the first attempt at delivering a complete geo-spatial knowledge discovery framework using spatial association rule mining

Monitoring land use changes using geo-information : possibilities, methods and adapted techniques

Monitoring land use with geographical databases is widely used in decision-making. This report presents the possibilities, methods and adapted techniques using geo-information in monitoring land use changes. The municipality of Soest was chosen as study area and three national land use databases, viz. Top10Vector, CBS land use statistics and LGN, were used. The restrictions of geo-information for monitoring land use changes are indicated. New methods and adapted techniques improve the monitoring result considerably. Providers of geo-information, however, should coordinate on update frequencies, semantic content and spatial resolution to allow better possibilities of monitoring land use by combining data sets

Engineering polymer informatics: Towards the computer-aided design of polymers

The computer-aided design of polymers is one of the holy grails of modern chemical informatics and of significant interest for a number of communities in polymer science. The paper outlines a vision for the in silico design of polymers and presents an information model for polymers based on modern semantic web technologies, thus laying the foundations for achieving the vision

CPAS/CCM experiences: Perspectives for AI/ES research in accounting

https://egrove.olemiss.edu/dl_proceedings/1111/thumbnail.jp

Developing Intellectual Capital Model for Energy Industry

Abstract. Intellectual capital is an important topic that has been viewed as one of the most value increase of company resources and key capitals in entrepreneurial development. This study aims to design a model for measuring intellectual capital. The previous models are reviewed and indicators for measuring are extracted. The population is 1104 managers and experts of 13 firms of Iran Transfo Company and 285 samples were selected randomly classified from companies. Data were collected by questionnaire, and we use structural equation modelling for the analysis. Our proposed intellectual capital model includes 5 aspects of human, structural, customer, the relational and systemic capital. All aspects have significant positive relationship with each other. Structural, relational and customer capital had the most intense relationships in the model and systemic and human capital were in fourth and fifth respectively. Keywords:  Customer capital, human capital, intellectual capital, relational capital, structural capita

Query Rewriting in Itemset Mining

Abstract. In recent years, researchers have begun to study inductive databases, a new generation of databases for leveraging decision support applications. In this context, the user interacts with the DBMS using advanced, constraint-based languages for data mining where constraints have been specifically introduced to increase the relevance of the results and, at the same time, to reduce its volume. In this paper we study the problem of mining frequent itemsets using an inductive database 1 . We propose a technique for query answering which consists in rewriting the query in terms of union and intersection of the result sets of other queries, previously executed and materialized. Unfortunately, the exploitation of past queries is not always applicable. We then present sufficient conditions for the optimization to apply and show that these conditions are strictly connected with the presence of functional dependencies between the attributes involved in the queries. We show some experiments on an initial prototype of an optimizer which demonstrates that this approach to query answering is not only viable but in many practical cases absolutely necessary since it reduces drastically the execution time