Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

Spectral analysis of the angular distribution function of back reflectors for thin film silicon solar cells

Nowadays, one of the most important challenges to enhance the efficiency of thin film silicon solar cells is to increase the short circuit intensity by means of optical confinement methods, such as textured back-reflector structures. In this work, two possible textured structures to be used as back reflectors for n-i-p solar cells have been optically analyzed and compared to a smooth one by using a system which is able to measure the angular distribution function (ADF) of the scattered light in a wide spectral range (350-1000 nm). The accurate analysis of the ADF data corresponding to the reflector structures and to the μc-Si:H films deposited onto them allows the optical losses due to the reflector absorption and its effectiveness in increasing light absorption in the μc-Si:H layer, mainly at long wavelengths, to be quantified.

Headspace needle-trap analysis of priority volatile organic compounds from aqueous samples: application to the analysis of natural and waste waters

Combining headspace (HS) sampling with a needle-trap device (NTD) to determine priority volatile organic compounds (VOCs) in water samples results in improved sensitivity and efficiency when compared to conventional static HS sampling. A 22 gauge stainless steel, 51-mm needle packed with Tenax TA and Carboxen 1000 particles is used as the NTD. Three different HS-NTD sampling methodologies are evaluated and all give limits of detection for the target VOCs in the ng L−1 range. Active (purge-and-trap) HS-NTD sampling is found to give the best sensitivity but requires exhaustive control of the sampling conditions. The use of the NTD to collect the headspace gas sample results in a combined adsorption/desorption mechanism. The testing of different temperatures for the HS thermostating reveals a greater desorption effect when the sample is allowed to diffuse, whether passively or actively, through the sorbent particles. The limits of detection obtained in the simplest sampling methodology, static HS-NTD (5 mL aqueous sample in 20 mL HS vials, thermostating at 50 °C for 30 min with agitation), are sufficiently low as to permit its application to the analysis of 18 priority VOCs in natural and waste waters. In all cases compounds were detected below regulated levels

Analysis of the process of inspection in recreational craft in Spain. Suggestions for safety improvement

Inspections of pleasure boats in Spain can be carried out by collaborating entities of inspection, entities that must be authorized by the Maritime Administration. This authorization allows to perform effective inspections and technical controls of recreational crafts. Recreational crafts are subjected to surveys that are based on the registration list and on the material used in the hull. In addition, required safety equipment of the recreational boat depends on the distance that the recreational boat is authorized to navigate. Following data obtained from inspections of recreational craft, this paper aims to analyze information about hulls within dry and afloat conditions, about the equipment for rescue and safety, and about other nautical equipment; as well as to perform and improve different verifications during the inspections. All this information points to several aspects relevant for the optimization of the inspection process, the ultimate target being increasing efficiency and effectiveness, and ensuring more safety in recreational craft.

Efficiency and Equity in Learning Communities and schools

Traditionally, school efficiency has been measured as a function of educational production. In the last two decades, however, studies in the economics of education have indicated that more is required to improve school efficiency: researchers must explore how significant changes in school organization affect the performance of at-risk students. In this paper we introduce Henry Levin’s adoption of the X-efficiency approach to education and we describe the efficient and cost-effective characteristics of one Learning Communities Project School that significantly improved its student outcomes and enrollment numbersand reduced its absenteeism rate to zero. The organizational change that facilitatedthese improvements defined specific issues to address. Students’ school success became the focus of the school project, which also offered specific incentives, selected teachers, involved parents and community members in decisions, and used the most efficient technologies and methods. This case analysis reveals new two elements—family training and community involvement—that were not explicit parts of Levin’s adaptation. The case of the Antonio Machado Public School should attract the attention of both social scientists and policy makers