Learning from experience: Analysis of the civil litigation regarding building structures on the court of bologna in the years 2011/2012

The present work is aimed to the study and the analysis of the defects detected in the civil structure and that are object of civil litigation in order to create an instruments capable of helping the different actor involved in the building process. It is divided in three main sections. The first part is focused on the collection of the data related to the civil proceeding of the 2012 and the development of in depth analysis of the main aspects regarding the defects on existing buildings. The research center “Osservatorio Claudio Ceccoli” developed a system for the collection of the information coming from the civil proceedings of the Court of Bologna. Statistical analysis are been performed and the results are been shown and discussed in the first chapters.The second part analyzes the main issues emerged during the study of the real cases, related to the activities of the technical consultant. The idea is to create documents, called “focus”, addressed to clarify and codify specific problems in order to develop guidelines that help the technician editing of the technical advice.The third part is centered on the estimation of the methods used for the collection of data. The first results show that these are not efficient. The critical analysis of the database, the result and the experience and throughout, allowed the implementation of the collection system for the data.

Learning styles vary among general surgery residents: analysis of 12 years of data

PURPOSE: Understanding the learning styles of individuals may assist in the tailoring of an educational program to optimize learning. General surgery faculty and residents have been characterized previously as having a tendency toward particular learning styles. We seek to understand better the learning styles of general surgery residents and differences that may exist within the population. METHODS: The Kolb Learning Style Inventory was administered yearly to general surgery residents at the University of Cincinnati from 1994 to 2006. This tool allows characterization of learning styles into 4 groups: converging, accommodating, assimilating, and diverging. The converging learning style involves education by actively solving problems. The accommodating learning style uses emotion and interpersonal relationships. The assimilating learning style learns by abstract logic. The diverging learning style learns best by observation. Chi-square analysis and analysis of variance were performed to determine significance. RESULTS: Surveys from 1994 to 2006 (91 residents, 325 responses) were analyzed. The prevalent learning style was converging (185, 57%), followed by assimilating (58, 18%), accommodating (44, 14%), and diverging (38, 12%). At the PGY 1 and 2 levels, male and female residents differed in learning style, with the accommodating learning style being relatively more frequent in women and assimilating learning style more frequent in men (Table 1, p < or = 0.001, chi-square test). Interestingly, learning style did not seem to change with advancing PGY level within the program, which suggests that individual learning styles may be constant throughout residency training. If a resident's learning style changed, it tended to be to converging. In addition, no relation exists between learning style and participation in dedicated basic science training or performance on the ABSIT/SBSE. CONCLUSIONS: Our data suggests that learning style differs between male and female general surgery residents but not with PGY level or ABSIT/SBSE performance. A greater understanding of individual learning styles may allow more refinement and tailoring of surgical programs.

Sustainable Wastewater Management: Is it Possible to Regulate Micropollution in the Future by Learning from the Past? A Policy Analysis

This paper applies a policy analysis approach to the question of how to effectively regulate micropollution in a sustainable manner. Micropollution is a complex policy problem characterized by a huge number and diversity of chemical substances, as well as various entry paths into the aquatic environment. It challenges traditional water quality management by calling for new technologies in wastewater treatment and behavioral changes in industry, agriculture and civil society. In light of such challenges, the question arises as to how to regulate such a complex phenomenon to ensure water quality is maintained in the future? What can we learn from past experiences in water quality regulation? To answer these questions, policy analysis strongly focuses on the design and choice of policy instruments and the mix of such measures. In this paper, we review instruments commonly used in past water quality regulation. We evaluate their ability to respond to the characteristics of a more recent water quality problem, i.e., micropollution, in a sustainable way. This way, we develop a new framework that integrates both the problem dimension (i.e., causes and effects of a problem) as well as the sustainability dimension (e.g., long-term, cross-sectoral and multi-level) to assess which policy instruments are best suited to regulate micropollution. We thus conclude that sustainability criteria help to identify an appropriate instrument mix of end-of-pipe and source-directed measures to reduce aquatic micropollution.

Learning kinds for students of technical high school : An analysis from the David Ausubel's theory

This article presents the findings of a field research, not experimental, observational, correlating, basic, of mixed data, micro sociologic, leading to a study of surveys.The object of study is to find learning kinds, and the unit of analysis were 529 high school students between 16 and 21 years old. Its purpose is to understand the impact of learning by rote, guided, self learned and meaningful learning and its achievement degree besides the learning outcomes of differentiated curriculum based on David Ausubel's thoughts, associated with different economic specialties (MINEDUC, 1998) where the population of the study is trained. To collect data, the test TADA - DO2 was used, this test has a reliability index of 0.911 according to Cronbach. From the hits it can be stated from the null hypothesis that there is a significant association (a = 0,05) between the learning kinds and the learning expected of differentiated training plan for both, male and female. It is complex to state that the training of the middle-level technicians leads to a successful employment.

Learning kinds for students of technical high school : An analysis from the David Ausubel's theory

This article presents the findings of a field research, not experimental, observational, correlating, basic, of mixed data, micro sociologic, leading to a study of surveys.The object of study is to find learning kinds, and the unit of analysis were 529 high school students between 16 and 21 years old. Its purpose is to understand the impact of learning by rote, guided, self learned and meaningful learning and its achievement degree besides the learning outcomes of differentiated curriculum based on David Ausubel's thoughts, associated with different economic specialties (MINEDUC, 1998) where the population of the study is trained. To collect data, the test TADA - DO2 was used, this test has a reliability index of 0.911 according to Cronbach. From the hits it can be stated from the null hypothesis that there is a significant association (a = 0,05) between the learning kinds and the learning expected of differentiated training plan for both, male and female. It is complex to state that the training of the middle-level technicians leads to a successful employment.

Learning kinds for students of technical high school : An analysis from the David Ausubel's theory

This article presents the findings of a field research, not experimental, observational, correlating, basic, of mixed data, micro sociologic, leading to a study of surveys.The object of study is to find learning kinds, and the unit of analysis were 529 high school students between 16 and 21 years old. Its purpose is to understand the impact of learning by rote, guided, self learned and meaningful learning and its achievement degree besides the learning outcomes of differentiated curriculum based on David Ausubel's thoughts, associated with different economic specialties (MINEDUC, 1998) where the population of the study is trained. To collect data, the test TADA - DO2 was used, this test has a reliability index of 0.911 according to Cronbach. From the hits it can be stated from the null hypothesis that there is a significant association (a = 0,05) between the learning kinds and the learning expected of differentiated training plan for both, male and female. It is complex to state that the training of the middle-level technicians leads to a successful employment.

Microarray analysis of autoimmune diseases by machine learning procedures

—Microarray-based global gene expression profiling, with the use of sophisticated statistical algorithms is providing new insights into the pathogenesis of autoimmune diseases. We have applied a novel statistical technique for gene selection based on machine learning approaches to analyze microarray expression data gathered from patients with systemic lupus erythematosus (SLE) and primary antiphospholipid syndrome (PAPS), two autoimmune diseases of unknown genetic origin that share many common features. The methodology included a combination of three data discretization policies, a consensus gene selection method, and a multivariate correlation measurement. A set of 150 genes was found to discriminate SLE and PAPS patients from healthy individuals. Statistical validations demonstrate the relevance of this gene set from an univariate and multivariate perspective. Moreover, functional characterization of these genes identified an interferon-regulated gene signature, consistent with previous reports. It also revealed the existence of other regulatory pathways, including those regulated by PTEN, TNF, and BCL-2, which are altered in SLE and PAPS. Remarkably, a significant number of these genes carry E2F binding motifs in their promoters, projecting a role for E2F in the regulation of autoimmunity.

Regularization for sparsity in statistical analysis and machine learning

Pragmatism is the leading motivation of regularization. We can understand regularization as a modification of the maximum-likelihood estimator so that a reasonable answer could be given in an unstable or ill-posed situation. To mention some typical examples, this happens when fitting parametric or non-parametric models with more parameters than data or when estimating large covariance matrices. Regularization is usually used, in addition, to improve the bias-variance tradeoff of an estimation. Then, the definition of regularization is quite general, and, although the introduction of a penalty is probably the most popular type, it is just one out of multiple forms of regularization. In this dissertation, we focus on the applications of regularization for obtaining sparse or parsimonious representations, where only a subset of the inputs is used. A particular form of regularization, L1-regularization, plays a key role for reaching sparsity. Most of the contributions presented here revolve around L1-regularization, although other forms of regularization are explored (also pursuing sparsity in some sense). In addition to present a compact review of L1-regularization and its applications in statistical and machine learning, we devise methodology for regression, supervised classification and structure induction of graphical models. Within the regression paradigm, we focus on kernel smoothing learning, proposing techniques for kernel design that are suitable for high dimensional settings and sparse regression functions. We also present an application of regularized regression techniques for modeling the response of biological neurons. Supervised classification advances deal, on the one hand, with the application of regularization for obtaining a na¨ıve Bayes classifier and, on the other hand, with a novel algorithm for brain-computer interface design that uses group regularization in an efficient manner. Finally, we present a heuristic for inducing structures of Gaussian Bayesian networks using L1-regularization as a filter. El pragmatismo es la principal motivación de la regularización. Podemos entender la regularización como una modificación del estimador de máxima verosimilitud, de tal manera que se pueda dar una respuesta cuando la configuración del problema es inestable. A modo de ejemplo, podemos mencionar el ajuste de modelos paramétricos o no paramétricos cuando hay más parámetros que casos en el conjunto de datos, o la estimación de grandes matrices de covarianzas. Se suele recurrir a la regularización, además, para mejorar el compromiso sesgo-varianza en una estimación. Por tanto, la definición de regularización es muy general y, aunque la introducción de una función de penalización es probablemente el método más popular, éste es sólo uno de entre varias posibilidades. En esta tesis se ha trabajado en aplicaciones de regularización para obtener representaciones dispersas, donde sólo se usa un subconjunto de las entradas. En particular, la regularización L1 juega un papel clave en la búsqueda de dicha dispersión. La mayor parte de las contribuciones presentadas en la tesis giran alrededor de la regularización L1, aunque también se exploran otras formas de regularización (que igualmente persiguen un modelo disperso). Además de presentar una revisión de la regularización L1 y sus aplicaciones en estadística y aprendizaje de máquina, se ha desarrollado metodología para regresión, clasificación supervisada y aprendizaje de estructura en modelos gráficos. Dentro de la regresión, se ha trabajado principalmente en métodos de regresión local, proponiendo técnicas de diseño del kernel que sean adecuadas a configuraciones de alta dimensionalidad y funciones de regresión dispersas. También se presenta una aplicación de las técnicas de regresión regularizada para modelar la respuesta de neuronas reales. Los avances en clasificación supervisada tratan, por una parte, con el uso de regularización para obtener un clasificador naive Bayes y, por otra parte, con el desarrollo de un algoritmo que usa regularización por grupos de una manera eficiente y que se ha aplicado al diseño de interfaces cerebromáquina. Finalmente, se presenta una heurística para inducir la estructura de redes Bayesianas Gaussianas usando regularización L1 a modo de filtro.

An analysis of the moderating effects of age in the acceptance of learning management systems

El presente estudio analiza las intenciones de los usuarios acerca del uso de sistemas de tele-enseñanza LMS (Learning Management Systems, basándose en un modelo que integra el Modelo de Aceptación Tecnológica (TAM, Technology Acceptance Model, la Teoría del Comportamiento Percibido (TPB, Theory of Planned Behavior) y la Teoría Unificada de la Aceptación y Uso de la Tecnología (UTAUT, Unified Theory of Acceptance and Use of Technology), tomando la edad como variable moderadora. Así, este artículo estudia la influencia de la intención conductual, la actitud hacia el uso, la facilidad de uso percibida, la utilidad percibida, la norma subjetiva y la influencia social en la intención de utilizar sistemas e-learning LMS. Como antecedentes de estos factores de influencia se plantean las características del sistema y del usuario. El resultado de la revisión teórica es un modelo unificado que ha sido validado con datos recogidos de 94 estudiantes a través de un cuestionario en línea. Estos datos han sido analizados utilizando la técnica de mínimos cuadrados parciales, y los principales resultados confirman la relevancia predictiva del modelo para usuarios de entre 26 y 35 años y de entre 36 y 45 años.

An interactive web-based learning assistant for structural analysis of continuous beams

There are significant levels of concern about the relevance and the difficulty of learning some issues on Strength of Materials and Structural Analysis. Most students of Continuum Mechanics and Structural Analysis in Civil Engineering usually point out some key learning aspects as especially difficult for acquiring specific skills. These key concepts entail comprehension difficulties but ease access and applicability to structural analysis in more advanced subjects. Likewise, some elusive but basic structural concepts, such as flexibility, stiffness or influence lines, are paramount for developing further skills required for advanced structural design: tall buildings, arch-type structures as well as bridges. As new curricular itineraries are currently being implemented, it appears appropriate to devise a repository of interactive web-based applications for training in those basic concepts. That will hopefully train the student to understand the complexity of such concepts, to develop intuitive knowledge on actual structural response and to improve their preparation for exams. In this work, a web-based learning assistant system for influence lines on continuous beams is presented. It consists of a collection of interactive user-friendly applications accessible via Web. It is performed in both Spanish and English languages. Rather than a “black box” system, the procedure involves open interaction with the student, who can simulate and virtually envisage the structural response. Thus, the student is enabled to set the geometric, topologic and mechanic layout of a continuous beam and to change or shift the loading and the support conditions. Simultaneously, the changes in the beam response prompt on the screen, so that the effects of the several issues involved in structural analysis become apparent. The system is performed through a set of web pages which encompasses interactive exercises and problems, written in JavaScript under JQuery and DyGraphs frameworks, given that their efficiency and graphic capabilities are renowned. Students can freely boost their self-study on this subject in order to face their exams more confidently. Besides, this collection is expected to be added to the "Virtual Lab of Continuum Mechanics" of the UPM, launched in 2013 (http://serviciosgate.upm.es/laboratoriosvirtuales/laboratorios/medios-continuos-en-construcci%C3%B3n)

A framework for adaptive e-learning for continuum mechanics and structural analysis

This paper presents a project for providing the students of Structural Engineering with the flexibility to learn outside classroom schedules. The goal is a framework for adaptive E-learning based on a repository of open educational courseware with a set of basic Structural Engineering concepts and fundamentals. These are paramount for students to expand their technical knowledge and skills in structural analysis and design of tall buildings, arch-type structures as well as bridges. Thus, concepts related to structural behaviour such as linearity, compatibility, stiffness and influence lines have traditionally been elusive for students. The objective is to facilitate the student a teachinglearning process to acquire the necessary intuitive knowledge, cognitive skills and the basis for further technological modules and professional development in this area. As a side effect, the system is expected to help the students improve their preparation for exams on the subject. In this project, a web-based open-source system for studying influence lines on continuous beams is presented. It encompasses a collection of interactive user-friendly applications accessible via Web, written in JavaScript under JQuery and Dygraph Libraries, taking advantage of their efficiency and graphic capabilities. It is performed in both Spanish and English languages. The student is enabled to set the geometric, topologic, boundary and mechanic layout of a continuous beam. While changing the loading and the support conditions, the changes in the beam response prompt on the screen, so that the effects of the several issues involved in structural analysis become apparent. This open interaction with the user allows the student to simulate and virtually infer the structural response. Different levels of complexity can be handled, whereas an ongoing help is at hand for any of them. Students can freely boost their experiential learning on this subject at their own pace, in order to further share, process, generalize and apply the relevant essential concepts of Structural Engineering analysis. Besides, this collection is being added to the "Virtual Lab of Continuum Mechanics" of the UPM, launched in 2013 (http://serviciosgate.upm.es/laboratoriosvirtuales/laboratorios/medios-continuos-en-construcci%C3%B3n)

Extending Working Lives: A comparative analysis of how governments influence lifelong learning, CEPS Special Report No. 111, July 2015

This report offers a comparative policy study on adult learning within the scope of complementary research conducted by Beblavý et al. (2013) on how people upgrade their skills during their adult lifetimes. To achieve our objectives, we identified regulatory policies and financial support in 11 countries for two main categories of learning: formal higher education and employer-based training. Drawing upon the results of the country reports carried out by our partners in the MoPAct project, we found that in none of the countries examined is there an ‘older student’ policy. In most cases grants and financial support are awarded only up until a certain age. In all of the countries studied, standard undergraduate and post-graduate studies are available for part-time students. The distribution of full-time students and part-time students in tertiary education varies from one country to another as well as from one age group to another. The participation in full-time tertiary education programmes decreases with the age of students. In Lithuania, Latvia, Poland and the UK, there are no mandatory policies to ensure employer-based training. However, in Belgium, Czech Republic, Denmark, Estonia, Germany, Italy, the Netherlands and Spain, employer-based training is more clearly regulated and the employers might have obligations to provide training for their staff. Taking into consideration Beblavý et al. (2013), we observe that comparative differences across countries can be related to policy differences only in some cases. The policy framework seems to impact more the employer-based training than the educational attainment (upgrade of ISCED level). In Denmark, the Netherlands, Latvia, Lithuania, Czech Republic and Poland, we find a perfect match between policy outcomes and the results of Beblavý et al. (2013) related to employer-based training. This is not the case in the United Kingdom, where the two aspects observed are not correlated.

Learning and earning : analysis of HEA Title II-B Graduate Library Fellowship Program recipients, fiscal years 1985-1991 /

"PLLI 97-8014"--P. [4] of cover.

A new and easy method of learning Hebrew without points. : To which is annex'd, by way of praxis, The book of Proverbs, divided according to the metre: with the masoretical reading in Roman letters, the interlinear version of Santes Pagninus, &c. A grammatical analysis, and short notes critical and explanatory ... /

Errata: p. [2]-[3] at end.

Optimization and Machine Learning Frameworks for Complex Network Analysis

Thesis (Ph.D.)--University of Washington, 2016-06