Bayesian density estimation using Skew Student-t-Normal mixtures

We present a Bayesian approach for modeling heterogeneous data and estimate multimodal densities using mixtures of Skew Student-t-Normal distributions [Gomez, H.W., Venegas, O., Bolfarine, H., 2007. Skew-symmetric distributions generated by the distribution function of the normal distribution. Environmetrics 18, 395-407]. A stochastic representation that is useful for implementing a MCMC-type algorithm and results about existence of posterior moments are obtained. Marginal likelihood approximations are obtained, in order to compare mixture models with different number of component densities. Data sets concerning the Gross Domestic Product per capita (Human Development Report) and body mass index (National Health and Nutrition Examination Survey), previously studied in the related literature, are analyzed. (c) 2008 Elsevier B.V. All rights reserved.

Community College Student and Faculty Information Needs and Information Seeking: an Ethnographic Study

This presentation was offered as part of the CUNY Library Assessment Conference, Reinventing Libraries: Reinventing Assessment, held at the City University of New York in June 2014.

Assessment as Engagement, Assessment as Outreach: Understanding Student Learning About Research at the Trinity College Library

This presentation was offered as part of the CUNY Library Assessment Conference, Reinventing Libraries: Reinventing Assessment, held at the City University of New York in June 2014.

Air Conditioning and Refrigeration Student Looking at Plans

A student from the New York Trade School in the Air Conditioning and Refrigeration Dept. looks at plans on top of a building. Black and white photograph contains some damage from adhesive and writing on the front.

Student at work with closed-circuit TV

A student in the Closed-circuit TV Dept. at the New York Trade School is shown working. Black and white photograph.

Closed-circuit Television Student Working

A student is show working with closed-circuit television at the New York Trade School. Black and white photograph.

Data Processing Student Working

A student from the Data Processing program at the New York Trade School is shown working. Black and white photograph with some edge damage due to writing in black along the top.

Professor and Student in Piano Crafts Department

Here a professor in the Piano Crafts Department at the New York Trade School is shown helping a student. Black and white photograph.

Welding Student at Work

A student in the Welding Department at the New York Trade School is pictured working. Notice the sparks that are being emitted from the equipment. Black and white photograph.

Sign Painting Student Working Outside

A Sign Painting student from the New York Trade School is pictured working outside on scaffolding on an AMOCO sign. Black and white photograph.

The Impact of the NIHERST/NGC National Science Centre, Trinidad and Tobago on Visiting Student Groups

The aim of this study was to asses the impact of a visit to the NIHERST/NGC National Science Centre in Trinidad on four different school-age visitor groups. The research was conducted through the administering of a post-visit questionnaire immediately upon completion of each visit by each group, and via visitor feedback obtained in post-visit or pre-visit activities conducted within two weeks of the visit for three groups. Teachers/instructors who accompanied the groups on their visit also completed post-visit questionnaires and provided additional information on follow-up activities via an interview. The results of this investigation suggest that the visit to this science centre provided entertainment/enjoyment value and potential educational value to most individuals. The nature of this enjoyment was noted for various age groups and genders in this study. Quantification of the educational impact was not possible within the constraints of this study, which was unable to capture long-term effects of the supply of ‘new knowledge’ to visitors which the visit to the science centre had provided.

A comparative study of immigrants’ political participation in Sweden and the Netherlands

This study deals with immigrants’ political participation in Sweden and the Netherlands. Scholars have recognized low level of political participation of immigrants in Sweden compared to the Netherlands. The main goal of this study is to analyze the institutional influence, mainly from political parties over immigrants’ motivation for active electoral participation. The modified actor-context model uses here as the main theoretical framework. In addition, social capital theory employs to analyze immigrants’ voluntary organizational membership. This study confirms that, Swedish immigrants have the lower participation rate in the political sphere, at lest to a certain extent, than its counterparts the Dutch immigrants. This study also confirms the argument that contextual factors can influence actor’s motivations in integration-oriented action, and similarly it validates the necessity of enlargement of the actor-context model.

ANFIS BASED MODELS FOR ACCESSING QUALITY OF WIKIPEDIA ARTICLES

Wikipedia is a free, web-based, collaborative, multilingual encyclopedia project supported by the non-profit Wikimedia Foundation. Due to the free nature of Wikipedia and allowing open access to everyone to edit articles the quality of articles may be affected. As all people don’t have equal level of knowledge and also different people have different opinions about a topic so there may be difference between the contributions made by different authors. To overcome this situation it is very important to classify the articles so that the articles of good quality can be separated from the poor quality articles and should be removed from the database. The aim of this study is to classify the articles of Wikipedia into two classes class 0 (poor quality) and class 1(good quality) using the Adaptive Neuro Fuzzy Inference System (ANFIS) and data mining techniques. Two ANFIS are built using the Fuzzy Logic Toolbox [1] available in Matlab. The first ANFIS is based on the rules obtained from J48 classifier in WEKA while the other one was built by using the expert’s knowledge. The data used for this research work contains 226 article’s records taken from the German version of Wikipedia. The dataset consists of 19 inputs and one output. The data was preprocessed to remove any similar attributes. The input variables are related to the editors, contributors, length of articles and the lifecycle of articles. In the end analysis of different methods implemented in this research is made to analyze the performance of each classification method used.