Longitudinal Study of Lanana Creek

A longitudinal study was done to collect data on the various conditions of LananaCreek in Nacogdoches, Texas over a seven week span from September 14 to November 2, 2018. The part of the creek studies is a 3.5 mile stretch from East Austin Street to Hoya Soccer Complex, mostly located on the campus of Stephen F. Austin State University. There were 6 different testing sites selected along this expanse. Collection of samples was performed by the General Chemistry I Honors class as part of the laboratory experience. Once collected, the samples were transported back to the lab for testing. The tests performed on the samples included determination of the pH, total solids, total dissolved solids, water hardness, anion concentration, and alkalinity. Each of these tests analyzes for a different parameter that is essential in evaluating the health of the ecosystem as a whole and gives a good reflection of the overall health of the creek’s surrounding environment. The results were compared to EPA standards. During the testing period, there were significant rain events generating variable results after each sampling, but the overall study shows that LananaCreek is healthy

HOPE Longitudinal Study: Year 2 Results

Abstract pending

Longitudinal Study of Child Face Recognition

We present a longitudinal study of face recognition performance on Children Longitudinal Face (CLF) dataset containing 3,682 face images of 919 subjects, in the age group [2, 18] years. Each subject has at least four face images acquired over a time span of up to six years. Face comparison scores are obtained from (i) a state-of-the-art COTS matcher (COTS-A), (ii) an open-source matcher (FaceNet), and (iii) a simple sum fusion of scores obtained from COTS-A and FaceNet matchers. To improve the performance of the open-source FaceNet matcher for child face recognition, we were able to fine-tune it on an independent training set of 3,294 face images of 1,119 children in the age group [3, 18] years. Multilevel statistical models are fit to genuine comparison scores from the CLF dataset to determine the decrease in face recognition accuracy over time. Additionally, we analyze both the verification and open-set identification accuracies in order to evaluate state-of-the-art face recognition technology for tracing and identifying children lost at a young age as victims of child trafficking or abduction

Longitudinal Study of Children's Reintegration in Moldova

This report documents a 22-month longitudinal study of the reintegration of children in residential care in Moldova. This research was carried out by Partnerships for Every Child, a Moldovan Non- Governmental Organisation (NGO), with the support of Family for Every Child, a network of national NGOs. The overall study -- which also examines the reintegration of street children in Mexico and of child domestic workers in Nepal -- aims to identify successful elements in strategies to ensure the sustainable reintegration of children without parental care by examining the reintegration process over four phases.Moldova leads the region in the proportion of its children living in residential care: 2.2 per cent of boys and girls live without parental care, with over 6,000 in residential care and more than 10,000 in family-based care (out of a population of approximately 750,000). Loss of parental care is caused by a complex array of underlying and immediate factors, which are detailed in the report