Online network use in schools: Social and educational opportunities

Most state governments in Australia have banned popular online networking sites from public schools after these sites were accused of supporting a broad host of threats to young people. This paper questions the effectiveness of these bans in light of recent empirical research that highlights the social and educational benefits that can accrue from young people's online network use. In doing so, this paper argues for a more informed policy debate that considers not only the risks involved in using online networks, but also the opportunities online networks afford and the capabilities young people require to use them effectively

Sticking together: teaching, learning and the art of research

In this paper we emphasise the importance for community educators of building bridges between emerging needs, research, teaching and learning. A case study of recent work is used to illustrate the way in which research in vocational education and training offers the potential for practical outcomes which are not necessarily defined by the Research Assessment Exercise (RAE). We believe that fragmentation must be resisted: the glue securing teaching, learning and research must be preserved. The project which functions as our case study concerned the education and training needs of youth and community arts practitioners. Situated in the north of England, the research was directed by a partnership comprising Yorkshire and Humberside Arts, West Yorkshire Youth Association, the Calouste Gulbenkian Foundation, youth and community arts practitioners and the University of Huddersfield. This innovative collaboration led to pragmatic outcomes in course development, teaching and learning: a new postgraduate course is planned in direct response to the research, a conference was held to share the findings with practitioners whose input, using a focus group approach, was vital in the writing of the final report. We also envisage the work having a practical impact on future approaches to teaching and learning. We analyse the glue which holds together the collaborative partnership and answer the question: what is the nature of cross-sectoral partnership and how do all the partners get what they want? We believe this brings us back to the good old fashioned idea that the purpose of educational research is to inspire change, and is not only to add to the sum of human knowledge. Sadly, all too often nowadays there is a tendency for research to serve the demands of the RAE

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Participant views on involvement in a trial of social recovery cognitive behaviour therapy

Background The PRODIGY trial (Prevention of long term social disability amongst young people with emerging psychological difficulties, ISRCTN47998710) is a pilot trial of social recovery cognitive behaviour therapy (SRCBT). Aims The PRODIGY qualitative substudy aimed to (a) explore individual experiences of participating in the pilot randomised, controlled trial (recruitment, randomisation, assessment) andinitial views of therapy, and (b) to explore perceived benefits of taking part in research v. ethical concerns and potential risks. Method Qualitative investigation using semi-structured interviews with thematic analysis. Results Analysis revealed participant experiences around the key themes of acceptability, disclosure, practicalities, altruism and engagement. Conclusions Participants in both trial arms perceived themselves as gaining benefits from being involved in the study, above and beyond the intervention. This has implications for the design of future research and services for this client group, highlighting the importance of being flexible and an individualised approach as key engagement tools

Response to Campbell et al., (2018) - Health risk perceptions and reasons for use of tobacco products among clients in addictions treatment

Campbell et al. (2018) paper focuses on an important issue, smoking amongst those seeking treatment for substance use disorder (SUD). The paper examines rates of use, health perceptions and reasons for use of tobacco and nicotine containing products in order to examine variables associated with product use

The Improvements and Advantages of Hybrid UAS Systems in the Detection of Metals and Other Anthropogenic Objects

The Northwestern Tier of New York is plagued by the past industrialization of the fracking industry. Anywhere west of Broome county, you are likely to find abandoned oil and fracking wells. Abandoned fracking wells are point sources for methane emissions with some estimations saying the unplugged wells, in a day, emit as much as the entire city of Buffalo\u27s cars emit in a year. Because all wells in New York State are considered abandoned, there is legislation preventing the new installation of wells. This means that across the Western Tier, there are countless wells which lay unmanned and unplugged – constantly polluting into the environment around them. Our research project is the development of a method for the efficient location and classification of orphaned wells in the hard-to-navigate terrain of the Northeast. In creating a uniform method for locating and classifying, the orphaned well dilemma can be better managed.https://orb.binghamton.edu/research_days_posters_2023/1065/thumbnail.jp

Cost Benefits: Injury Prevention Shoulder Program and Insurance Premiums

The shoulder complex of the baseball athlete is exposed to countless stressors that can potentially cause injury. There are numerous predisposing risk factors that could possibly increase the rate at which injury occurs. Athletes at the collegiate level, due to age, are at the highest risk for significant shoulder injury. Those injuries can be extremely costly and athletes at the collegiate level tend to be at the highest risk for financial loss. As of 2005, the NCAA mandated that each student-athlete that participates in any NCAA practice or game must have health insurance that could potentially cover up to $90,000 worth of claims. The institution has two decision to either leave all leftover costs to the responsibility of the student-athlete or purchase a secondary insurance that will help cover remaining costs that the primary insurance does not cover. The choice of an institution to purchase secondary insurance can be a burden due to the extra costs that tax the athletic department’s budget. With each and every shoulder injury that is suffered by a baseball student-athlete the insurance premium of the school will be increased thus putting an unnecessary cost on the school’s budget. In order to decrease this cost, the use of an injury prevention shoulder program that is applied to a Division I baseball program was utilized and the premiums were analyzed in order to see the decrease in costs that were adding to the insurance program. Insurance claims were tallied for the years 2012-2013, 2013-2014, 2014-2015 and 2015-2016. The amount of shoulder injuries from baseball student-athletes were analyzed. The results showed that there was a decrease in the amount of shoulder injury after the injury maintenance shoulder program was implemented, thus decreasing the medical expenses that are spent on shoulder injuries for the baseball student-athlete. These results show that there is indeed a positive correlation between the use of an injury maintenance shoulder program and decreasing the amount of medical expenditures that come from the Baseball student-athlete

Identification of cement manufacturing raw materials using machine vision

In the mining and manufacturing industry, there is a need for a non-extractive system to identify raw materials on conveying systems. Such a system would allow identification of raw materials on conveying systems preventing cross-contamination when the materials arrive at the final storage location. This project used machine vision techniques to identify cement manufacturing raw materials (clinker, gypsum and, limestone). Firstly, a representative sample (25 x 10kg samples of each material) was collected using a stratified random sampling procedure. This stratified random sampling procedure ensured the sample accurately represented the raw material in the stockpile. A dual purpose test bed and controlled lighting camera enclosure (for static model development and future dynamic system implementation) were constructed to minimise the effect of varying ambient light. This test bed and camera enclosure allowed the CMOS global shutter industrial camera to take twenty, 24bit colour images (8bit for each colour) of each sample. These images were catalogued and stored in a database for further model training and verification purposes. These images were pre-processed by a median filter which allowed any over saturated pixels (due to raw material surface moisture reflection) to have their intensity level reduced by replacing its value by the median value of its local neighbours. From the filtered image the individual red, green and blue (RGB) components were passed to a Histogram function which binned (255 bins for 8-bit colour) the various pixel intensities. The statistical features (weighted mean, skewness and kurtosis) of each colour's histogram were then stored in an array which then passed to the image feature database. A varying amount of feature arrays were used to train and verify the success of a probabilistic neural network (PNN) model. Initial optimisation of the PNN model was conducted using a local search algorithm which changed the smoothing parameter which achieved 94.83% accuracy. This model was then improved by implementing a Supervised Learning Probabilistic Neural Network (SLPNN). This model added data weight which changed the height of the Gaussian distribution function and input variable vector weight which changes the width of Gaussian distribution function. The implementation of the Supervised Learning Probabilistic Neural Network improved the models accuracy to 99.57%. Further model field testing will be required to verify the system in an operational environment where the camera enclosure will be subjected to dust, noise, varying temperatures and moisture. The Supervised Learning Probabilistic Neural Network outperforms the standard Probabilistic Neural Network which has been proven by this work. This work supports the claim that Machine Vision can be successfully be used to identify cement manufacturing raw materials with a high success rate. It also contributes to the literature by classifying clinker, gypsum and limestone in one body of work