Automatic Deforestation Detection based on the Deep Learning in Ukraine

Ukraine's big problem is the disappearance of forest cover. According to the international forest monitoring project Global Forest Watch, Ukraine lost 1.08Mha of forests from 2000 to 2020. Such sad statistics are possible only due to the lack of monitoring tools for the forest industry in Ukraine. Such a tool can be created by combining Remote Sensing and Deep Learning approaches. To implement such approach for the automatic use, we combine Optical and Synthetic Aperture Radar images of the Sentinel-2 and Sentinel-1 satellite missions on which object-detection is performed using a U-Net-based neural network trained with use of the semi-supervised learning technique. This approach is being tested and shows its effectiveness in Kyiv region and going to be implemented in the same way for the Lviv, Odessa and Zakarpatya oblasts

Exploring the Career Motivations, Strengths, and Challenges of Autistic and Non-autistic University Students: Insights From a Participatory Study

Supports for the growing number of autistic university students often focus on helping them succeed in university. However, even educated autistic people experience discrimination and other challenges which can make it very difficult for them to obtain meaningful jobs. Little remains known about how universities can better support their autistic students and alumni in overcoming barriers to meaningful employment. In this participatory study, a team of autistic and non-autistic researchers asked autistic (n = 92) and non-autistic (n = 774) university students about their career aspirations, strengths they believe will help them succeed in their “dream jobs,” and obstacles they expect to encounter. Autistic participants’ top goal in attending college was to improve their career prospects. However, relatively few autistic students reported learning career-specific skills at university. Autistic students were more likely to seek an academic job and less likely to seek a career in healthcare than non-autistic students. Autistic students highlighted writing skills and detail orientation as strengths that could help them succeed in their dream jobs more often than non-autistic students. However, they were also more likely to expect discrimination, social, and psychological difficulties to stand in the way of their dream jobs. These findings suggest that universities should prioritize experiential learning opportunities to help autistic (and non-autistic) students develop employment-related skills while providing mental health supports. Universities should demonstrate their commitment to supporting diverse learners by seeking out and hiring autistic professionals and by teaching their own staff and employers how to appreciate and support autistic colleagues

A participatory approach to iteratively adapting game design workshops to empower autistic youth

IntroductionAutistic people face systemic barriers to fair employment. Informal learning may promote the self-determination transition-age autistic youth need to overcome and/or transform these barriers. This report focuses on the iterative process of developing video game design workshops guided by feedback from autistic students about instructional strategies they found engaging. This study is part of a three-year-long NSF-funded program of research that seeks to empower autistic youth to move toward successful careers by teaching educators how to more effectively guide them.MethodsIn the Summer of 2021, educators at an award-winning NYC-based, not-for-profit, education program, Tech Kids Unlimited (TKU) collaborated with researchers, including autistic students, to iteratively develop and assess two online game design workshops for transition-age autistic youth. Participants selected which workshop they were available for (Workshop 1: n = 18; M age = 16.72  years; Workshop 2: n = 16; M age = 16.56  years). Students in Workshop 2  had more varied support needs and were less motivated to learn video game design than students in Workshop 1. Students completed assessments before and after each workshop and rated their interest in specific workshop activities after each activity. Guided by data from Workshop 1, we revised instructional strategies before conducting Workshop 2.ResultsWe found little evidence for our hypothesis that attentional style would impact educational engagement. However, video game design self-efficacy and self-determination were often positively associated with engagement. Two industry speakers, one of whom was autistic, were among the highest-rated activities. As hypothesized, video game design self-efficacy and self-determination (and unexpectedly) spatial planning improved from pre- to post-test following Workshop 1. Despite our efforts to use what we learned in Workshop 1 to improve in Workshop 2, Workshop 2 did not lead to significant improvements in outcomes. However, students highlighted instructional strategies as a strength of Workshop 2 more often than they had for Workshop 1. Educators highlighted the importance of group “temperature checks,” individualized check-ins, social–emotional support for students and educators, and fostering a positive atmosphere.DiscussionFindings suggest that interactive multimodal activities, stimulating discussions, and opportunities to engage with neurodivergent industry professionals may engage and empower diverse autistic youth