Participants will investigate the results of doubling & tripling the dimensions of triangles. Mathematical foci include measurement, area, perimeter, and similarity & congruence.

In response to recent declines, forested riparian wetland areas have become an increased conservation and management area of concern focusing on increasing biodiversity and promoting healthy ecosystem services. Additionally, passerine birds have also experienced a sharp global decline in that associated habitat. To mitigate further declines of both habitat and species numbers government programs and agencies have intensified conservation efforts. However, the practices employed are often assumed to be beneficial without conducting dedicated surveys to measure efficacy and practicality of current approaches. As such, visual evidence and statistics are often needed to promote or validate further support and funding for continuing with current polices or creating new focal areas and practices. This study strives to provide an inexpensive, efficient way to assess conservation areas based on a target species through a generalized and adaptive methodology. The Cypress Creek National Wildlife Refuge in southern Illinois provides an opportunity to do just that with a focus on songbirds. The methodology outlined in this study implements multiple remote sensing land use and land cover classification techniques utilizing Landsat imagery from 1984 to 2014 to create a temporal analysis of the region from pre-refuge era to current refuge designated era. Field surveys from the 2015 songbird summer breeding and fall migration seasons as well as vegetation surveys for field-truthing supplement the remote sensing results. The classification methodology incudes a combination of pan-sharpening Landsat images to a 15 m x 15 m spatial resolution, texture analysis, object based image analysis, and Random Forests to produce land use and land cover maps. For the sake of comparison the same classification process is performed with the untransformed, source images at 30 m x 30 m spatial resolution. Landscape metrics such as the interspersion and juxtaposition index and the contiguity index also provide further insight to temporal landscape patterns. At the completion of the study it was found that there was a minimal difference between the overall classification accuracy of transformed and untransformed images and that lowest overall accuracy in the study was 91% while the highest was 98%. The key survey statistics concluded that during the summer and fall observation periods songbirds in forested wetland areas had a propensity to utilize areas closest to the wetland edge as opposed to inland areas. Furthermore, during fall migration it was concluded that the mixed forest habitat type had a direct effect on observation numbers. Overall, with the aid of multiple landscape metrics, it was shown that the region was increasing in forested area, patch density, and contiguity; in response the passerines were using the area at a high rate, especially near wetland edges creating a sustainable focal area for conservation and management. The methodology and results in this study contribute to an ongoing effort to provide visual and statistical evidence that is reliable and accessible for policy making. The potential to manipulate the generalized methods used in this study to enhance any land use and land class classifications and apply to any targeted species certainly exists. Future studies will want to investigate the use of higher spatial resolution images or actively take reflectance recordings in the field and supplement the temporal maps with a multi-year dedicated species dataset for maximum benefit.

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[pt] As tarefas de segmentação e classificação automáticas de áudio vêm se tornando cada vez mais importantes com o crescimento da produção e armazenamento de mídia digital. Este trabalho se baseia em características do padrão MPEG, que é considerado o padrão para acervos digitais, para gerir algoritmos de grande eficiência para realizar essas arefas. Ao passo que há muitos estudos trabalhando a partir do vídeo, o áudio ainda é pouco utilizado de forma eficiente para auxiliar nessas tarefas. Os algoritmos sugeridos partem da leitura apenas dos fatores de escala presentes no Layer 2 do áudio MPEG para ambas as tarefas. Com isso, é necessária a leitura da menor quantidade possível de informações, o que diminui significativamente o volume de dados manipulado durante a análise e torna seu desempenho excelente em termos de tempo de processamento. O algoritmo proposto para a classificação divide o áudio em quatro possíveis tipos: silêncio, fala, música e aplausos. Já o algoritmo de segmentação encontra as mudanças ignificativas de áudio, que são indícios de segmentos e mudanças de cena. Foram realizados testes com diferentes tipos de vídeos, e ambos os algoritmos mostraram bons resultados. / [en] With the growth of production and storing of digital media, audio segmentation and classification are becoming increasingly important. This work is based on characteristics of the MPEG standard, considered to be the standard for digital media storage and retrieval, to propose efficient algorithms to perform these tasks. While there are many studies based on video analysis, the audio information is still not widely used in an efficient way. The suggested algorithms for both tasks are based only on the scale factors present on layer 2 MPEG audio. That allows them to read the smallest amount of information possible, significantly diminishing the amount of data manipulated during the analysis and making their performance excellent in terms of processing time. The algorithm proposed for audio classification divides audio in four possible types: silent, speech, music and applause. The segmentation algorithm finds significant changes on the audio signal that represent clues of audio segments and scene changes. Tests were made with a wide range of types of video, and both algorithms show good results.

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