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Pinterest Can Help Teachers Cook a Casserole, but What About LGBTQIA+ Affirming Lesson Plans for Students of Color?
Get PDFWe have learned to be crafty homemakers, small space decorators, and even teachers through the eye-catching appeal of sites like Pinterest or Teachers Pay Teachers (TPT). The accessibility and ease of searching for a preset lesson saves time, and in a society where teachers are paid far less than what they are worth and asked to work longer hours than they are paid for, this makes sense. Using the theoretical frameworks of CRT, QueerCrit, and CRP, along with the concepts of intersectionality, can build learning tools for new teachers to disrupt previous exclusionary practices that prevent LGBTQIA+ students of Color and all LGBTQIA+ students from being supported within school structures and curricula, creating spaces for traditionally marginalized students to be creators, and knowledge holders, in their community
EXTENDED PROGRAM NOTES FOR A VIOLA GRADUATE RECITAL
Get PDFMaría del Mar Añasco Mina, for the Master of Music degree in Performance, presented on April 10, 2025, at Southern Illinois University Carbondale.
TITLE: EXTENDED PROGRAMS NOTES FOR A VIOLA GRADUATE RECITAL MAJOR PROFESSOR: Dr. Rossana Cauti.
This research paper is an expanded version of the program notes for the author’s viola graduate recital on December 8, 2024, at the Old Baptist Foundation in Carbondale, Illinois. The paper includes two works originally written for the instrument and two adapted. With Dr. Rossana Cauti’s help, the author chose four works to prepare a viola graduate recital, including works from different countries and eras that challenge the performer’s technique and interpretation. The research paper will include each composer’s background, historical context, and analysis of the Prelude, Sarabande, and Gigue of the Suite No.3 in C Major for Cello Solo BWV 1009, by Johann Sebastian Bach (transcribed for viola), the Viola Sonata in B-flat Major Op. 36, written by Henri Vieuxtemps, the Concerto for Viola Sz. 120, BB by Béla Bartók, and the Danza Nocturna composed by Francisco Gonzáles Giraldo
A Low-Complexity Edge-based Object Detection Algorithm
No full textIn recent years, the development of the Back-Propagation Algorithm has led to the emergence of numerous object detectors, significantly advancing their visibility. State-of-the-art architectures now enable the learning and prediction of instance locations with remarkable accuracy. Most of these detectors rely on segmentation technologies to directly connect raw image pixels and object coordinates. However, approach tend to be computationally expensive. This study introduces Selection , a novel two-stage online training algorithm based on self-supervised learning and Convolutional Neural Networks (CNNs), which demonstrate substantial improvements in the efficiency of object detection compared to the conventional end-to-end regression structure using ground truth box coordinates. Selection establishes a bridge between Instance and Semantic Segmentation for the first time, overcoming mask training limitations imposed by contour polygons in instance box ground truth annotations. Without relying on an additional mask task branch, Selection leverages edge detection technology to extract object contour features directly from image representations. This approach effectively avoids distractions from unrelated tasks, such as confidence rate prediction, ensuring robustness during training while conserving computational resources. In addition, Selection employs a clustering concept to collaborate with edge feature locations of objects within proximity from neural network outputs. Furthermore, a highly parallel clustering algorithm, Pyramid, has been developed and embedded within the Selection framework. It accumulates contour features into a converged point pattern and generates valid instance centers based on corresponding density rates, without requiring additional online training. Compared to six existing clustering algorithms, Pyramid outperforms in both Average Precision (AP) and time efficiency. Unlike traditional methods, this approach not only offers greater flexibility but also makes the learning process more interpretable from a human perspective. The Selection framework along with the Pyramid clustering algorithm have been validated using the COCO dataset, achieving a 72.8% mean Average Precision on a random batch of 5,000 images while utilizing 44.3 million parameters. Compared to Faster R-CNN, Selection demonstrates a 1.3% improvement in AP and a 20% reduction in parameter count. These results strongly demonstrate the superior regression performance of Selection
The Sign of the Moon
No full textThis thesis is the first section of a planned historical novel. It takes place during 1627, 1657, and 1667 through 1669, in France and in territories now encompassed by New York State and the province of Quebec. The main events concern the first years in Canada of René-Robert Cavelier, le Sieur de la Salle, an explorer best known for traveling to the mouth of the Mississippi River. While the scenes are imagined, the story involves several historical figures as well as fictional characters. The action largely occurs within the ancestral, traditional and contemporary lands of First Nations including the Innu Nation; Anishnaabe peoples including the Odawa, Algonquin and Ojibwe Nations; and those of the Haudenosaunee Confederacy
Drawer Fever, Nine Personal Essays
No full textDrawer Fever is a collection of essays which explores experiences of immigration, living in Iranian diaspora, multilinguality, loss of identity and home, grief, friendship and love among other thing
Even in Death, Divided by Law: The Permanent Injustice of Cemetery Segregation in Southern Illinois and the Legacy of Isaac Burns, Local Civil War Veteran
Get PDFIn death, are we truly equal? A Cemetery in Pinckneyville, Illinois, bears silent witness to a relentless history that preserves a racial divide thought to be buried away. Hidden in the segregated section lies Isaac Burns, an African American Civil War veteran, separated from those buried with honor. His grave lies alongside those of other African Americans buried in an area marked not by the unity of service but by the nation\u27s refusal to see them as equals. Burn\u27s grave is a reminder that the legacy of his sacrifice, once given in the name of unity and freedom, is overshadowed by the dark history of segregation. This Article identifies an examines examples of continued segregation, present in cemeteries in Illinois and across the country, such as with Burns’ burial place. This Article also critiques the existing legislation addressing cemetery segregation and proposes new legislation for Illinois to address cemetery segregation most effectively. The goal of this proposed legislation is to explicitly prohibit and remedy cemetery segregation to ensure those like Burns do not continue to face the consequences of a country often willfully blind to its history of segregation
SPATIAL DISTRIBUTIONS AND OCCUPANCY DYNAMICS OF CARNIVORES IN A CENTRAL HARDWOOD FOREST
No full textExtirpation of apex predators, caused primarily by anthropogenic alterations to natural environments and persecution, has led to mesocarnivore release in these areas. Mesocarnivore release is an ecological phenomenon in which mesocarnivores thrive in the absence of apex predator dominance within the carnivore hierarchy. Mesopredators fill this dominant role on the landscape as de facto apex predators, however, this can lead to changes in inter-guild species space use, predator-prey dynamics, activity patterns, and interspecific competition. Understanding patterns in wildlife spatial distributions, which indicate variability in habitat space use across spatiotemporal scales, is critical for developing effective management and conservation plans and leads to a better understanding of ecological processes. I used 2 independent camera trap datasets gathered throughout 16,058 km2 of southern Illinois, USA: one collected between 2008 – 2010 across 357 camera clusters and the other collected between 2022 – 2024 across 409 camera clusters. Using multiple occupancy analysis techniques and kernel density estimation, I quantified the influences of habitat features and co-occurrence of competing species on the spatiotemporal dynamics of 6 mesocarnivore guild members: coyote (Canis latrans), bobcat (Lynx rufus), red fox (Vulpes vulpes), gray fox (Urocyon cinereoargenteus), striped skunk (Mephitis mephitis), and raccoon (Procyon lotor). Naïve occupancy (i.e., ndetected/nsurveyed) of gray fox declined from 0.20 to 0.06 between 2008 – 2010 and 2022 – 2024. Predicted occupancy ranged from 0.01 – 0.47 using the past dataset while the contemporary model had predicted occupancy ranging from 0.02 – 0.10, a 4-fold decline in occupancy estimates across 99% of my study extent. Most habitat features had different directional effects on gray fox occupancy between the 2 temporal periods, illustrating the complexity of gray fox habitat preferences and a shift in their ecology. Intra-specific activity overlap was high (range = 0.79 - 0.95) for my focal species between decades, however, activity patterns of striped skunk, raccoon, and domestic dogs were significantly different. Intraspecific diel niche also changed for gray fox, striped skunk, and raccoon. There were 6 interspecific activity patterns amongst focal species that had experienced a change in their significance between decadal periods. Native large-bodied carnivores had consistent different activity patterns with smaller-bodied carnivores and domestic dogs between decades. Larger-bodied carnivore species may be altering activity patterns of smaller-bodied members in areas experiencing one-sided-ness from mesopredator release, thereby decreasing competition and negative interspecific interactions. Coyotes and bobcats exhibited stability in occupancy dynamics at both narrow (coyote: γ = 0.89 ± 0.13, ε = 0.11 ± 0.07; bobcat: γ = 1 ± 0.01, ε = 0.00 ± 0.05) and broad temporal (coyote: γ = 0.96 ± 0.06, ε = 0.09 ± 0.03; bobcat: γ = 0.87 ± 0.14, ε = 0.31 ± 0.09) scales, supporting the idea of established priority effects. The extinction rates of smaller-bodied mesocarnivores, red fox (narrow: ε = 0.19 ± 0.40, broad: ε = 0.605 ± 0.11), gray fox (narrow: ε = 0.59 ± 0.16, broad: ε = 0.90 ± 0.04), and striped skunks (narrow: ε = 0.24 ± 0.13, broad: ε = 0.76 ± 0.06) dramatically increased and were higher than colonization rates, another indication that the establishment and persistence of these species is waylaid by extreme competitive exclusion from larger-bodied mesocarnivores. Furthermore, exurban environments are potentially increasing the complexity of these interactions, providing access to human subsidized resources. Co-occurrence models suggested that native and non-native co-occurrence increased with the presence of anthropogenic landscape features, increasing the chances of interspecific competition, persecution from humans, and potential disease transmission. Overall, my dissertation highlights the complex interactions that native and non-native species have across spatiotemporal scales, and the implications they can have on the subordinate species\u27 population persistence
LAYER-WISE PREDICTION OF OVERHANG-RELATED GEOMETRIC DEVIATION IN METAL ADDITIVE MANUFACTURING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS
No full textEnsuring dimensional precision in parts with complex overhangs is a significant concern in Metal Additive Manufacturing (MAM), as undetected geometric deviations can compromise functionality and reliability. This research introduces a Conditional Generative Adversarial Network (cGAN), specifically the Pix2Pix framework, to predict layer-wise geometric deviations in Laser Powder Bed Fusion (LPBF) printed parts with overhang geometries using paired 2D CAD slices and corresponding X-ray Computed Tomography (XCT) based ground truth images. A key innovation is using RGB color-coded CAD slices to encode overhang angle information, enhancing feature distinction and prediction accuracy compared to non-color-coded inputs. Eighteen Pix2Pix models were trained across three data groups and varying batch sizes, with performance evaluated using PSNR, SSIM, LPIPS, FID, and a novel Edge IoU metric for edge preservation. The results demonstrate that color-coded models achieve higher accuracy and training stability. A generalized model trained on a balanced dataset of seven overhang geometries also effectively predicted deviations in unseen designs. This framework aids early stage deviation prediction, guiding Design for Additive Manufacturing (DfAM) by reducing trial-and-error cycles, material waste, and support dependency
Using Machine Learning to Predict Maintenance Intentions of Septic System Owners
No full textThe scope of literature related to septic system maintenance from an educational and behavioral perspective, rather than a quantitative water quality approach, is limited. The water resources management community needs improved insight into the human factors related to septic system maintenance decisions and identification of effective intervention strategies. Using a modified Theory of Planned Behavior (TPB; Ajzen 1991) framework, the purpose of this study was to identify factors that predict homeowners’ intention to have their systems inspected and pumped within the next three years. As part of a small-scale educational program, a survey was sent to 1,374 homeowners with septic systems in Jackson and Matagorda counties, Texas. A Boruta feature-selection algorithm was applied under the structure of random forests classification to four models with the following variable domains: 1) demographic variables only, 2) septic system variables only, 3) past behavior variables only, and 4) perceptions of septic system maintenance (TPB) variables only. A fifth comprehensive model with all variables was also tested to compare the influence of all variables in a saturated model. Application of the machine-learning algorithm revealed that the most important factors predicting positive intentions of septic system maintenance were length of time since last inspection, inspection frequency, service contract enrollment, cost of annual maintenance, and the TPB attitude statement “I think maintaining my septic system is helpful for the environment.” Though less influential, septic system age and type were also reliable predictors of intentions to participate in septic system maintenance. This study provides new information for educational initiatives addressing the human dimensions of septic system management and could be a stepping-stone for future research to expand this approach to broader, generalizable studies and other water resource topics