Illinois Mathematics and Science Academy
Illinois Mathematics and Science Academy: DigitalCommons@IMSANot a member yet
9795 research outputs found
Sort by
Closed-Loop Deep Brain Stimulation Based on a Dual Machine Learning System Analyzing Brain Functional Networks
No full textNeurodegeneration impairs memory, with treatments mainly addressing symptoms, not underlying dysfunction. Deep brain stimulation (DBS) shows promise by directly modulating memory. This study hypothesizes that DBS improves memory when targeted towards poor encoding states by influencing semantic organization. Data from 38 epilepsy patients with implanted electrodes were analyzed and it was discovered that LTC stimulation improved semantic organization during free recall, a critical factor for overall memory accuracy. LTC stimulation had a 27.54% success rate, higher than other memory-related regions (e.g. hippocampus, medial temporal lobe).
Next, 38 patient-specific convolutional neural network (CNN) models were trained using various brain functional networks including envelope correlation and directed phase lag index during the first 200 milliseconds of memory encoding. These models identified states of poor memory encoding, achieving an AUC of 72 ± 13%. Connecting these model outputs with logistic regression, LTC stimulation during poor-memory encoding states achieved an AUC of 89%, outperforming the 57%–67% scores in other areas.
These findings support the potential of a dual-system machine learning approach targeting the LTC to improve memory
Evaluating LLM Arithmetic Capabilities Using External Tools
No full textThe rapid advancements of Large Language Models (LLMs) have allowed a significant enhancement in natural language processing, allowing human-like text generation to be coupled with a similar level of reasoning. Although LLMs have shown success in various fields, they remain largely inconsistent in their arithmetic accuracy. This study aims to benchmark LLMs on their strengths, limitations, and overall practical implication in regards to using their arithmetic capabilities in realistic tasks. By forming a benchmark to evaluate LLM-generated answers against human evaluations, we assess their numerical reasoning abilities and problem- solving effectiveness on a variety of levels with a variety of situations. Our methodology involves literature review, analysis of existing benchmarks and an iterative process of developing a new evaluation framework to assess various LLMs, including ones commonly used by the public and even developing ones in order to fully grasp the status quo for LLM performance in arithmetic. Additionally, we explore the integration of external tools to enhance LLMs’ arithmetic accuracy to help refine LLM benchmarking standards and serve as a recommendation for their utilization in larger, scientific and technical workflows
Effect of Somatic Growth on Fontan Conduits
No full textSingle ventricular defects are a type of congenital heart disease that can be treated through the Fontan Procedure, where a conduit is implanted connecting the inferior vena cava to the pulmonary artery (PA). Native vasculature grows over time, whereas the synthetic conduit does not. This study focused on growth of the PA over time, resulting in conduit shape and hemodynamic changes. Five patients were analyzed at two timepoints spanning a range of one to four years, all of which had 18-20 mm Fontan conduits. Each timepoint’s desired Fontan route was created into a 3D model through a process called segmentation using MRI scans in Scan IP software. Abaqus CAE software was utilized to simulate exercise pressure conditions and investigate changes in structure. Finally, growth mapping was performed and shape index and curvedness values were found using MATLAB software. Results demonstrated inconsistent growth patterns, meaning growth is likely not enough to explain anterior shifts in the Fontan route. Next steps include obtaining Computational Fluid Dynamics data on XFlow software for a thorough analysis on hemodynamic state. In the future, this research can inform patient-specific conduit placement and size to achieve ideal hemodynamics, thus enhancing the Fontan Procedure to improve patient outcomes
Applications of Machine Learning in Identification and Prediction of Muscle Atrophy using EMG signals
No full textMachine learning (ML) has significantly enhanced EMG signal processing, which has eased neuromuscular diagnosis and movement analysis. Previous studies focused on developing a variety of different ML models like Bayesian Techniques, Artificial Neural Networks, and Recurrent Neural Networks without a standardized way of comparing. Our work aims to contrast the performance between supervised, unsupervised, and neural network models in a standardized environment to accurately compare their effectiveness. Musculoskeletal and surface-EMG (sEMG) measurements were collected for four daily activities that measured gesture, movement, posture, and activity recognition. The signals were analyzed to estimatevarious parameters like FFT, Average, and RMS. The data along with participant demographic information such as age, gender, and self-reported physical activity level were used to train the model. The processed data served as the input to a Random Forest Classifier with 100 trees, a Support Vector Model with a linear kernel, and an Artificial Neural Network Model with a 64- neuron input unit, 32-neuron hidden unit, and 1 output, all using the sklearn library, and tested using the remaining 20% of the data. The Random Forest Classifier predicted the progression of the disease 3.9% more effectively than the ANN and 9.4% more effectively than the SVM
Learning from Hank\u27s Mistakes in Science Class
Get PDFIn this interactive presentation, we showcase a fictitious student named Hank and his group overcoming chemistry misconceptions through engaging daily bellringers. These scenarios prompt open discussions among students, encouraging self-awareness and reinforcing expected learning behaviors. These bellringers also help with AP preparation and integrate NGSS science practices in an entertaining and non-threatening way. Participants will participate in conversations to develop scenario-writing skills for various subject
Understanding the European Union: Why You Don’t Teach it But Should
Get PDFBorder crisis, currency crisis, populism, culture wars, real war? No, that is the European Union (EU). This session will introduce the basic history and functional elements of the EU\u27s intent, structure, and function (dysfunction?). Based on work and travel with the Center for EU Studies, attendees will get everything they need to teach the topic
2025 MLK Celebration
Get PDFOvercoming Alienation and Empowering Our Voices
Presented by Brotherhood-Sister Circle (BHSC)
Black National Anthem “Lift Every Voice and Sing” by James Weldon Johnson, Performed by IMSA Choirhttps://digitalcommons.imsa.edu/mlk_celebration/1011/thumbnail.jp
