Undoubtedly, the cornerstone of the project is the exploration of possible improvements for convolutional neural networks. CNNs have been used for object recognition a million times, and having a specific genus of fungi as a subject is nothing special enough to warrant a research paper. However, they do present an interesting issue: they are similar enough to cause a standard CNN issue with identification. Worse still, there is an even bigger host of issues arising from sourcing data from open datasets, such as obscured images, bad positioning, incorrect labeling, and countless others.

Ailanthus Altissima, also known as the Tree of Heaven, is an invasive species that causes ecological damage by secreting toxic chemicals into the soil and competing with native species. Aside from ecological damages, it also serves as a host plant for numerous pests and insects, including the spotted lanternfly. The challenge posed by the Tree of Heaven necessitates efforts in management. Through this research study, the Tree of Heaven is monitored remotely using satellite images and machine learning.

In today’s world, a robotic surgeon manually manipulates the robot via a console using joystick-like controllers. However, such manual methods of control require the surgeon to spend a significant amount of time performing routine but important tasks, such as suturing or tissue cutting, thousands of times over the course of a single surgery. By automating these tasks, we can improve the accuracy and efficiency of the surgery while also allowing the surgeon more time to focus on the more complex surgical tasks at hand.

Growing up reading Isaac Asimov’s robot series, I always envisioned a future where mobile robots will run around helping humans. Of course, this has not happened, and I realized that there are many difficulties to achieving my dream future-cost, energy use, technical difficulties, etc. Although I did not have any significant experience with robotics, I have always been involved with maker technology, both through reading research and news articles and through making smaller-scale gadgets.

Cardiovascular disease (CVD) is responsible for an estimated 17.9 million annual deaths. Myocardial infarction (MI), a prominent symptom of CVD, occurs when reduced blood flow causes heart muscle death. Since permanent damage to the heart muscle begins within 30 minutes of blood flow restriction, MI is extremely dangerous and time sensitive. Electrocardiogram (ECG) is one of the most efficient methods for MI detection; however, it requires expertise to identify characteristic waveform features and it is also prone to interobserver bias.

When a person goes to check on a skin lesion or a runner wants to improve their form, a scanner is often used to track points on the body for measurements. Currently, there exists no solution that can instantaneously (in less than a second) compute the location of all these points at once. MiniMesh is a novel, resource-efficient algorithm that can accomplish this task on a small computer (like a phone or laptop) in real time from a single image.

Climate change is the greatest existential threat to humanity. Throughout high school, I have connected myself to a massive global movement of youth fighting to change this. Over the past four years, I have dedicated my time to pursuing policy solutions to environmental issues and spearheading climate education initiatives in my local community, as well as at the national and global levels. Through these projects, I’ve engaged with other inspiring activists and learned the importance of collaboration and leadership - especially among young people whose futures are most impacted by global warming.

As Vladimir Putin retains his strong grip on political power in Russia, growing networks of conservative actors in the United States have drawn together the potential political futures of both countries (Stoeckl and Uzlaner, eds. 2020). Since the mid 2010s, conservative support for Russia has increased, a trend which continued during the commencement of the Ukrainian invasion in February 2022 (Gallup, 2022). Despite the bipartisan condemnation of the invasion and the humanitarian concerns expressed by many on the political left, several vocal leaders on the Christian right continue to express support for Putin and his authoritarian regime, and as data has demonstrated, this has significantly impacted the favorability that Americans show for Russia, especially the conservative far-right (Perry, Samuel L.

Recall that the problem statement of my project is to quickly and autonomously navigate and map a burning building, identify trapped inhabitants, and send recovery/escape routes to firefighters as fast as possible. During my background investigation of this subject, I discovered that navigating fires has traditionally posed a challenge for robotic systems. Traditional LiDAR (Light based) sensors are often employed for SLAM (Simultaneous Localization and Mapping: A class of perception and mapping algorithms), but these sensors lose accuracy significantly in smoke.

Recall that the problem statement of my project is to quickly and autonomously navigate and map a burning building, identify trapped inhabitants, and send recovery/escape routes to firefighters as fast as possible. During my background investigation of this subject, I discovered that navigating fires has traditionally posed a challenge for robotic systems. Traditional LiDAR (Light based) sensors are often employed for SLAM (Simultaneous Localization and Mapping: A class of perception and mapping algorithms), but these sensors lose accuracy significantly in smoke.