The power of neural nets

Implementation of the Hopfield net which is used in the image processing type of applications where only partial information about the image may be available is discussed. The image classification type of algorithm of Hopfield and other learning algorithms, such as the Boltzmann machine and the back-propagation training algorithm, have many vital applications in space

COVID-19 and Campus Life: Student Perspectives

The COVID-19 pandemic has caused unprecedented changes to campus life as students have adjusted to the hybrid class model and physical distancing framework. Simply residing on campus this semester has been a privilege; many Spiders, especially international students and students with pre-existing health conditions, could not come at all. Among students on campus, there are varying attitudes about how this semester of “Protecting Our Web” has gone. To document this historic semester, I interviewed three students in mid- October: Colin Sparkevicius, a senior from Pennsylvania majoring in business administration Tereza Hernandez, a sophomore from Virginia majoring in global studies Karthik Lalwani, a first-year student from North Carolina majoring in chemistr

Letter From the Editor

Letter form the Editor-in-Chief, Ryan Shah

ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewing

Given the rapid ascent of large language models (LLMs), we study the question: (How) can large language models help in reviewing of scientific papers or proposals? We first conduct some pilot studies where we find that (i) GPT-4 outperforms other LLMs (Bard, Vicuna, Koala, Alpaca, LLaMa, Dolly, OpenAssistant, StableLM), and (ii) prompting with a specific question (e.g., to identify errors) outperforms prompting to simply write a review. With these insights, we study the use of LLMs (specifically, GPT-4) for three tasks: 1. Identifying errors: We construct 13 short computer science papers each with a deliberately inserted error, and ask the LLM to check for the correctness of these papers. We observe that the LLM finds errors in 7 of them, spanning both mathematical and conceptual errors. 2. Verifying checklists: We task the LLM to verify 16 closed-ended checklist questions in the respective sections of 15 NeurIPS 2022 papers. We find that across 119 {checklist question, paper} pairs, the LLM had an 86.6% accuracy. 3. Choosing the "better" paper: We generate 10 pairs of abstracts, deliberately designing each pair in such a way that one abstract was clearly superior than the other. The LLM, however, struggled to discern these relatively straightforward distinctions accurately, committing errors in its evaluations for 6 out of the 10 pairs. Based on these experiments, we think that LLMs have a promising use as reviewing assistants for specific reviewing tasks, but not (yet) for complete evaluations of papers or proposals

Design of equipment for lunar dust removal

NASA has a long range goal of constructing a fully equipped, manned lunar base on the near side of the moon by the year 2015. During the Apollo Missions, lunar dust coated and fouled equipment surfaces and mechanisms exposed to the lunar environment. In addition, the atmosphere and internal surfaces of the lunar excursion module were contaminated by lunar dust which was brought in on articles passed through the airlock. Consequently, the need exists for device or appliance to remove lunar dust from surfaces of material objects used outside of the proposed lunar habitat. Additionally, several concepts were investigated for preventing the accumulation of lunar dust on mechanisms and finished surfaces. The character of the dust and the lunar environment present unique challenges for the removal of contamination from exposed surfaces. In addition to a study of lunar dust adhesion properties, the project examines the use of various energy domains for removing the dust from exposed surfaces. Also, prevention alternatives are examined for systems exposed to lunar dust. A concept utilizing a pressurized gas is presented for dust removal outside of an atmospherically controlled environment. The concept consists of a small astronaut/robotic compatible device which removes dust from contaminated surfaces by a small burst of gas