Hazel Larsen Archer and Photography at Black Mountain College, 1933 - 1957

Senior Project submitted to The Division of Arts of Bard College

Bone Density Following Three Years of Recovery from Long-Duration Space Flight

It is well recognized that bone mineral density [BMD] at load-bearing sites of the hip and spine sustain significant loss during space flight, estimated at approximately 0.5-1.0% per month. However, the long-term effects on bone health following return from long-duration space flight remain unclear. It is unknown whether BMD for men recovers beyond 1 year following return from space to what would be predicted or if deficits persist. Using our previously created prediction models, we compared the observed BMD of male US crew following 3 years since returning from longduration space flight with what would be predicted if they had not been exposed to microgravity

Does Short Duration Space Flight have a Negative Effect on Bone Density?

No abstract availabl

Utilising Deep Learning techniques for effective zero-day attack detection

Machine Learning (ML) and Deep Learning (DL) have been used for building Intrusion Detection Systems (IDS). The increase in both the number and sheer variety of new cyber-attacks poses a tremendous challenge for IDS solutions that rely on a database of historical attack signatures. Therefore, the industrial pull for robust IDS capable of flagging zero-day attacks is growing. Current outlier-based zero-day detection research suffers from high false-negative rates, thus limiting their practical use and performance. This paper proposes an autoencoder implementation to detect zero-day attacks. The aim is to build an IDS model with high recall while keeping the miss rate (false-negatives) to an acceptable minimum. Two well-known IDS datasets are used for evaluation—CICIDS2017 and NSL-KDD. To demonstrate the efficacy of our model, we compare its results against a One-Class Support Vector Machine (SVM). The manuscript highlights the performance of a One-Class SVM when zero-day attacks are distinctive from normal behaviour. The proposed model benefits greatly from autoencoders encoding-decoding capabilities. The results show that autoencoders are well-suited at detecting complex zero-day attacks. The results demonstrate a zero-day detection accuracy of [89% - 99%] for the NSL-KDD dataset and [75% - 98%] for the CICIDS2017 dataset. Finally, the paper outlines the observed trade-off between recall and fallout

Bone Density Following Long Duration Space Flight and Recovery

At approx.12 months, Bone Mineral Density (BMD) at most sites in men remained lower than would be predicted, raising concerns for long-term bone health consequences following space flight. Additional analyses based on longer follow-up are being conducted. Although the N is too small for definitive conclusions, women had lower rates of loss at load-bearing sites of the hip and spine immediately post-flight relative to men and smaller differences between observed vs. predicted BMD at most sites, both immediately and 12 months post-flight, relative to men. The role of other exposures/risk factors need to be explored to further understand these possible gender differences in BMD loss and recovery following long-duration space flight

Distortion correction of two-component - two-dimensional PIV using a large imaging sensor with application to measurements of a turbulent boundary layer flow at Reτ=2386Re_{\tau} = 2386

In the past decade, advances in electronics technology have made larger imaging sensors available to the experimental fluid mechanics community. These advancements have enabled the measurement of 2-component 2-dimensional (2C-2D) velocity fields using particle image velocimetry (PIV) with much higher spatial resolution than previously possible. However, due to the large size of the sensor, the lens distortion needs to be taken into account as it will now have a more significant effect on the measurement quality that must be corrected to ensure accurate high-fidelity 2C-2D velocity field measurements. In this paper, two dewarping models, a second-order rational function (R2) and a bicubic polynomial (P3) are investigated with regards to 2C-2D PIV measurements of a turbulent boundary layer (TBL) using a large imaging sensor. Two approaches are considered and compared: (i) dewarping the images prior to the PIV cross-correlation analysis and (ii) undertaking the PIV cross-correlation analysis using the original recorded distorted images then followed by using the mapping functions derived for image dewarping to provide the correct spatial location of the velocity measurement point. The results demonstrate that the use of P3 dewarping model to correct lens distortion yields better results than the R2 dewarping model. Furthermore, both approaches for the P3 dewarping model yield results which are statistically indistinguishable