In this study, three models are used to test the hypothesis that data-centric artificial intelligence (AI) will improve the performance of machine learning.
Read More...Comparing model-centric and data-centric approaches to determine the efficiency of data-centric AI
In this study, three models are used to test the hypothesis that data-centric artificial intelligence (AI) will improve the performance of machine learning.
Read More...Statistical evaluation of the effects of surface processing on aerospace fastener tested strength
In the aerospace industry, various surface processing or coatings are widely used. However, no detailed research on the aerospace fastener tensile and double shear strength variation due to surface processing has been conducted. Thus, the purpose of this study was to systematically evaluate the effect of surface processing on the standard aerospace fastener's tensile and shear properties.
Read More...Blockchain databases: Encrypted for efficient and secure NoSQL key-store
Although commonly associated with cryptocurrency, blockchains offer security that other databases could benefit from. These student authors tested a blockchain database framework, and by tracking runtime of four independent variables, they prove this framework is feasible for application.
Read More...Developing a wearable, skin-based triboelectric nanogenerator
The authors designed a system that runs off of body heat to track body temperature that could help prevent injuries that result from elevated body temperature.
Read More...Comparing the performance of lateral control algorithms on long rigid vehicles in urban environments
Here, seeking to better understand the control algorithms used in autonomous vehicles, the authors compared the Stanley and pure pursuit control algorithms along with a new version of each. Unexpectedly, they found that no control algorithm offered optimal performance, but rather resulted in tradeoffs between the various ideal results.
Read More...Differential privacy in machine learning for traffic forecasting
In this paper, we measured the privacy budgets and utilities of different differentially private mechanisms combined with different machine learning models that forecast traffic congestion at future timestamps. We expected the ANNs combined with the Staircase mechanism to perform the best with every value in the privacy budget range, especially with the medium high values of the privacy budget. In this study, we used the Autoregressive Integrated Moving Average (ARIMA) and neural network models to forecast and then added differentially private Laplacian, Gaussian, and Staircase noise to our datasets. We tested two real traffic congestion datasets, experimented with the different models, and examined their utility for different privacy budgets. We found that a favorable combination for this application was neural networks with the Staircase mechanism. Our findings identify the optimal models when dealing with tricky time series forecasting and can be used in non-traffic applications like disease tracking and population growth.
Read More...The effects of food type on mediator-less microbial fuel cell electricity output
The authors look at how different food types impact the ability of bacteria to produce electricity.
Read More...An efficient approach to automated geometry diagram parsing
Here, beginning from an initial interest in the possibility to use a computer to automatically solve a geometry diagram parser, the authors developed their own Fast Geometry Diagram Parser (FastGDP) that uses clustering and corner information. They compared their own methods to a more widely available, method, GeoSolver, finding their own to be an order of magnitude faster in most cases that they considered.
Read More...Utilizing the Magnus effect to produce more downforce than a standard wing
Here, seeking a better solution to produce downforce that keeps a vehicle grounded at high speeds than wings which tend to result in degraded car performance due to increased air resistance, the authors considered using the Magnus effect as a replacement. The authors found that a spinning cylinder generated significantly more downforce through the Magnus effect than a standard wing at all wind speeds as simulated through the use of a leaf blower. They suggest that a cylinder could be a potential replacement for a wing when downforce is a priority.
Read More...Design and implementation of a cryptographically secure electronic voting infrastructure
In this study, the authors present proposed cryptographic controls for election sites with the hypothesis that this will mitigate risk and remediate vulnerabilities.
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