Gallery — Project / Lab Report

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Accurate prognosis and prediction of a patient's current disease state is critical in an ICU. The use of vast amounts of digital medical information can help in predicting the best course of action for the diagnosis and treatment of patients. The proposed technique investigates the strength of using a combination of latent variable models (latent dirichlet allocation) and structured data to transform the information streams into potentially actionable knowledge. In this project, I use Apache Spark to predict mortality among ICU patients so that it can be used as an acuity surrogate to help physicians identify the patients in need of immediate care.

Gliding is an efficient and versatile way to traverse large distances whilst expending as little energy as possible. Work done in the field of biomimetic robotics has demonstrated further benefits to gliding in increasing trajectory control and reducing landing impact loads. A small-scale micro-glider was built to fit a specific design envelope with the objective of maximizing its glide range. A linear dynamics model was used to design and predict the gliding performance of the robot. Once manufactured, it achieved a glide distance of 1.8m and the performance was accurately captured by the dynamics model.

Modelo Relatório

Soctepmlate unofficial - SOČ = Středoškolská odborná činnost - Czech competition Author: Vojtěch Boček Edit by: Jaroslav Páral Source code: https://github.com/RoboticsBrno/soctemplate/ Base on: http://www.jcmm.cz/cz/sablona-soc.html License: CC BY 4.0

This paper is a report of an assignment of a course Computational Intelligence. The main goal of the assignment is to apply computational intelligence techniques in a practical setting - building a controller for a race car in The Open Racing Car Simulator (TORCS) using artificial neural network and evolving that network with evolutionary algorithm techniques. Keywords: computational intelligence, car controller, artificial neural network

Trabalho de Cálculo 4 - CEFET/MG

For an electron moving in a circular path in a magnetic field, if we know the magnetic field strength, accelerating voltage, and radius of the electron's trajectory, then we can make an estimation of the electron's charge to mass ratio. We calculated an average charge to mass ratio of \(2.08 \times 10^{11} \pm 1.81 \times 10^8\) Coulombs per kilogram.

As part of the NASA IMPACT program to model mechanical interactions with bodies in space such as comets, asteroids, and other Near Earth Objects (NEOs), the Colorado School of Mines team is designing a motor stage apparatus to interact with JSC-1A regolith simulant surfaces. This initial study involved development and testing of a prototype motor stage apparatus which was used to drive three types of probes into JSC-1A surfaces while collecting force data under standard Earth atmospheric conditions. The probes used were a conical-tipped probe, a wedge-tipped probe, and an anchoring probe. Main goals of the prototype system were to acquire general force trends for each interaction, and to isolate the most important design features for a more-complex in-vacuum system. Our data revealed force interactions that were very small in magnitude—on the order of tenths of Newtons—and more complex than our simple stiff beam probe and mount model could accurately predict. Our results lead us to recommend a more complex experimental model that can accurately represent deflection in the probes while also allowing for better measurement of regolith movement near the tip of the probes. Specifically, we recommend the following design features for the in-vacuum system: a load cell capable of measuring at very low ranges (thousandths of Newtons), reliability of structural axis alignment between trials, a robust mounting system that can accommodate each different type of probe, and consistency of sample preparation between trials.