Articles — Project / Lab Report

Time Domain Reflectometry DIT

Understanding dating behavior is intrinsically interesting and practically important for every individual in the society. People want to find someone who they want to share stories and emotions, understand and sympathize, commit the rest of life together. Accordingly, people spend a huge part of life finding "the one" or "soul-mate" who they believe potentially maximize their happiness and satisfaction in life. Ironically, they often end up breaking up and saying "He/She was not the right person". Researchers in many areas have studied dating behavior in varying ways to understand why people repeat the vicious circle and still get in there to find the right person. Here, we investigated dating behavior by analyzing relations between multi-aspect variables that include physical and psychological features of individuals and the probability of match in a speed-dating situation. We used theoretical approach and machine learning approach to investigate the pattern of dating behavior and to find the best predictor of match in dataing. For theory driven approach, we used multilevel linear model and multilevel logistic regression. For machine-learning approach, we used learning vector quantization and extreme gradient boosting.

This study aimed to determine the effects of climate change on forest fire trends in Canada by measuring correlations between weather conditions and the frequency and size of forest fires. Upon identifying the correlations, a model was created to understand future forest fire trends. The purpose of this study was to prevent the increasing trend of forest fires and devise solutions to reduce their damages. The data obtained from the Canadian National Fire Database underwent a linear regression and a machine learning algorithm to respectively predict and correlate weather conditions with future forest fire trends. It was concluded that temperature and wind speed experienced a positive correlation with forest fire frequency and size and precipitation experienced a negative correlation. To reduce the harmful effects of forest fires, cloud seeding can be used to create more precipitation and wind farms can be built to lower wind speed and attract lightning. However, more research and stricter policies directly targeting climate change are necessary for long term stability or decrease in forest fire trends.

In this work, we investigate the STO as a detector with in-plane geometry using field modulation Spin Torque ferromagnetic resonance (FM-STFMR), during which microwave signal is injected into the device and output response is measured in terms of RMS voltage across lock-in amplifier. The microwave signal injected externally to STO, efficiently synchronizes signal at two times the frequency of free oscillation of the nanomagnet (f0). The synchronization efficiently enhances signal sensitivity at 2f0 which opens other potential for development of spintronic devices. The effect of synchronization in STO under applied input RF power follows a consistent decrease in sensitivity with increasing power. Better synchronization at 2f0 is noticed above threshold current and shows good agreement with the results of numerical simulations.

En el siguiente informe se muestran los datos obtenidos en el laboratorio numero 1 de circuitos y dispositivos, el cual se basa en circuitos en serie y paralelo, y cuales son sus voltajes corrientes y potencias.

Objetivos: Estudo do movimento oscilatório, oscilações livres não amortecidas e amortecidas, e oscilações forçadas e amortecidas.

A nice report I did for my Radiative Processes Course.

In this paper, we measure the memory performance throughout the Phoronix test "RAMspeed SMP". We decide to test this specific benchmark because we know how important is the memory for the system performance. This document shows how much the memory performance could change if we modify some variables in the linux kernel.

A report created with the Project Report template at howtotex.com.