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Sincronización en un modelo de actividad neuronal basado en mapas caóticos sometidos a perturbaciones
Sincronización en un modelo de actividad neuronal basado en mapas caóticos sometidos a perturbaciones
Se busco la posibilidad de desincronizar una red de mapas acoplados mediante la aplicacion de una perturbacion externa.
Claudio Santiago Condor Diestra
Dissertation CSS
Dissertation CSS
Excerpt from main dissertation
Michelle Baltazar
On the link between finite difference and derivative of polynomials
On the link between finite difference and derivative of polynomials
The main aim of this paper to establish the relations between forward, backward and central finite (divided) differences (that is discrete analog of the derivative) and partial & ordinary high-order derivatives of the polynomials.
Kolosov Petro
Analysis of Material Properties under Bending Load
Analysis of Material Properties under Bending Load
In this experiment, we attempt to better understand how materials properties are tested. We tested a number of simple beams of different materials under a stress. The bending of the materials allowed for us to calculate the Poisson's Ratio and elastic moduli for each material. From this, we were able to not only compare materials but also methods of measuring elasticity. Despite some error in our results, which can be explained by the scale of our measurements in relation to the stiffness of certain materials, we find both strain gauges and equations of cantilever to be appropriate measurement techniques for measuring the elastic modulus of simple beams.
Stephen Yonke
NTI 9-12
NTI 9-12
HW4
Marshal
BIO 230 Probability Theory and Applications HW I
BIO 230 Probability Theory and Applications HW I
This is only a homework draft
Lana N A
A Religião do Cristão
A Religião do Cristão
Estudo bíblico baseado no livro: Contracultura Cristã de Jhon Stott.
Egmon Pereira
Trabalho Prático Computação Móvel
Trabalho Prático Computação Móvel
O trabalho descreve um simples aplicativo desenvolvido em para sistema android studio
Mateus Santos
Evolving robots to play dodgeball
Evolving robots to play dodgeball
In nearly all videogames, creating smart and complex artificial agents helps ensure an enjoyable and challenging player experience. Using a dodgeball-inspired simulation, we attempt to train a population of robots to develop effective individual strategies against hard-coded opponents. Every evolving robot is controlled by a feedforward artificial neural network, and has a fitness function based on its hits and deaths. We evolved the robots using both standard and real-time NEAT against several teams. We hypothesized that interesting strategies would develop using both evolutionary algorithms, and fitness would increase in each trial. Initial experiments using rtNEAT did not increase fitness substantially, and after several thousand time steps the robots still exhibited mostly random movement. One exception was a defensive strategy against randomly moving enemies where individuals would specifically avoid the area near the center line. Subsequent experiments using the NEAT algorithm were more successful both visually and quantitatively: average fitness improved, and complex tactics appeared to develop in some trials, such as hiding behind the obstacle. Further research could improve our rtNEAT algorithm to match the relative effectiveness of NEAT, or use competitive coevolution to remove the need for hard-coded opponents.
Daniel and Uriel