The viscosity of a particular fluid is an interesting parameter that plays an important role in fluid dynamics of that fluid. We chose the common household cooking item canola oil. Using a ball drop, we set out to measure viscosity at various temperatures and create a model for the viscosity of canola oil as a function of temperature, as well as an accurate measurement for viscosity at room temperature. It was found that the viscosity between 0 and 40 degrees Celsius can be approximated using an exponential function and that an estimation for viscosity at room temperature was not very difficult to obtain. The precision of this measurement was limited by uncertainty in lab equipment used to measure various quantities as well as the image analysis software we used and the limited frame-rate of our camera.
Computer vision systems can be applied to a wide variety of tasks, but some of the most interesting are those related with security and surveillance. Within this group, our application for Video Surveillance for Road Traffic Monitoring can be placed. We propose a solution based on machine learning and video analysis techniques that involves the whole process: database evaluation, background estimation, foreground segmentation, video stabilization and object tracking. As a result of this, our system will be able to monitorize some basic parameters of traffic flow as vehicles counting or speed estimation.
C. Carmona, A. Flores, A. Hernández, A. Imbernon, A. Mosella
El barómetro es un instrumento de medición atmosérica, específicamente utilizado en la determinación de la fuerza por unidad de superficie ejercida por el peso de la atmósfera. Existe un gran número de equipos atmoféricos con distintos tipos de estos aparátos y son diariamente utilizados ya que la presión atmosférica juega un papel importante en la determinación y pronóstico del tiempo así como en el área de investigación al momento de realizarse experimentos ya que pueden llegar a afectar o hacer variar el funcionamiento de muchos aparatos electrónicos y mecánicos.
In this document we focus on modifying the Linux Kernel through memory and scheduler parameters. The main objective is to study the performance of a computer during the execution of AIO-Stress Benchmark. It was necessary to run the test several times since three of the parameter mentioned in this project were modified 5 times. After completing the test, the results were displayed on graphs, showing that all the variables have a noticeable influence on the performance of the computer.
Quantum Dots are semiconductor nanocrystals whose diameter is in the range of 2-10 nm, corre- sponding to 10 to 50 atoms in diameter and a total of 100 to 100,000 atoms within the quantum dot volume. Many types of quantum dot emit light of specific frequencies if electricity or light is applied to them, and these frequencies can be precisely tuned by changing the dots’ size, shape and material, giving rise to many applica- tions. Because of their high tunable properties, quantum dots are of wide interest. It finds its applications in nanotechnology, medical imaging, transistors, solar cells, LED’s, diode lasers, quantum computing, etc. With this project, we intend to further understand and study the properties of quantum dots by using atomic force microscopy.
Cet article étudie deux méthodes utilisées dans le cadre du transport humanitaire en cas de crise (désastre, épidémie...). Le Covering Tour Problem se focalise sur l'équité de distribution des vivres, alors que le Capacitated Vehicle Routing Problem se concentre sur l'urgence de la distribution. Nous proposons une nouvelle approche mélangeant ces deux approches pour former une solution à la fois équitable et rapide. Ce article a été rédigé dans le cadre du TER 2014-2015.
Dimitry Berardi, Abdelwahab Heba, Boris Terooatea, Maël Valais
Although the analysis of data is a task that has gained the interest of the statistical community in recent years and whose familiarity with the statistical computing environment, they encourage the current statistical community (to students and teachers of the area) to complete statistical analysis reproducible by means of the tool R. However for years there has been a gap between the calculation of matrices on a large scale and the term "big data", in this work the Normalized Cut algorithm for images is applied. Despite the expected, the R environment to do image analysis is poorly, in comparison with other computing platforms such as the Python language or with specialized software such as OpenCV.
Being well known the absence of such function, in this work we share an implementation of the Normalized Cut algorithm in the R environment with extensions to programs and processes performed in C ++, to provide the user with a friendly interface in R to segment images. The article concludes by evaluating the current implementation and looking for ways to generalize the implementation for a large scale context and reuse the developed code.
Key words: Normaliced Cut, image segmentation, Lanczos algorithm, eigenvalues and eigenvectors, graphs, similarity matrix, R (the statistical computing environment), open source, large scale and big data.