Articles tagged Project / Lab Report
If you conduct a scientific experiment or undertake a piece of research, you’ll usually need to write up a corresponding project or lab report, to summarize the objective of your task, the methods you followed, the results you obtained, and the conclusions you drew from your work. Here we provide a sample of great templates for producing such reports, which include layout guidelines to help guide you through the process.
Recent
![Adaptive Learning Rate Clipping Stabilizes Learning](https://writelatex.s3.amazonaws.com/published_ver/10572.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T143214Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=35b780ab06315922c56d2163c0f764d8c4a6a8bdacca2d10463886371bb96e95)
Adaptive Learning Rate Clipping Stabilizes Learning
Adaptive learning rate clipping (ALRC) stabilizes learning by limiting backpropagated losses.
Jeffrey M. Ede, Richard Beanland
![A Regression based approach for link residual time prediction in MANETs](https://writelatex.s3.amazonaws.com/published_ver/8771.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T143214Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=c1c872c4d8167f44d91479914026ffeaa53c61d3e193696aa4fced7f9d15753e)
A Regression based approach for link residual time prediction in MANETs
Mobile ad-hoc network (MANET) is a collection of mobile
terminals forming an infrastructure less and quick deployable network,
which can communicate to each other via multiple hops or single hop.
Such ad-hoc networks have always been important for various applications like defence applications especially for countries like India having
boundaries and regions with large geographical diversity. Mobility attribute is a notable one in MANETs, as this leads to frequent topology
changes which are the primary cause of route failure. A route is an ordered set of links, hence for predicting future availability of any particular
route, it is important to estimate the availability of its currently available constituent links. This paper explores various link availability prediction model and proposes a least square polynomial regression-based
statistical approach to predict the availability of link. Proposed approach
assumes that movement of nodes are based on column mobility model i.e
each node in the network is linearly moving with constant speed. Each
node in the network periodically broadcasts hello packets to its neighbours to inform it’s availability in the network. Neighbour node receives
hello packet and uses its signal strength to estimate distance between
sender and receiver of hello packet. A monotonically decreasing signal
strength of hello packets at receiver node indicates that nodes are moving away from each other and link between them may break in future so
it starts link residual time prediction algorithm to predict the time when
the distance between them will exceed the pre-defined threshold value.
The proposed algorithm is simulated using NS 2.35. The performance
of the algorithm has been analyzed for identified parameters. The results are also been compared by simulating other existing link prediction
approaches based on interpolation.
Heman Pathak
![Measurement of the dynamic viscosity of Canola Oil using a ball drop](https://writelatex.s3.amazonaws.com/published_ver/8083.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T143214Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=db081072d5d0a19cfba9254ee30f52db82a0a2432e46f64e7212a80ab2af641f)
Measurement of the dynamic viscosity of Canola Oil using a ball drop
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.
Jamie Clark
![Informe práctica 1](https://writelatex.s3.amazonaws.com/published_ver/9924.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T143214Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=037de18324baec5feaa2ffb1a7a03b53736057e53dc2aeafa85a514465d3f72d)
Informe práctica 1
Informe 1
Luis Felipe Diaz, Felipe Guzman, Valentina Rivera
![Analysis of Material Properties under Bending Load](https://writelatex.s3.amazonaws.com/published_ver/3091.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T143214Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=4cee765aa8202824f72cdccd1c25258966977ef8bf0b93ebac4ca8fc32ddf7e8)
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
![Video Surveillance for Road Traffic Monitoring](https://writelatex.s3.amazonaws.com/published_ver/3090.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T143214Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=d0ba665487b53c4e71434847438ee28e679316413c4cda244b7a447e230c7245)
Video Surveillance for Road Traffic Monitoring
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
![Linear Multistep Methods](https://writelatex.s3.amazonaws.com/published_ver/1147.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T143214Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=a452d7b83f252b145772312296895604a77bbb35121975332acde47746822561)
Linear Multistep Methods
Part 3 project plan
Philip Osborne
![DSA Project Report](https://writelatex.s3.amazonaws.com/published_ver/8954.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T143214Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=d16f5671d6d583f105cc47e61ae7979591f931447fef06fef5e251f82c69a54f)
DSA Project Report
DSA Project Report
Javid
![Modèle linéaire à effets mixtes](https://writelatex.s3.amazonaws.com/published_ver/1680.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240630T143214Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240630/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=beaa5420af34a63d3cafae73c812d25910b5353ebe3e315b7993d3985ff484b3)
Modèle linéaire à effets mixtes
Le modèle linéaire mixte a été mis en oeuvre dès les années 1950, essentiellement dans le domaine de la génétique animale (réf. Henderson[1],[2]). Il n’a toutefois connu une utilisation plus générale qu’au cours des années 1990, en relation avec le développement de nouvelles procédures de calcul dans le cadre des logiciels statistiques. L’utilisation du modèle linéaire mixte soulève, par rapport aux modèles classiques d’analyse de la variance, un certain nombre de difficultés particulières, tant en ce qui concerne l’estimation des différents paramètres que la réalisation des tests d’hypothèses. Des informations peuvent être trouvées à ce sujet dans les articles de Littell [2002], McLean et al. [1991], et Piepho et al. [2003], et dans les livres de Demidenko [2004], McCulloch et Searle [2001],
Amin Elg