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Know the LaTeX command you want to use but can't remember how to write it? Here we present a great tips sheet produced by Dave Richeson; it's pre-loaded in Overleaf so you can see how the commands work instantly. Simply click on the button above to open a version in Overleaf for editing (and to quickly copy and paste the commands you need!). For more comments visit this page on Dave's site, or if you'd like to work through a fuller introduction to LaTeX why not check out our free online course?

Personal Rapid Transit (PRT) is an emerging urban transport mode. A PRT system operates much like a conventional hackney taxi system, except that the vehicles are driven by computer (no human driver) between stations in a dedicated network of guideways. The world's first two PRT systems began operating in 2010 and 2011. In both PRT and taxi systems, passengers request immediate service; they do not book ahead. Perfect information about future requests is therefore not available, but statistical information about future requests is available from historical data. If the system does not use this statistical information to position empty vehicles in anticipation of future requests, long passenger waiting times result, which makes the system less attractive to passengers, but using it gives rise to a difficult stochastic optimisation problem. This paper develops three lower bounds on achievable mean passenger waiting time, one based on queuing theory, one based on the static problem, in which it is assumed that perfect information is available, and one based on a Markov Decision Process model. An evaluation of these lower bounds, together with a practical heuristic developed previously, in simulation shows that these lower bounds can often be nearly attained, particularly when the fleet size is large. The results also show that low waiting times and high utilisation can be simultaneously obtained when the fleet size is large, which suggests important economies of scale.

A Russian poem demonstrating how to use Cyrillic fonts with UTF-8 encoding and the babel package.

Actualizacion plantilla tesis Universidad Tecnologica de Pereira

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.

Estudo bíblico baseado no livro: Contracultura Cristã de Jhon Stott.

Bluetooth is a short range communication protocol. Bluetooth-enabled devices can be detected using road-side equipment, and each detected device reports a unique identifier. These unique identifiers can be used to track vehicles through road networks over time. The focus of this paper is on reconstructing the paths of vehicles through a road network using Bluetooth detection data. A method is proposed that uses Hidden Markov Models, which are a well-known tool for statistical pattern recognition. The proposed method is evaluated on a mixture of real and synthetic Bluetooth data with GPS ground truth, and it outperforms a simple deterministic strategy by a large margin (30%-50%) in this case.

Simple template for approving software components.

This is the LaTeX template to Per Musi journal developed by Flávio Schiavoni and Thiago Campolina in June 2020 (pandemic times, yes I know).