Articles — Project / Lab Report

Reseña del Autor del premio Nobel

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.

En este informe se presenta detalladamente el desarrollo de la primera practica de laboratorio, en la cual encontramos la ley de ohm y sus aplicaciones en los circuitos en paralelo y en serie, teniendo en cuenta las normas de laboratorio para así lograr la correcta finalización de dicha guía.

DSA Project Report

The joining of ceramics with metals is widely used in aerospace engineering where high strength and excellent heat insulation materials are desired. In this paper, a new multifunctional bolted joint with load bearing-heat insulation integration is prepared with porous ZrO2/(ZrO2+Ni) sandwich ceramics. Double-shear behavior of the bolted joint connecting C/SiC plates is analyzed by ABAQUS codes. It is found that shearing damage occurs at shearing faces of the bolt, the shearing failure faces are layered rather than smooth. To improve its shearing strength, we introduce the shear band (ZrO2+V%Ni of thickness h) to its shearing faces. Results show that the shear band can improve the shearing strength and slow down the attenuation of load bearing capacity after reaching the shearing strength, without obviously increasing the thermal conductivity. An optimal structural design is performed and proper shear band is defined to balance the shearing strength and heat insulation performance of the ceramic joint.

This report is about Python and Django and can be useful for students for report submission.

Sleeper's Attendance is a paper describing a method to be used on a University's attendance system that can essentially bypass it and allow the attacker to register for all their classes. The paper also briefly describes about QR attendance systems in general and some ways to improve it.

Homework Durante este escrito veremos como son las diferencias de utilizar lex y programas normales con if, else tomando como referencia el tiempo que toma para poder transformar texto en tokens

The Contextual and Numerically Augmented QANet (CNAQANet) is a QA model that builds on NAQANet in order to improve performance on arithmetic reasoning in question and answering tasks. CNAQANet is specifically trained and tested on the DROP dataset.