National University of Computer and Emerging Sciences

About: National University of Computer and Emerging Sciences is a education organization based out in Islamabad, Pakistan. It is known for research contribution in the topics: Computer science & The Internet. The organization has 1506 authors who have published 2438 publications receiving 26786 citations.

Gravitational Dust Collapse in f (R) Gravity

Abstract: This paper is devoted to investigate gravitational collapse of dust in metric f(R) gravity We take FRW metric for the interior region while the Schwarzchild spacetime is considered for the exterior region of a star The junction conditions have been derived to match interior and exterior spacetimes The assumption of constant scalar curvature is used to find a solution of field equations Gravitational mass is found by using the junction conditions It is concluded that the constant curvature term f(R 0) plays the role of the cosmological constant involved in the field equations of general relativity

Stellar hydrostatic equilibrium compact structures in f(,T) gravity

Abstract: In this paper, stellar hydrostatic equilibrium configuration of the compact stars (neutron stars and strange stars) has been studied for f(𝒢,T) gravity model, with 𝒢 and T being the Gauss–Bonnet invariant and the trace of energy–momentum tensor, respectively. After deriving the hydrostatic equilibrium equations for f(𝒢,T) gravity, the fluid pressure for the neutron stars and the strange stars has been computed by implying two equation of state models corresponding to two different compact stars. For the f(𝒢,T) = α𝒢n + λT gravity model, with α, n, and λ being some specific parameters, substantial change in the behavior of the physical attributes of the compact stars like the energy density, pressure, stellar mass, and total radius has been noted with the corresponding change in λ values. Meanwhile, it has been shown that for some fixed central energy density and with increasing values of λ, the stellar mass both for the neutron stars and the strange stars increases, while the total stellar radius R exhibit...

Subspace Gaussian Mixture Model for Continuous Urdu Speech Recognition using Kaldi

Abstract: Automatic Speech Recognition Systems (ASR) have significantly improved in recent years, where deep learning is playing an important role in the development of end to end ASR's ASR is the task of converting spoken language into computer readable text ASRs are becoming ever more prevalent way to interact with technology, thereby significantly closing the gap in terms of how humans interact with computers, making it more natural Urdu is an under resourced language, for which training such a system requires a huge amount of data that is not readily available In this paper we present improvements to the architecture of a statistical automatic speech recognition system for which the components involved in a statistical ASR have been explored in great detail We also present the results on various statistical models that are trained for Urdu language We choose the Kaldi toolkit for training the Urdu ASR using approximately 100 hours of transcribed data The refined Subspace Gaussian Model gives a word error rate of 9% on the test set

A Survey on the Noncooperative Environment in Smart Nodes-Based Ad Hoc Networks: Motivations and Solutions

Abstract: In ad hoc networks, the communication is usually made through multiple hops by establishing an environment of cooperation and coordination among self-operated nodes. Such nodes typically operate with a set of finite and scarce energy, processing, bandwidth, and storage resources. Due to the cooperative environment in such networks, nodes may consume additional resources by giving relaying services to other nodes. This aspect in such networks coined the situation of noncooperative behavior by some or all the nodes. Moreover, nodes sometimes do not cooperate with others due to their social likeness or their mobility. Noncooperative or selfish nodes can last for a longer time by preserving their resources for their own operations. However, such nodes can degrade the network's overall performance in terms of lower data gathering and information exchange rates, unbalanced work distribution, and higher end-to-end delays. This work surveys the main roots for motivating nodes to adapt selfish behavior and the solutions for handling such nodes. Different schemes are introduced to handle selfish nodes in wireless ad hoc networks. Various types of routing techniques have been introduced to target different types of ad hoc networks having support for keeping misbehaving or selfish nodes. The major solutions for such scenarios can be trust-, punishment-, and stimulation-based mechanisms. Some key protocols are simulated and analyzed for getting their performance metrics to compare their effectiveness.

Optimizing the Signal to Noise Ratio of Microcavity Sensors

Abstract: Optical microcavities provide a sensitive platform for biological and chemical sensing applications. Previous works have focused on optimizing the device performance by increasing the quality factor of the cavity. However, this approach overlooks the impact of the quality factor on the signal-to-noise ratio (SNR) of the sensor. Here, our purpose is to show the existence of optimum parameters, both theoretically and experimentally, for achieving maximum SNR in the microcavity sensors. Although toroidal cavities are used here, this letter is easily generalizable to any cavity geometry, enabling the performance optimization of a wide range of microcavity sensors.