Chandigarh University

About: Chandigarh University is a education organization based out in Mohali, India. It is known for research contribution in the topics: Materials science & Computer science. The organization has 1358 authors who have published 2104 publications receiving 10050 citations.

Predictive Urban Traffic Flow Model using Vehicular Big Data

Abstract: Objectives: Intelligent Transportation System (ITS) is raising the interests of the research community in the field of communication. The main objectives of this work are to implement ITS scenario and evaluate the Traffic Density Estimation for different cities for checking the density of vehicles on the different roads and perform a comparative evaluation of traffic densities in the different number of city based scenarios and to increase the accuracy of the density prediction technique for ITS. Method/Statistical Analysis: In this manner, an advanced density prediction technique has been proposed for the prediction of density on the road. The proposed technique is based on the number of vehicles on the road, in which vehicle on the map of the three cities at a particular instance of time has been estimated. After estimating the density of vehicle, prediction of that density has been done which shows that there is a maximum density on the lane and in future density on the road has been predicted. Finding: A range of values has been generated with the help of a dedicated simulation scenario using SUMO simulator. The computed values have been used for estimating the density of vehicles in Chandigarh, Delhi and Kolkata based on road side scenarios using Poisson distribution for randomly generated of vehicles and the obtained values has been evaluated to compare the densities of vehicles for these three cities. Improvement: When we are talking about traffic, then the term comes in our mind is congestion. To avoid that congestion on the roads, we use the Poisson distribution in which vehicle generates after every instance of time. With the help of this distribution, the amount of congestion on the roads can be decreased and this technique is very effective on the hurdle like jam.

Targeting COPD with PLGA-Based Nanoparticles: Current Status and Prospects

Abstract: Chronic obstructive pulmonary disease (COPD) is pulmonary emphysema characterized by blockage in the airflow resulting in the long-term breathing problem, hence a major cause of mortality worldwide. Excessive generation of free radicals and the development of chronic inflammation are the major two episodes underlying the pathogenesis of COPD. Currently used drugs targeting these episodes including anti-inflammatory, antioxidants, and corticosteroids are unsafe, require high doses, and pose serious side effects. Nanomaterial-conjugated drugs have shown promising therapeutic potential against different respiratory diseases as they are required in small quantities which lower overall treatment costs and can be effectively targeted to diseased tissue microenvironment hence having minimal side effects. Poly lactic-co-glycolic acid (PLGA) nanoparticles (NPs) are safe as their breakdown products are easily metabolized in the body. Drugs loaded on the PLGA NPs have been shown to be promising agents as anticancer, antimicrobial, antioxidants, and anti-inflammatory. Surface modification of PLGA NPs can further improve their mechanical properties, drug loading potential, and pharmacological activities. In the present review, we have presented a brief insight into the pathophysiological mechanism underlying COPD and highlighted the role, potential, and current status of PLGA NPs loaded with drugs in the therapy of COPD.