Comparative Analysis of Aerodynamic Characteristics of F16 and F22 Combat Aircraft using Computational Fluid Dynamics

This paper presents the computational investigation of air flow over an aircraft at realistic speeds while demonstrating the importance of extending the existing analysis to the complete airplane and how pivotal it is in improving its in-flight performance. The study is done for F16 and F22 aircraft using ANSYS Fluent (19.2) to obtain pressure distribution, shear stress distribution and temperature variation on the complete surface of the aircraft. Since the front section of the aircraft is prone to direct initial impact of surrounding environment, this portion is also examined. Here, as the speed is doubled from Mach 1 to Mach 2, a rise in the value of all the three variables is noticed for the F16 aircraft, whereas the pressure distribution for F22 aircraft shows strange behaviour for the highest speed (Mach 2). On comparing the results over the whole surface, it is seen that F16 experiences smaller pressure (29% lower for Mach 1 and 30% for Mach 2), temperature (9.5% lower for Mach 1 and 30% for Mach 2) and shear stress relative to F22 and the stress shows a huge change (90% lower for Mach 1 and 83% for Mach 2). Results of the present study imply that the design of the aircraft highly influences its performance as the parameters discussed touch their limits

A perspective review of deadly viral diseases: An era of viruses

This review article overviewed briefly about the era of deadly viruses. Humans have been combating viruses since before our species had even evolved into its recent form. In some cases of viral infections, vaccines and antiviral drugs have allowed us to treat infections from spreading broadly, and have facilitated to patient recover. But it is far from over to fight the viruses. In recent decades, a number of viruses have sprung from animals to humans and have caused massive outbreaks, claiming thousands of lives such as the virus that led to the 2014-2016 Ebola outbreak in West Africa kills up to 90% of the population, making it the deadliest member of the Ebola family. But there are some viruses that are equally deadly, and some are even more deadly. Some viruses, including the novel coronavirus currently undergoing global outbreaks, have a low mortality rate but still pose a serious health risk as we have no means of access to the health facilities and scarcity of resources and infrastructure. Here we are reporting such type of ten deadly viruses. those have infected humans within last 50 years

Leveraging BI Systems to Overcome Infobesity: A Comparative Analysis of Incumbent and New Entrant firms

Infobesity is a condition whereby firms collect more information than they need or more information than they can efficiently use. As both incumbent firms and new entrant firms face different information-rich technological and economic environments, they are at a greater risk of infobesity which can compromise their innovation outcomes. In this study we leverage a research design that integrates inductive analytics and abductive discovery to uncover how incumbent and new-entrant firms leverage Business Intelligence systems and digital collaboration activities to innovate in the face of infobesity. We find that new entrant firms encounter a threshold effect governed by the use of BI systems to filter information from their customer network. On the other hand, we found that while most incumbents are able to innovate, there are uninventive incumbents that are unable to develop new products when they deploy only moderate levels of BI systems to filter their supplier data

Virtual View Networks for Object Reconstruction

All that structure from motion algorithms "see" are sets of 2D points. We show that these impoverished views of the world can be faked for the purpose of reconstructing objects in challenging settings, such as from a single image, or from a few ones far apart, by recognizing the object and getting help from a collection of images of other objects from the same class. We synthesize virtual views by computing geodesics on novel networks connecting objects with similar viewpoints, and introduce techniques to increase the specificity and robustness of factorization-based object reconstruction in this setting. We report accurate object shape reconstruction from a single image on challenging PASCAL VOC data, which suggests that the current domain of applications of rigid structure-from-motion techniques may be significantly extended

Need for Speed in the Sharing Economy: How IT capability drives Innovation Speed?

Though innovation is considered to be the lifeblood of business, speed of innovation is more critical than innovation itself. IT plays a critical role in the process of open innovation as it is based upon collaborating with suppliers and customers. IT enables increased collaboration and generation of insights across the firm’s partner network. We examine the role of IT-enabled capabilities in determining the speed of innovation. We hypothesize that collaboration with customers is more effective than collaboration with suppliers for firms to speedily innovate. Further, a firm’s digital collaboration with customers is more effective when Business Intelligence systems are used. Econometric analyses of data from 249 U.S. firms yields strong support for our hypotheses. While both customer-side and supplier- side digital collaboration are positively associated with innovation speed, the effect of customer-side digital collaboration on innovation speed is stronger. Furthermore, Business Intelligence systems use amplifies the effect of customer-side digital collaboration

Category-Specific Object Reconstruction from a Single Image

Object reconstruction from a single image -- in the wild -- is a problem where we can make progress and get meaningful results today. This is the main message of this paper, which introduces an automated pipeline with pixels as inputs and 3D surfaces of various rigid categories as outputs in images of realistic scenes. At the core of our approach are deformable 3D models that can be learned from 2D annotations available in existing object detection datasets, that can be driven by noisy automatic object segmentations and which we complement with a bottom-up module for recovering high-frequency shape details. We perform a comprehensive quantitative analysis and ablation study of our approach using the recently introduced PASCAL 3D+ dataset and show very encouraging automatic reconstructions on PASCAL VOC.Comment: First two authors contributed equally. To appear at CVPR 201