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

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

Too Many Cooks Spoil the Broth: Infobesity in Multicultural Firms During Covid-19

Globalized firms maintain a presence across multiple countries encompassing multiple cultures. Cross-border, multicultural firms can leverage digital technologies to harness diverse information spread across the organization to generate insights and innovation. Conversely, digital technologies can cause organizations to suffer from infobesity. We examine this dialectic tension in the context of the Covid-19 pandemic. We theorize that multicultural firms exhibited better performance, assessed through market measures, during the onset of the pandemic. We further maintain that the use of digital technologies to generate insights from data has a negative effect on the relationship between multiculturism and firm performance due to infobesity. Analysis of Fortune 500 firms, having 56,587 subsidiaries present in 179 distinct countries, demonstrates that multicultural firms witnessed relatively superior stock market returns during the first quarter of 2020. We make significant contributions to information systems and cross-cultural research and to broader inter-disciplinary management research