Tweeting the Mind and Instagramming the Heart: Exploring Differentiated Content Sharing on Social Media

Understanding the usage of multiple OSNs (Online Social Networks) has been of significant research interest as it helps in identifying the unique and distinguishing trait in each social media platform that contributes to its continued existence. The comparison between the OSNs is insightful when it is done based on the representative majority of the users holding active accounts on all the platforms. In this research, we collected a set of user profiles holding accounts on both Twitter and Instagram, these platforms being of prominence among a majority of users. An extensive textual and visual analysis on the media content posted by these users revealed that both these platforms are indeed perceived differently at a fundamental level with Instagram engaging more of the users' heart and Twitter capturing more of their mind. These differences got reflected in almost every microscopic analysis done upon the linguistic, topical and visual aspects.Comment: 4 pages, 8 figure

Analyzing User Activities, Demographics, Social Network Structure and User-Generated Content on Instagram

Instagram is a relatively new form of communication where users can instantly share their current status by taking pictures and tweaking them using filters. It has seen a rapid growth in the number of users as well as uploads since it was launched in October 2010. Inspite of the fact that it is the most popular photo sharing application, it has attracted relatively less attention from the web and social media research community. In this paper, we present a large-scale quantitative analysis on millions of users and pictures we crawled over 1 month from Instagram. Our analysis reveals several insights on Instagram which were never studied before: 1) its social network properties are quite different from other popular social media like Twitter and Flickr, 2) people typically post once a week, and 3) people like to share their locations with friends. To the best of our knowledge, this is the first in-depth analysis of user activities, demographics, social network structure and user-generated content on Instagram.Comment: 5 page

Formalizing behavior-based planning for nonholonomic robots

In this paper we present a formalization of behavior-based planning for nonholonomic robotic systems. This work provides a framework that integrates features of reactive planning models with modern control-theory-based robotic approaches in the area of path-planning for nonholonomic robots. In particular, we introduce a motion description language, MDLe, that provides a formal basis for robot programming using behaviors, and at the same time permits incorporation of kinematic models of robots given in the form of differential equations. The structure of the language MDLe is such as to allow descriptions of triggers (generated by sensors) in the language. Feedback and feedforward control laws are selected and executed by the triggering events. We demonstrate the use of MDLe in the area of motion planning for nonholonomic robots. Such models impose limitations on stabilizability via smooth feedback, i.e. piecing together open loop and closed loop trajectories becomes essential in these circumstances, and MDLe enables one to describe such piecing together in a systematic manner. A reactive planner using the formalism of the paper is described. We demonstrate obstacle avoidance with limited range sensors as a test of this planner.

Modeling Gas Kick Behavior in Water and Oil-Based Drilling Fluids

This thesis presents a semi-analytical model to simulate the behavior of a gas kick in an annulus that accounts for gas solubility in oil-based drilling fluids. This simulator examines critical kick indicators such as Pit Gain and Wellhead Pressure with time. It models the gas behavior using a drift-flux approach with bubble rise velocity appropriate for flow through an annulus. It also uses the Peng-Robison equation of state, van der Waals mixing rules, along with binary interaction coefficients appropriate for drilling fluids, to account for gas solubility in oil-based mud. The simulation results predict that a five-barrel (bbl.) gas kick, would reach the wellhead of a 10,000 ft deep, non-circulating, vertical well in approximately 78 minutes. But it would only take 35 minutes to traverse the same well, if the well is circulating at 702 gallons per minute. This variation in kick travel times results from the difference in the bubble translational velocity in the two cases. The average translational velocity is 2.1 ft/sec when there is no circulation, as opposed to 4.68 ft/sec, when the mud is circulating. The simulations also predict that if there is a constant kick influx of 1 scf/sec, the first gas bubbles would reach the wellhead of the same, non-circulating well in 4.45 hours. But only take 52 minutes when it is circulating. The bubble’s shape, size, and rise velocity are the primary causes for this significant difference in kick travel time between the two non-circulating cases. The single, 5 bbl. bubble travels as a Taylor bubble with an average rise velocity of 2.1 ft/sec, while the smaller bubbles in the constant influx case migrate at an average velocity of 0.64 ft/sec. Incorporating gas solubility into these simulations revealed that the choice of drilling fluid volume factor (Bo) correlation affects the results significantly. It also showed that some of the existing Bo correlations fail, for drilling fluid swelling calculations, at higher pressures and temperatures. Finally, the results indicate that a gas kick would take longer to reach the wellhead when it is soluble in the mud than when it is not, regardless of the choice of Bo correlation. Most of the existing kick simulators either partially or entirely overlook the effects of solubility on gas migration. This model accounts for the gas kick's solubility in Oil-based drilling fluids, an issue that is critical for off-shore drilling. Applicability of empirical two-phase flow correlations developed for flow in cylindrical conduits, to a gas kick situation is questionable. This simulator addresses this issue by using a semi-analytical approach for modeling two-phase flow in an annulus