Avini\u27s city: Shahri Dar Aasemaan .

This thesis examines the documentary Shahri dar Aasemaan (i.e. A City in the Sky) by the late filmmaker Sayyed Morteza Avini\u27s in order to establish its key elements and argue for Avini as an auteur with a unique cinematic style that includes strong personal and ideological ties. Shahri dar Aasemaan, which was Avini\u27s last documentary, covers the initial forty-five-day battle leading to the Iraqi occupation of the Iranian city of Khorramshahr when the Iran-Iraq war broke out in October of 1980. In order to better comprehend Avini as an auteur and his work, this study begins with a brief introduction to Avini\u27s biography and the history of the Iran-Iraq war. The following chapter is a comparison to The War, a documentary in seven episodes by American director Ken Burns in 2007 about the Second World War. The purpose of this comparison is to discuss Shahri dar Aasemaan in the context of another film that has documented a war at length rather than in isolation, a type of analysis that has not yet been conducted either inside or outside of Iranian borders about Avini\u27s films. The focus of the thesis\u27 remaining chapters is on Shahri dar Aasemaan as both artistic and cultural artifact

Plasma sheet structure in the magnetotail: kinetic simulation and comparison with satellite observations

We use the results of a three-dimensional kinetic simulation of an Harris current sheet to propose an explanation and to reproduce the ISEE-1/2, Geotail, and Cluster observations of the magnetotail current sheet structure. Current sheet flapping, current density bifurcation, and reconnection are explained as the results of the kink and tearing instabilities, which dominate the current sheet evolution.Comment: Submitted to Geophys. Res. Lett. (2003

Secure Peer-to-Peer Networks for Scientific Information Sharing

The most common means of remote scientific collaboration today includes the trio of e-mail for electronic communication, FTP for file sharing, and personalized Web sites for dissemination of papers and research results. With the growth of broadband Internet, there has been a desire to share large files (movies, files, scientific data files) over the Internet. Email has limits on the size of files that can be attached and transmitted. FTP is often used to share large files, but this requires the user to set up an FTP site for which it is hard to set group privileges, it is not straightforward for everyone, and the content is not searchable. Peer-to-peer technology (P2P), which has been overwhelmingly successful in popular content distribution, is the basis for development of a scientific collaboratory called Scientific Peer Network (SciPerNet). This technology combines social networking with P2P file sharing. SciPerNet will be a standalone application, written in Java and Swing, thus insuring portability to a number of different platforms. Some of the features include user authentication, search capability, seamless integration with a data center, the ability to create groups and social networks, and on-line chat. In contrast to P2P networks such as Gnutella, Bit Torrent, and others, SciPerNet incorporates three design elements that are critical to application of P2P for scientific purposes: User authentication, Data integrity validation, Reliable searching SciPerNet also provides a complementary solution to virtual observatories by enabling distributed collaboration and sharing of downloaded and/or processed data among scientists. This will, in turn, increase scientific returns from NASA missions. As such, SciPerNet can serve a two-fold purpose for NASA: a cost-savings software as well as a productivity tool for scientists working with data from NASA missions

Social Networking Adapted for Distributed Scientific Collaboration

Share is a social networking site with novel, specially designed feature sets to enable simultaneous remote collaboration and sharing of large data sets among scientists. The site will include not only the standard features found on popular consumer-oriented social networking sites such as Facebook and Myspace, but also a number of powerful tools to extend its functionality to a science collaboration site. A Virtual Observatory is a promising technology for making data accessible from various missions and instruments through a Web browser. Sci-Share augments services provided by Virtual Observatories by enabling distributed collaboration and sharing of downloaded and/or processed data among scientists. This will, in turn, increase science returns from NASA missions. Sci-Share also enables better utilization of NASA s high-performance computing resources by providing an easy and central mechanism to access and share large files on users space or those saved on mass storage. The most common means of remote scientific collaboration today remains the trio of e-mail for electronic communication, FTP for file sharing, and personalized Web sites for dissemination of papers and research results. Each of these tools has well-known limitations. Sci-Share transforms the social networking paradigm into a scientific collaboration environment by offering powerful tools for cooperative discourse and digital content sharing. Sci-Share differentiates itself by serving as an online repository for users digital content with the following unique features: a) Sharing of any file type, any size, from anywhere; b) Creation of projects and groups for controlled sharing; c) Module for sharing files on HPC (High Performance Computing) sites; d) Universal accessibility of staged files as embedded links on other sites (e.g. Facebook) and tools (e.g. e-mail); e) Drag-and-drop transfer of large files, replacing awkward e-mail attachments (and file size limitations); f) Enterprise-level data and messaging encryption; and g) Easy-to-use intuitive workflow

Transverse and non-boost longitudinal expansion of (2+1)dimensional relativistic ideal-hydrodynamics flow in heavy ion collisions

This study investigates the evolution of quark gluon plasma (QGP) within a generalized Bjorken flow framework. The medium under consideration is assumed to possess a finite transverse size and to expand both radially and along the beam axis. However, we assume that the boost invariance of longitudinal expansion is broken. To be more specific, we generalize the Bjorken solution to include the acceleration and transverse expansion of the fluid. We analytically study the (2 + 1) dimensional longitudinal acceleration expansion of hot and dense quark matter, applying a perturbation approach to solve the relativistic hydrodynamics equations. This procedure enables us to obtain exact algebraic expressions for fluid velocities and energy densities in both transverse and longitudinal directions. To simplify our calculations, we assume that the fluid is produced in central collisions, and therefore, we consider azimuthal symmetry. We compare the radial velocity and correction energy density with those obtained from the Gubser model. Furthermore, we determine the fluid's acceleration parameter and longitudinal correction energy density, which exhibits a Gaussian distribution

Physics Mining of Multi-Source Data Sets

Powerful new parallel data mining algorithms can produce diagnostic and prognostic numerical models and analyses from observational data. These techniques yield higher-resolution measures than ever before of environmental parameters by fusing synoptic imagery and time-series measurements. These techniques are general and relevant to observational data, including raster, vector, and scalar, and can be applied in all Earth- and environmental science domains. Because they can be highly automated and are parallel, they scale to large spatial domains and are well suited to change and gap detection. This makes it possible to analyze spatial and temporal gaps in information, and facilitates within-mission replanning to optimize the allocation of observational resources. The basis of the innovation is the extension of a recently developed set of algorithms packaged into MineTool to multi-variate time-series data. MineTool is unique in that it automates the various steps of the data mining process, thus making it amenable to autonomous analysis of large data sets. Unlike techniques such as Artificial Neural Nets, which yield a blackbox solution, MineTool's outcome is always an analytical model in parametric form that expresses the output in terms of the input variables. This has the advantage that the derived equation can then be used to gain insight into the physical relevance and relative importance of the parameters and coefficients in the model. This is referred to as physics-mining of data. The capabilities of MineTool are extended to include both supervised and unsupervised algorithms, handle multi-type data sets, and parallelize it