arXiv subjects
Publications and source records attributed to Parul Gupta.
For quadratic forms in $4$ variables defined over the rational function field in one variable over $\mathbb C(\!(t)\!)$, the validity of the local-global principle for isotropy with respect to different sets of discrete valuations is examined.
The ruled residue theorem characterises residue field extensions for valuations on a rational function field. Under the assumption that the characteristic of the residue field is different from $2$ this theorem is extended here to function fields of conics. The main result is that there is at most one extension of a valuation from on the base field to the function field of a conic for which the residue field extension is transcendental but not ruled. Furthermore the situation when this valuation is present is characterised.
We present \textbf{FakeET}-- an eye-tracking database to understand human visual perception of \emph{deepfake} videos. Given that the principal purpose of deepfakes is to deceive human observers, FakeET is designed to understand and evaluate the ease with which viewers can detect synthetic video artifacts. FakeET contains viewing patterns compiled from 40 users via the \emph{Tobii} desktop eye-tracker for 811 videos from the \textit{Google Deepfake} dataset, with a minimum of two viewings per video. Additionally, EEG responses acquired via the \emph{Emotiv} sensor are also available. The compiled data confirms (a) distinct eye movement characteristics for \emph{real} vs \emph{fake} videos; (b) utility of the eye-track saliency maps for spatial forgery localization and detection, and (c) Error Related Negativity (ERN) triggers in the EEG responses, and the ability of the \emph{raw} EEG signal to distinguish between \emph{real} and \emph{fake} videos.
We present here an exploratory and investigatory study of the requirements, design, and implementation of two opensource software systems: the Distributed Modular Audio Recognition Framework (DMARF), and the General Intensional Programming System (GIPSY). The inception, development, and evolution of the two systems have overlapped and in terms of the involved developers, as well as in their applications. DMARF is a platform independent collection of algorithms for pattern recognition, identification and signal processing in audio and natural language text samples, become a rich platform for the research community in particular to use, test, and compare various algorithms in the broad field of pattern recognition and machine learning. Intended as a platform for intensional programming, GIPSY's inception was intended to push the field of intensional programming further, overcoming limitations in the available tools two decades ago. In this study, we present background research into the two systems and elaborate on their motivations and the requirements that drove and shaped their design and implementation. We subsequently elaborate in more depth about various aspects their architectural design, including the elucidation of some use cases, domain models, and the overall class diagram of the major components. Moreover, we investigated existing design patterns in both systems and provided a detailed view of the involved components in such patterns. Furthermore, we delve deeper into the guts of both systems, identifying code smells and suggesting possible refactorings. Patchsets of implementations of selected refactorings have been collected into patchsets and could be committed into future releases of the two systems, pending a review and approval of the developers and maintainers of DMARF and GIPSY.
The paper discusses an application of the field effected transistor (FET) as a voltage controlled resistance which can be done in under-graduate labs either as a routine experiment or as a project.