182 research outputs found
Verification of Hybrid Systems using Abstractions
No full textions ? Anuj Puri and Pravin Varaiya Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA 94720 Abstract. A hybrid system models both discrete event and continuous dynamics. We present a modeling formalism and a verification methodology for hybrid systems. The verification methodology is based on abstracting the continuous dynamics in the hybrid system by simpler continuous dynamics. We present two methods for doing this: in the first method, a differential inclusion is replaced with a simpler differential inclusion; in the second method, we look at the timing information that is relevant to the verification problem, and construct an abstraction of the hybrid system with a timed automaton. We illustrate our methodology by applying it to the train-gate-controller example. 1 Introduction Traditional control theory and system theory have been successfully used in design of a large class of systems. But in the design of large, complex distribu..
Accelerating Population Balance Model - based particulate process simulations via parallel computing
No full textThe use of Population Balance Models (PBM) for simulating dynamics of particulate systems are inevitably limited at some point by the demands they place on computational resources. PBMs are widely used to describe the time evolutions and distributions of many industrial particulate processes, and its efficient and quick simulation would certainly be beneficial for process design, control and optimization. This thesis is an elucidation of how MATLAB's Parallel Computing Toolbox (PCT), a third-party toolbox called JACKET, and the MATLAB Distributed Computing Server (MDCS) may be combined with algorithmic modification of the PBM to speed up these computations on a CPU (Central Processing Unit), GPU (Graphics Processing Unit) and a computer cluster respectively. Parallel algorithms were developed for three dimensional and four dimensional population balance models incorporating hardware class-specific parallel constructs such as SPMD and gfor. Results indicate significant reduction in computational time without compromising numerical accuracy for all cases except for the GPU. The GPU seemed promising for larger problems despite its limitations of lower clock speeds and on-board memory compared to the CPU. Evaluations of the speedup and scalability further affirm the algorithms' performance.M.S.Includes bibliographical referencesIncludes vitaby Anuj Varghese Prakas
The group right to mutual privacy
No full textContemporary privacy challenges go beyond individual interests and result in collective harms. To address these challenges, this article argues for a collective interest in Mutual Privacy which is based on our shared genetic, social, and democratic interests as well as our common vulnerabilities against algorithmic grouping. On the basis of the shared interests and participatory action required for its cumulative protection, Mutual Privacy is then classified as an aggregate shared participatory public good which is protected through the group right to Mutual Privacy
Quantum transport in graphene nanotransistors
No full textOver the past decade, interest in using graphene in condensed-matter physics and materials science applications has exploded, owing to its unique electrical properties. Narrow strips of graphene, called graphene nanoribbons, also display exotic behavior. A nanoribbon’s edge geometry determines its electronic transport properties, and the rich behavior
of conductance of nanoribbons in response to external potentials makes them ideal for use within transistors.
In this thesis, we work towards creating an accurate model of graphene nanoribbon transistors, and we asses two possible applications which exploit their amazing potential. We begin by outlining the basic theoretical and computational framework for the model developed in this work. We then demonstrate the capability of graphene nanoribbon transistors, with nanopores, to electronically detect, characterize, and manipulate translocating DNA
strands. Specifically, we explore the tunability of such devices, by examining the role of lattice geometry, such as a quantum point contact constriction, on their performance. We perform a demonstration of the ability to detect the passage of double and single-stranded
DNA, through molecular dynamics simulations. The transistors presented are capable of sensing the helical shape of double-stranded DNA molecules, the unraveling of a DNA helix into a planar-zipper form, and the passage of individual nucleotides of a single strand of DNA
through the nanopore. We outline a preliminary analysis on the proper design of a multilayer transistor stack to control both the electronic properties of the conducting membrane, as well as the motion of the DNA. Lastly, we present another type of nanoribbon device,
an all-carbon spintronic transistor for use in cascaded logic circuits. A thorough analysis of the transport properties of zigzag nanoribbon transistors in magnetic fields, in addition to the design and construction of logic gate circuits containing these spintronic transistors, is presented.Submission published under a 24 month embargo labeled 'U of I only', the embargo will last until 2017-05-01The student, Anuj Girdhar, accepted the attached license on 2015-04-18 at 16:01.The student, Anuj Girdhar, submitted this Dissertation for approval on 2015-04-18 at 16:02.This Dissertation was approved for publication on 2015-04-24 at 10:12.DSpace SAF Submission Ingestion Package generated from Vireo submission #7936 on 2015-07-22 at 14:18:16Made available in DSpace on 2015-07-22T22:33:35Z (GMT). No. of bitstreams: 2
GIRDHAR-DISSERTATION-2015.pdf: 31622280 bytes, checksum: ab959d673849be0b7d88d6f28e7e70d5 (MD5)
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Previous issue date: 2015-04-24Embargo set by: Seth Robbins for item 79875
Lift date: 2017-07-22T22:34:16Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Only Restriction Lifted for Item 79875 on 2017-07-23T09:15:20Z
The group right to privacy
No full textIn the age of Big Data Analytics and Covid-19 Apps, the conventional conception of privacy that focuses excessively on the identification of the individual is inadequate to safeguard an individual’s identity and autonomy, when she is targeted on the basis of her interdependent social and algorithmic group affiliations. In order to overcome these limitations, this interdisciplinary research develops a theoretical framework of the group right to privacy (GRP), which is based on privacy as a social value (Pᵥ).
The quadrumvirate formulation of GRP is articulated on the dual lines of the individual’s right as a member of a group and the right of the group itself. An individual’s interest in her social identity and her socially embedded autonomous self is protected through GRP₁. The individual’s right against algorithmic grouping, GRP₂, is motivated by an interest in group-related aspects of informational self-determination. Thirdly, I provide a non-reductionist account of instances where some organized groups may be entitled to privacy in their own right as GRP₃. Lastly, I articulate the collective interest in Mutual Privacy, understood as an aggregate participatory shared public good which is protected through GRP₄. In all four GRP, I carve out a limited exception for contact tracing by Covid-19 Apps during the extraordinary circumstances of the pandemic while safeguarding against the creation of a new normal of erosion of privacy and the rise of post-pandemic simveillance.
To test its efficacy, this theoretical model is critically analysed against the technological challenges posed by Big Data Analytics and Covid-19 Apps. I further examine international privacy legislations to highlight the way this expansive privacy model can be incorporated in the regulatory landscape. In conclusion, this thesis emphasizes that our privacy is not only interdependent in nature, but also existentially cumulatively interlinked and should be protected through the GRP."This work was supported by the St Leonard’s College Interdisciplinary Doctoral
Scholarship, which was jointly funded by the University of St Andrews, the School
of Management and the School of Philosophical, Anthropological & Film Studies" -- Fundin
Statistical Profile Generation of Real-time UAV-based Traffic Data
No full textSmall unmanned vehicles are used to provide the eye-in-the-sky alternative to monitoring and regulating traffic dynamically. Spatial-temporal visual data are collected in real-time and they are used to generate traffic-related statistical profiles, serving as inputs to traffic simulation models. Generated profiles, which are continuously updated, are used to calibrate traffic model parameters, to obtain more accurate and reliable simulation models, and for model modifications. This method overcomes limitations of existing traffic simulation models, which suffer from outdated data, poorly calibrated parameters, questionable accuracy and poor predictions of traffic patterns
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