317 research outputs found
Distributed scalar quantization for computing: High-resolution analysis and extensions
No full textCommunication of quantized information is frequently followed by a computation. We consider situations of distributed functional scalar quantization: distributed scalar quantization of (possibly correlated) sources followed by centralized computation of a function. Under smoothness conditions on the sources and function, companding scalar quantizer designs are developed to minimize mean-squared error (MSE) of the computed function as the quantizer resolution is allowed to grow. Striking improvements over quantizers designed without consideration of the function are possible and are larger in the entropy-constrained setting than in the fixed-rate setting. As extensions to the basic analysis, we characterize a large class of functions for which regular quantization suffices, consider certain functions for which asymptotic optimality is achieved without arbitrarily fine quantization, and allow limited collaboration between source encoders. In the entropy-constrained setting, a single bit per sample communicated between encoders can have an arbitrarily large effect on functional distortion. In contrast, such communication has very little effect in the fixed-rate setting.National Science Foundation (U.S.) (Grant 0729069
Functional quantization
No full textThesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 119-121).Data is rarely obtained for its own sake; oftentimes, it is a function of the data that we care about. Traditional data compression and quantization techniques, designed to recreate or approximate the data itself, gloss over this point. Are performance gains possible if source coding accounts for the user's function? How about when the encoders cannot themselves compute the function? We introduce the notion of functional quantization and use the tools of high-resolution analysis to get to the bottom of this question. Specifically, we consider real-valued raw data Xn/1 and scalar quantization of each component Xi of this data. First, under the constraints of fixed-rate quantization and variable-rate quantization, we obtain asymptotically optimal quantizer point densities and bit allocations. Introducing the notions of functional typicality and functional entropy, we then obtain asymptotically optimal block quantization schemes for each component. Next, we address the issue of non-monotonic functions by developing a model for high-resolution non-regular quantization. When these results are applied to several examples we observe striking improvements in performance.Finally, we answer three questions by means of the functional quantization framework: (1) Is there any benefit to allowing encoders to communicate with one another? (2) If transform coding is to be performed, how does a functional distortion measure influence the optimal transform? (3) What is the rate loss associated with a suboptimal quantizer design? In the process, we demonstrate how functional quantization can be a useful and intuitive alternative to more general information-theoretic techniques.by Vinith Misra.M.Eng
The Post Office Horizon system and Seema Misra
No full textThe author highlights the significance of the Seema Misra case in raising questions about the reliablity of the Post Office Horizon system and more widely suggesting that all digital systems have the possibility of latent defects, and these can never be discounted. He argues that when the efficacy of digital systems is called into question in legal proceedings, the onus of proof must be placed on the supplier of these systems and not the accuser.Index words: Post Office; Horizon; prosecutions; software errors; disclosure Full transcript of the trial Regina v Seema Misra, T2009007 (England & Wales; theft; electronic evidence; Post Office Horizon System; ‘reliability’ of computers) with case commentary and index to original papers held in the Documents Supplement of Volume 12: 2015
Ultralow-Power Electronics for Cardiac Monitoring
No full textUltralow-power electronics for cardiac monitoring make possible the development of new light-weight and low-cost devices that are ideal for long-term medical measurements and home-based tele-monitoring services. Nowadays, these devices are seen as a critical technology for reducing health-care costs. In this paper, we present several methods for reducing power consumption while retaining the precision necessary for cardiac monitoring. In particular, we describe a micropower electrocardiograph, an ultralow-power pulse oximeter, an ultralow-power phonocardiograph, an integrated-circuit switched-capacitor model of the heart, and an ultracompact and efficient lithium-ion battery charger. These components are, to our knowledge, currently the most power-efficient or minimal-size designs present in the literature in each respective category
Erratum: Myocardial ischaemia and valve insufficiency caused by a dysplastic aortic valve cusp: A previously unreported unique morphologic anomaly (Cardiology in the Young (2020) (1-4) DOI: 10.1017/S1047951120001377)
No full text© The Author(s), 2020. The authors apologise that upon publication of this case report an author was left off. The online version of this article has been updated to list the authors correctly. Sharmeen Samuel, Preeta Dhanantwari, Nilanjana Misra, and David B. Meyer
Symmetry breaking during homodimeric assembly activates an E3 ubiquitin ligase
No full textCitation: Ye, Z., Needham, P. G., Estabrooks, S. K., Whitaker, S. K., Garcia, B. L., Misra, S., . . . Camacho, C. J. (2017). Symmetry breaking during homodimeric assembly activates an E3 ubiquitin ligase. Scientific Reports, 7(1). doi:10.1038/s41598-017-01880-4C-terminus of Hsc/p70-Interacting Protein (CHIP) is a homodimeric E3 ubiquitin ligase.Each CHIP monomer consists of a tetratricopeptide-repeat (TPR), helix-turn-helix (HH), and U-box domain.In contrast to nearly all homodimeric proteins, CHIP is asymmetric.To uncover the origins of asymmetry, we performed molecular dynamics simulations of dimer assembly.We determined that a CHIP monomer is most stable when the HH domain has an extended helix that supports intra-monomer TPR-U-box interaction, blocking the E2-binding surface of the U-box.We also discovered that monomers first dimerize symmetrically through their HH domains, which then triggers U-box dimerization.This brings the extended helices into close proximity, including a repulsive stretch of positively charged residues.Unable to smoothly unwind, this conflict bends the helices until the helix of one protomer breaks to relieve the repulsion.The abrupt snapping of the helix forces the C-terminal residues of the other protomer to disrupt that protomer's TPR-U-box tight binding interface, swiftly exposing and activating one of the E2 binding sites.Mutagenesis and biochemical experiments confirm that C-terminal residues are necessary both to maintain CHIP stability and function.This novel mechanism indicates how a ubiquitin ligase maintains an inactive monomeric form that rapidly activates only after asymmetric assembly. © 2017 The Author(s)
Parallel session 9 : Institutional management
No full textPresented Titles: Living in Uncertainty: The COVID-19 Pandemic and Higher Education in Hong Kong [Authors: Jisun Jung; Hugo Horta; Gerard A. Postiglione] Internalisation of China’s Higher Education and It’s Development Model [Author: Rochester Lima] Unprepared Cost of Survival: Revisiting Academic Returnees’ Cross-border Capital and Cultural Adaptation in Shanghai Universities [Authors: Jiaxin Chen; Xiaoxin Du] Us and Them: How Regions Shape the Boundaries of Elite Higher Education? [Author: Debananda Misra
Bernoulli Embeddings for Graphs
No full textJust as semantic hashing can accelerate information retrieval, binary valued embeddings can significantly reduce latency in the retrieval of graphical data. We introduce a simple but effective model for learning such binary vectors for nodes in a graph. By imagining the embeddings as independent coin flips of varying bias, continuous optimization techniques can be applied to the approximate expected loss. Embeddings optimized in this fashion consistently outperform the quantization of both spectral graph embeddings and various learned real-valued embeddings, on both ranking and pre-ranking tasks for a variety of datasets
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