188 research outputs found
Topics in statistical finance
No full textThis thesis is divided into three parts. The first part investigates the presence of long term dependence in stock price data via a permutation test based on the correlation structure of the underlying stock prices. These tests reveal the short term nature of stock price dependence structure. The second part extends
Ramprasath and Singh(2007)'s `statistical options' to define a group of American type options based on robust estimators of location. The payoff functions of these path dependent options are based on a new set of stochastic processes which are defined using various robust estimators of location. The asymptotic distributional behavior of these new processes is ascertained which in turn is used in pricing
the options. Markov Chain Monte Carlo (MCMC) methods were used to compute the prices of the statistical options. The third part explores a stock price model parameter estimation problem and interprets a growth rate parameter.Ph.D.Includes bibliographical references (p. 81-83)
Rectal Cancer Treatment Outside of the Screening Age in Australia and New Zealand: An Analysis of the Bi-National Colorectal Cancer Audit (BCCA)
No full textPoster Abstract - P-251.
Corrected by: Corrigendum to “Rectal Cancer Treatment Outside of the Screening Age in Australia and New Zealand: An Analysis of the Bi-National Colorectal Cancer Audit (BCCA)” [Eur J Surg Oncol 46/2 (2020) e106- e106]. https://doi.org/10.1016/j.ejso.2020.03.209, in Volume 46, Issue 6, June 2020, Page 1200. The authors regret that Dr. Nagendra Dudi-Venkata is missing from the author list and is actually a co-author of this abstract. The authors would like to apologise for any inconvenience caused.Abstract not availableMeike Van Harten, Emma Greenwood, Sergei Bedrikovetski, Nagendra Dudi-Venkata, Ronald Hunter, Hidde Kroon, Tarik Sammou
Polymer functionalized metal nano-particle for nonvolatile random access memory device application
No full textAbstract: Please refer to full text to view abstract.Ph.D. (Chemistry
Informetrics on M. N. Srinivas
No full textM. N. Srinivas, the well known sociologist is widely recognised as architect of modern Indian sociology and social anthropology. His publications have been analysed by year, domain, authorship pattern, channels of communication used. Keywords, etc. The results indicate that the papers published by him are of a nature that qualify him to be a 'role model' for the younger generations to emulate.
By the end of 1995, Srinivas had to his credit 144 papers which, included 33 broad papers in sociology and anthropology; 18 papers in social change; 28 papers in village studies; 12 papers on religion; 17 papers on caste and 36 papers of general popular interest. The periods 1958-61 and 1974-77, when Srinivas was 38-41 and 58-61 years old. were his most productive periods with highest publication activity
Neural Architecture Search Survey: A Hardware Perspective
No full textWe review the problem of automating hardware-aware architectural design process of Deep Neural Networks (DNNs). The field of Convolutional Neural Network (CNN) algorithm design has led to advancements in many fields, such as computer vision, virtual reality, and autonomous driving. The end-to-end design process of a CNN is a challenging and time-consuming task, as it requires expertise in multiple areas such as signal and image processing, neural networks, and optimization. At the same time, several hardware platforms, general- and special-purpose, have equally contributed to the training and deployment of these complex networks in a different setting. Hardware-Aware Neural Architecture Search (HW-NAS) automates the architectural design process of DNNs to alleviate human effort and generate efficient models accomplishing acceptable accuracy-performance tradeoffs. The goal of this article is to provide insights and understanding of HW-NAS techniques for various hardware platforms (MCU, CPU, GPU, ASIC, FPGA, ReRAM, DSP, and VPU), followed by the co-search methodologies of neural algorithm and hardware accelerator specifications.This article is published as Chitty-Venkata, Krishna Teja, and Arun K. Somani. "Neural architecture search survey: A hardware perspective." ACM Computing Surveys 55, no. 4 (2022): 1-36.
DOI: 10.1145/3524500
Copyright 2022 Copyright held by the owner/author(s).
Attribution 4.0 International (CC BY 4.0).
Posted with permission
Data to develop a mechanical model for growth of atherosclerotic plaque
No full textThe data is generated by considering various experimental data published by various author
Neural Architecture Search Benchmarks: Insights and Survey
No full textNeural Architecture Search (NAS), a promising and fast-moving research field, aims to automate the architectural design of Deep Neural Networks (DNNs) to achieve better performance on the given task and dataset. NAS methods have been very successful in discovering efficient models for various Computer Vision, Natural Language Processing, etc. The major obstacles to the advancement of NAS techniques are the demand for large computation resources and fair evaluation of various search methods. The differences in training pipeline and setting make it challenging to compare the efficiency of two NAS algorithms. A large number of NAS Benchmarks to simulate the architecture evaluation in seconds have been released over the last few years to ease the computation burden of training neural networks and can aid in the unbiased assessment of different search methods. This paper provides an extensive review of several publicly available NAS Benchmarks in the literature. We provide technical details and a deeper understanding of each benchmark and point out future directions.This article is published as Chitty-Venkata, Krishna Teja, Murali Emani, Venkatram Vishwanath, and Arun K. Somani. "Neural Architecture Search Benchmarks: Insights and Survey." IEEE Access 11 (2023): 25217 - 25236.
DOI: 10.1109/ACCESS.2023.3253818.
Copyright 2023 The Author(s).
Attribution 4.0 International (CC BY 4.0).
Posted with permission
Where Is My Tag?: Unveiling Alternative Uses of the Apple FindMy Service
No full textBluetooth trackers, or tags, have quickly become ubiquitous and widely supported by multiple vendors. Beyond their original design of finding lost objects, these devices have the ability to extend the capabilities of current wireless smart devices. Since its launch in 2019, Apple’s FindMy enables any devices from their brand to be easily tracked by more than 1 billion active iPhones and iPads on the market. While convenient, these systems may even serve further uses, including as a result of this work, crowd sensing and a side channel for mobile communication. But they also raise privacy concerns for their users. In this paper, we demonstrate how Apple FindMy can be used as a privacy-friendly tool for crowd monitoring, and how it may inadvertently leak information on a person’s location in case of deliberate tracking. Additionally, we design and evaluate a proof of concept protocol, using the Apple FindMy and a crafted tag using a simple microcontroller. We show how such system could be used to transmit information at very low bit rates, while the devices transporting the information remain unaware of this covert channel, yielding an out of band communication channel.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Information and Communication Technolog
Thermochemical reactors and processes for hydrolysis of cupric chloride
No full textA thermochemical reactor (4) and associated processes are disclosed. The reactor (4) and processes are used to conduct reactions relating to the hydrolysis of cupric chloride (CuCl2) within any one of the five-, four- and three-step Cu—Cl cycles. The reactor (4) comprises a reaction chamber (22) including a first zone (24) configured to conduct a spray operation and a second zone (26) configured to conduct a fluidized, fixed and/or moving bed operation. The first zone (24) includes a first inlet (28) configured to introduce a first reactant and an additional inlet (30) configured to introduce an additional reactant. A distributor (34) is configured to introduce the additional reactant to the second zone (26). One or more product outlets (44, 46) for communication with the reaction chamber (22) are provided
Carbon Nitride-Supported Zinc Oxide Nanocomposite for the Electrochemical Detection of Dopamine and the Development of Disposable Sensors
No full textAbstract
The carbon nitride-supported zinc oxide (CNZO) nanocomposite was synthesized through a high-temperature synthesis method, resulting in zinc oxide nanoparticles with an average size of ~44 nm, dispersed on a carbon nitride matrix. X-ray diffraction confirmed the formation of the hexagonal wurtzite phase of zinc oxide, with a space group of P63mc. X-ray photoelectron spectroscopy and Fourier-transform infrared analysis further verified the presence of both zinc oxide and carbon nitride. The CNZO nanocomposite served as a catalyst for the electrochemical detection of dopamine, achieving limit of detection and sensitivity of 2.66 μM and 6.23 μA μM−1 cm−2 respectively, using square wave voltammetry technique. Cyclic voltammetry experiments demonstrated excellent electroactivity of the CNZO nanocomposite in a neutral pH environment. An electrochemical paper-based analytical device (EPAD) was designed and successfully employed for the electrochemical analysis of dopamine in pharmaceutical samples using CNZO nanocomposites. Additionally, CNZO was used as an active material in the development of a disposable dopamine sensor based on an extended gate field-effect transistor (EG-FET). This sensor exhibited a sensitivity and limit of detection 18.22 μA μM−1 cm−2 and 0.36 μM, respectively, with a correlation coefficient of 0.99.Abstract
The carbon nitride-supported zinc oxide (CNZO) nanocomposite was synthesized through a high-temperature synthesis method, resulting in zinc oxide nanoparticles with an average size of ~44 nm, dispersed on a carbon nitride matrix. X-ray diffraction confirmed the formation of the hexagonal wurtzite phase of zinc oxide, with a space group of P63mc. X-ray photoelectron spectroscopy and Fourier-transform infrared analysis further verified the presence of both zinc oxide and carbon nitride. The CNZO nanocomposite served as a catalyst for the electrochemical detection of dopamine, achieving limit of detection and sensitivity of 2.66 μM and 6.23 μA μM−1 cm−2 respectively, using square wave voltammetry technique. Cyclic voltammetry experiments demonstrated excellent electroactivity of the CNZO nanocomposite in a neutral pH environment. An electrochemical paper-based analytical device (EPAD) was designed and successfully employed for the electrochemical analysis of dopamine in pharmaceutical samples using CNZO nanocomposites. Additionally, CNZO was used as an active material in the development of a disposable dopamine sensor based on an extended gate field-effect transistor (EG-FET). This sensor exhibited a sensitivity and limit of detection 18.22 μA μM−1 cm−2 and 0.36 μM, respectively, with a correlation coefficient of 0.99
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