51 research outputs found
Evaluating intervention strategies in controlling coronavirus disease 2019 (COVID-19) spread in care homes : an agent-based model - Corrigendum
No full textIn the above article1, the author names should appear as follows: Le Khanh Ngan Nguyen, Susan Howick, Dennis McLafferty, Gillian H. Anderson, Sahaya J. Pravinkumar, Robert Van Der Meer and Itamar Megiddo
Switch level optimization for CMOS circuits
No full textDue to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to [email protected], referencing the URI of the item.Includes bibliographical references.Issued also on microfiche from Lange Micrographics.In this report, 'Input vs Path Matrix 'Techique' and 'Node vs Input Matrix Technique' techniques for reducing transistor count in the pull-up and the pull-down array of CMOS circuits are proposed. Also, algorithms for optimization of both the pull-up tree and the pull-down tree, based on the above techniques, which results in a reduced number of transistors in the optimized tree in comparison to the original structure of CMOS circuits are proposed. A comparison has been done for area, delay and power of the optimized and unoptimized CMOS structures. Simulations for power and delay have been done in HSPICE [8] for both the optimized and unoptimized CMOS structures. Some of the optimized CMOS structures are the multiplexers, adders and gray to binary converters. The optimized CMOS structures have been found to be faster, lower in power dissipation and taking less layout area in comparison to the unoptimized CMOS structures. The above techniques can also be applied to the Pseudo-NMOS and Dynamic CMOS circuits besides the regular CMOS circuits
Multidimensional Model Based Speech Signal Representations For Automatic Speaker Identification
No full textA novel Model based Automatic Speaker Identification (M-ASI) technique employing multidimensional representations of the Linear Prediction (LP) coefficients, and the LP residual is proposed. During the training mode, the LP coefficients, and the LP residuals extracted from the speech signal are projected into multiple domains, and vector quantized codebooks are obtained using energy based split vector quantization. During the running mode, a closest match is found by comparing the speech vectors of the unknown speaker, and the reconstructed speech employing each of the known codebooks stored in the database. Employing a normalized matching accuracy measure, the proposed technique is consistently found to obtain enhanced ASI accuracy in comparison with Vector Quantization (VQ) employing existing single dimensional LP based ASI approaches at the expense of a modest increase in computational complexity. 100% speaker identification accuracy is obtained with a low signal-coding rate of less than 2.91 bps
Long-term survival in critically ill hematologic malignancy: Issues about learning curves pending
No full textPalliative Radiotherapy for Malignant Airway Obstruction Requiring Mechanical Ventilation: Answer or Anguish?
No full textA novel approach for protein secondary structure prediction using encoder–decoder with attention mechanism model
No full textComputational biology faces many challenges like protein secondary structure prediction (PSS), prediction of solvent accessibility, etc. In this work, we addressed PSS prediction. PSS is based on sequence-structure mapping and interaction among amino acid residues. We proposed an encoder–decoder with an attention mechanism model, which considers the mapping of sequence structure and interaction among residues. The attention mechanism is used to select prominent features from amino acid residues. The proposed model is trained on CB513 and CullPDB open datasets using the Nvidia DGX system. We have tested our proposed method for Q
3 and Q
8 accuracy, segment of overlap, and Mathew correlation coefficient. We achieved 70.63 and 78.93% Q
3 and Q
8 accuracy, respectively, on the CullPDB dataset whereas 79.8 and 77.13% Q
3 and Q
8 accuracy on the CB513 dataset. We observed improvement in SOV up to 80.29 and 91.3% on CullPDB and CB513 datasets. We achieved the results using our proposed model in very few epochs, which is better than the state-of-the-art methods
An evaluation of the technique of photothermal radiometry for the non-destructive testing and characterisation of plasma-sprayed coatings
No full textSIGLEAvailable from British Library Document Supply Centre- DSC:DX84973 / BLDSC - British Library Document Supply CentreGBUnited Kingdo
<span style="font-size:11.0pt;font-family: "Times New Roman","serif";mso-fareast-font-family:"Times New Roman";mso-bidi-font-family: Mangal;mso-ansi-language:EN-GB;mso-fareast-language:EN-US;mso-bidi-language: HI" lang="EN-GB">Oxygen reduction reaction of manganese oxide/graphene oxide nanocomposite</span>
No full text177-181<span style="font-size:11.0pt;font-family:
" times="" new="" roman","serif";mso-fareast-font-family:"times="" roman";mso-bidi-font-family:="" mangal;letter-spacing:-.3pt;mso-ansi-language:en-gb;mso-fareast-language:en-us;="" mso-bidi-language:hi"="" lang="EN-GB">MnO2/graphene oxide composite coating has been
prepared by electrochemical anodic deposition method. Optimization of current
density and deposition efficiency is reported. The formation of
α-MnO2/graphene oxide nanocomposite is elucidated through X ray
diffraction and infrared reflection measurements. Morphological studies reveal
the increase in porosity and exfoliation of graphene oxide by MnO2
particles. The extent of oxygen reduction reaction occurring at the surface of
MnO2/graphene oxide composite coating have been analyzed by cyclic
voltammetry and electrochemical impedance spectroscopy in aqueous 1 M Li2SO4
solution. The composite coating is observed to possess better catalytic
properties towards oxygen reduction.</span
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