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It can be shown, that, theoretically, all binary code trees are equivalent in sense of representing the entropy of the original symbols provided that each node of the corresponding trees corresponds to an appropriately initialized probability model. (...) Table 1 : Exp-Golomb codes (left) and their related models, where different models are depicted by different colors (right). (...) By using a single, unified binarization scheme, each syntax element uses at least 4 different models: 3 models switching between the first, the second and all remaining bins of the prefix bins, and one additional model for all suffix bits.
Language:English
Score: 851398 - https://www.itu.int/wftp3/av-a...e/2001_12_Pattaya/VCEG-O18.doc
Data Source: un
q15d43 ITU – Telecommunications Standardization Sector STUDY GROUP 16 Video Coding Experts Group _________________ Tampere, April 21-24 1998 Document Q15-D-43 Filenames: q15d43.doc & q15d43.xls Question: Q.15/16 Source: University of Strathclyde Author: Richard Fryer e-mail rjf@cs.strath.ac.uk Title: An Excel-based implementation of the adopted H.26L Delay Model Introduction This document presents a ‘Version 1’ implementation of the adopted Delay Model for the particular case that the order of encoded frames in the data stream is the same as their order in the source sequence. (...) Black text embodies the model and should not be adjusted Blue text indicates information that is codec and/or run dependent. (...) The various columns are headed to indicate the nature of the corresponding value. Nomenclature is as in the Delay Model Description in the Call for Proposals.
Language:English
Score: 851270 - https://www.itu.int/wftp3/av-a...video-site/9804_Tam/q15d43.doc
Data Source: un
This is not only imported for the meta-models themselves, but also for the language tool design based on this models. (...) Meta-language and corresponding meta-tools form generator frameworks in the sense of generative engineering. 5 OOMM and Generative Engineering of Language Tools for SDL In this section, we want to illustrate the usage of OOMM language descriptions and generative engineering for the specification of SDL and the development of prototypical SDL tools. 5.1 A meta-model for the SDL language A meta-model is just an object-oriented model of SDL’s language constructs. (...) The SDL meta-model thereby specifies a set of valid SDL models.
Language:English
Score: 848075.4 - https://www.itu.int/dms_pub/it.../06/18/T06180000010042PDFE.pdf
Data Source: un
 Page 44 - ITU Journal: Volume 2, No. 1 - Special issue - Propagation modelling for advanced future radio systems - Challenges for a congested radio spectrum           Basic HTML Version Table of Contents View Full Version Page 44 - ITU Journal: Volume 2, No. 1 - Special issue - Propagation modelling for advanced future radio systems - Challenges for a congested radio spectrum P. 44 ITU Journal: ICT Discoveries, Vol. 2(1), December 2019 distribution parameters. For off-body propagation, The parameters were derived from full-wave due to the inability to de-embed the antennas’ numerical simulations, and from wideband radiation patterns from measurements, the measurements using physical liquid phantoms with measured loss corresponds to the system loss. The one antenna fixed at 3.5 cm from the phantom’s model parameters represent a typical indoor office surface while the other was moved in the air over a environment [1-2], for static, quasi-dynamic spatial grid [4], or in vivo. (...) This effect is not captured by 0 conventional MIMO channel models. where is the Tx-Rx distance, 0, / ( ) is the MPL Measurements in [9] indicate that individual 0 at the reference distance usually taken at 1 cm, multipath components (MPCs) have a limited 0 and and are slopes of the MPL models. lifetime within the cluster when the user equipment moves with different MPCs of a cluster active at The in-body channel corresponds to links established between two implants (in2in).
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Score: 847689.3 - https://www.itu.int/en/publica...1/files/basic-html/page44.html
Data Source: un
X.694 (01/2004) 5 e) for each model group definition whose model group has a compositor of sequence or choice, an ASN.1 type assignment shall be generated by applying clause 17 to the model group definition. (...) NOTE – This means that all ASN.1 type reference names in the ASN.1 module can be imported into other modules. 10 Name conversion 10.1 General 10.1.1 This Recommendation | International Standard specifies the generation of: a) ASN.1 type reference names corresponding to the names of model group definitions, top-level element declarations, top-level attribute declarations, top-level complex type definitions, and user-defined top-level simple type definitions; b) ASN.1 identifiers corresponding to the names of top-level element declarations, top-level attribute declarations, local element declarations, and local attribute declarations; c) ASN.1 identifiers for the mapping of certain simple type definitions with an enumeration facet (see 12.4.1 and 12.4.2); ISO/IEC 8825-5:2004 (E) ITU-T Rec. (...) X.694 (01/2004) 9 10.4 Order of the mapping 10.4.1 An order is imposed on the top-level schema components of the source XSD Schema on which the mapping is performed. This applies to model group definitions, top-level complex type definitions, user-defined top-level simple type definitions, top-level attribute declarations, and top-level element declarations.
Language:English
Score: 846180.1 - https://www.itu.int/ITU-T/2005-2008/com17/languages/X694.pdf
Data Source: un
 Page 1052 - Shaping smarter and more sustainable cities - Striving for sustainable development goals           Basic HTML Version Table of Contents View Full Version Page 1052 - Shaping smarter and more sustainable cities - Striving for sustainable development goals P. 1052 Work FG‐SSC SDO Document Corresponding Standardization Future needs area deliverable(s) working number document title gap in this area and suggestions related to this on this released by to SG5 work area area this SDO ONVIF Interface Guide Specifi‐ cation ONVIF WSDL and XML Sche‐ mas Specifications Physical Service Model Security Interoper‐ ability Alliance PSIA Common Metadata & Event Model PSIA Common Security Model IP Media Device specification Recording and Content Management specifi‐ cation Video Analytics specification Area Control specification 3.3.3.8 Smart metering There are Technical Reports on ICT infrastructure for SSC which involves facilities of IoT in FG‐SSC [b‐FG‐SSC infrastructure], water management [ITU‐T TR water], and integrated management for SSC [ITU‐T TR management]. (...) Work FG‐SSC SDO Document Corresponding Standardization Future needs area deliverable(s) working number document title gap in this area and suggestions related to this on this released by to SG5 work area area this SDO Smart Smart water To develop metering management guidelines for for SSC [ITU‐T applications TR water] using smart metering technologies in SSC ITU‐T FG Use Cases for Smart Grid Smart (Focus Group on Smart Grid) Requirements of communica‐ tion for Smart Grid Smart Grid Architecture Smart Grid Overview Terminology 1042 ITU‐T's Technical Reports and Specifications     1047     1048     1049     1050     1051     1052     1053     1054     1055     1056     1057          
Language:English
Score: 846149.7 - https://www.itu.int/en/publica...files/basic-html/page1052.html
Data Source: un
FML model training module [ITU-T F.FML-TS-FR (Q5/16)]: An executable programme to be used to training FML models with ML model training datasets. 19. FML model training [ITU-T F.FML-TS-FR (Q5/16)]: Groups of processes to train FML models. 20. FML model utilizing [ITU-T F.FML-TS-FR (Q5/16)]: Groups of processes to utilize trained FML models. 21.
Language:English
Score: 845794.8 - https://www.itu.int/en/ITU-T/c...es/scv/Documents/SCV-TD03.docx
Data Source: un
Note that it would be however always possible to adapt this quantization step size for instance on each component or per residual frame type. Modeling of transform coefficient subbands Each transform coefficient subband marginal distribution is modeled as a Generalized Gaussian Density (GGD) by adaptively varying two parameters α and β where α models the width of the Probability Density Function (PDF) peak (standard deviation), while β is inversely proportional to the decreasing rate of the peak. Sometimes, α is referred to as the scale parameter while is called the shape parameter. The GGD model contains the Gaussian and Laplacian PDFs as special cases, using β=1 and β=2, respectively. (...) However, the distributions may not change a lot for a given type along the sequence, which would allow to have pre-defined parameters per frame type without requiring to model the distribution and to avoid transmitting the parameters.
Language:English
Score: 845385.5 - https://www.itu.int/wftp3/av-a...ite/2005_04_Busan/JVT-O046.pdf
Data Source: un
Green Climate Fund Delivers Correspondence Management Training with UNICC Learning Team Guidance - UNICC Skip to content Home Who We Are Clients and Partner Organizations Global Presence Governance and Management History Strategic Partnerships What We Do Common Secure Conference COVID-19 Pandemic Response Data Action Portfolio Gender, Diversity and Inclusiveness Robotic Process Automation: Working Smarter UNICC for the Sustainable Development Goals What Makes Us Unique Working with Us News Centre Resources Photo: Pexels/Ferguson Green Climate Fund Delivers Correspondence Management Training with UNICC Learning Team Guidance Posted on 25 August, 2020 | by Maria Thomsen UNICC has built a customised, self-paced course to train Green Climate Fund (GCF) personnel in the management of official and executive correspondence in Microsoft Dynamics 365. GCF uses the Microsoft Dynamics Executive Correspondence Management system for official and executive correspondence, including postal letters and electronic mail, tracked upon receipt and replied to in a timely manner. (...) The training has been developed using Articulate Storyline 360, compliant with the Shareable Content Object Reference Model (SCORM) and was executed following Success Approximation Model (SAM) principles.
Language:English
Score: 845006.4 - https://www.unicc.org/news/202...-unicc-learning-team-guidance/
Data Source: un
A list of deliverables for the FG-AI4H was planned and corresponding groups was established, with 9 deliverables (DEL 1-9) focus on generalized consideration on ethics, regulatory, requirement, data processing, model training, model evaluation, adoption and scale-up, etc., and 20 topic groups (DEL 10.1-10.20) within specific health domains with corresponding AI/ML benchmarking tasks. (...) The aim is to train the most accurate model for each group without harming any minority group of patients. (...) It is from an overview perspective of developing AI4H model in corresponding use cases, specific information on benchmarking can be found in DEL 10: AI4H use cases: Topic description docs.
Language:English
Score: 844096.1 - https://www.itu.int/en/ITU-T/f...ocuments/all/FGAI4H-J-043.docx
Data Source: un