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 Page 39 - Methodology for measurement of Quality of Service (QoS) Key Performance Performance Indicators (KPIs) for Digital Financial Services           Basic HTML Version Table of Contents View Full Version Page 39 - Methodology for measurement of Quality of Service (QoS) Key Performance Performance Indicators (KPIs) for Digital Financial Services P. 39 MTDR Rate/ Probability Money Transfer Duplication Rate Start Success (use for validity check) use content for valida- tion use content for valida- tion MTLR Rate/ Probability Money Transfer Loss Rate Start Success (use for validity check) use content for validation use content for validation MTAST Time Money Transfer Account Stabilization Time Start Success (use for validity check) use content for validation use content for validation MTASSR Rate/ Probability Money Transfer Account Stabilization Success Rate Start Success (use for validity check) use content for validation use content for validation MTFTRR Rate/ Probability Money Transfer Failed Transaction Resolution Rate Success (use for validity check) use content for validation use content for validation MTFNR Rate/ Probability Money Transfer False Negative Rate Start Success (use for validity check) use content for validation use content for validation MTFPR Rate/ Probability Money Transfer False Positive Rate Success (use for validity check) use content for validation use content for validation ■  NOTE 1: For a time value, all sub-phases where human interaction is involved need to be eliminated, and, eventually, a normalized/typical time value has to be used ■  NOTE 3: use all available elements to calculate eligible time intervals (only use the times which MTCT Time Money Transfer completion time X (3) X (3) X (3) X (3) End (1) MTCR Rate/ Probability Money Transfer completion rate X (2) X (2) X (2) X (2) Success ■  NOTE 2: Used to create detail information in case of failure (identify sub-phase where failure occurred).
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Score: 748051.7 - https://www.itu.int/en/publica...t/files/basic-html/page39.html
Data Source: un
This boundary, defined in terms of probability, leads to a value for use in system design that is approximately 20% lower in DGD value and two orders of magnitude less in probability than the values that would be obtained without a statistical specification. (...) IEC 61282-3 describes a method of determining a maximum (defined in terms of probability) so that if a distribution passes the Method 1 requirement, the DGD across links comprised of only optical fibre cable will exceed the maximum DGD with a probability less than 6.5(10-8. (...) If the computed probability is less than the specified value (6.5(10-8), the distribution passes Method 2.
Language:English
Score: 746883.06 - https://www.itu.int/itudoc/itu...tory/g650.2a1/g6502a1s_ww9.doc
Data Source: un
The results (Table 7) show that the probability of being inactive decreases the higher the level of education. (...) In Centro young people have a higher probability to be inactive for other reasons (15 per cent), while in the Lisbon Metropolitan Area the probability is higher for disability (by 16.2 per cent). (...) TABLE A2: PROBABILITY 1 2 3 4 5 Care responsibilities Illness/disability Re-entrants Discouraged Other VARIABLES Inactivity among young people (15-29) Age group (15-24=1; 25-29=0) Probability Probability Probability Probability Probability Sex (female=1; male=0) Probability Probability Probability Probability Probability 1.Education: Less than lower secondary Probability Probability Probability Probability Probability 2.Education: Upper secondary Probability Probability Probability Probability Probability 3.Education: Tertiary Probability Probability Probability Probability Probability 4.Region: name X Probability Probability Probability Probability Probability 5.Region: name Y Probability Probability Probability Probability Probability . 17 ANNEX II: Regional breakdown (by characteristics) of average probability of being inactive2 NORTE Education Primary Secondary Tertiary Sex Male Female Male Female Male Female Age group 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 Inactivity 10.92% 9.27% 15.44% 13.33% 4.89% 4.02% 7.46% 6.24% 3.19% 2.57% 5.04% 4.15% Family/care responsibilities 3.49% 5.47% 24.09% 31.18% 1.97% 3.23% 17.10 % 23.04% 3.32% 5.23% 23.40% 30.39% Illness or disability 55.04% 67.50% 38.18% 51.04% 28.44% 40.40% 15.93 % 25.13% 6.05% 11.06% 2.40% 4.94% Discouragement 18.37% 12.80% 12.64% 8.40% 22.57% 16.17% 15.98 % 10.94% 5.05% 3.04% 2.99% 1.71% Awaiting recall to work 6.23% 4.80% 4.32% 3.27% 13.01% 10.49% 9.61% 7.60% 10.60% 8.43% 7.68% 6.00% Other reasons 17.67% 13.38% 4.32% 11.32% 36.02% 29.50% 32.31 % 26.11% 59.21% 52.08% 55.25% 48.05% ALGARVE Education Primary Secondary Tertiary Sex Male Female Male Female Male Female Age group 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 Inactivity 23.56% 20.78% 30.60% 27.41% 12.61% 10.78% 17.57% 15.27% 8.95% 7.54% 12.92% 11.05% Family/care responsibilities 5.65% 8.50% 31.76% 39.68% 3.35% 5.27% 23.53% 30.55% n.a. 8.16% n.a. 38.82% Illness or disability 33.67% 46.23% 19.79% 30.08% 13.17% 21.44% 6.11% 11.15% n.a. 3.82% n.a. 1.39% Discouragement 30.57% 22.89% 22.65% 16.23% 35.95% 27.62% 27.36% 20.14% n.a. 6.93% n.a. 4.24% Awaiting recall to work 5.55% 4.25% 3.82% 2.87% 11.83% 9.48% 8.66% 6.81% n.a. 7.57% n.a. 5.34% Other reasons 18.47% 14.05% 15.90% 11.92% 37.16% 30.56% 33.41% 27.12% n.a. 53.29% n.a. 49.27% 2 n.a.= probability cannot be estimated since there are no individuals with those specific characteristics. 18 CENTRO Education Primary Secondary Tertiary Sex Male Female Male Female Male Female Age group 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 Inactivity 12.50% 10.68% 17.44% 15.14% 5.76% 4.76% 8.67% 7.29% 3.81% 3.10% 5.94% 4.91% Family/care responsibilities 2.10% 3.44% 17.82% 23.90% 1.13% 1.94% 12.12% 16.94% 1.99% 3.27% 17.24% 23.21% Illness or disability 43.37% 56.36% 27.61% 39.46% 19.39% 29.58% 9.83% 16.75% 3.26% 6.46% 1.16% 2.59% Discouragement 25.94% 18.74% 18.95% 13.09% 30.96% 23.22% 22.99% 16.51% 8.32% 5.28% 5.19% 3.14% Awaiting recall to work 1.98% 1.44% 1.27% 0.90% 4.97% 3.79% 3.39% 2.53% 3.84% 2.88% 2.57% 1.89% Other reasons 31.97% 25.81% 28.45% 22.65% 54.04% 46.84% 50.02% 42.84% 75.57% 69.55% 72.29% 65.93% ÁREA METROPOLITANA DE LISBOA Education Primary Secondary Tertiary Sex Male Female Male Female Male Female Age group 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 Inactivity 9.62% 8.12% 13.78% 11.83% 4.20% 3.43% 6.49% 5.39% 2.70% 2.17% 4.33% 3.54% Family/care responsibilities 9.56% 13.69% 42.20% 50.64% 6.01% 8.99% n.a. 40.87% 9.19% 13.21% n.a. 49.75% Illness or disability 34.22% 46.84% 20.21% 30.61% 13.50% 21.89% n.a. 11.44% 1.86% 3.95% n.a. 1.45% Discouragement 21.83% 15.56% 15.38% 10.47% 26.44% 19.37% n.a. 13.42% 6.47% n.a. 3.99% 2.31% Awaiting recall to work 2.72% 2.01% 1.78% 1.29% 6.50% 5.03% n.a. 3.43% 5.09% 3.88% n.a. 2.60% Other reasons 13.60% 10.04% 11.52% 8.38% 29.86% 23.90% n.a. 20.89% 52.49% 45.29% n.a. 41.32% 19 ALENTEJO Education Primary Secondary Tertiary Sex Male Female Male Female Male Female Age group 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 Inactivity 9.67% 8.17% 13.85% 11.89% 4.23% 3.45% 6.53% 5.43% 2.72% 2.19% 4.36% 3.57% Family/care responsibilities 4.74% 7.25% 28.77% 36.42% 2.76% n.a. n.a. 27.62% 4.52% 6.94% n.a. n.a.
Language:English
Score: 746321.4 - https://www.ilo.org/wcmsp5/gro...ts/publication/wcms_546273.pdf
Data Source: un
The results (Table 7) show that the probability of being inactive decreases the higher the level of education. (...) In Centro young people have a higher probability to be inactive for other reasons (15 per cent), while in the Lisbon Metropolitan Area the probability is higher for disability (by 16.2 per cent). (...) TABLE A2: PROBABILITY 1 2 3 4 5 Care responsibilities Illness/disability Re-entrants Discouraged Other VARIABLES Inactivity among young people (15-29) Age group (15-24=1; 25-29=0) Probability Probability Probability Probability Probability Sex (female=1; male=0) Probability Probability Probability Probability Probability 1.Education: Less than lower secondary Probability Probability Probability Probability Probability 2.Education: Upper secondary Probability Probability Probability Probability Probability 3.Education: Tertiary Probability Probability Probability Probability Probability 4.Region: name X Probability Probability Probability Probability Probability 5.Region: name Y Probability Probability Probability Probability Probability . 17 ANNEX II: Regional breakdown (by characteristics) of average probability of being inactive2 NORTE Education Primary Secondary Tertiary Sex Male Female Male Female Male Female Age group 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 Inactivity 10.92% 9.27% 15.44% 13.33% 4.89% 4.02% 7.46% 6.24% 3.19% 2.57% 5.04% 4.15% Family/care responsibilities 3.49% 5.47% 24.09% 31.18% 1.97% 3.23% 17.10 % 23.04% 3.32% 5.23% 23.40% 30.39% Illness or disability 55.04% 67.50% 38.18% 51.04% 28.44% 40.40% 15.93 % 25.13% 6.05% 11.06% 2.40% 4.94% Discouragement 18.37% 12.80% 12.64% 8.40% 22.57% 16.17% 15.98 % 10.94% 5.05% 3.04% 2.99% 1.71% Awaiting recall to work 6.23% 4.80% 4.32% 3.27% 13.01% 10.49% 9.61% 7.60% 10.60% 8.43% 7.68% 6.00% Other reasons 17.67% 13.38% 4.32% 11.32% 36.02% 29.50% 32.31 % 26.11% 59.21% 52.08% 55.25% 48.05% ALGARVE Education Primary Secondary Tertiary Sex Male Female Male Female Male Female Age group 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 Inactivity 23.56% 20.78% 30.60% 27.41% 12.61% 10.78% 17.57% 15.27% 8.95% 7.54% 12.92% 11.05% Family/care responsibilities 5.65% 8.50% 31.76% 39.68% 3.35% 5.27% 23.53% 30.55% n.a. 8.16% n.a. 38.82% Illness or disability 33.67% 46.23% 19.79% 30.08% 13.17% 21.44% 6.11% 11.15% n.a. 3.82% n.a. 1.39% Discouragement 30.57% 22.89% 22.65% 16.23% 35.95% 27.62% 27.36% 20.14% n.a. 6.93% n.a. 4.24% Awaiting recall to work 5.55% 4.25% 3.82% 2.87% 11.83% 9.48% 8.66% 6.81% n.a. 7.57% n.a. 5.34% Other reasons 18.47% 14.05% 15.90% 11.92% 37.16% 30.56% 33.41% 27.12% n.a. 53.29% n.a. 49.27% 2 n.a.= probability cannot be estimated since there are no individuals with those specific characteristics. 18 CENTRO Education Primary Secondary Tertiary Sex Male Female Male Female Male Female Age group 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 Inactivity 12.50% 10.68% 17.44% 15.14% 5.76% 4.76% 8.67% 7.29% 3.81% 3.10% 5.94% 4.91% Family/care responsibilities 2.10% 3.44% 17.82% 23.90% 1.13% 1.94% 12.12% 16.94% 1.99% 3.27% 17.24% 23.21% Illness or disability 43.37% 56.36% 27.61% 39.46% 19.39% 29.58% 9.83% 16.75% 3.26% 6.46% 1.16% 2.59% Discouragement 25.94% 18.74% 18.95% 13.09% 30.96% 23.22% 22.99% 16.51% 8.32% 5.28% 5.19% 3.14% Awaiting recall to work 1.98% 1.44% 1.27% 0.90% 4.97% 3.79% 3.39% 2.53% 3.84% 2.88% 2.57% 1.89% Other reasons 31.97% 25.81% 28.45% 22.65% 54.04% 46.84% 50.02% 42.84% 75.57% 69.55% 72.29% 65.93% ÁREA METROPOLITANA DE LISBOA Education Primary Secondary Tertiary Sex Male Female Male Female Male Female Age group 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 Inactivity 9.62% 8.12% 13.78% 11.83% 4.20% 3.43% 6.49% 5.39% 2.70% 2.17% 4.33% 3.54% Family/care responsibilities 9.56% 13.69% 42.20% 50.64% 6.01% 8.99% n.a. 40.87% 9.19% 13.21% n.a. 49.75% Illness or disability 34.22% 46.84% 20.21% 30.61% 13.50% 21.89% n.a. 11.44% 1.86% 3.95% n.a. 1.45% Discouragement 21.83% 15.56% 15.38% 10.47% 26.44% 19.37% n.a. 13.42% 6.47% n.a. 3.99% 2.31% Awaiting recall to work 2.72% 2.01% 1.78% 1.29% 6.50% 5.03% n.a. 3.43% 5.09% 3.88% n.a. 2.60% Other reasons 13.60% 10.04% 11.52% 8.38% 29.86% 23.90% n.a. 20.89% 52.49% 45.29% n.a. 41.32% 19 ALENTEJO Education Primary Secondary Tertiary Sex Male Female Male Female Male Female Age group 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 15-24 25-29 Inactivity 9.67% 8.17% 13.85% 11.89% 4.23% 3.45% 6.53% 5.43% 2.72% 2.19% 4.36% 3.57% Family/care responsibilities 4.74% 7.25% 28.77% 36.42% 2.76% n.a. n.a. 27.62% 4.52% 6.94% n.a. n.a.
Language:English
Score: 746321.4 - www.ilo.org/wcmsp5/grou...ts/publication/wcms_546273.pdf
Data Source: un
In contrast, with micro simulation, probabilities are applied to individuals in the popula- tion. (...) The probabilities of first marriage ate a function of a woman's age. (...) Foetal death: spontaneous abortion' Age Probability Age Probability 0.40 0.47 0.50 0.55 12.
Language:English
Score: 745058.1 - https://www.un.org/en/developm...fertility-programmes/chap7.pdf
Data Source: un
Safety Concept & Wording - Hazard A hazard is characterized by its: Severity Probability of occurrence (likelihood)  The severity expresses the consequences of the hazard on flight safety. (...) Safety Concept & Wording – Probability of occurence The probability of occurrence is : • Proportional to the causes of the hazard • Evaluated on a 5 level scale (from frequent to extremely remote) using a probability of occurrence table defined by the ANSP • Can be evaluated with a qualitative or quantitative approach 03/09/2015 ICAO 9859 Probability of occurrence classification table ICAO AFPP French ANSP table © AIRBUS ProSky S.A.S. (...) Safety Concept & Wording - Risk The risk associated to an hazard is the combination of the probability of occurrence and the severity. The acceptability of the risk is evaluated, based on the probability of occurrence and the severity, and using a risk classification matrix (defined by the ANSP).
Language:English
Score: 744628.47 - https://www.icao.int/WACAF/Afr.../7.0%20Safety%20Activities.pdf
Data Source: un
The Indicated category includes Indicated PIIP, Probable TEUR, Probable EUR and Probable SER, all of which have a moderate level of confidence (G1+G2). (...) F1.1 F1.2 F1.3 F2.1 F2.2 F2.3 F3.1 F3.2 F3.3 F4 E1.1 1 2 3 4 E1.2 1 2 3 E2 4 4 4 4 5 E3.1 12 12 12 12 12 12 E3.2 6 6 6 8 9 10 E3.3 7 7 7 7 11 9 Class Sub-class Code GB/T 19492 -2004 Classes and Categories Commercial Projects On Production 1 Proved Developed Reserves Approved for Development 2 Proved Undeveloped EUR Justified for Development 3 Proved Undeveloped EUR Potentially Commercial Projects Development Pending 4 Proved SER, Probable EUR, Probable SER, Possible TEUR Development on Hold 5 Proved SER, Probable EUR, Probable SER, Possible TEUR Non- Commercial Projects Development Unclarified 6 Proved SER, Probable SER, Possible TEUR. (...) Potentially commercial and non-commercial projects sub- categorization 36. The Proved SER, Probable EUR, Probable SER and Possible TEUR in GB/T 19492 -2004 correspond to the UNFC-2009 sub-class “Potentially Commercial Projects”.
Language:English
Score: 744608.06 - https://unece.org/DAM/energy/s...GBT_19492_-2004_and_UNFC-e.pdf
Data Source: un
If in our empirical analysis we find that the probability of war impacts negatively the probability of RTA signature, this is consistent with this view. (...) This directly leads to our third testable implication: Testable implication 3 The frequency of recent wars reduces the probability of RTA formation The previous two results imply that the probability of war and the realizations of war potentially affect the probability of RTA formation in opposite directions. (...) The construction of T̂ is detailed in section 3.2, we know turn to our measurement of war probability, WAR. A natural proxy for this probability is the historical frequency of wars between each country pair.
Language:English
Score: 744344.14 - https://www.wto.org/english/re...tdw_e/wkshop09_e/thoenig_e.pdf
Data Source: un
To be more specific, the encoder should know the concealment probability and output of each macroblock. In packet-switched networks, this calculation is fairly straightforward, because we can directly use packet loss probability to generate macroblock concealment probability. (...) As the parameters in the bit-stream have unequal importance in the decoding result (e.g. header bits are more important than prediction error bits), we cannot directly generate macroblock concealment probability from bit error probability. Moreover, if the receiving terminal does not discard erroneous packets, we cannot generate macroblock concealment probability from the statistics of correctly received packets. (...) For example, the last macroblock of a GOB is more probably concealed than the first macroblock of a GOB.
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Score: 743783.2 - https://www.itu.int/wftp3/av-a...video-site/9910_Red/q15i55.doc
Data Source: un
Have they stayed ent from focusing on testing individuals with the highest closer than 6 feet or stayed in the same room for a probability of infection, which is what current systems while? (...) However, a reasonable model would be Example: Assume that two individuals and are in- to use a concave function of time to estimate the fected with probabilities 0.1 and 0.3, respectively. How- link probability. ever, assume that the expected number of individuals that encounters is 50 times larger than the expected • Testing results. (...) To do this, one way is to Such an integration can yield us the following kind of interpret the probability that a person is infected given improvements: the partial observations, such as (“noisy”) contact graph or test results of a few individuals from the graph etc. • Reduced inaccuracies and better estimates of the These algorithms could be based upon the susceptibil- link probabilities.
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Score: 743783.2 - https://www.itu.int/en/publica.../files/basic-html/page114.html
Data Source: un