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  Mapping of IMDRF essential principles to AI for health software - Att.1 - Spreadsheets for cluster c

., safely implement updates) 5.8.2 98 Informed consent 5.2.2 182 Instructions 5.12.1 199 Instructions 5.12.2 54 Intended usage environment 5.1.5 23 Intended use 5.1.2 62 Intended use 5.1.6 178 Intended use 5.12.1 222 Intended use 5.12.3 273 Intended use 7.2.1 293 Intended use 7.2.4 297 Intended use environment 7.2.4 295 Intended user 7.2.4 2 Intendeded conditions of use 5.1.1 212 Interpretation of results 5.12.2 155 IT networks characteristics 5.8.4 157 IT security measures 5.8.4 174 Lay user 5.12.1 188 Lay user 5.12.2 214 Lay users 5.12.3 100 Leftover specimen 5.2.2 265 Likelihood ratios 7.2.1 17 MD life cycle 5.1.2 251 Measuring interval/range 7.2.1 147 Memory 5.8.3 151 Minimum requirements 5.8.4 139 Mobile computing platforms 5.8.3 192 Near-patient testing 5.12.2 218 Near-patient testing 5.12.3 263 Negative predictive value 7.2.1 285 Numerical values 7.2.3 6 Patient benefits 5.1.1 4 Perform as intended 5.1.1 1 Performance 5.1.1 14 Performance 5.1.2 117 Performance 5.8.1 169 Performance 5.10.1 224 Performance 5.12.3 233 Performance characteristics 7.2.1 291 Performance evaluation 7.2.4 261 Positive predictive value 7.2.1 96 Pre-study protocol review 5.2.2 113 Precision 5.8.1 311 Prevalence rates 7.2.4 126 Principles of development life cycle (e.g., rapid development cycles, frequent changes, the cumulative effect of changes) 5.8.2 159 Protection against unauthorized access 5.8.4 163 Protection against unauthorized access 5.8.5 81 Published scientific literature 5.2.1 11 Quality 5.1.2 283 Reference materials of higher order 7.2.2 281 Reference measurement procedures 7.2.2 299 Relevant population 7.2.4 111 Reliability 5.8.1 309 Representative population 7.2.4 48 Residual risk information for user 5.1.4 90 Rights 5.2.2 22 Risk 5.1.2 70 Risk 5.1.9 26 Risk control 5.1.2 38 Risk control 5.1.3 32 Risk control measures 5.1.3 25 Risk elimination 5.1.2 128 Risk management (e.g., changes to system, environment, and data) 5.8.2 20 Risk management plan 5.1.2 9 Risk management system 5.1.2 208 Risk of error 5.12.2 50 Risk reduction 5.1.5 52 Risk reduction 5.1.5 121 Risk reduction 5.8.1 201 Risk reduction 5.12.2 206 Risk reduction 5.12.2 42 Risks that cannot be eliminated 5.1.3 39 Safe design 5.1.3 3 Safety 5.1.1 12 Safety 5.1.2 92 Safety 5.2.2 115 Safety 5.8.1 167 Safety 5.10.1 195 Safety 5.12.2 34 Safety principles compliance 5.1.3 176 Self-testing 5.12.1 190 Self-testing 5.12.2 216 Self-testing 5.12.3 67 Shelf life 5.1.8 72 Side-effects 5.1.9 119 Single fault conditions 5.8.1 141 Size 5.8.3 105 Software 5.8.1 107 Software as a medical device 5.8.1 253 Specimen stability 7.2.1 65 Stability 5.1.8 287 Standardized units 7.2.3 36 State of the art 5.1.3 124 State of the art 5.8.2 241 State of the art 7.2.1 60 Stress resistance 5.1.6 243 Traceability of calibrators and controls 7.2.1 279 Traceability of values 7.2.2 203 Training 5.12.2 30 Update control measures 5.1.2 18 Updating 5.1.2 180 Usage variations (user technique, usage environment) 5.12.1 46 User training 5.1.3 289 User understanding 7.2.3 230 Valid result 5.12.3 134 Validation 5.8.2 239 Validation 7.2.1 269 Validation 7.2.1 132 Verification 5.8.2 220 Verification 5.12.3 226 Warning 5.12.3 94 Well-being 5.2.2 &A Page &P ep key concepts with clusters Chronology Keyword Section Cluster 1 Cluster 2 Cluster 3 1 Performance 5.1.1 Analytical performance Clinical performance 2 Intendeded conditions of use 5.1.1 Intended use 3 Safety 5.1.1 Safety 4 Perform as intended 5.1.1 Intended use Safety 5 Acceptable risks 5.1.1 Risk and Alarms 6 Patient benefits 5.1.1 Benefit-risk Clinical performance 7 Health 5.1.1 Clinical performance 9 Risk management system 5.1.2 Risk and Alarms 11 Quality 5.1.2 Analytical performance Clinical performance 12 Safety 5.1.2 Safety 14 Performance 5.1.2 Analytical performance Clinical performance 15 Continuous, iterative risk management 5.1.2 Risk and Alarms 17 MD life cycle 5.1.2 Life cycle 18 Updating 5.1.2 Control Safety 20 Risk management plan 5.1.2 Risk and Alarms 21 Identify and analyze hazards 5.1.2 Risk and Alarms Safety 22 Risk 5.1.2 Risk and Alarms 23 Intended use 5.1.2 Intended use 24 Foreseeable misuse 5.1.2 Safety Risk and Alarms 25 Risk elimination 5.1.2 Risk and Alarms 26 Risk control 5.1.2 Risk and Alarms 27 Continuous, iterative risk management 5.1.2 Risk and Alarms 28 Continuous, iterative risk management 5.1.2 Risk and Alarms 30 Update control measures 5.1.2 Control Safety 32 Risk control measures 5.1.3 Risk and Alarms 34 Safety principles compliance 5.1.3 Safety 36 State of the art 5.1.3 38 Risk control 5.1.3 Risk and Alarms 39 Safe design 5.1.3 Safety 40 Alarms 5.1.3 Risk and Alarms Safety 42 Risks that cannot be eliminated 5.1.3 Risk and Alarms Documentation 44 Alarms 5.1.3 Risk and Alarms 46 User training 5.1.3 Documentation Intended user 48 Residual risk information for user 5.1.4 Documentation Intended use 50 Risk reduction 5.1.5 Risk and Alarms 52 Risk reduction 5.1.5 Risk and Alarms 54 Intended usage environment 5.1.5 Intended use Documentation 57 Consider user knowledge 5.1.5 Intended user 60 Stress resistance 5.1.6 Safety External factors 62 Intended use 5.1.6 Intended use 63 Expected life of device 5.1.6 Documentation Safety 65 Stability 5.1.8 Life cycle Change management Data quality 67 Shelf life 5.1.8 Life cycle 70 Risk 5.1.9 Risk and Alarms 72 Side-effects 5.1.9 Risk and Alarms 75 Clinical evaluation 5.2.1 Clinical performance 77 Benefit-risk determination 5.2.1 Benefit-risk 79 Clinical investigation report 5.2.1 Clinical performance 81 Published scientific literature 5.2.1 Clinical performance 83 Clinical experience 5.2.1 Clinical performance 86 Ehtical prinicples 5.2.2 Ethical compliance 88 Declaration of Helsinki 5.2.2 Ethical compliance 90 Rights 5.2.2 Ethical compliance 92 Safety 5.2.2 Safety 94 Well-being 5.2.2 Benefit-risk Clinical performance 96 Pre-study protocol review 5.2.2 Ethical compliance 98 Informed consent 5.2.2 Ethical compliance 100 Leftover specimen 5.2.2 Ethical compliance 103 Electronic programmable systems 5.8.1 Software 105 Software 5.8.1 107 Software as a medical device 5.8.1 109 Accuracy 5.8.1 Analytical performance Safety 111 Reliability 5.8.1 Analytical performance Technical interfaces 113 Precision 5.8.1 Safety Analytical performance 115 Safety 5.8.1 Safety 117 Performance 5.8.1 Analytical performance Intended use 119 Single fault conditions 5.8.1 Risk and Alarms 121 Risk reduction 5.8.1 Risk and Alarms 124 State of the art 5.8.2 126 Principles of development life cycle (e.g., rapid development cycles, frequent changes, the cumulative effect of changes) 5.8.2 Life cycle Safety 128 Risk management (e.g., changes to system, environment, and data) 5.8.2 Risk and Alarms 130 Information security (e.g., safely implement updates) 5.8.2 Technical interfaces 132 Verification 5.8.2 Analytical performance Control 134 Validation 5.8.2 Analytical performance Control 136 Change management process 5.8.2 Change management 139 Mobile computing platforms 5.8.3 Technical interfaces 141 Size 5.8.3 Technical interfaces 143 Contrast ratio of the screen 5.8.3 Technical interfaces 145 Connectivity 5.8.3 Technical interfaces 147 Memory 5.8.3 Technical interfaces 149 External factors related to their use (varying environment as regards level of light or noise) 5.8.3 External factors 151 Minimum requirements 5.8.4 Technical interfaces 153 Hardware 5.8.4 Technical interfaces 155 IT networks characteristics 5.8.4 Technical interfaces 157 IT security measures 5.8.4 Technical interfaces 159 Protection against unauthorized access 5.8.4 Safety Technical interfaces 161 Cybersecurity 5.8.5 Technical interfaces Safety Documentation 163 Protection against unauthorized access 5.8.5 Safety Technical interfaces 165 Information [Manual] 5.10.1 Documentation Intended use 167 Safety 5.10.1 Safety 169 Performance 5.10.1 Documentation Intended user 171 Easily understood 5.10.1 Explainability Intended user Intended use 174 Lay user 5.12.1 Intended user 176 Self-testing 5.12.1 Intended use Intended user 178 Intended use 5.12.1 Intended use 180 Usage variations (user technique, usage environment) 5.12.1 Intended use Intended user 182 Instructions 5.12.1 Documentation Intended use 184 Easy to understand 5.12.1 Explainability Intended user 186 Easy to apply 5.12.1 Intended user Documentation 188 Lay user 5.12.2 Intended user 190 Self-testing 5.12.2 Intended use Intended user 192 Near-patient testing 5.12.2 Safety Intended user Intended use 195 Safety 5.12.2 Safety 197 Accuracy 5.12.2 Analytical performance 199 Instructions 5.12.2 Documentation Intended use 201 Risk reduction 5.12.2 Risk and Alarms 203 Training 5.12.2 Documentation Intended user 206 Risk reduction 5.12.2 Risk and Alarms 208 Risk of error 5.12.2 Risk and Alarms 210 Handling 5.12.2 Documentation Intended use 212 Interpretation of results 5.12.2 Interpretability Intended user 214 Lay users 5.12.3 Intended user 216 Self-testing 5.12.3 Intended use Intended user 218 Near-patient testing 5.12.3 Safety Intended user 220 Verification 5.12.3 Analytical performance Control 222 Intended use 5.12.3 Intended use 224 Performance 5.12.3 Safety Intended user 226 Warning 5.12.3 Risk and Alarms Safety 228 Failure 5.12.3 Safety Risk and Alarms 230 Valid result 5.12.3 233 Performance characteristics 7.2.1 Analytical performance Clinical performance 235 Analytical performance 7.2.1 Analytical performance 237 Clinical performance 7.2.1 Clinical performance 239 Validation 7.2.1 Analytical performance Control 241 State of the art 7.2.1 243 Traceability of calibrators and controls 7.2.1 Analytical performance 245 Accuracy of measurements (trueness and precision) 7.2.1 Analytical performance Measurements 247 Analytical sensitivity/Limit of detection 7.2.1 Analytical performance 249 Analytical specificity 7.2.1 Analytical performance 251 Measuring interval/range 7.2.1 Analytical performance 253 Specimen stability 7.2.1 Analytical performance 255 Clinical performance 7.2.1 Clinical performance 257 Diagnostic/clinical sensitivity 7.2.1 Clinical performance 259 Diagnostic/clinical specificity 7.2.1 Clinical performance 261 Positive predictive value 7.2.1 Clinical performance 263 Negative predictive value 7.2.1 Clinical performance 265 Likelihood ratios 7.2.1 Clinical performance 267 Expected values in normal and affected populations. 7.2.1 Clinical performance 269 Validation 7.2.1 Analytical performance Control 271 Control procedures 7.2.1 Safety Control 273 Intended use 7.2.1 Intended use 275 Calibrators 7.2.2 Measurements Analytical performance 277 Control materials 7.2.2 Measurements Analytical performance 279 Traceability of values 7.2.2 Measurements Data quality 281 Reference measurement procedures 7.2.2 Measurements Data quality 283 Reference materials of higher order 7.2.2 Measurements Data quality 285 Numerical values 7.2.3 Interpretability 287 Standardized units 7.2.3 Measurements Data quality Change management 289 User understanding 7.2.3 Documentation Intended user Change management 291 Performance evaluation 7.2.4 Intended user Intended use 293 Intended use 7.2.4 Intended use 295 Intended user 7.2.4 Intended user Explainability 297 Intended use environment 7.2.4 Intended use 299 Relevant population 7.2.4 Clinical performance Data quality 301 Appropriate representation 7.2.4 Intended use Data quality 303 Ethnicity 7.2.4 Data quality Clinical performance 305 Gender 7.2.4 Clinical performance 307 Genetic diversity 7.2.4 Clinical performance 309 Representative population 7.2.4 Clinical performance Data quality 311 Prevalence rates 7.2.4 Clinical performance Data quality &"Times New Roman,Regular"&12&A &"Times New Roman,Regular"&12Page &P ai4h concepts with clusters Super-cluster name Cluster-name AI4H concept name Super-cluster ID Cluster ID AI4H concept ID Performance Analytical performance Two-class classification metrics A a 1 Performance Analytical performance Mutli-class classification metrics A a 2 Performance Analytical performance Regression metrics A a 3 Life Cycle Change management Evolution of the AI algorithm D a 1 Risk and Control Control Cross-validation B a 1 Risk and Control Control Statistical tests B a 2 Risk and Control Control Information criteria B a 3 Risk and Control Control Robustness validation B a 4 Risk and Control Control Out of sample testing B a 5 Risk and Control Control Attribution methods B a 6 Risk and Control Data quality Data diversity B b 1 Risk and Control Data quality Preprocessing B b 2 Risk and Control Data quality Normalization B b 3 Risk and Control Data quality Expert labels B b 4 Risk and Control Data quality Data collection procedure B b 5 Usability and Documentation Documentation Datasheets for data sets C a 1 Usability and Documentation Documentation Modelcards for ML models C a 2 Ethical Compliance Ethical Compliance FAT optimization objectives (“FAT training”) F a 1 Ethical Compliance Ethical Compliance FAT validation F a 2 Ethical Compliance Ethical Compliance Data acceptance and handling F a 3 Ethical Compliance Ethical Compliance Patient consent F a 4 Usability and Documentation Explainability see B) Risk and Control a) Control 6) Attribution methods (“Explainable AI (XAI)”) C b 1 Usability and Documentation Explainability Counterfactual explanations C b 2 Usability and Documentation Intended use Specification for inputs C c 1 Usability and Documentation Intended use see C) Usability and Documentation a) Documentation 1) Datasheets for data sets C c 2 Usability and Documentation Intended use see C) Usability and Documentation a) Documentation 2) Modelcards for ML models C c 3 Usability and Documentation Interpretability see B) Risk and Control a) Control 6) Attribution methods (“Explainable AI (XAI)”) C e 1 Life Cycle Life Cycle AI software life cycle D b 1 Performance Measurements see B) Risk and Control b) Data quality A d 1 Risk and Control Risk and Alarms Uncertainty quantification B c 1 Risk and Control Risk and Alarms Outlier detection B c 2 Risk and Control Safety Robust training B d 1 Dependencies Technical Interfaces Compression of AI4H models E b 1 Dependencies Technical Interfaces Response time E b 2 Dependencies Technical Interfaces Memory E b 3 Dependencies Technical Interfaces Compute E b 4 Dependencies Technical Interfaces Networking E b 5 Dependencies Technical Interfaces Operating system E b 6 Dependencies Technical Interfaces Displays E b 7 Dependencies Technical Interfaces Sensors for input data E b 8 &"Times New Roman,Regular"&12&A &"Times New Roman,Regular"&12Page &P clusters with super-clusters Clusters Super-clusters My order Analytical performance Performance 1 Benefit-risk Performance 1 Clinical performance Performance 1 Measurements Performance 1 Control Risk and control 2 Data quality Risk and control 2 Risk and Alarms Risk and control 2 Safety Risk and control 2 Documentation Usability and documentation 3 Explainability Usability and documentation 3 Intended use Usability and documentation 3 Intended user Usability and documentation 3 Interpretability Usability and documentation 3 Change management Life cycle 4 Life cycle Life cycle 4 External factors Dependencies 5 Technical interfaces Dependencies 5 Ethical compliance Ethical compliance 6 Software &"Times New Roman,Regular"&12&A &"Times New Roman,Regular"&12Page &P

Score: 681602.05 - https://www.itu.int/en/ITU-T/f...ents/all/FGAI4H-G-038-A01.xlsx

  PowerPoint Presentation

This information is subject to Sprint policies regarding use and is the property of Sprint and/or its relevant affiliates and may contain restricted, confidential or privileged materials intended for the sole use of the intended recipient. (...) This information is subject to Sprint policies regarding use and is the property of Sprint and/or its relevant affiliates and may contain restricted, confidential or privileged materials intended for the sole use of the intended recipient. (...) This information is subject to Sprint policies regarding use and is the property of Sprint and/or its relevant affiliates and may contain restricted, confidential or privileged materials intended for the sole use of the intended recipient.

Score: 674179.6 - https://www.itu.int/en/ITU-T/W.../Seth_Bravin_Presentation_.pdf

  SCG Iran ITU Event 2019 07 06

The ability to share data across domains is contributing to new learnings and innovations Source: Synergy Consulting Group 11 This document is confidential & proprietary, intended for the sole internal company use of its intended recipient 42% 43% 40% 35% 33% 34% 33% 46% 38% 34% 38% 37% 30% 33% Analytics, Big data Digital strategy, Financial Modeling Digital marketing Security, privacy, risk, complaince Smart product dev. (...) Today In 3 Yrs Critical skills gaps for digital transformation THE DIGITAL TALENT GAP But it is the “hard” business and technical skills that have the highest gaps for organizations undergoing digital transformaiton Source: Cognizant, 2018 12 This document is confidential & proprietary, intended for the sole internal company use of its intended recipient 0.42 0.30 0.23 0.22 0.19 0.16 0.15 0.15 0.14 0.12 0.11 0.10 0.10 0.10 0.09 0.08 0.06 0.06 IC T M ed ia Pr of es sio na l S er vic es Av iat ion M an uf ac tu rin g Fin an cia l S er vic es Ph ar m a Ut ilit ies Co ns um er G oo ds M ini ng Ed uc at ion Ho sp ita lit y Re ta il Tr an sp or t Re al Es ta te Go ve rn m en t Co ns tru ct ion He alt hc ar e Global: Workforce digital skills readiness index by sector (Q4 2018) THE DIGITAL TALENT GAP Across the 18 industries we surveyed globally, aside from the ICT industry sector, most others are still in need of further digital skills development Source: Synergy Consulting Group’s Workforce Digital Skills Readiness Survey, 2018 Q4 Note: Index is a calculation based on % of employees having working knowledge of at least one digital sub-skill 13 This document is confidential & proprietary, intended for the sole internal company use of its intended recipient Di git al Op s Ag ile , S CR UM , D ev Op s An aly tic s & D at a S cie nc e De sig n T hin kin g & CX M AP Is, Ec os ys te m , P lat fo rm s Di git al M ar ke tin g Co din g & P ro gr am m ing Vi rtu ali za tio n & Cl ou d Di git al Ch an ne ls Cy be rse cu rit y Global: Workforce digital skills readiness by skill type (2018) THE DIGITAL TALENT GAP Across all industries and countries, firms have focused on developing skills required for digitizing operations, agile, DevOps, analytics and customer experience management Source: Synergy Consulting Group’s Workforce Digital Skills Readiness Survey, 2018 Q4 Note: Index is a calculation based on % of employees having working knowledge of at least one digital sub-skill 14 This document is confidential & proprietary, intended for the sole internal company use of its intended recipient 0.28 0.21 0.21 0.21 0.20 0.19 0.18 0.16 0.16 0.15 0.14 0.13 0.12 0.11 0.10 Si ng ap or e Au str ali a De nm ar k Sw ed en Ne w Ze ala nd UK US A Ca na da UA E Ne th er lan ds Tu rk ey Eg yp t RS A Sa ud i Re st of P GC C Global: Workforce digital skills readiness index by country (Q4 2018) THE DIGITAL TALENT GAP The Middle Eastern countries have some ways to go to reach the level of workforce digital skills readiness of leading countries such as Singapore & Australia Source: Synergy Consulting Group’s Workforce Digital Skills Readiness Survey, 2018 Q4 Note: Index is a calculation based on % of employees having working knowledge of at least one digital sub-skill 15 This document is confidential & proprietary, intended for the sole internal company use of its intended recipient Design Thinking & CX THE DIGITAL TALENT GAP From one sample industry (banking) we see that the Middle Eastern countries are ranked low in workforce digital skills readiness across most skills categories Overall Digital Market- ing Digital channel Digital Ops Eco- system mangmt Analytic & data science Virtual- ization, cloud Agile, DevOps Coding, program -mming Cyber- security Netherlands Canada Singapore Australia New Zealand UK USA Denmark Sweden South Africa UAE Saudi Rest of PGCC Egypt Source: Synergy Consulting Group’s Workforce Digital Skills Readiness Survey, 2018 Q4 Turkey 75+ score 50-74 score 25-49 score 0-24 score 16 This document is confidential & proprietary, intended for the sole internal company use of its intended recipient MEA US, Canada SEA, Oceana W. (...) Europe Source: Synergy Consulting Group’s Workforce Digital Skills Readiness Survey, 2018 Q4 17 This document is confidential & proprietary, intended for the sole internal company use of its intended recipient Telco sector Bank sector THE DIGITAL TALENT GAP And our survey findings demonstrate that the gap in workforce digital skills between digital leader firms vs laggards is substantial Source: Synergy Consulting Group’s Workforce Digital Readiness Survey, 2018 Q4 Note: Index is a calculation based on % of employees having working knowledge of at least one digital sub-skill 37% 26% 18% 13% Digital Leader Digitally Mature Digitally Developing Digital Laggard 2.9x 34% 25% 17% 11% Digital Leader Digitally Mature Digitally Developing Digital Laggard 3.1x 18 This document is confidential & proprietary, intended for the sole internal company use of its intended recipient Talent gap of organizations by firm digital maturity THE DIGITAL TALENT GAP But not only are digital laggards far behind in skills readiness, they also find it very hard to attract and retain digital talent compared to digital leaders 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1 2 3 4 5 6 7 8 9 10 We can attract digital talent Our digital talent gap Digital laggards Digitally developing Digitally maturing Source: MITSloan Survey, 2016 Digital laggards find it hard to attract & retain digital talent 19 This document is confidential & proprietary, intended for the sole internal company use of its intended recipient 13% 29% 59% Early in digital transformation Digitally developing Digitally mature Question asked: am satisfied with how my organization is helping me prepare for the changes necessary for working in a digital environment Organization’s level of support in enabling workforce skills updating by digital maturity (% of respondents) THE DIGITAL TALENT GAP One of the reasons digital leaders have a higher workforce digital skills readiness is their focus on developing and updating their employees’ skills Source: MIT Sloan Survey, 2018 20 This document is confidential & proprietary, intended for the sole internal company use of its intended recipient Utilize consultants Utilize consultants Digital Laggards Digitally Mature Digital Leaders External partnerships Develop employees Develop employees External partnerships Recruit digital employees Recruit digital leaders Utilize consultants External partnerships Recruit digital employees M ai n m et ho ds o f f ill in g di gi ta l t al en t g ap s Source: Synergy Consulting Group But if you are at the beginning of your digital transformation journey, how do you manage to fill your skills gaps in the short term?

Score: 668738.6 - https://www.itu.int/en/ITU-D/R...U%20Event%202019%2007%2006.pdf

  Decision on Motion to Specify the Documents Disclosed by the Prosecutor's that Delalic's Defence Int

Decision on Motion to Specify the Documents Disclosed by the Prosecutor's that Delalic's Defence Intends to Use as Evidence IN THE TRIAL CHAMBER Before: Judge Adolphus G. (...) The Defence therefore asserted that, similarly, there is no obligation on the Defence under the Rules to supply a list of the documents which it intends to use at trial.   III. FINDINGS   6. The Prosecution asserts that Sub-rule 67(C) obliges the Defence to indicate which documents it intends to use at trial, so that the Prosecution can prepare itself and inspect properly those documents. (...) This Motion is, in other words, not intended to obtain the disclosure of particular documents, but, on the contrary, to gain an insight into the Defence’s strategy at trial. 7.

Score: 667376.95 - https://www.icty.org/x/cases/mucic/tdec/en/70908EV25719.htm

  Ex-CROs-Analysis

“System of certification of electrical equipment intended for use in explosive atmospheres», 7 Contents Common Regulatory Objectives for equipment intended for use in explosive atmospheres developed by the UNECE Working Party on Regulatory Cooperation and Standardization Policies (WP. 6) IEC System for Certification to Standards relating to Equipment for use in Explosive Atmospheres (IECEx System) IECEx 01 1.Title DIRECTIVE 94/9/EC OF THE EUROPEAN PARLIAMENT AND THE COUNCIL of 23 March 1994 on the approximation of the laws of the Member States concerning equipment and protective systems intended for use in potentially explosive atmospheres - АТЕХ Russia document). 12. (...) Technical regulations «On safety of equipment intended for use in explosive atmospheres» 8 Contents Common Regulatory Objectives for equipment intended for use in explosive atmospheres developed by the UNECE Working Party on Regulatory Cooperation and Standardization Policies (WP. 6) IEC System for Certification to Standards relating to Equipment for use in Explosive Atmospheres (IECEx System) IECEx 01 1.Title DIRECTIVE 94/9/EC OF THE EUROPEAN PARLIAMENT AND THE COUNCIL of 23 March 1994 on the approximation of the laws of the Member States concerning equipment and protective systems intended for use in potentially explosive atmospheres - АТЕХ Russia 19. (...) The documentation accompanying the equipment has to cover instructions about the intended use, and details for installation and repair.

Score: 665293.26 - https://unece.org/DAM/trade/wp...vironment/Ex-CROs-Analysis.pdf

  PowerPoint-Präsentation

Changes in - performance - input / types of input - intended use Snapshot + Continuous? Drift? Jo ha nn es S ta rli ng er A I4 H ea lth W G -C E 10 /2 02 0 mailto:johannes@starlinger.plus johannes@starlinger.plus - AI4Health WG-CE 2020 Tech Company Regulatory Clinical Evaluation Task Claim Build AI Deklare Proove Theme Business Strategy Data Availability Intended Use Study Design When Which indication(s)? (...) Changes in - performance - input / types of input - intended use Snapshot + Continuous? Drift? Jo ha nn es S ta rli ng er A I4 H ea lth W G -C E 10 /2 02 0 mailto:johannes@starlinger.plus johannes@starlinger.plus - AI4Health WG-CE 2020 Tech Company Regulatory Clinical Evaluation Task Claim Build AI Deklare Proove Theme Business Strategy Data Availability Intended Use Study Design When Which indication(s)? (...) Changes in - performance - input / types of input - intended use Snapshot + Continuous? Drift? Jo ha nn es S ta rli ng er A I4 H ea lth W G -C E 10 /2 02 0 mailto:johannes@starlinger.plus johannes@starlinger.plus - AI4Health WG-CE 2020 Tech Company Regulatory Clinical Evaluation Task Claim Build AI Deklare Proove Theme Business Strategy Data Availability Intended Use Study Design When Which indication(s)?

Score: 660244.43 - https://www.itu.int/en/ITU-T/f...ents/ws/2010_presentation3.pdf

  Order on Defendant's Request for Relief from the Trial Chamber's Order of 31 August 1998

Clark Street, Suite 3100 Chicago, IL USA 60601 Telephone: (312) 641-6888 Facsimile: (312) 641-6895   THIS TRIAL CHAMBER of the International Tribunal for the Prosecution of Persons Responsible for Serious Violations of International Humanitarian Law Committed in the Territory of the Former Yugoslavia since 1991 ("the Tribunal"), BEING SEISED of the confidential "Defendant’s Request for Relief from the Trial Chamber’s Order of 31 August 1998" (Official Record at Registry Page ("RP") D1957 - D1956) filed on 18 September 1998 ("the Request"); NOTING its Order of 31 August 1998 ("the Order"), in which the Trial Chamber ordered the Defence to "notify the Prosecution and the Trial Chamber by 21 September 1998 of the names of the Defence witnesses which it wishes to recall and any other witnesses which it intends to call"; CONSIDERING that certain documents, if relevant, as of 18 September 1998, have not yet been produced to the Defence; CONSIDERING the Defendant’s Requests for a stay of the Trial Chamber’s Order of 31 August 1998 as well as to "grant the Defence 14 days from the time it receives the documents….to determine which witnesses it intends to call"; PURSUANT to Rule 54 of its Rules of Procedure and Evidence; HEREBY ORDERS that: 1. paragraphs 2(b), (c), (d) and (e), and 3(b) and (c) of the Order of 31 August 1998 are stayed; 2. the Defence shall: (a) notify the Prosecution and the Trial Chamber, within 14 days of it receiving the documents, if relevant, of the names of the Defence witnesses which it wishes to recall and any other witnesses which it intends to call; (b) file by the above date of notification (in sub-paragraph (b)) the statements of any new witnesses which it intends to call; (c) where relevant, notify the Prosecution and the Trial Chamber, within 14 days of receiving the names of any witnesses which the Prosecution intends to call in rebuttal, of the names of any witnesses which it intends to call in rejoinder; (d)file by the above date of notification (in sub-paragraph (c)) the statements of any witnesses which it intends to call in rejoinder; 3. the Prosecution shall: (a)where relevant, notify the Defence and the Trial Chamber within 5 days of receiving the notification in terms of paragraph 2(a) of this Order, of the names of any witnesses which it intends to call in rebuttal; and (b)file by the above date (in sub-paragraph (a)) the statements of any witnesses which it intends to call in rebuttal.

Score: 660207.8 - https://www.icty.org/x/cases/furundzija/tord/en/80921MS2.htm

  Fertility Prospects in Israel: Ever Below Replacement Level? Sergio DellaPergola The S. Argov Chair

ACTUAL AND INTENDED PARITY TRANSITIONS ISRAEL, MARRIED JEWS, 2005 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0-1 1-2 2-3 3-4 4-5 Parity transition Women actual Men actual Women intended Men intended NUMBER OF INTENDEDa VS. (...) Same number of children Intended and Appropriate. e. Number of children Appropriate 3, 4, or 5, and fewer children Intended. f. (...) Source: Survey of Attitudes and Behaviors Concerning Family Size among Israel’s Jewish Population 2005 Logistic regression odd ratios for selected characteristics of Jewish couples with consistent intended and appropriate n. of children – Israel, 2005 0.000 0.500 1.000 1.500 2.000 2.500 3.000 3.500 4.000 4.500 5.000 0-2 3 4 5+ Intended & Appropriate Children O dd s R at io s 24-29 30-34 35-39 40+ Age 0.010 0.100 1.000 10.000 100.000 0-2 3 4 5+ Intended & Appropriate Children O dd s R at io s (L og S ca le ) Secular end Secular orientation Intermediate Religious orientation Religious end Religiosity 0.000 0.200 0.400 0.600 0.800 1.000 1.200 1.400 1.600 1.800 2.000 0-2 3 4 5+ Intended & Appropriate Children O dd s R at io s <12 12 13-16 17+ Education 0.000 0.200 0.400 0.600 0.800 1.000 1.200 1.400 0-2 3 4 5+ Intended & Appropriate Children O dd s R at io s (L og S ca le ) Much better Somewhat better Same Somewhat worse Much worse Family economic situation Source: Survey of Attitudes and Behaviors Concerning Family Size among Israel’s Jewish Population, 2005 ALTERNATIVE EXPLANATIONS OF INCONSISTENCIES: INTENDED > APPROPRIATE TOTAL CHILDREN N. of children appropriate to repondent’s social status N. of children actually intended by respondent N. of children actually intended by respondent N. of children appropriate to repondent’s social status Wish to out-perform appropriate social norm, investing more of own resources Fear to out-perform appropriate social norm, lacking necessary own resources Logistic regression odd ratios for selected characteristics of Jewish couples with inconsistent intended and appropriate n. of children – Israel, 2005 0 1 2 3 4 5 6 7 8 9 10 11 12 24-29 30-34 35-39 40+ Age O dd R at io s Intended LOWER than Appropriate Intended HIGHER than Appropriate 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 Secular end Secular orientation Intermediate Religious orientation Religious end Religiosity O dd R at io s Intended LOWER than Appropriate Intended HIGHER than Appropriate 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 <12 12 13-16 17+ Education O dd R at io s Intended LOWER than Appropriate Intended HIGHER than Appropriate 0 1 2 3 4 5 6 7 8 9 Much better than others Somewhat better Same+don’t know Somewhat worse Much worse Family's economic situation O dd R at io s Intended LOWER than Appropriate Intended HIGHER than Appropriate Source: Survey of Attitudes and Behaviors Concerning Family Size among Israel’s Jewish Population, 2005 DIRECT AND INDIRECT SOCIETAL ROLES OF VALUES AND NORMS AFFECTING FAMILY AND REPRODUCTION IN ISRAEL Desirability History and society Social values and norms: Family and reproduction Legislative, executive, judiciary system Social policies: Family and reproduction Demographic trends: Family and reproduction Feasibility Main factor affecting having one additional child above number intended – Currently married Jewish women, Israel, 2005 Number of Intended vs.

Score: 659381.15 - https://www.un.org/en/developm...f/expert/15.5/DellaPergola.pdf

  DEL07C: AI technical test metric specification

Method Description b. Intended Use c. AI Requirements d. Data Requirements e. (...) Method Description b. Intended Use c. AI Requirements d. Data Requirements e. (...) Method Description b. Intended Use c. AI Requirements d. Data Requirements e.

Score: 657288.57 - https://www.itu.int/en/ITU-T/f...ents/all/FGAI4H-G-207-A03.docx

  Gender and forestry

Gender Mainstreaming in Forestry in Africa - Zambia (2007) This is a study on Gender Mainstreming in Zambia intended to assess the gender balance and responsibilities in the management and use of forest resources. (...) Gender Mainstreaming in Forestry in Africa – Ghana (2007) This is a study on Gender Mainstreming in Ghana intended to assess the gender balance and responsibilities in the management and use of forest resources. (...) Gender Mainstreaming in Forestry in Africa - Kenya (2007) This is a study on Gender Mainstreming in Kenya intended to assess the gender balance and responsibilities in the management and use of forest resources.

Score: 654919.3 - https://www.fao.org/forestry/gender/91553/en/