LIST OF TABLES AND FIGURES a) Each volume shall contain a list of all tables and figures within that volume.
b) The List of Tables and Figures will not count against the page limitations for their respective volumes.
LIST OF TABLES AND FIGURES. Table 4.1: Human-machine interaction touchpoints… 124-126 Figure 2.1: Operation of an anti-personnel mine 32 Figure 2.2: Manually-operated weapon system… 34 Figure 2.3: Lethal autonomous weapon system… 35 Figure 2.4: Deep neural network and its hidden layers… 63 Figure 2.5: A RNN’s take on breakfast… 64 Figure 2.6: Adversarial images… 80 Figure 2.7: Adversarial objects… 80 Figure 2.8: A simplified two-dimensional manifold… 82 Figure 5.1: Targeting categories… 147 Figure 5.2: The engagement continuum… 151 Figure 5.3: The NATO Joint Targeting Cycle… 152 Figure 5.4: The US Joint Targeting Cycle 152 Figures 5.5-5.8: Various targeting activities undertaken by a range of battle staffs ……………………………………………………………………………………...172 Figure 6.1: Establishing the ‘ground truth’ in a relatively complex environment… 191 Figure 7.1: The chronology of targeting 264 Figure 8.1: Alternative deployment scenarios and the ‘threshold of lawfulness’… 282 A2/AD Anti-access/area-denial AI Artificial intelligence AMW Air and Missile Warfare (Manual) AP I Additional Protocol I ATR Automatic Target Recognition CCM Convention on Cluster Munitions CCW Convention on Certain Conventional Weapons CDEM Collateral Damage Estimation Methodology CIHL Customary International Humanitarian Law Study CNN Convolutional neural network CODE Collaborative Operations in Denied Environments DARPA Defense Advanced Research Projects Agency DMA Definite military advantage DNN Deep neural network DoD Department of Defense (US) ECD Estimated collateral damage ECMA Effective contribution to military action EO/IR Electro-optical/infrared F2T2EA Find, Fix, Track, Target, Engage, Assess GC Geneva Convention(s) GGE Group of Governmental Experts (meeting) GPS Global Positioning System HVT High-value target ICRC International Committee of the Red Cross IHL International humanitarian law ISR Intelligence, surveillance and reconnaissance JFC Joint Force Commander JTCB Joint Targeting Coordination Board LAWS Lethal autonomous weapon system(s) LOAC Law of armed conflict (Manual) MAA Military advantage anticipated MHC Meaningful human control MN-H Military necessity-humanity (balance) MoD Ministry of Defence (UK) NATO North Atlantic Treaty Organisation NGO Non-governmental organisation OODA Observe, Orient, Decide, Act PGM Precision-guided munition PID Positive identification PNT Position, Navigation, Timing RNN Recurrent neural network XXX Rules of engagement T&E Testing and evaluation TLC Tactical-level combat TRACE Target...
LIST OF TABLES AND FIGURES. Tables Figures
LIST OF TABLES AND FIGURES. Figure 1: The CompBioMed Logo (‘standard’ version) 11 Figure 2: The CompBioMed Logo ('header’ version) 12 Figure 3: CompBioMed Slide Tempate 13 Figure 4: The CompBioMed Twitter Account 15 V1.0 01/12/2016 Xxxx Xxxxxx First Draft V1.1 15/12/2016 Xxxx Xxxxxx Second Draft Xxxx Xxxxxx CBK Sci Con Author Xxxxxx Xx Xxxxxxxxx UPF Editor Xxxxxxx Xxxxxxx BSC Editor Xxxx Xxxx BSC Editor XxX Centre of Excellence WP Work Package KPI Key Performance Indicator HPC High Performance Computing SME Small and Medium Enterprise R&D Research and Development COST European Cooperation in Science and Technology MoU Memorandum of Understanding Computational methods, based on human biology, are now reaching maturity in the biomedical domain, rendering predictive models of health and disease increasingly relevant to clinical practice by providing a personalized aspect to treatment. Computer based modelling and simulation is well established in the physical sciences and engineering, where the use of high performance computing (HPC) is now routine. CompBioMed is a user-driven Centre of Excellence (XxX) in Computational Biomedicine, designed to nurture and promote the uptake and exploitation of high performance computing within the biomedical modelling community. Our user communities come from academia, industry and clinical practice. The CompBioMed Centre of Excellence in Biomedical Computing is distributed in nature, relying on collaboration within the project, and also with external stakeholders. To this end, CompBioMed will develop and coordinate dissemination activities that enable us to engage external stakeholders in academia, healthcare and industry with the activities of the project. The success of CompBioMed relies on its messages, developments, activities, and results being disseminated into the biomedical community, as well as growing and interacting with its user communities. This deliverable, D3.2: Dissemination Action Plan, acts as a detailed and comprehensive report on the dissemination actions that will be carried out by the project. This deliverable is linked to CompBioMed’s Task 3.1: Production of a Dissemination Action Plan, and the release of it is also Milestone 2 in the project. This action plan is a ‘living document’ that will be updated throughout the project, as required.
LIST OF TABLES AND FIGURES. Figure.1 Placement of the high-definition camera.
LIST OF TABLES AND FIGURES. INTRODUCTION 1 II. THE ERA-ENVHEALTH STRATEGY AND TOOLS FOR DISSEMINATION 1
LIST OF TABLES AND FIGURES. Figure 1 ERA-ENVHEALTH’s dissemination and communication strategy 2 Figure 2 ERA-ENVHEALTH stakeholders 5 Figure 3 Diagram presenting the instruments used by the ERA- ENVHEALTH project to disseminate and communicate its outputs. 9 Table 1 ERA-ENVHEALTH target audiences and different tools in relation to the Communication and Dissemination Strategy 13 Table 2 Scheduled information to be communicated 15 Table 3 Indicators monitored by the project coordinator and WP5 leader to ensure that the dissemination and communication strategy is running in an efficient way. 18
LIST OF TABLES AND FIGURES. Table 2.1. Programmes of propagation of Islam broadcast by television channels in 2015.
LIST OF TABLES AND FIGURES. Table 1 Definitions of Adjusted Predictors (Except for the PM2.5) in Poisson Log-Linear Regression Model 28 Table 2 Descriptive Analysis of Grid PM2.5 and Its Three-Day Moving Average from 2001 to 2007 28 Table 4 Geographic Distribution of Mean and Standard Deviation of Three-Day Moving Average Ambient PM2.5 Concentrations 29 Table 5 Rate Ratio and 95% Confidence Intervals from Poisson Log-Linear Regression Models for Increases in Three-Day Moving Average Ambient PM2.5 Concentrations. Figure 2 Distribution of Daily Grid Cells PM2.5 Concentrations from 2001 to 2007 Figure 3 Distribution of Predicted PM2.5 at Grid Cell Level from 2001 to 2007 32 Figure 4 Distribution of PM2.5 (Three-day moving average) at Grid Cell Level from 2001 to 2007 32 Particulate matter is regarded as one of three most important pollutants in ambient air, with ozone (O3) and nitrogen oxides (NOx) (Xxxxxxxxx and Xxxxxxx 2012). The toxicology of particulate particles is strongly associated with their size (Xxxxxxx et al.
LIST OF TABLES AND FIGURES. Table 1 Table 2 Table 3 Table 4 NCI CTCAE category and grade for respiratory AEs 38 Bivariate analysis of respiratory AE vs no respiratory AE groups… 40 Bivariate analysis of early versus late respiratory AEs… 41 Multivariable logistic regression analysis (respiratory AE vs no respiratory AE) 42 Table 5 Multivariable survival analysis with Xxx PH model for recurrent events (respiratory AE vs no respiratory AE) 43 Figure 1 CONSORT diagram demonstrating subject eligibility 37 Figure 2 Time-to-event distribution from initial presentation 39 Figure 3 Survival analysis: time to fluid overload state… 44 Figure 4 Total days in fluid overload state… 45 Figure 5 Infection subtypes… 46 Figure 6 Survival analysis: time to infection state… 47
