38 research outputs found
An Efficient Approach To Object Recognition For Mobile Robots.
In robotics, the object recognition approaches developed so far have proved very valuable, but their high
memory and processing requirements make them suitable only for robots with high processing capability
or for offline processing. When it comes to small size robots, these approaches are not effective and light-
weight vision processing is adopted which causes a big drop in recognition performance. In this research,
a computationally expensive, but efficient appearance-based object recognition approach is considered and
tested on a small robotic platform which has limited memory and processing resources. Rather than processing
the high resolution images, all the times, to perform recognition, a novel idea of switching between high and
low resolutions, based on the “distance to object” is adopted. It is also shown that much of the computation
time can be saved by identifying the irrelevant information in the images and avoid processing them with
computationally expensive approaches. This helps to bridge the gap between the computationally expensive
approaches and embedded platform with limited processing resources
Implementation Of Distributed Mosaic Formation And Object Detection In Modular Robotic Systems.
In reconfigurable modular robotics, when robot modules joins to form a robotic organism, they create a dis-
tributed processing environment in a unified system. This research builds on the efficient use of these dis-
tributed processing resources and presents the manner these resources can be utilised to implement distributed
mosaic formation and object detection within the organism. The generation of mosaics provides surrounding
awareness to the organism and helps it to localise itself with reference to the objects in the mosaics. Whereas,
the detection of objects in the mosaic helps in identifying parts of the mosaic which needed processing
Vision Based Environment Mapping By Network Connected Multi-Robotic System.
The conventional environment mapping solutions are computationally very expensive and cannot effectively
be used in multi-robotic environment, where small size robots with limited memory and processing resources
are used. This study provides an environment mapping solution in which a group of small size robots extract
simple distance vector features from the on-board camera images. The robots share these features between
them using a wireless communication network setup in infrastructure mode. For mapping the distance vector
features on a global map and to show a collective map building operation, the robots needed their accurate
location and heading information. The robots location and heading information is computed using two ceiling
mounted cameras, which collective localises the robots. Experimental results show that the proposed method
provides the required environmental map which can facilitate the robot navigation operation in the environ-
ment. It was observed that, using the proposed approach, the near by object boundaries can be mapped with
higher accuracy comparatively the far lying objects
Vision Based Object Recognition and Localisation by a Wireless Connected Distributed Robotic Systems
Object recognition and localisation are important processes in computer vision and robotics. Advances in computer vision have resulted in many object recognition techniques, but most of them are computationally very intensive and require robots with powerful processing systems. For small robots, these techniques are not applicable because of the constraints of execution time. In this study, an optimised implementation of SURF based recognition technique is presented. Suitable image pre-processing techniques were developed which reduced the recognition time on small robots with limited processing resources. The recognition time was reduced from 39 seconds to 780 milliseconds. This recognition technique was adopted by a team of small robots which were given prior training to search for objects of interest in the environment. For the localisation of the robots and objects a new template, designed for passive markers based tracking, was introduced. These markers were placed on the top of each robot and they were tracked by the two ceiling mounted cameras. The information from both sources, that is ceiling mounted cameras and team of robots, was used collectively to localise the objects in the environment. The objects were localised with an error ranging from 2.8cm to 5.2cm from their actual positions in the test arena which has the dimensions of 150x163cm
Development and evaluation of vision processing algorithms in multi-robotic systems.
The trend in swarm robotics research is shifting to the design of more complicated systems in which the robots have abilities to form a robotic organism. In such systems, a single robot has very limited memory and processing resources, but the complete system is rich in these resources. As vision sensors provide rich surrounding awareness and vision algorithms also requires intensive processing. Therefore, vision processing tasks are the best candidate for distributed processing in such systems. To perform distributed vision processing, a number of scenarios are considered in swarm and the robotic organism form. In the swarm form, as the robots use low bandwidth wireless communication medium, so the exchange of simple visual features should be made between robots. This is addressed in a swarm mode scenario, where novel distance vector features are exchanged within a swarm of robots to generate a precise environmental map. The generated map facilitates the robot navigation in the environment. If features require encoding with high density information, then sharing of such features is not possible using the wireless channel with limited bandwidth. So methods were devised which process such features onboard and then share the process outcome to perform vision processing in a distributed fashion. This is shown in another swarm mode scenario in which a number of optimisation stages are followed and novel image pre-processing techniques are developed which enable the robots to perform onboard object recognition, and then share the process outcome in terms of object identity and its distance from the robot, to localise the objects. In the robotic organism, the use of reliable communication medium facilitates vision processing in distributed fashion, and this is presented in two scenarios. In the first scenario, the robotic organism detect objects in the environment in distributed fashion, but to get detailed surrounding awareness, the organism needs to learn these objects. This leads to a second scenario, which presents a modular approach to object classification and recognition. This approach provides a mechanism to learn newly detected objects and also ensure faster response to object recognition. Using the modular approach, it is also demonstrated that the collective use of 4 distributed processing resources in a robotic organism can provide 5 times the performance of an individual robot module. The overall performance was comparable to an individual less flexible robot (e.g., Pioneer-3AT) with significant higher processing capability
ASME 2004-59928 NUCLEATE BOILING INSIDE THE EVAPORATOR OF THE PLANAR LOOP HEAT PIPE
ABSTRACT The Loop Heat Pipe (LHP) under development is a next generation micro heat transfer device that utilizes the latent heat of a working fluid and has excellent transfer capacity compared with that of standard metallic cooling devices. A typical LHP consists of an evaporator, a reservoir (also called the compensation chamber), vapor and liquid lines, a subcooler, and a condenser. As heat is applied to the evaporator, all of the input energy goes into the evaporation of the liquid in the pores of the primary CPS wick or leak to the bottom. The nucleate boiling, which occurs beneath the primary wick in the evaporator, is a very significant phenomena. It affects critical operating issues, such as dry out of the primary wick. Using a clear evaporator machined from Pyrex glass, the nucleation, which occurred in the evaporator, was studied. De-ionized water was utilized as the working fluid. INTRODUCTION The loop heat pipe (LHP) is a thermal control and heat transport device. LHPs were originally invented and developed in the former Soviet Union in the mid 1980's, and has been employed in a reliable and versatile thermal control system for space applications. LHPs can transport very large thermal power loads over long distances through flexible, small diameter tubes and against high gravitational heads due to capillary forces in the evaporator. LHPs are two-phase heat transfer devices that utilize the latent heat and are completely self-circulating systems that have no mechanical moving parts and add no unwanted vibration to the spacecraft
Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial
Background
Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy
Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050
Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US per capita, purchasing-power parity-adjusted US8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or 40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that 13.7 billion was targeted toward the COVID-19 health response. 1.4 billion was repurposed from existing health projects. 2.4 billion (17.9%) was for supply chain and logistics. Only 1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe
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Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050
Background
The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020.
Methods
We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US per capita, purchasing-power parity-adjusted US8·8 trillion (95% uncertainty interval [UI] 8·7–8·8) or 40·4 billion (0·5%, 95% UI 0·5–0·5) was development assistance for health provided to low-income and middle-income countries, which made up 24·6% (UI 24·0–25·1) of total spending in low-income countries. We estimate that 13·7 billion was targeted toward the COVID-19 health response. 1·4 billion was repurposed from existing health projects. 2·4 billion (17·9%) was for supply chain and logistics. Only 1519 (1448–1591) per person in 2050, although spending across countries is expected to remain varied.
Interpretation
Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all
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Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021
Background
Accurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios.
Methods
To estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline.
Findings
During the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction.
Interpretation
Fertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world