| 1. |
- Feigin, Valery L., et al.
(författare)
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Global, regional, and national burden of stroke and its risk factors, 1990-2019 : a systematic analysis for the Global Burden of Disease Study 2019
- 2021
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Ingår i: Lancet Neurology. - : Elsevier. - 1474-4422 .- 1474-4465. ; 20:10, s. 795-820
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Tidskriftsartikel (refereegranskat)abstract
- Background Regularly updated data on stroke and its pathological types, including data on their incidence, prevalence, mortality, disability, risk factors, and epidemiological trends, are important for evidence-based stroke care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) aims to provide a standardised and comprehensive measurement of these metrics at global, regional, and national levels. Methods We applied GBD 2019 analytical tools to calculate stroke incidence, prevalence, mortality, disability-adjusted life-years (DALYs), and the population attributable fraction (PAF) of DALYs (with corresponding 95% uncertainty intervals [UIs]) associated with 19 risk factors, for 204 countries and territories from 1990 to 2019. These estimates were provided for ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, and all strokes combined, and stratified by sex, age group, and World Bank country income level. Findings In 2019, there were 12.2 million (95% UI 11.0-13.6) incident cases of stroke, 101 million (93.2-111) prevalent cases of stroke, 143 million (133-153) DALYs due to stroke, and 6.55 million (6.00-7.02) deaths from stroke. Globally, stroke remained the second-leading cause of death (11.6% [10.8-12.2] of total deaths) and the third-leading cause of death and disability combined (5.7% [5.1-6.2] of total DALYs) in 2019. From 1990 to 2019, the absolute number of incident strokes increased by 70.0% (67.0-73.0), prevalent strokes increased by 85.0% (83.0-88.0), deaths from stroke increased by 43.0% (31.0-55.0), and DALYs due to stroke increased by 32.0% (22.0-42.0). During the same period, age-standardised rates of stroke incidence decreased by 17.0% (15.0-18.0), mortality decreased by 36.0% (31.0-42.0), prevalence decreased by 6.0% (5.0-7.0), and DALYs decreased by 36.0% (31.0-42.0). However, among people younger than 70 years, prevalence rates increased by 22.0% (21.0-24.0) and incidence rates increased by 15.0% (12.0-18.0). In 2019, the age-standardised stroke-related mortality rate was 3.6 (3.5-3.8) times higher in the World Bank low-income group than in the World Bank high-income group, and the age-standardised stroke-related DALY rate was 3.7 (3.5-3.9) times higher in the low-income group than the high-income group. Ischaemic stroke constituted 62.4% of all incident strokes in 2019 (7.63 million [6.57-8.96]), while intracerebral haemorrhage constituted 27.9% (3.41 million [2.97-3.91]) and subarachnoid haemorrhage constituted 9.7% (1.18 million [1.01-1.39]). In 2019, the five leading risk factors for stroke were high systolic blood pressure (contributing to 79.6 million [67.7-90.8] DALYs or 55.5% [48.2-62.0] of total stroke DALYs), high body-mass index (34.9 million [22.3-48.6] DALYs or 24.3% [15.7-33.2]), high fasting plasma glucose (28.9 million [19.8-41.5] DALYs or 20.2% [13.8-29.1]), ambient particulate matter pollution (28.7 million [23.4-33.4] DALYs or 20.1% [16.6-23.0]), and smoking (25.3 million [22.6-28.2] DALYs or 17.6% [16.4-19.0]). Interpretation The annual number of strokes and deaths due to stroke increased substantially from 1990 to 2019, despite substantial reductions in age-standardised rates, particularly among people older than 70 years. The highest age-standardised stroke-related mortality and DALY rates were in the World Bank low-income group. The fastest-growing risk factor for stroke between 1990 and 2019 was high body-mass index. Without urgent implementation of effective primary prevention strategies, the stroke burden will probably continue to grow across the world, particularly in low-income countries.
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| 2. |
- Abbasi, Shirin, et al.
(författare)
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A fault-tolerant adaptive genetic algorithm for service scheduling in internet of vehicles
- 2023
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Ingår i: Applied Soft Computing. - : Elsevier Ltd. - 1568-4946 .- 1872-9681. ; 143
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Tidskriftsartikel (refereegranskat)abstract
- Over the years, a range of Internet of Vehicles services has emerged, along with improved quality parameters. However, the field still faces several limitations, including resource constraints and the time response requirement. This paper extracts cost, energy, processing power, service management, and resource allocation parameters. Mathematical equations are then defined based on these parameters. To simplify the process complexity and ensure scalability, we propose an algorithm that uses the genetic algorithm for fault and cost management during resource allocation to services. The main concept is to pick resources for services using a genetic algorithm. We discuss the processing and energy costs associated with this function, which is the algorithm's objective function and is created to optimize cost. Our approach goes beyond the conventional genetic algorithm in two stages. In the first step, services are prioritized, and resources are allocated in accordance with those priorities; in the second step, load balancing in message transmission paths is ensured, and message failures are avoided. The algorithm's performance is evaluated using various parameters, and it was shown to outperform other metaheuristic algorithms like the classic genetic algorithm, particle swarm, and mathematical models. Different scenarios with various nodes and service variables are defined in various system states, including fault occurrences to various percentages of 10, 20, and 30. To compare methods, we consider different parameters, the most significant being performance success rate. Moreover, the cost optimization has a good convergence after iterations, and the rate of improvement in the big scenario has slowed down after 150 iterations. Besides, it provides acceptable performance in response time for services.
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| 3. |
- Micah, Angela E., et al.
(författare)
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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
- 2021
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Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 398:10308, s. 1317-1343
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Forskningsöversikt (refereegranskat)abstract
- 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$, 2020 US$ per capita, purchasing-power parity-adjusted US$ per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached $8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total, $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 $54.8 billion in development assistance for health was disbursed in 2020. Of this, $13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and $1.4 billion was repurposed from existing health projects. $3.1 billion (22.4%) of the funds focused on country-level coordination and $2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7%) of COVID-19 development assistance for health went to Latin America, despite this region reporting 34.3% of total recorded COVID-19 deaths in low-income or middle-income countries in 2020. Spending on health is expected to rise to $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.
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| 4. |
- Kiani, Vahdaneh, et al.
(författare)
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Real-time Scheduling for CPU and Hard Disk Requirements-Based Periodic Task with Aim of Minimising Energy Consumption
- 2015
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Ingår i: International Journal of Information Technology and Computer Science. - : Modern education and computer science press. - 2074-9007 .- 2074-9015. ; 7:10, s. 54-60
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- In recent years, with an increasing number ofrequests, energy, power and temperature have beenimportant keys in embedded systems, which decrease thelifetime of both CPUs and hard disks. The energyconsumption is an important issue in computer systems,particularly real-time embedded systems. The frequencyand the Revolutions Per Minute are major factors in thereduction of energy consumption in both processors andhard disk drives. Therefore, the main goal of this paper isto present a scheduling mechanism for a real timeperiodic task that can save more energy. This mechanismis based on increasing, as much as possible, the executiontime of the CPU and/or the Read/Write time of the harddisk without passing the task deadline. This will be doneby dynamically changing the CPU frequency and/or theRPM of hard disk. Our experimental results demonstratethat the proposed algorithm manages to lower energyconsumption by an average of 25% and to reduce thenumber of missed tasks by 80%.
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| 5. |
- Maleki, Neda, et al.
(författare)
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TMaR : a two-stage MapReduce scheduler for heterogeneous environments
- 2020
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Ingår i: Human-centric Computing and Information Sciences. - : Springer. - 2192-1962. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- In the context of MapReduce task scheduling, many algorithms mainly focus on the scheduling of Reduce tasks with the assumption that scheduling of Map tasks is already done. However, in the cloud deployments of MapReduce, the input data is located on remote storage which indicates the importance of the scheduling of Map tasks as well. In this paper, we propose a two-stage Map and Reduce task scheduler for heterogeneous environments, called TMaR. TMaR schedules Map and Reduce tasks on the servers that minimize the task finish time in each stage, respectively. We employ a dynamic partition binder for Reduce tasks in the Reduce stage to lighten the shuffling traffic. Indeed, TMaR minimizes the makespan of a batch of tasks in heterogeneous environments while considering the network traffic. The simulation results demonstrate that TMaR outperforms Hadoop-stock and Hadoop-A in terms of makespan and network traffic and achieves by an average of 29%, 36%, and 14% performance using Wordcount, Sort, and Grep benchmarks. Besides, the power reduction of TMaR is up to 12%.
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| 6. |
- Mansoor, Ali, et al.
(författare)
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Optimized reverse converters with multibit soft error correction support at 7nm technology
- 2023
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Ingår i: Computers & electrical engineering. - Oxford : Elsevier. - 0045-7906 .- 1879-0755. ; 107
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Tidskriftsartikel (refereegranskat)abstract
- Residue number system (RNS) speeds up digital signal processing systems involving dominant addition and multiplication. Addition and multiplication are accelerated further and performed with a balanced performance on one-hot coded (OHC) residue digits. However, the high complexity of the RNS reverse converter (RC) may kill the performance gain. This paper proposes a high-speed and scalable RNS-RC for both regular and one-hot RNS. For redundant RNS (RRNS), an RRNS-RC is proposed, which based on majority-voting between OHC residue digits, corrects multibit soft errors occurring in a single residue channel. With pass-transistor logic and low-power FinFETs, the proposed RCs are optimized. The simulated RRNS-RC corrected 98.5% of soft errors, while consuming 7, 6.2 and 0.4% of the system's area, leakage power and dynamic power, respectively. As compared to the leading lookup table RC in the literature, RNS-RC exhibited 10.3X, 4.4X and 1.8X savings in area, average power, and delay, respectively. © 2023 The Author(s)
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| 7. |
- Mohseni, Zeynab, et al.
(författare)
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A Task Scheduling Model for Multi-CPU and Multi-Hard Disk Drive in Soft Real-time Systems
- 2019
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Ingår i: International Journal of Information Technology and Computer Science. - : Modern education and computer science press. - 2074-9007 .- 2074-9015. ; 11:1
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- In recent years, by increasing CPU and I/O devices demands, running multiple tasks simultaneously becomes a crucial issue. This paper presents a new task scheduling algorithm for multi-CPU and multi-Hard Disk Drive (HDD) in soft Real-Time (RT) systems, which reduces the number of missed tasks. The aim of this paper is to execute more parallel tasks by considering an efficient trade-off between energy consumption and total execution time. For study purposes, we analyzed the proposed scheduling algorithm, named HCS (Hard disk drive and CPU Scheduling) in terms of the task set utilization, the total execution time, the average waiting time and the number of missed tasks from their deadlines. The results show that HCS algorithm improves the above mentioned criteria compared to the HCS_UE (Hard disk drive and CPU Scheduling _Unchanged Execution time) algorithm.
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| 8. |
- Rahmani, Amir-Mohammad, et al.
(författare)
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Power-aware NoC router using central forecasting-based dynamic virtual channel allocation
- 2010
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Ingår i: 2010 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS. ; , s. 3224-3227
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Konferensbidrag (refereegranskat)abstract
- In this paper, we propose a high performance central dynamic virtual channel allocation mechanism for on-chip routers. This central management unit devotes each input port a number of virtual channels (VC) among a shared VC bank based on a traffic forecasting technique. The forecasting technique exploits the link and VC utilizations in predicting the traffic. Based on the predicted traffic, for each input port, the number of active virtual channels may be increased, decreased, or kept unchanged. The clock-gating power management technique is used to activate/deactivate the VCs. Simulation results using uniform and Negative Exponential Distribution (NED) traffic profiles show that a considerable power savings in the virtual channels and overall router power consumption may be achieved especially in low traffic loads. The area overhead of the technique is negligible.
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