Presentation titled, COVID-19: Implications and Policy Responses for the Caribbean,' delivered by CDB's Deputy Director, Economics Department, Ian Durant at the 31st Inter-Sessional Meeting of the Caribbean Community (CARICOM) Heads of Government on April 15, 2020.
Coronavirus Impact Assessment And Mitigation Strategies On Cruise Industry Co...SlideTeam
Showcase the impact of covid19 on consumer perception and risk mitigation with the help of our Coronavirus Impact Assessment And Mitigation Strategies On Cruise Industry Complete Deck PowerPoint Presentation. In the coronaviridae PPT presentation, we have given an overview of the global cruise industry and tourism to showcase the significant impact of covid19 on GDP growth forecast. The presentation shows a halt in the working of cruise operators, port congestion in marine shipping, and negative impacts from container shipping to oil tankers. The nidovirales PowerPoint layout also highlights the risks caused in the industry like disruption due to social distancing, plummeting employee productivity, impact and disruption on the supply chains, economic instability, civil unrest, and business operations severity. A well-designed risk management plan has been shared in the RNA virus PPT slides conveying outbreak management. Different policies were designed by the firms including sanitation, medical facilities, screening, an inspection of health, and crewmember training. Combined coronavirus incident reports and risk maturity models have also been shared in the sars-cov-2 PPT templates. https://bit.ly/3i5TBCY
Presentation delivered by CDB President, Dr. William Warren Smith at the 2019 Annual News Conference on February 7, 2019 at CDB's Headquarters in Barbados.
Measuring the effect of social distancing On CoronavirusJames Orr
This was an attempt to see if I could measure the effect of social distancing. While the method is immature, it definitely shows that movement into regions by infectious persons is defeating "social distancing" in most areas. Only New York and Washington show progress. Texas "social distancing" appears overwhelmed by movement of new infectious persons into Texas
Similar to COVID-19 in the Caribbean: June 25 Report on Daily New Cases (10)
Presentation delivered by CDB's President (Ag.), Mr. Isaac Solomon, President (Ag.) at the 2024 Annual News Conference on February 20, 2024 at CDB's Headquarters in Barbados.
Presentation delivered by CDB's Director of Economics, Mr. Ian Durant at the 2024 Annual News Conference on February 20, 2024 at CDB's Headquarters in Barbados.
Presentation delivered by CDB's Director of Projects, Mrs. Therese Turner-Jones at the 2024 Annual News Conference on February 20, 2024 at CDB's Headquarters in Barbados.
Keynote: From Structural Vulnerability to Resilient Prosperity in Small Islan...Caribbean Development Bank
Keynote address delivered by Dr Emily Wilkinson, Senior Research Fellow and Director, Resilient and Sustainable Islands Initiative, ODI at UK Caribbean Infrastructure Conference in November 2023.
Despite the well-recognised potential for, and steps to promote, energy efficiency progress in deployment has been slow.
Scaling up an integrated utility service model presents an opportunity for the utility to become a player within the emerging energy service paradigm in the region.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
3. Objectives of Publication
The objectives of this publication are:
• to provide statistics and display trends regarding the spread of the Novel
Coronavirus disease in Borrowing Member Countries of the Caribbean
Development Bank.
• to keep the general public informed regarding the evolution of relevant data
which have the potential to impact social and economic development in the
Region.
4. Definitions
Abbreviations:
CDB - Caribbean Development Bank
BMC - Borrowing Member Country
COVID-19: Coronavirus disease 2019 as defined by the World Health Organisation. In
this publication COVID-19 is used as a proxy for all infections with the severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2).
Data Sources:
• Johns Hopkins University via Github.com
• Caribbean Disaster Emergency Management Agency (CDEMA) and Pan American
Health Organisation (PAHO) COVID-19 Situation Reports
• Worldometers website https://www.worldometers.info/coronavirus
• Some data points might vary from national data due to delayed reporting
5. Table of Contents
Confirmed aggregated COVID-19 cases in the Caribbean Region
Confirmed COVID-19 cases in CDB’s BMCs
Confirmed COVID-19 cases in Other Selected Caribbean Countries
Confirmed COVID-19 cases in Other CDB Member Countries and the United
States of America
15. Dynamics of New Cases
t = Day of first case in respective country
0
1,000
2,000
3,000
4,000
5,000
6,000
t + 1 t + 16 t + 31 t + 46 t + 61 t + 76 t + 91 t + 106
Haiti
Jamaica
Suriname
16. Dynamics of New Cases
t = Day of first case in respective country
0
50
100
150
200
250
t + 1 t + 16 t + 31 t + 46 t + 61 t + 76 t + 91 t + 106
Guyana
Cayman Islands
Trinidad and Tobago
The Bahamas
Barbados
Antigua and Barbuda
St. Vincent and the
Grenadines
17. Dynamics of New Cases
t = Day of first case in respective country
0
5
10
15
20
25
t + 1 t + 16 t + 31 t + 46 t + 61 t + 76 t + 91 t + 106
Grenada
Belize
Saint Lucia
Dominica
St. Kitts and Nevis
Turks and Caicos
Islands
Montserrat
Virgin Islands
Anguilla
18. Dynamics of New Cases per 100,000 Population
t = Day of first case in respective country
0
50
100
150
200
250
300
350
t + 1 t + 16 t + 31 t + 46 t + 61 t + 76 t + 91 t + 106
Cayman Islands
Montserrat
19. Dynamics of New Cases per 100,000 Population
t = Day of first case in respective country
0
10
20
30
40
50
60
70
80
t + 1 t + 16 t + 31 t + 46 t + 61 t + 76 t + 91 t + 106
Antigua and Barbuda
Suriname
Haiti
Barbados
Turks and Caicos Islands
The Bahamas
St. Vincent and the
Grenadines
Dominica
St. Kitts and Nevis
20. Dynamics of New Cases per 100,000 Population
t = Day of first case in respective country
0
5
10
15
20
25
30
t + 1 t + 16 t + 31 t + 46 t + 61 t + 76 t + 91 t + 106
Guyana
Jamaica
Grenada
Virgin Islands
Saint Lucia
Trinidad and Tobago
Anguilla
Belize
21. Total Confirmed Cases, Weekly Replication
Factors in BMCs, 2020
The table to the left displays total confirmed cases as of a specific date and the table to the right displays the replication factor of total confirmed
cases over successive seven-day periods. Generally speaking seven-day replication factors are displaying a downward trend.
total cases as of … seven-day replication factor of total cases
25-Jun 18-Jun 11-Jun 4-Jun 28-May 21-May 25-Jun 18-Jun 11-Jun 4-Jun 28-May
Anguilla 3 3 3 3 3 3 1.00 1.00 1.00 1.00 1.00
Antigua and Barbuda 65 26 26 26 25 25 2.50 1.00 1.00 1.04 1.00
The Bahamas 104 104 103 102 101 97 1.00 1.01 1.01 1.01 1.04
Barbados 97 97 96 92 92 90 1.00 1.01 1.04 1.00 1.02
Belize 23 22 20 18 18 18 1.05 1.10 1.11 1.00 1.00
Cayman Islands 196 193 186 160 140 121 1.02 1.04 1.16 1.14 1.16
Dominica 18 18 18 18 16 16 1.00 1.00 1.00 1.13 1.00
Grenada 23 23 23 23 23 22 1.00 1.00 1.00 1.00 1.05
Guyana 215 183 158 153 150 127 1.17 1.16 1.03 1.02 1.18
Haiti 5,543 4,916 3,941 2,640 1,320 734 1.13 1.25 1.49 2.00 1.80
Jamaica 682 636 609 589 567 532 1.07 1.04 1.03 1.04 1.07
Montserrat 11 11 11 11 11 11 1.00 1.00 1.00 1.00 1.00
Saint Lucia 19 19 19 19 18 18 1.00 1.00 1.00 1.06 1.00
St. Kitts and Nevis 15 15 15 15 15 15 1.00 1.00 1.00 1.00 1.00
St. Vincent and the Grenadines 29 29 27 26 25 18 1.00 1.07 1.04 1.04 1.39
Suriname 373 277 168 82 12 11 1.35 1.65 2.05 6.83 1.09
Trinidad and Tobago 123 123 117 117 116 116 1.00 1.05 1.00 1.01 1.00
Turks and Caicos Islands 15 12 12 12 12 12 1.25 1.00 1.00 1.00 1.00
Virgin Islands 8 8 8 8 8 8 1.00 1.00 1.00 1.00 1.00
BMCs total 7,562 6,715 5,560 4,114 2,672 1,994 1.13 1.21 1.35 1.54 1.34