The objective was to identify and select indicators to assess the impact on health of the social context and the latest economic recession in Spain and its regions. The proposals for improvements that emerged during this work may be useful to increase the quality of the statistical processes and products from key sources that use official statistics.
Drug Encyclopedia - a Linked Data Application for PhysiciansJakub Kozák
This a presentation of our paper delivered at ISWC 2015 in Bethlehem, PA, USA on Oct 13, 2015. It presents our project Drug Encyclopedia, which means integration of drug related data and serving them in a web application (www.lekovaencyklopedie.cz/en).
Drug Encyclopedia - a Linked Data Application for PhysiciansJakub Kozák
This a presentation of our paper delivered at ISWC 2015 in Bethlehem, PA, USA on Oct 13, 2015. It presents our project Drug Encyclopedia, which means integration of drug related data and serving them in a web application (www.lekovaencyklopedie.cz/en).
Els lc metrics_reference_cards_v1.0_slides_2016Jenny Delasalle
Each slide covers one of a selection of metrics, with definitions and information about how it might be used. This is just part of a suite of resources from https://libraryconnect.elsevier.com/metrics
Els lc metrics_reference_cards_v2.0_slides_dec2016Jenny Delasalle
Version 2 includes the new Citescore metric. I worked on the research behind these cards, but am not the copyright owner. Originals provided at https://libraryconnect.elsevier.com/articles/librarian-quick-reference-cards-research-impact-metrics
http://www.yourcareerzone.org Health care assistants are a fundamental portion of the health care and hospice industry since they perform the 1st and very last duties of an doctor. These are with people first to present ambulatory assist, checking pertaining to vital symptoms, prepare paperwork for doctor and perhaps they are the last to view off your patients. To.
Journal of Forensic Science & Criminology (JFSC) is an open access, significant and reliable source of contemporary knowledge on advancements in the field of forensic science. JFSC publishes peer reviewed research articles, critical reviews and short communications focused on forensic science and criminology. JFSC encompasses the full spectrum of forensic science including forensic biology, forensic chemistry, cyber forensics and crime scene investigation
Els lc metrics_reference_cards_v1.0_slides_2016Jenny Delasalle
Each slide covers one of a selection of metrics, with definitions and information about how it might be used. This is just part of a suite of resources from https://libraryconnect.elsevier.com/metrics
Els lc metrics_reference_cards_v2.0_slides_dec2016Jenny Delasalle
Version 2 includes the new Citescore metric. I worked on the research behind these cards, but am not the copyright owner. Originals provided at https://libraryconnect.elsevier.com/articles/librarian-quick-reference-cards-research-impact-metrics
http://www.yourcareerzone.org Health care assistants are a fundamental portion of the health care and hospice industry since they perform the 1st and very last duties of an doctor. These are with people first to present ambulatory assist, checking pertaining to vital symptoms, prepare paperwork for doctor and perhaps they are the last to view off your patients. To.
Journal of Forensic Science & Criminology (JFSC) is an open access, significant and reliable source of contemporary knowledge on advancements in the field of forensic science. JFSC publishes peer reviewed research articles, critical reviews and short communications focused on forensic science and criminology. JFSC encompasses the full spectrum of forensic science including forensic biology, forensic chemistry, cyber forensics and crime scene investigation
Using Social Media to Measure the Consumer Confidence: The Twitter Case in SpainManu García
The goal of this project is to make an index which contains the consumer confidence. The source of information used to create this indicator has been Twitter, the methodology comes from opinion mining sentiment analysis and the metric used to check if this information can be usefull is the pearson's correlation coeficient.
There is evidence that the consumer confidence can be found in social media and these findings might be usefull to create alternative indexes in shorter intervals of time, or even in regional basis.
Running Head: WEEK 1 1
WEEK 1 4
Analysis of Asthma Patients
Course
March 25, 2020
Introduction:
Information processing is any method by which the retrieval or assistance in the retrieval of information is planned. Selection is accomplished by seeking and receiving the necessary data from persons or organizations via the correct vehicle. The data is given explicitly by the respondent (self-enumeration) or by the investigator. Set also involves the retrieval of institutional details. Data collection applies to any mechanism that transforms the information given to the respondent into an electronic format. The process is either automatic or requires the workers to plugging the gathered data (keys). Data coding is any method that assigns a numeric value to an answer. Programming is frequently automatic, but more complicated decisions typically need human input (coders). Survey operations also require a large level of optimization, which contributes to the accessibility of data, knowledge relevant to the survey phase. Instances of para data include an indication of whether or not a device is in the survey, a list of calls and meetings, a record of keystrokes (audit record), a system of compilation, managerial details (e.g. interview blog) and expense details. Data is not just a source of statistics, it is also the primary interaction that a polling organization has with the population who wants to be encouraged to participate. Data collection and encoding are the structured data for use as output by all future survey operations. Data processing, data analysis, and coding activities frequently entail a substantial portion of the research expenditure and require considerable humor. Plan the collection procedure to reduce the stress on the participant and the expense of processing, and to optimize timeliness and quality of the results. Data may be obtained by self-reporting, voice interviews or informal interviews through either a document or an online survey (e.g. automated data recording, the Web, computer-assisted interviewing).
What is PHIS?
Global Health Information Systems (PHIS) are the essential elements of public health services, offering details about how community programs obtain and manage public health treatment data. Such results help public health initiatives, such as the monitoring of illnesses or the implementation of public health systems for teen smokers. Countries also create PHIS via the state health department in order to collect data that will be used relevantly to assess the health condition of the country. In this report, the PHIS toolkit will be used in order to analyze the patients of asthma, and database records have been collected.
Asthma Database Analyses:
Create effective sample management protocols and controls for all data gathering .
Running Head: WEEK 1 1
WEEK 1 4
Analysis of Asthma Patients
Course
March 25, 2020
Introduction:
Information processing is any method by which the retrieval or assistance in the retrieval of information is planned. Selection is accomplished by seeking and receiving the necessary data from persons or organizations via the correct vehicle. The data is given explicitly by the respondent (self-enumeration) or by the investigator. Set also involves the retrieval of institutional details. Data collection applies to any mechanism that transforms the information given to the respondent into an electronic format. The process is either automatic or requires the workers to plugging the gathered data (keys). Data coding is any method that assigns a numeric value to an answer. Programming is frequently automatic, but more complicated decisions typically need human input (coders). Survey operations also require a large level of optimization, which contributes to the accessibility of data, knowledge relevant to the survey phase. Instances of para data include an indication of whether or not a device is in the survey, a list of calls and meetings, a record of keystrokes (audit record), a system of compilation, managerial details (e.g. interview blog) and expense details. Data is not just a source of statistics, it is also the primary interaction that a polling organization has with the population who wants to be encouraged to participate. Data collection and encoding are the structured data for use as output by all future survey operations. Data processing, data analysis, and coding activities frequently entail a substantial portion of the research expenditure and require considerable humor. Plan the collection procedure to reduce the stress on the participant and the expense of processing, and to optimize timeliness and quality of the results. Data may be obtained by self-reporting, voice interviews or informal interviews through either a document or an online survey (e.g. automated data recording, the Web, computer-assisted interviewing).
What is PHIS?
Global Health Information Systems (PHIS) are the essential elements of public health services, offering details about how community programs obtain and manage public health treatment data. Such results help public health initiatives, such as the monitoring of illnesses or the implementation of public health systems for teen smokers. Countries also create PHIS via the state health department in order to collect data that will be used relevantly to assess the health condition of the country. In this report, the PHIS toolkit will be used in order to analyze the patients of asthma, and database records have been collected.
Asthma Database Analyses:
Create effective sample management protocols and controls for all data gathering .
In the present research work, the importance of municipal administrative data as a source of data collection for statistical purposes is disclosed. To this end, a characterization questionnaire of the administrative data was prepared to know the current status of the same. The municipal plans and programs were analyzed and a bibliographic review of the legal framework of the competences of the municipalities was carried out. The production of administrative data is highly relevant for the collection of information, considering the comparative advantages they have over other types of statistical processes. In addition, in coordination and collaboration with other institutions, the administrative data present the opportunity and possibility of being transformed into statistics, for the generation of public policies of the different instances. The vision that is taken from the analysis carried out is to make a later study of the administrative data as an instrument of data collection to generate the same statistical information obtained with the censuses.
Statistics as a subject (field of study):
Statistics is defined as the science of collecting, organizing, presenting, analyzing and interpreting numerical data to make decision on the bases of such analysis.(Singular sense)
Statistics as a numerical data:
Statistics is defined as aggregates of numerical expressed facts (figures) collected in a systematic manner for a predetermined purpose. (Plural sense) In this course, we shall be mainly concerned with statistics as a subject, that is, as a field of study
Notes of BBA /B.Com as well as BCA. It will help average students to learn Business Statistics. It will help MBA and PGDM students in Quantitative Analysis.
A series of modules on project cycle, planning and the logical framework, aimed at team leaders of international NGOs in developing countries.
Part 8 of 11
Statistics is a basic and important tool for professionals in all fields all over the worlds. This document provides the importance and scope of Statistics in major fields of study like a business, management, planning etc.
This slide pack illustrates the Office for National Statistics’ (ONS) research into developing an alternative approach to producing administrative data-based population stocks and flows.
20190528_Data4Impact_Open Science and Big data in support of measuring R&I In...OpenAIRE
Presented by Vilius Stanciauskas, Rainer Frietsch, Alexander Feidenheimer, Haris Papageorgiou, Ioanna Grypari, Iason Demiros and Gustaf Nelhans
during the OpenAIRE workshop "Research policy monitoring in the era of Open Science and Big Data" taking place in Ghent, Belgium on May 27th and 28th 2019
Day 2: Open Science and Big Data in support of measuring R&I Indicators
https://www.openaire.eu/research-policy-monitoring-in-the-era-of-open-science-and-big-data-the-what-indicators-and-the-how-infrastructures
Statistics is the scientific methods for collecting, organizing, presenting and analyzing data as well as deriving the valid conclusion and making reasonable decision on the basis of this analysis.
Similar to Improvement Proposals For The Official Statistics On Social Determinants Of Health: An Experience From The Users’ Perspective (20)
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
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.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
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.
Business update Q1 2024 Lar España Real Estate SOCIMI
Improvement Proposals For The Official Statistics On Social Determinants Of Health: An Experience From The Users’ Perspective
1. This project is being developed by members of the Biomedical
Research Networking Centre on Public Health and Epidemiology.
Our main goal
is,
to
provide
indicators
to
assess
the
impact
of
the
social
context
and
the
latest
economic
recession,
on
health,
in
Spain
and
its
regions.
2. This figure depicts the whole process we followed to achieve our
goal.
Following the Spanish conceptual framework of the social
inequality determinants in health, we identified indicators
sequentially from key documents, Web of Science, and from
organizations that produce official statistics.
The information gathered resulted in a large directory of
indicators…
3. that was reviewed by an expert panel.
We then selected a set of indicators according to geographic and
temporal criteria.
Finally, we created a database for the selected contextual
indicators.
4. So, to date, we have identified more than 200 contextual indicators
related to social determinants of health.
The Spanish Statistics Institute provided the main information
sources for the selected indicators.
This table shows what the directory of indicators is like. Each row is
an indicator and each column gathers information about this
indicator.
Only half of the identified indicators satisfied the selection criteria.
5. So, we managed to produce this database with all the selected
indicators, over 100, in only one file.
Each row contains the data for the indicators for a specific year,
gender and region.
For example, the data for ID3, for 2007, for both sexes and for
Andalusia, is sixty-seven point eight nine.
The ID label, and other information about the indicator, is available
on the directory. In this case, ID3 is the unemployment rate.
Both, the directory of indicators and the database, will be available
online in the near future.
6. Finally, during the identification and selection of indicators and
data, we detected various areas in need of improvement. To give
some examples:
- There is still a need to create more indicators on some areas of
the SDH (e.g. psychosocial factors or ethnic minorities).
- It is also vital to have both more accurate and more data on
regions.
- To identify indicators on SDH, it would be very useful, for
example, if the organizations which produce official statistics,
published the indicators and the data of users’ most frequent
requests.
7. Some more examples:
- Related to the interactivity between sources, a lot of users’ time
would be saved, if direct links to the tables for the data requests
were provided (e.g. the bookmarks provided by Eurostat).
- Finally, answering the users’ data requests, is perhaps the most
important factor in generating trust among users. For example, in
our study, 26% of our requests received no reply; e.g. requests
related to the Spanish Health System, or the Ministry of Education).