I'll admit. I have a fixation on 3D charts. Namely, destroying them any time I come across them. Here you'll see why I have such a problem with them.
Don't fall into the trap of "fun" effects that Excel can do.
Line charts are just about the most difficult chart to format for clarity. It doesn't take too many lines before the whole thing looks like a pile of undercooked spaghetti.
You've been doing your NFIRS reports, making sure they're good, submitting them. You're doing everything right for the System and now it's time to get something back.
Sometimes a table is going to outpace any chart(s) you can make. Presenting a table doesn't need a lot and I use the same principles for tables that I apply to charts.
Line charts are just about the most difficult chart to format for clarity. It doesn't take too many lines before the whole thing looks like a pile of undercooked spaghetti.
You've been doing your NFIRS reports, making sure they're good, submitting them. You're doing everything right for the System and now it's time to get something back.
Sometimes a table is going to outpace any chart(s) you can make. Presenting a table doesn't need a lot and I use the same principles for tables that I apply to charts.
When it comes to reporting to the National Fire Incident Reporting System, there are several myths floating around. As a trainer I hear them in almost every class. Find the truth behind common myths in this short presentation. Spread the truth afterwards! Note: there are some links specific to Kansas Fire Incident Reporting System. They may still be applicable but please defer to your state's guidelines.
Cómo evitar contratar al hábil y pícaro mentiroso. detección de engaño. nuevas tecnologías. Aplicadas en pre selección de personal y ascensos a puestos de confianza
The backbone of any National Fire Incident Reporting System report is the Incident Type. With 176 choices it can be overwhelming to get started. Use this short presentation to help in your search for not only the correct code, but data quality.
- Frameworks para desenvolvimento móvel
- O que é o Apache Cordova?
- Prós e Contras
- Integração com frameworks (Sencha, Ionic, Jquery Mobile, etc)
- Configurando o ambiente de desenvolvimento
- Ionic/Cordova CLI – Principais Comandos
- Conhecendo os diretórios e o arquivo config.xml
- Alterando ícones do aplicativo
- Criando builds nativas e testando no dispositivo
- Debug remoto de aplicações hibridas
- Overview plug-ins
- Eventos Nativos
- Exibindo notificações
- Utilizando armazenamento de dados
- Acesso aos dados dos dispositivos
- Usando o plug-in InAppBrowser
- Trabalhando com Push Notification
- Desenvolvendo nossa primeira aplicação
- Ionic Creator
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...2023240532
Quantitative data Analysis
Overview
Reliability Analysis (Cronbach Alpha)
Common Method Bias (Harman Single Factor Test)
Frequency Analysis (Demographic)
Descriptive Analysis
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
When it comes to reporting to the National Fire Incident Reporting System, there are several myths floating around. As a trainer I hear them in almost every class. Find the truth behind common myths in this short presentation. Spread the truth afterwards! Note: there are some links specific to Kansas Fire Incident Reporting System. They may still be applicable but please defer to your state's guidelines.
Cómo evitar contratar al hábil y pícaro mentiroso. detección de engaño. nuevas tecnologías. Aplicadas en pre selección de personal y ascensos a puestos de confianza
The backbone of any National Fire Incident Reporting System report is the Incident Type. With 176 choices it can be overwhelming to get started. Use this short presentation to help in your search for not only the correct code, but data quality.
- Frameworks para desenvolvimento móvel
- O que é o Apache Cordova?
- Prós e Contras
- Integração com frameworks (Sencha, Ionic, Jquery Mobile, etc)
- Configurando o ambiente de desenvolvimento
- Ionic/Cordova CLI – Principais Comandos
- Conhecendo os diretórios e o arquivo config.xml
- Alterando ícones do aplicativo
- Criando builds nativas e testando no dispositivo
- Debug remoto de aplicações hibridas
- Overview plug-ins
- Eventos Nativos
- Exibindo notificações
- Utilizando armazenamento de dados
- Acesso aos dados dos dispositivos
- Usando o plug-in InAppBrowser
- Trabalhando com Push Notification
- Desenvolvendo nossa primeira aplicação
- Ionic Creator
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...2023240532
Quantitative data Analysis
Overview
Reliability Analysis (Cronbach Alpha)
Common Method Bias (Harman Single Factor Test)
Frequency Analysis (Demographic)
Descriptive Analysis
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
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.
1. Fire data isn’t ugly
Presenting fire data effectively series
Episode: 3D is for the movies
July 2015
2. A makeover of fire department
data to transform it from
unclear and underperforming
to powerfully informative.
3. Microsoft Excel is not just a powerful tool to keep data
and spreadsheets. It’s a friend for creating quick charts.
However, you need to maintain integrity in the information
you present using those charts.
6. Pie may be bad
but There is nothing you can
learn from an exploded pie
7. Trauma,
8%
Other, 9%
Abdominal
Pain, 10%
Cardiac,
15%
General
Weakness,
17%
Respiratory
, 20%
Neurological
, 21%
Initial Patient Complaint
The problem with 3D is the strain it puts on your eye’s
ability to perceive not only the area but angle of each pie
slice. Exploding the pie chart just makes it that much
worse.
These are the same numbers presented again “flat”.
Trauma, 8%
Other, 9%
Abdominal
Pain, 10%
Cardiac, 15%
General
Weakness,
17%
Respiratory,
20%
Neurological,
21%
Initial Patient Complaint
8. The eye will treat the shadows as part of the category,
overemphasizing the size of them.
So if you want to make something seem bigger or more
important, sure, use 3D but you are responsible for the
integrity of the information you present.
9. The center of the pie chart also moves up and shrinks
any categories at the back.
See how much longer the red arrow is? Your eye can’t
compete with that kind of damaged presentation.
10. Say it with me now:
Just because 3d explosions are
an available choice doesn’t mean
you should ever use them
11. Even without 3D a pie chart is not the most appropriate
choice for the data we’re presenting. A bar chart would
be perfect.
See Episode: Pie is rarely a good idea to view the whole
transformation.
8%
9%
10%
15%
17%
20%
21%
0% 5% 10% 15% 20% 25%
Trauma
Other
Abdominal Pain
Cardiac
General Weakness
Respiratory
Neurological
Initial Patient Complaint
Other, 9%
Abdominal
Pain, 10%
Cardiac,
15%
General
Weakness,
17%
Respiratory,
20%
Neurological
, 21%
Initial Patient Complaint
12. What happens if we use 3D on a bar chart? Nothing
good.
Our bars look completely different in 3D.
8%
9%
10%
15%
17%
20%
21%
0% 5% 10% 15% 20% 25%
Trauma
Other
Abdominal Pain
Cardiac
General Weakness
Respiratory
Neurological
Initial Patient Complaint
0% 10% 20% 30%
Trauma
Other
Abdominal Pain
Cardiac
General Weakness
Respiratory
Neurological
8%
9%
10%
15%
17%
20%
21%
Initial Patient Complaint
13. Technically, the point ends at the bottom corner but
that’s not what our eyes see. Our eyes can’t really tell
where the bars end. Even Respiratory at 20% doesn’t
line up with the gridline.
0% 5% 10% 15% 20% 25%
Trauma
Other
Abdominal Pain
Cardiac
General Weakness
Respiratory
Neurological
8%
9%
10%
15%
17%
20%
21%
Initial Patient Complaint
14. And those shadows on the end? You guessed it. They
interfere with your eye’s ability to judge length.
Not to mention how bad the labels look without lining
up to the bars.
0% 5% 10% 15% 20% 25%
Trauma
Other
Abdominal Pain
Cardiac
General Weakness
Respiratory
Neurological
8%
9%
10%
15%
17%
20%
21%
Initial Patient Complaint
15. The 3D effect itself changes the way your eye can
perceive each bar.
The bars aren’t flat, distorting your eye’s ability to judge
the length even without the shadows.
0% 5% 10% 15% 20% 25%
Trauma
Other
Abdominal Pain
Cardiac
General Weakness
Respiratory
Neurological
8%
9%
10%
15%
17%
20%
21%
Initial Patient Complaint
16. While we’re on the topic of distortion, changing the bars
to cones is even worse. Now your eye is stuck at the
base of all the cones with a teensy little end.
The purpose of a chart is to help visualize the data.
Make sure your choices reflect that purpose.
0% 5% 10% 15% 20% 25%
Trauma
Other
Abdominal Pain
Cardiac
General Weakness
Respiratory
Neurological
Initial Patient Complaint
17. A column chart fairs no better in 3D.
You still have the shadows and tilted columns but now
you have some columns with a huge amount of shadow
and another with hardly any shadow.
0%
5%
10%
15%
20%
25%
8% 9% 10%
15% 17% 20% 21%
Initial Patient Complaint
19. As do cones.
Literally all I’ve done is change the chart type to one of
the 3D “fun” varieties.
0%
5%
10%
15%
20%
25%
8% 9% 10%
15% 17% 20% 21%
Initial Patient Complaint
20. Charts are not for fun. They are for informing.
Simple, clean designs that make it easy on our eyes are
perfect. They’re all you need, really.
8%
9%
10%
15%
17%
20%
21%
0% 5% 10% 15% 20% 25%
Trauma
Other
Abdominal Pain
Cardiac
General Weakness
Respiratory
Neurological
We need to add training for neurological complaints to the calendar,
as we have mostly focused training on trauma and cardiac incidents.
21. Avoid 3d at all costs
Unless your data has something
to hide using 3d is always a bad
choice
22. Hello! I’m Sara Wood and I love converting fire service members into
NFIRS operatives. I’m the State NFIRS program manager for Kansas and
enjoy providing classes to help bring fire departments into the era of data
driven decisions. If you need help creating a presentation or analyzing
your data, I’d love to hear from you!