How to Add Colour Kanban Records in Odoo 17 NotebookCeline George
In Odoo 17, you can enhance the visual appearance of your Kanban view by adding color-coded records using the Notebook feature. This allows you to categorize and distinguish between different types of records based on specific criteria. By adding colors, you can quickly identify and prioritize tasks or items, improving organization and efficiency within your workflow.
No, it's not a robot: prompt writing for investigative journalismPaul Bradshaw
How to use generative AI tools like ChatGPT and Gemini to generate story ideas for investigations, identify potential sources, and help with coding and writing.
A talk from the Centre for Investigative Journalism Summer School, July 2024
How to Show Sample Data in Tree and Kanban View in Odoo 17Celine George
In Odoo 17, sample data serves as a valuable resource for users seeking to familiarize themselves with the functionalities and capabilities of the software prior to integrating their own information. In this slide we are going to discuss about how to show sample data to a tree view and a kanban view.
Still I Rise by Maya Angelou
-Table of Contents
● Questions to be Addressed
● Introduction
● About the Author
● Analysis
● Key Literary Devices Used in the Poem
1. Simile
2. Metaphor
3. Repetition
4. Rhetorical Question
5. Structure and Form
6. Imagery
7. Symbolism
● Conclusion
● References
-Questions to be Addressed
1. How does the meaning of the poem evolve as we progress through each stanza?
2. How do similes and metaphors enhance the imagery in "Still I Rise"?
3. What effect does the repetition of certain phrases have on the overall tone of the poem?
4. How does Maya Angelou use symbolism to convey her message of resilience and empowerment?
Webinar Innovative assessments for SOcial Emotional SkillsEduSkills OECD
Presentations by Adriano Linzarini and Daniel Catarino da Silva of the OECD Rethinking Assessment of Social and Emotional Skills project from the OECD webinar "Innovations in measuring social and emotional skills and what AI will bring next" on 5 July 2024
The Jewish Trinity : Sabbath,Shekinah and Sanctuary 4.pdfJackieSparrow3
we may assume that God created the cosmos to be his great temple, in which he rested after his creative work. Nevertheless, his special revelatory presence did not fill the entire earth yet, since it was his intention that his human vice-regent, whom he installed in the garden sanctuary, would extend worldwide the boundaries of that sanctuary and of God’s presence. Adam, of course, disobeyed this mandate, so that humanity no longer enjoyed God’s presence in the little localized garden. Consequently, the entire earth became infected with sin and idolatry in a way it had not been previously before the fall, while yet in its still imperfect newly created state. Therefore, the various expressions about God being unable to inhabit earthly structures are best understood, at least in part, by realizing that the old order and sanctuary have been tainted with sin and must be cleansed and recreated before God’s Shekinah presence, formerly limited to heaven and the holy of holies, can dwell universally throughout creation
Slide Presentation from a Doctoral Virtual Open House presented on June 30, 2024 by staff and faculty of Capitol Technology University
Covers degrees offered, program details, tuition, financial aid and the application process.
Credit limit improvement system in odoo 17Celine George
In Odoo 17, confirmed and uninvoiced sales orders are now factored into a partner's total receivables. As a result, the credit limit warning system now considers this updated calculation, leading to more accurate and effective credit management.
AI Risk Management: ISO/IEC 42001, the EU AI Act, and ISO/IEC 23894PECB
As artificial intelligence continues to evolve, understanding the complexities and regulations regarding AI risk management is more crucial than ever.
Amongst others, the webinar covers:
• ISO/IEC 42001 standard, which provides guidelines for establishing, implementing, maintaining, and continually improving AI management systems within organizations
• insights into the European Union's landmark legislative proposal aimed at regulating AI
• framework and methodologies prescribed by ISO/IEC 23894 for identifying, assessing, and mitigating risks associated with AI systems
Presenters:
Miriama Podskubova - Attorney at Law
Miriama is a seasoned lawyer with over a decade of experience. She specializes in commercial law, focusing on transactions, venture capital investments, IT, digital law, and cybersecurity, areas she was drawn to through her legal practice. Alongside preparing contract and project documentation, she ensures the correct interpretation and application of European legal regulations in these fields. Beyond client projects, she frequently speaks at conferences on cybersecurity, online privacy protection, and the increasingly pertinent topic of AI regulation. As a registered advocate of Slovak bar, certified data privacy professional in the European Union (CIPP/e) and a member of the international association ELA, she helps both tech-focused startups and entrepreneurs, as well as international chains, to properly set up their business operations.
Callum Wright - Founder and Lead Consultant Founder and Lead Consultant
Callum Wright is a seasoned cybersecurity, privacy and AI governance expert. With over a decade of experience, he has dedicated his career to protecting digital assets, ensuring data privacy, and establishing ethical AI governance frameworks. His diverse background includes significant roles in security architecture, AI governance, risk consulting, and privacy management across various industries, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: June 26, 2024
Tags: ISO/IEC 42001, Artificial Intelligence, EU AI Act, ISO/IEC 23894
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Find out more about ISO training and certification services
Training: ISO/IEC 42001 Artificial Intelligence Management System - EN | PECB
Webinars: https://pecb.com/webinars
Article: https://pecb.com/article
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Front Desk Management in the Odoo 17 ERPCeline George
Front desk officers are responsible for taking care of guests and customers. Their work mainly involves interacting with customers and business partners, either in person or through phone calls.
3. If and else
The simplest form of flow control is conditional execution using if.
if takes a logical value (more precisely, a logical vector of length one) and
executes the next statement only
if that value is TRUE:
if(TRUE) message("It was true!")
## It was true!
if(FALSE) message("It wasn't true!")
Missing values aren’t allowed to be passed to if; doing so throws an error: if(NA)
message("Who knows if it was true?")
## Error: missing value where TRUE/FALSE needed Where you may have a missing
value, you should test for it using is.na:
if(is.na(NA)) message("The value is missing!")
## The value is missing!
5. a <- 33
b <- 33
if (b > a) {
print("b is greater than a")
} else if (a == b) {
print ("a and b are equal")
}
a <- 200
b <- 33
if (b > a) {
print("b is greater than a")
} else if (a == b) {
print("a and b are equal")
} else {
print("a is greater than b")
}
6. x <- 41
if (x > 10) {
print("Above ten")
if (x > 20) {
print("and also above 20!")
} else {
print("but not above 20.")
}
} else {
print("below 10.")
}
[1] "Above ten"
[1] "and also above 20!"
8. Loop
There are three kinds of loops in R:
Repeat
While, and for
they can still come in handy for repeatedly executing code
Repeat:
i<-0
repeat
{
print(i)
i<-i+1
if(i>=3)
break
}
11. Functions
A function is a block of code which only runs when
it is called.
You can pass data, known as parameters, into a
function.
A function can return data as a result.
12. Creating and Calling Function in R
In order to understand functions better, let’s take a look
at what they consist of.
Typing the name of a function shows you the code that
runs when you call it.
The terms "parameter" and "argument" can be used for the
same thing: information that are passed into a function.
From a function's perspective:
A parameter is the variable listed inside the parentheses
in the function definition.
An argument is the value that is sent to the function when
it is called.
14. Passing Functions to and from Other
Functions
Functions can be used just like other variable
types, so we can pass them as arguments to other
functions, and return them from functions.
One common example of a function that takes
another function as an argument is do.call.
do.call(function(x, y) x + y, list(1:5, 5:1))
## [1] 6 6 6 6 6
15. do.call()
#create three data frames
df1 <- data.frame(team=c('A', 'B', 'C'), points=c(22, 27, 38))
df2 <- data.frame(team=c('D', 'E', 'F'), points=c(22, 14, 20))
df3 <- data.frame(team=c('G', 'H', 'I'), points=c(11, 15, 18))
#place three data frames into list
df_list <- list(df1, df2, df3)
#row bind together all three data frames
do.call(rbind, df_list)
16. Variable Scope
A variable’s scope is the set of places from which you can see the variable.
For example, when you define a variable inside a function, the rest of the
statements in that function will have access to that variable.
In R subfunctions will also have access to that variable.
In this next example, the function f takes a variable x and passes it to the
function g. f also defines a variable y, which is within the scope of g, since g
is a sub‐ function of f.
17. So, even though y isn’t defined inside g, the example works:
f <- function(x)
{
y <- 1
g <- function(x)
{
(x + y) / 2 #y is used, but is not a formal argument of g }
g(x)
}
f(sqrt(5)) #It works! y is magically found in the environment of f
## [1] 1.618
18. String Manipulation
String manipulation basically refers to the process of
handling and analyzing strings.
It involves various operations concerned with
modification and parsing of strings to use and change its
data.
Paste:
str <- paste(c(1:3), "4", sep = ":")
print (str)
## "1:4" "2:4" "3:4"
Concatenation:
# Concatenation using cat() function
str <- cat("learn", "code", "tech", sep = ":")
print (str)
## learn:code:tech
20. Loading and Packages
R is not limited to the code provided by the R Core Team.
It is very much a community effort, and
there are thousands of add-on packages available to
extend it.
The majority of R packages are currently installed in an
online repository called CRAN (the Comprehensive R
Archive Network1)
which is maintained by the R Core Team. Installing and
using these add-on packages is an important part of the R
experience
21. Loading Packages
To load a package that is already installed on your
machine, you call the library function
We can load it with the library function:
library(lattice)
the functions provided by lattice. For example,
displays a fancy dot plot of the famous Immer’s barley
dataset:
dotplot(
variety ~ yield | site,
data = barley,
groups = year
)
22. Scatter Plot
A "scatter plot" is a type of plot used to display the relationship between two
numerical variables, and plots one dot for each observation.
It needs two vectors of same length, one for the x-axis (horizontal) and one
for the y-axis (vertical):
Example
x <- c(5,7,8,7,2,2,9,4,11,12,9,6)
y <- c(99,86,87,88,111,103,87,94,78,77,85,86)
plot(x, y)