This is an interactive presentation which contains the information about Algebra for student-teacher , who are going to teach maths. Further, it contains information about the curriculum alignment and objectives of algebraic teaching which are mentioned in Curriculum of Pakistan.
Powerpoint presentation about Division of Integers. Best for demo teaching. Designed for an online class and face-to-face with review, motivation, groupings, quiz, and homework.
* Find zeros of polynomial functions
* Use the Fundamental Theorem of Algebra to find a function that satisfies given conditions
* Find all zeros of a polynomial function
This is an interactive presentation which contains the information about Algebra for student-teacher , who are going to teach maths. Further, it contains information about the curriculum alignment and objectives of algebraic teaching which are mentioned in Curriculum of Pakistan.
Powerpoint presentation about Division of Integers. Best for demo teaching. Designed for an online class and face-to-face with review, motivation, groupings, quiz, and homework.
* Find zeros of polynomial functions
* Use the Fundamental Theorem of Algebra to find a function that satisfies given conditions
* Find all zeros of a polynomial function
Updated version of this talk as presented at Pacific Northwest Software Quality Conference in 2012. This is a longer version, including content on scatter diagrams and standard deviation.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
2. • If you listen to weather forecasts you could
hear expressions like these:
• ‘There is a strong likelihood of rain
tomorrow’.
• ‘In the afternoon there is a possibility of
thunder’.
• ‘The rain will probably clear towards
evening’.
• Weather forecasts are made by studying
charts and weather data to tell us how
3. • Probability uses numbers to tell us
how likely something is to happen.
• The probability or chance of
something happening can be
described by using words such as
• Impossible, Unlikely, Even, Chance,
Likely or Certain
4. • An event which is certain to happen
has a probability of 1.
• An event which cannot happen has a
probability of 0.
• All other probabilities will be a
number greater than 0 and less than 1.
• The more likely an event is to happen,
the closer the probability is to 1
6. • There is an even chance that the
next person you meet on the Street
will be a male.
• It is certain that the sun will rise
tomorrow.
• It is impossible to get 7 when a
normal dice is rolled.
8. • Before you start a certain game you
must throw a dice and get a six
• The act of throwing is called a
trial
• The numbers 1,2,3,4,5,6 are the
possible outcomes
• The required result is called the
event
9. • In general the letter E represents
the event, probability is denoted by
the letter P
• The formal definition of
probability is as follows
10. • The probability of any event cannot
be less than 0 or greater than 1
• The probability of a certainty is 1
• An impossibility is 0
11. Example 1
• A card is drawn from a pack of 52
playing cards. Find the probability
that the card is (i)a diamond (ii) a
queen (iii) a king or a queen
• (i)There are 13 diamonds in a pack
therefore
12. • (ii) there are 4 queens in a pack
therefore:
• (iii) there are 8 queens or kings in a
pack therefore
13. Roulette
ODD EVEN
2 2 1 11 21
2 1
6 6 3 1
0 2 12 22
1 6 5
3 13 23
2
1 4
4 14 24
7
1 2 5 15 25
9 2
1 8 6 16 26
4 7 17 27
2 2
8 8 18 28
9
1 1 9 19 29
0 1
10 20 30
3 2
0 1 to 10 11 to 20 21 to 30
9 2 RED BLACK
7
7 1
2 8
1
1 3
2 2
1
3
5 P(odd number) = 15/30 = ½ or 50%
5 4
P(1 to 10) = 10/30 = 1/3 or 33%
P(Black) = 15/30 = ½ or 50%
P(number 1) = 1/30 or 3.3%
14. Probability of an event not
occurring
• The probability of drawing spade
from a pack of cards is....
• Therefore the probability of not
drawing a spade is simply the
probability of drawing any other
card in the pack, therefore...
• This illustrates the probability of not
drawing a spade is one minus the
probability of drawing a spade ,
written as...
15. Two events –the use of
sample space
• When two coins are tossed the set
of possible outcomes is as follows
• There could be two heads
• There could be a head and a tail
• There could be a tail and a head
• Or there could be two tails
16. • This is written as follows:
• {HH,HT,TH,TT}
• Where H=head and T=tail
• This set of possible outcomes is
called sample space. By using this
sample space we can write down
the probability of { HH } for
example as
17. • The probability of one head and one
tail is obtained by taking HT and TH
18. • Similarly if two dice are thrown
and the numbers on the dice are
added, we can set out sample space
of results as Number on first dice
follows:
1 2 3 4 5 6
Number on second Dice
1 2 3 4 5 6 7
2 3 4 5 6 7 8
3 4 5 6 7 8 9
4 5 6 7 8 9 10
5 6 7 8 9 10 11
6 7 8 9 10 11 12
19. • There are 36 points in this sample
space.
• From the sample space we can see,
that the sum of 10 occurs three
times
• Therefore.....
25. What is Probability?
• Probability is a number from 0 to 1 that tells
you how likely something is to happen.
• Probability can be either theoretical or
experimental.
26. Probability
THEORETICAL EXPERIMENTAL
Theoretical probability Experimental probability is
can be found without found by repeating an
doing and experiment and
experiment. observing the
outcomes.
27. THEORETICAL PROBABILITY
• Take for example a coin
It has a heads side and a
tails side HEADS
Since the coin has only 2
sides, there are only 2
possible outcomes when TAILS
you flip it. It will either
land on heads, or tails
28. THEORETICAL PROBABILITY
• When flipping the coin,
the probability that my HEADS
coin will land on heads is
1 in 2
• What is the probability
TAILS
that my coin will land on
tails??
30. Theoretical probability
When I spin this
spinner, I have a 1 in
4 chance of landing A A
on the section with
the red A in it. A A
31. Theoretical Probability
A 1 in 4 chance can be written 2 ways:
• As a fraction: ¼
• As a decimal: .25 A A
A A
32. Theoretical Probability
I have three marbles in a bag.
1 marble is red
1 marble is blue
1 marble is green
• I am going to take 1 marble from the bag.
• What is the probability that I will pick out
a red marble?
33. Theoretical Probability
• Since there are three
marbles and only one is
red, I have a 1 in 3 chance
of picking out a red
marble.
• I can write this in two
ways:
• As a fraction: 1/3
• As a decimal: .33
35. Experimental Probability
• Returning again to the bag of
marbles?
• The bag has only 1 red, 1 green, and 1
blue marble in it.
• There are a total of 3 marbles in the
bag.
• Theoretical Probability says there is a
1 in 3 chance of selecting a red, a
green or a blue marble.
36. Experimental Probability
• We draw 1 marble from the bag.
It is a red marble.
Record the outcome on the tally sheet
Marble
number red blue green
1 1
2
3
4
5
6
37. Experimental Probability
• If we put the red marble back in the bag
and draw again.
• This time you drew a green marble.
• Record this outcome on the tally sheet.
Marble
number red blue green
1 1
2 1
3
4
38. Experimental Probability
• We place the green marble back in the bag.
• We then continue drawing marbles and
recording outcomes until we have drawn 6
times. (remember it is essential that each
marble is placed is back in the bag before
drawing again)
39. Experimental Probability
• After 6 draws your chart
Marble
will look similar to this. number red blue green
• Look at the red column. 1 1
2 1
• Of our 6 draws, we 3 1
selected a red marble 2 4 1
5 1
times. 6 1
Total 2 1 3
40. Experimental Probability
• The experimental
Marble
probability of drawing a
number red blue green
red marble was 2 in 6. 1 1
• This can be expressed as a 2 1
fraction: 2/6 or 1/3 3 1
4 1
a decimal : .33 or
5 1
a percentage: 33% 6 1
Total 2 1 3
41. Experimental Probability
Marble
• Notice the number red blue green
Experimental 1 1
2 1
Probability of
3 1
drawing a red, 4 1
blue or green 5 1
6 1
marble. Total 2 1 3
2/6 3/6
Exp. or or
Prob. 1/3 1/6 1/2
42. Comparing Experimental and
Theoretical Probability
• Look at the chart at
the right.
• Is the experimental red blue green
Exp.
probability always the
Prob. 1/3 1/6 1/2
same as the Theo.
theoretical Prob. 1/3 1/3 1/3
probability?
43. Comparing Experimental and
Theoretical Probability
• In this experiment, the
experimental and
red blue green
theoretical
Exp.
probabilities of
Prob. 1/3 1/6 1/2
selecting a red marble Theo.
are equal. Prob. 1/3 1/3 1/3
44. Comparing Experimental and
Theoretical Probability
• The experimental
probability of selecting a
blue marble is less than the
red blue green
theoretical probability.
Exp.
• The experimental Prob. 1/3 1/6 1/2
probability of selecting a Theo.
green marble is greater Prob. 1/3 1/3 1/3
than the theoretical
probability.
45. Probability Review
Probability is a number from 0 to 1 that tells
you how likely something is to happen.
There are 2 types of probability:
• Theoretical (can be found without doing an
experiment)
• Experimental (can be found by repeating an
experiment and recording outcomes.)