Here are 2 questions about the notes:
1. What are the key differences between pure science and applied science?
2. What are the essential components that make up a valid scientific experiment?
Molded together from two powerpoints on the internet:
www.biologyjunction.com/Scientific%20Method.ppt
and
newton.uor.edu/facultyfolder/tyler_nordgren/.../FYS_SciMethod.ppt
Molded together from two powerpoints on the internet:
www.biologyjunction.com/Scientific%20Method.ppt
and
newton.uor.edu/facultyfolder/tyler_nordgren/.../FYS_SciMethod.ppt
Step by step introduction to scientific methods for juniorsdakter Cmc
A step by step introduction to scientific methods starting from Observation to communicating the result. Followed by an appropriate example for the target group.
Step by step introduction to scientific methods for juniorsdakter Cmc
A step by step introduction to scientific methods starting from Observation to communicating the result. Followed by an appropriate example for the target group.
First Quarter-Scientific Method Powerpoint Presentation
Content Standard-Scientific ways of acquiring knowledge and solving problems
Performance Standard
perform in groups
in guided
investigations involving community- based problems using locally available materials
Most Essential Learning
Competencies
-Describe the components
of a scientific investigation (Week 1) S7MTIa-
1
OBJECTIVES
Describe the components of the scientific method
Follow the steps of the scientific method and perform experiments using it.
SCIENTIFIC METHOD
a systematic process of empirical investigation
It is the key to unlock the bodies of knowledge by helping the researcher in organizing his or her thoughts and procedures and making him or her confident of the findings from the expirements
COMPONENTS OF A SCIENTIFIC INVESTIGATION
1. Statement of the Problem
-You should have existing knowledge of the problem
This part answers the following questions:
What questions do you have about your topic?
What do you want to know?
EXAMPLE
How does fertilizer affect the growth of plants?
2. Formulation of Hypothesis
Hypothesis-simple statement that presents the possible solution to the problem. It can be tested, and it is based on knowledge and research.
Hypothesis may be stated in two ways:
a. Null Hypothesis (Ho)-states that no relationship between variables
Example: The fertilizer DOES NOT affect the growth of plants
b. Alternative hypothesis (Ha)-states a relationship between variables
Example: There is significant relationship between the growth of plants and the use of fertilizer
Ha2 : There is a negative relationship between A and B
(Less A is involved, the better B)
Ha3 There is a positive relationship between A and B.
(More B is involved, the better A)
3. Testing Hypothesis and Gathering of Data
Experiments-a set of manipulations or specific observations of nature, and it is considered the most important part of the scientific method.
Three Types of Experiments
1. Controlled Experiment-the observer tests the hypothesis by looking for changes brought by alteration to a variable
Variable- a characteristic, number, or quantity that increases or decreases over time or takes different values in different situations.
a. Controlled variables-variables that are kept constant.
b. Independent variables-factors that you change or alter during the experiment.
c. Dependent variables-variables that you observe. and they are considered the response to an independent variable
2. Natural experiments or quasi-experiments-Here, the observer does not manipulate any variable but simply collects all the possible data to determine the factors affecting a particular phenomenon.
3. Field experiment-named to draw a contrast with laboratory experiments. It examines the real world using scientific method.
Example: Political sciences, economics, and psychology
Prediction
a forecast of future events based on past observations.
Example: The plants will grow faster and strong
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
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.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
3. • Whether Pure or Applied, good Science
relies heavily on the ability to:
– Design valid experiments and make good
observations
Inquiry/Experimentation Making Observations
4. • Dictionaries describe science as the
observation, identification, description,
experimental investigation (scientific
method), and theoretical explanation of
phenomena.
• This is a good description for fields like
chemistry and physics where specific
experiments can be run but what about
other fields like archaeology, or geology
where it is not so straightforward? Are
these examples of science?
5. • Science – A way of learning about the
natural world through observations and
logical reasoning, and allows for
growth and change as new ideas are
explored.
– Though simple, this definition is all
encompassing
– Within this we can separate out 2 distinct
forms of science:
Pure Science Applied Science
6. • Pure Science – Pure science is an aspect
of the field that deals directly with research
simply for the sake of research.
– Experiments are developed and hypothesis’
are tested with the sole purpose of finding out
what happens. It is the search for new
information or the discovery of a new fact.
– Motivated by curiosity
– Can basically be thought of as the “search
for new information”
7. • Applied Science (technology) – This is
the aspect that involves actually using
science, what was discovered using pure
science, to improve the technology around
us and to improve and ease everyday life.
8. • A large part of being a good scientist is
observation. When we observe there are two
types of observations that we can make:
– Qualitative – These observations consist only of
words. Describe things such as the color, shape, or
odor of an object.
• Practice Making Qualitative Observations
– Quantitative – These observations use actual
numbers. They describe aspects of an object that
can be measured. Examples would be mass, length,
speed, etc.
• Practice Making Qualitative Observations
Questions
9. Make 3 Qualitative Observations
1. The product is blue
Click for answer 2. The reactants are red and yellow
Click for answer
3. A gas was produced during the reaction
Click for answer
10. Make 3 Quantitative Observations
1. There for answerof
Click are 94 mL 2. The product has a mass of 112 g
Click for answer
reactant
3. 12 mL of reactants were changed into a gas
Click for answer
11. Scientific Inquiry
The practice of pure science is often referred to as
scientific inquiry
In scientific inquiry, an unknown question is
presented, an idea (hypothesis) is
suggested as a solution, the possible
solution is tested (experimentation),
and then a conclusion is drawn.
This process of inquiry is best described through what is
known as the scientific method
12. Scientific Method
The scientific method consists of eight (8) steps:
• State the question (what am I trying to find out?)
• Collect information (what do we already know?)
• Form a hypothesis (what do you think will happen?)
• Test your hypothesis (perform the experiment)
• Observe your results (ongoing during the experiment)
• Record the data (ongoing during the experiment)
• Analyze the data
• Form a conclusion (either supporting or disproving
your hypothesis)
13. Experimentation
Other than forming a hypothesis, the most important part
of the scientific method is the experiment.
An experiment is an organized procedure for testing a
hypothesis
In order for an experiment to be scientifically valid, it must
have two important parts:
1) A valid experimental setup
2) Valid experimental subjects
14. Valid Experimental Subjects
In any experiment, you also must have something to
compare the results with, therefore you must have two
different types of experimental subjects:
• Test Group – this is the subject where you change one
variable to see what effect it will have
• Control Group – this is used as a standard for
comparison. In the control group, no variables get
changed
15. Valid Experimental Setup
In any good experiment, you need to be very careful of
what you are testing and what you are doing to affect your
results. Therefore, you must be careful to only have:
• Independent (manipulated) variable – what factor in an
experiment that you change. There can only be ONE
independent variable in any experiment.
• Dependent (responding) variable – what factor in an
experiment you are measuring the change as a result of
changing the independent variable. The amount of
change in the dependent variable is your “results”
• Constants – all of the other factors in the experiment
which must remain unchanged
16. Example:
A student wants to see how watering a plant with salt
water affects its growth. He has twenty plants. The first
five he waters with regular water, the second five he
uses water with 5 tablespoons of salt, the third five he
uses water with 10 tablespoons of salt, and the last 5 he
uses water with 15 tablespoons of salt. The first group
of plants grows to an average height of 14 inches, the
second group to an average height of 11 inches, the
third to an average height of 8 inches and the last group
to an average height of 4 inches.
• Which group is the control group? The test groups?
Control – Plants with regular water; Test – Plants with salt water
Click for Answer
• What is the independent variable? The dependent
variable?
IV – amount of salt in water; DV – height that plants grow
Click for Answer
• What are some constants involved in this experiment?
Click for Answer
Type of plant, amount of sunlight, amount of water, type of dirt, pots
17. Scientific Method
• Important to remember:
– The scientific method is a tool to help
scientists solve problems. It is not set in
stone and not every step is always used and
its not always followed in that exact order. It
is mainly a guideline.
– Experimentation usually goes more like this
18.
19. • What is the difference between pure and
applied Science?
Pure science is done for its own sake, because the scientist
Click for Answer
wants to know more about the world. Applied Science is
done in order to improve life; to make things easier.
• Which category do you think most Science
done today falls into? Why?
20. • What are the key components of a valid
experiment?
– A single independent variable
Click for answer
– A measurable dependent variable
– All other variables kept constant
21. • Identify the following as qualitative or
quantitative observations
- The car moved fast Qualitative
- The car was traveling 50 mph Quantitative
– The flowers were blue Qualitative
– There were 5 flowers Quantitative
– The ball had a mass of 10 kg Quantitative
Remember to write out 2-5 questions
about the notes for class!!