The document describes the development of a contactless calliper that uses a laser pointer to determine properties of glass sheets without contact. It outlines the theoretical model, experiments conducted, and comparison of theory to experiments. Two experiments were conducted to measure the thickness and refractive index of glass sheets. The results found a refractive index of 1.53 with a margin of error of around 4.8% due to uncertainties in measurement of angles, distances, and refractive index.
การใช้ยาในสตรีมีครรภ์และมารดาที่ให้นมบุตร
(Drug used in pregnancy and lactation)
อ.ภญ.นันทวรรณ กิติกรรณากรณ์
แหล่งข้อมูล
http://phamacy.nkh.go.th/Doc/Lactation.pdf
การใช้ยาในสตรีมีครรภ์และมารดาที่ให้นมบุตร
(Drug used in pregnancy and lactation)
อ.ภญ.นันทวรรณ กิติกรรณากรณ์
แหล่งข้อมูล
http://phamacy.nkh.go.th/Doc/Lactation.pdf
How DevOps is Transforming IT, and What it Can Do for AcademiaNicole Forsgren
Today's business climate is challenging companies to innovate and respond to the market, and forcing them to do so with much greater pressure than ever before. DevOps provides organizations with the ability to respond to this challenge, helping them to innovate and create at velocity and bring value to their business through software, because there really aren't any major companies that aren't software companies.
But the *real* message here is that DevOps is more than just technology. We have been beating our drum for years that DevOps is revolutionary because it goes so far beyond just the technology (tools) -- it is also the practices and the culture. All three of these are required for DevOps to truly effect transformational change. Technology professionals also realized they had to reach out to peers in other silos and collaborate with them in all three areas in order to truly succeed -- and that if the changes were done courageously, with empathy, embracing the new diversity of thought and methodology, things would be amazing. And they ARE.
Academia is facing similar challenges to innovate in the face of new challenges. As a fellow academic (or very recent academic! I still feel like a member of the tribe), I felt these pressures. Perhaps we can look to DevOps methodologies for inspiration and ideas to innovate at velocity. It will take more than just tools, it will take novel practices and collaboration with peers we haven't traditionally worked with.
A deep introduction to supervised and unsupervised Machine Learning with examples in R.
Techniques covered for Regression:
- Linear Regression
- Polynomial Regression
Techniques covered for Classification:
- Simple and Multiple Logistic Regression
- Linear and Quadratic Discriminant Analysis
- K-Nearest Neighbors
Clustering:
- K-Means clustering
- Hierarchical clustering
Deflection of curved beam |Strength of Material LaboratorySaif al-din ali
SAIF ALDIN ALI MADIN
سيف الدين علي ماضي
S96aif@gmail.com
Experiment Name:- Deflection of curved beam
2. Introduction
The deflection of a beam or bars must be often be limited in order to provide
integrity and stability of structure or machine. Plus, code restrictions often require
these members not vibrate or deflect severely in order to safely support their
intended loading.
This experiment helps us to show some kind of deflection and how to calculate the
deflection value by using Castigliano’s Theorem and make a comparison between
result of the experiment and the theory.
Sources:
Visual - various maths sites (credits to original creator)
Questions - Dong Zong's Textbook
suitable for SUEC (Maths), SPM (Maths and Add Maths) too
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.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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.
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.
2. CONTACTLESS CALLIPER
Invent and construct an optical device that uses a laser pointer and
allows contactless determination of thickness, refractive index, and other
properties of a glass sheet.
25.02.2017 2Giga Khizanishvili
3. Problem
Theoretical model
Experiments
The margin of error
Compare of theory and experiments
Conclusion
25.02.2017 3Giga Khizanishvili
11. 25.02.2017Giga Khizanishvili 11
1
𝑛 𝑎𝑖𝑟
=
1
1,0002926
= 0,9997 ⇒ 𝐸𝑟𝑟𝑜𝑟 = 1 − 0,9997 =0,03%
The margin of error of the refractive index of the
air
12. 25.02.2017Giga Khizanishvili 12
The margin of the error of the angle ( 𝛼1)
𝑙
ℎ = 132 ± 0,5 cm
𝑥
𝑎
𝑥 = 126 ± 0.5 cm
ℎ
𝑡𝑔𝑎 𝑚𝑎𝑥 =
126 + 0.5
132 − 0.5
= 0,961965
𝑡𝑔𝑎 𝑚𝑖𝑛 =
126 − 0.5
132 + 0.5
= 0.94749
17. 2.37
2.28
2.19
2.28
2.2
0.0001
0 0.5 1 1.5 2 2.5
I Exp
II Exp
III Exp
IV exp
V Exp
Vi asfas
I Exp II Exp III Exp IV exp V Exp Vi asfas
Di electrical permeability 2.37 2.28 2.19 2.28 2.2 0.0001
Di electrical permeability
25.02.2017Giga Khizanishvili 17
26. 1.5
4.96
1.54
5.09
0 1 2 3 4 5 6
n
d
n d
Experiment 1.54 5.09
Theory 1.5 4.96
d = 4.96mm
Experiment Theory
25.02.2017Giga Khizanishvili 26
27. 1.5
2.39
1.51
2.44
0 0.5 1 1.5 2 2.5 3
n
d
n d
Experiment 1.51 2.44
Theory 1.5 2.39
d = 2.39mm
Experiment Theory
25.02.2017Giga Khizanishvili 27
28. 1.5
6.21
1.48
6.14
0 1 2 3 4 5 6 7
n
d
n d
Experiment 1.48 6.14
Theory 1.5 6.21
d = 6.21mm
Experiment Theory
25.02.2017Giga Khizanishvili 28
29. 1.5
3.24
1.51
3.28
0 0.5 1 1.5 2 2.5 3 3.5
n
d
n d
Experiment 1.51 3.28
Theory 1.5 3.24
d = 3.24mm
Experiment Theory
25.02.2017Giga Khizanishvili 29
30. 1.5
3.91
1.485
3.85
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
n
d
n d
Experiment 1.485 3.85
Theory 1.5 3.91
d = 3.91mm
Experiment Theory
25.02.2017Giga Khizanishvili 30
31. We came up with a mechanism that measures the thickness of glass sheet
The thickness of a glass sheet depends upon 𝑎, 𝑛, 𝑥.
We have derived a formula for the refractive index of glass
Experimental Errors we are measured
Experiments have been conducted
Thickness of glass sheet and refractive index have been determined
Theoretical model was compared to experiments
We have solved the problem
25.02.2017 31Giga Khizanishvili
32. Baldwin, G. C.; Solem, J. C. (1997). "Recoilless gamma-ray lasers". Reviews of
Modern Physics 69 (4): 1085–1117.
Vogel, Werner. Physics of Glass. Wiley, 1985.
Bundschuh, Bernhard; Himmel, Jörg: Optische Informationsübertragung.
Oldenbourg Verlag, München, Wien 2003
Baldwin, G. C.; Solem, J. C. (1982). "Is the time ripe? Or must we wait so long for
breakthroughs?". Laser Focus 18
25.02.2017 32Giga Khizanishvili