Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
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
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
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.
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.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
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
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.
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.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Chapter 3 part 1 ( 3.1 3.4 )
1. Chapter 3 : Chemical Formulae and
Equations
3.1 Relative Atomic Mass & Relative Molecular Mass
3.2 Relationship between the Number of Moles and the Number
of Particles
3.3 Relationship between the Number of Moles of a Substance
and its Mass
3.4 Relationship between the Number of Moles of a Gas and its
Volume
3.5 Chemical Formulae
3.6 Chemical Equations
3.7 Scientific Attitudes and Values in Investigating Matter
2. 3.1 Relative Atomic Mass and Relative
Molecular Mass
Relative
Atomic Mass (Ar) – the number of
times one atom of the element is heavier
than one twelfth of the mass of a carbon-12
atom
3. Example:
Sodium atom , Na is 23 time heavier than onetwelfth of the mass of one carbon-12 atom.
Thus the relative atomic mass of Na is 23.
Mass of one Na atom (23)
1
× mass of one carbon - 12 atom
12
= 23
4. Relative
Molecular Mass (Mr) – the number of
one molecule of the compound is heavier
than one-twelfth of the mass of a carbon-12
atom
5. Example:
A methane molecule , CH4 is 16 time heavier
than one-twelfth of the mass of one carbon-12
atom. Thus the relative molecular mass of CH4
is 16.
Mass of one CH 4 molecule (16)
= 16
1
× mass of one carbon - 12 atom
12
6. 3.2 Relationship between the Number
of Moles and the Number of Particles
Mole
– the amount of substance which
contains the same number of particles
(atoms/ions/molecules) as there are in 12
grams of carbon-12.
The number of atoms in 12grams of carbon12 is 6.02 x 1023 (Avogadro’s Number or
Avogadro’s Constant (NA)
7.
Example:
- 1 mol of gold contains 6.02 x 1023 of gold
atoms
- 1 mol of magnesium ions contains 6.02 x
1023 Mg2+ ions
- 1 mol of magnesium chloride (MgCl2)
contains 6.02 x 1023 Mg2+ ions and 2 x 6.02 x
1023 Cl- ions.
- 1 mol of carbon dioxide contains 6.02 x 10 23
CO2 molecules
CO2 is a covalent compounds; chemical bond that involves the
sharing of electron pairs between atoms.
8. Conversion
of the number of moles to the
numbers of particles and vice versa:-
Number of Particles = Number of mole x NA
Number of Moles = Number of particles ÷ NA
Example:-
Calculate the number of particles in 0.75 mol
of aluminium atoms,Al.
Solution:
0.75 mol x 6.02 x 1023 Al atoms = 4.52 x 1023 Al
atoms.
9. 3.3 Relationship between the Number
of Moles of a Substance and Its Mass
Molar
mass – mass of a substance that
contains one mole of the substance
The molar mass of any substance contains
6.02 x 1023 particles
The mole atom = relative atomic mass of an
atom but expressed in gram.
Eg: 1 mole atom of Al = 27g
The mole molecule = relative molecular mass
of a compund expressed in gram.
Eg: 1 mole molecule of water ,H2O = 18g
10. Conversion
of the number of moles of a
substance to its mass and vice versa:Number of mole-atom = mass in gram ÷
relative atomic mass
Number of mole-molecule = mass in
gram ÷ relative molecular mass
Mass in gram = Number of mole x relative
atomic mass or relative molecular mass
11. Example:
Calculate the number of moles of 23.5g of
copper (II) nitrate , Cu(NO3)2.
[ RAM: Cu = 64, N=14, O=16]
Solution:
1 mol of Cu(NO3)2 = 64 + 2[14+3(16)] g
= 188 g RMM
23.5 g of Cu(NO3)2 = 23.5 × 1 mol
188
= 0.125 mol
12. Example:
Determine the mass for 0.08 mol of ascorbic
acid , C6H8O6.
[RAM: C=12,H=1,O=16]
Solution:
1 mol of C6H8O6
= 6(12) + 8(1)+ 6(16)
0.08 mol of C6H8O6
= 176g
= 0.08 x 176g
=14.08g
13. 3.4 Relationship between the Number
of Moles of a Gas and Its Volume
One
mole of any gas at room temperature
and 1 atm presure occupies a volume of
24dm3 ( 24000 cm3)
At standard temperature and pressure,s.t.p
( 0oC and 1 atm), one mole of gas occupies a
volume of 22.4dm3 ( 22400 cm3).
Molar volume – volume occupied by one
mole of any gas.
14. Conversion
of the number of moles of a
gas to its volume and vice versa:Number of mole of a gas = volume of gas
÷ molar volume
Volume of gas = Number of mole of a gas
x molar volume
15. Example:
Calculate the number of moles of
4.8dm3 of chlorine gas at room
temperature.
[1 mol of gas occupies a volume of
24dm3 at room temperature]
Solution:
3
4.8dm
Number of moles=
×1 mol
3
24dm
= 0.2 mol
16. Example:
Calculate the volume of 0.75 mol of
nitrogen gas at s.t.p.
[ 1 mol of gas occupies a volume of
22.4dm3 at s.t.p]
Solution:
Volume of nitrogen gas = 0.75 mol x
22.4dm3
= 16.8dm3
17.
18. 3.5 Chemical Formulae
Used
to represent a chemical compound
It shows:- the elements (denoted by symbols)
- the relative numbers (indicated by subscript
after the symbol)
Example:-
H2 O
19. Chemical formulae of some covalent
compounds
Name of
compound
Chemical
formula
Number of each
element in the
compound
Oxygen
O2
2 oxygen atoms
Water
H2O
2 hydrogen atoms
1 oxygen atom
20. Chemical formulae of some ions
(cations)
Charge
Cation
Symbol
+1
Sodium ion
Na+
+2
Magnesium ion
Mg 2+
+3
Iron(III) ion
Fe3+
21. Chemical formulae of some ions
(anions)
Charge
Anion
Symbol
-1
Fluoride ion
F-
-2
Oxide ion
O2-
-3
Nitride ion
N3-
22. To
write the chemical formula of an ionic
compounds:- write the formula of the ions involved in
forming the compound
- balance the positive and negative charge
(use subscript)
- Write the chemical formula of the ionic
compound without the charges.
24. Formulae of some ionic compounds
Cation
Anion
Chemical
formula
Na+
Cl-
NaCl
Ca2+
Cl-
CaCl2
Al3+
N3-
AlN
25. Empirical
formulae of a compound:- shows the simplest ratio of the atoms of the
elements that combine to form a compound
- steps to determine the empirical formula of a
compound:1) write the mass / percentage of each
element in the compound
2) calculate the number of moles for each
element
3) Divide each number by the smallest
number to obtain simplest ratio
4) Write the empirical formula of the
compound
27. Molecular
formulae of the compound:- shows the actual numbers of the atoms of the
elements that combine to form the compound
Compound
Molecular
formula
Simplest
ratio of the
elements
Empirical
formula
Water
H2O
H:O = 2:1
H2O
Ethene
C2H4
C:H=1:2
CH2
Glucose
C6H12O6
C:H:O=1:2:1
CH2O
28. 3.6 Chemical Equations
Chemical
reaction can be represented by a
chemical equation
Reactants – chemicals that are reacting.
Written on LHS.
Products – chemicals formed in the reaction.
Written on the RHS
29. Writing
a chemical equation:1) write the correct formulae of all reactants on
the LHS of the equation
2) write the correct formulae of all products on
the RHS of the equation
3) the equation is then balanced.
4) make sure the number of atoms before and
after reaction are the same
5) Write the physical state of each reactants
and products