The document discusses the heuristic usability evaluation of Microsoft Word 2013. It evaluates the software based on 10 usability heuristics: visibility of system status, match between system and real world, user control and freedom, consistency and standards, error prevention, recognition rather than recall, flexibility and efficiency of use, aesthetic and minimalist design, help users recognize, diagnose and recover from errors, and help and documentation. Examples are provided for each heuristic on how Microsoft Word adheres to or supports the usability principle.
Chapter 11: User support
from
Dix, Finlay, Abowd and Beale (2004).
Human-Computer Interaction, third edition.
Prentice Hall. ISBN 0-13-239864-8.
http://www.hcibook.com/e3/
EclipseCon '09 - The Happy Marriage of EMF, Data binding, UI Forms and Field ...Tonny Madsen
Imagine you have to develop a larger Eclipse RCP based application with many dozens - maybe hundreds - of views, dialogs and wizards all based on a large common EMF based data model. How do you make sure you get a consistent and modern interface that can be extended in the future without redesigning everything again and again?
Chapter 11: User support
from
Dix, Finlay, Abowd and Beale (2004).
Human-Computer Interaction, third edition.
Prentice Hall. ISBN 0-13-239864-8.
http://www.hcibook.com/e3/
EclipseCon '09 - The Happy Marriage of EMF, Data binding, UI Forms and Field ...Tonny Madsen
Imagine you have to develop a larger Eclipse RCP based application with many dozens - maybe hundreds - of views, dialogs and wizards all based on a large common EMF based data model. How do you make sure you get a consistent and modern interface that can be extended in the future without redesigning everything again and again?
what is user support system???
This file will provide detailed overview about the user support system and how it will works in human computer interaction and why we need it .....
Here's a summarised version of the slides shared by Nielsen at the DataScience SG meetup on 20 Apr 2015. Thanks to our generous speakers for sharing on their data science endeavours =D
DataKind SG sharing on our first DataDive with Humanitarian Organization for Migration Economics (HOME) and Earth Hour.
Know of other non-profits we can help? Reach out to singapore@datakind.org or drop me a note =)
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In this presentation, we will look at one such drones-at-work application to reveal some of the behind-the-scene processes and technologies employed. Specifically, we will dive into the precision agriculture domain and share some of the computer vision problems we face, and take a look at various potential solutions to these challenges.
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This deck was used in the IDA facilitation of the John Hopkins' Data Science Specialization course for Statistical Inference. It covers the topics in week 3 (hypothesis testing and t tests).
The data and R script for the lab session can be found here: https://github.com/eugeneyan/Statistical-Inference
Statistical inference: Probability and DistributionEugene Yan Ziyou
This deck was used in the IDA facilitation of the John Hopkins' Data Science Specialization course for Statistical Inference. It covers the topics in week 1 (probability) and week 2 (distribution).
what is user support system???
This file will provide detailed overview about the user support system and how it will works in human computer interaction and why we need it .....
Here's a summarised version of the slides shared by Nielsen at the DataScience SG meetup on 20 Apr 2015. Thanks to our generous speakers for sharing on their data science endeavours =D
DataKind SG sharing on our first DataDive with Humanitarian Organization for Migration Economics (HOME) and Earth Hour.
Know of other non-profits we can help? Reach out to singapore@datakind.org or drop me a note =)
Garuda Robotics x DataScience SG Meetup (Sep 2015)Eugene Yan Ziyou
What exactly goes on in the commercial drone/UAV industry in Singapore and globally? Behind the hype of consumer “selfie” drones lies a vast number of interesting commercial applications, where drones become an enabler for enterprises to gain new aerial perspectives of their facilities and estates, to make intelligent decisions incorporating this additional dimension of data.
In this presentation, we will look at one such drones-at-work application to reveal some of the behind-the-scene processes and technologies employed. Specifically, we will dive into the precision agriculture domain and share some of the computer vision problems we face, and take a look at various potential solutions to these challenges.
A Study on the Relationship between Education and Income in the USEugene Yan Ziyou
What is the relationship between education and income? Is education truly the great equalizer or do factors such as gender and family income at the age of 16 affect current income?
As part of the Coursera Data Analysis and Statistical Inference course, these issues were examined using data from the US General Social Survey in R.
Kaggle Otto Challenge: How we achieved 85th out of 3,514 and what we learntEugene Yan Ziyou
Our team achieved 85th position out of 3,514 at the very popular Kaggle Otto Product Classification Challenge. Here's an overview of how we did it, as well as some techniques we learnt from fellow Kagglers during and after the competition.
Statistical inference: Hypothesis Testing and t-testsEugene Yan Ziyou
This deck was used in the IDA facilitation of the John Hopkins' Data Science Specialization course for Statistical Inference. It covers the topics in week 3 (hypothesis testing and t tests).
The data and R script for the lab session can be found here: https://github.com/eugeneyan/Statistical-Inference
Statistical inference: Probability and DistributionEugene Yan Ziyou
This deck was used in the IDA facilitation of the John Hopkins' Data Science Specialization course for Statistical Inference. It covers the topics in week 1 (probability) and week 2 (distribution).
Statistical inference: Statistical Power, ANOVA, and Post Hoc testsEugene Yan Ziyou
This deck was used in the IDA facilitation of the John Hopkins' Data Science Specialization course for Statistical Inference. It covers the topics in week 4 (statistical power, ANOVA, and post hoc tests).
The data and R script for the lab session can be found here: https://github.com/eugeneyan/Statistical-Inference
Sharing about my data science journey and what I do at LazadaEugene Yan Ziyou
Was invited to share with the SMU Masters of IT in Business students on (i) how I got to my current position as a data scientist and (ii) what I do in my current position.
Includes suggested areas to focus on (e.g., distributed systems and processing) and how to gain more experience (e.g., volunteering). I also go through the problems that we solve at Lazada using machine learning and a high level architecture of how we do it.
“Markets are certainly looking at election results with some apprehension, but what is also true is that they are in for a correction. Elections might act as the trigger for such a correction,” said Jagannadham Thunuguntla, equity head at SMC Capitals.
These Notes from the class of BS EDUCATION 1st Semester (Spring) Session 2023-2027 Teacher :Ch Naveed Afzal
semester started in march 2023 and end in july 2023
Slide 4 - User Interface Design.pptx interface rather than its functionality ...DennisAnaafi1
interface rather than its functionality
•A poorly designed interface can cause a user to make catastrophic errors
•Poor user interface design is the reason why so many software systems are never used
User Experience & Design…Designing for others…UEDPreeti Chopra
User-centered design (UCD) techniques,
Simplification of technology as per user’s needs,
User is right,
User testing,
Information architecture,
Interaction design,
ui,
ued
ux
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.
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™:
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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
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"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.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
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Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
3. Visibility of system status
The system keep users informed about what is going on,
through appropriate feedback within reasonable time
(feedback). Microsoft word program, after save you work,
again if you want edit, the ask enable, you can click enable.
4. Match between system and the real
world
The system speak the users' language, with words, phrases
and concepts familiar to the user. Follow real-world
conventions, making information appear in a natural and
logical order. Microsoft word program has insert option have
online video part or links here you can follow real word
conventions.
5. User control and freedom
Users choose this system functions by mistake and will need
a clearly marked "exit" to leave the unwanted state. For
example, Microsoft word program can support undo and
redo.
6. Consistency and standards
Users should not have to wonder whether different words,
situations, or actions mean the same thing. Follow platform
conventions. For example, Microsoft word program use same
style toolbar with the same primary menu options such as
home, page, and layout.
7. Error prevention
Even better than good error messages is a careful design
which prevents a problem from occurring in the first place.
Either eliminate error-prone conditions or check for them and
present users with a confirmation option before they commit to
the action. In Microsoft Word program when you write word if
it spelling is wrong automatically coming the word’s underline
red it is error prevention.
8. Recognition rather than recall
Minimize the user's memory load by making objects, actions,
and options visible. The user should not have to remember
information from one part of the dialogue to another.
Instructions for use of the system should be visible or easily
retrievable whenever appropriate. Microsoft word program
has home option there is minimize font names, if you can
write something you can choose font types.
9. Flexibility and efficiency of use
Accelerators—unseen by the novice user—may often speed
up the interaction for the expert user such that the system
can cater to both inexperienced and experienced users. For
example, Microsoft word you can create table then list of
keyboard shortcuts and accelerators.
10. Aesthetic and minimalist design
Every extra unit of information in a dialogue competes with
the relevant units of information and diminishes their relative
visibility. Visual layout should respect layout should respect
the principles of contrast, repetition, alignment and proximity.
Microsoft word program – contrast: Not bold text is used
menu options. Repetition: the blue color used menu options.
11. Help users recognize, diagnose, and
recover from errors
Error messages should be expressed in plain
language (no codes), precisely indicate the problem,
and constructively suggest a solution.
12. Help and documentation
Even though it is better if the system can be used without
documentation, it may be necessary to provide help and
documentation. Any such information should be easy to
search, focused on the user's task, list concrete steps to be
carried out, and not be too large. For example Microsoft word
program word help opens then answering the most like
questions about filed or instructions.