This document describes the design and implementation of a visualization tool to provide more information about the impact of academic publications than citation counts alone. It represents references, citations, and self-citations over time and allows viewing individual papers or collections in different contexts. The tool uses shape grammars to classify papers by impact level into glyphs for compact overviews. It has been implemented in D3 and deployed on the INSPIRE platform for high energy physics publications. Future work may include a Chrome extension and exploring better impact metrics.
Enhancing a Social Science Model-building Workflow with Interactive Visualisa...Cagatay Turkay
Slides for my talk on our paper titled "Enhancing a Social Science Model-building Workflow with Interactive Visualisation by Turkay, C., Slingsby, A., Lahtinen, K., Butt, S., & Dykes, J., presented at ESANN 2016 in Brugge on April 2016." The talk gives the details of our collaborative work as a team of social scientists and visualisation researchers investigating novel ways to improve the model building process through interactive approaches. Related publication can be found on this link: http://openaccess.city.ac.uk/14232/
GradTrack: Getting Started with Statistics September 20, 2018Nancy Garmer
Dr. Gary Burns, Professor, School of Psychology, Florida Institute of Technology Evans Library Introduction to Statistics: Don't be afraid
Video presentation with audio available on YouTube:http://bit.ly/GradTrackStatistics2018
The Five Graphs of Government: How Federal Agencies can Utilize Graph TechnologyNeo4j
In this session from Neo4j Government Graphday, Philip Rathle discusses how federal agencies and contractors can utilize graphs to power their applications.
Enhancing a Social Science Model-building Workflow with Interactive Visualisa...Cagatay Turkay
Slides for my talk on our paper titled "Enhancing a Social Science Model-building Workflow with Interactive Visualisation by Turkay, C., Slingsby, A., Lahtinen, K., Butt, S., & Dykes, J., presented at ESANN 2016 in Brugge on April 2016." The talk gives the details of our collaborative work as a team of social scientists and visualisation researchers investigating novel ways to improve the model building process through interactive approaches. Related publication can be found on this link: http://openaccess.city.ac.uk/14232/
GradTrack: Getting Started with Statistics September 20, 2018Nancy Garmer
Dr. Gary Burns, Professor, School of Psychology, Florida Institute of Technology Evans Library Introduction to Statistics: Don't be afraid
Video presentation with audio available on YouTube:http://bit.ly/GradTrackStatistics2018
The Five Graphs of Government: How Federal Agencies can Utilize Graph TechnologyNeo4j
In this session from Neo4j Government Graphday, Philip Rathle discusses how federal agencies and contractors can utilize graphs to power their applications.
Journey of The Connected Enterprise - Knowledge Graphs - Smart DataBenjamin Nussbaum
We live in an era where the world is more connected than ever before and the trajectory is such that data relationships will only continue to increase with no signs of slowing down.
Connected data is the key to your business succeeding and growing in today’s connected world.
Leading enterprises will be the ones that utilize relationship-centric technologies to leverage connections from their internal operations and supply chain to their customer and user interactions. This ability to utilize connected data to understand all the nuanced relationships within their organization will propel them forward as they act on more holistic insights.
Every organization needs a knowledge graph because connected data is an essential foundation to advancing business. Knowledge graphs provide:
- Increased visibility between internal groups
- Efficiency gains
- Cross-functional data collaboration
- Core complete and reliable business insights
- Better customer engagement
The live presentation and discussion can be found here: https://www.youtube.com/watch?v=RQGdw82rAes
Additional reading on why connected data is beneficial: https://www.graphgrid.com/why-connected-data-is-more-useful/
Connected data solutions available by Benjamin and his team via GraphGrid and AtomRain: https://www.graphgrid.com and https://www.atomrain.com
How to Design Retail Recommendation Engines with Neo4jNeo4j
Recommendations are at the core of digital transformation in retail today. Whether you’re building features such as product recommendations, promotion recommendations, personalized customer experience, or re-imagining your supply chain to meet customer demands for same day delivery — you’re facing challenges that require the ability to leverage connections from many different data sources, in real-time. There’s no better technology to meet these challenges than a native graphDB technology such as Neo4j.
Relational databases were conceived to digitize paper forms and automate well-structured business processes, and still have their uses. But RDBMS cannot model or store data and its relationships without complexity, which means performance degrades with the increasing number and levels of data relationships and data size. Additionally, new types of data and data relationships require schema redesign that increases time to market.
A native graph database like Neo4j naturally stores, manages, analyzes, and uses data within the context of connections meaning Neo4j provides faster query performance and vastly improved flexibility in handling complex hierarchies than SQL.
This webinar explains why companies are shifting away from RDBMS towards graphs to unlock the business value in their data relationships.
Slides from presentation at GraphConnect London 19/11/2013 about performing an impact analysis using Neo4J graph database in the domain of web service integration.
IBM Graph – Graph Database-as-a-Service: Managing Data and Its Relationships ...Alexander Pozdneev
The slides presented by Alexander Pozdneev at GraphHPC-2017 conference (http://www.dislab.org/GraphHPC-2017/en/agenda.php).
Graph databases are increasingly popular in managing the information where the relationships between the data entities are of highest priority. However, a technical task of deploying, managing, and maintaining a graph database on-a-premise is decoupled from the process of solving an applied problem. IBM Graph is a graph database-as-a-service available on the IBM Bluemix cloud platform-as-a-service. IBM Graph is built upon open-source components while featuring high-availability and scalability on-demand. In this talk, we will introduce the main concepts behind IBM Graph and show how to leverage its API and the Bluemix console GUI.
Discussion Post Rubric
(20) Possible Points
Category 4 Points 2 Points 0 Points
Length of Post The author’s post
consisted of 150 – 200
words.
The author’s post
consisted of 150 - 100
words.
The author’s post
consisted of 100 words
or less.
Grammar, usage,
spelling
The author’s post
contained less than 2
The author’s post
contained 3 – 4
The author’s post
contained over 5
grammar, usage, or grammar, usage, or grammar, usage, or
spelling errors. spelling errors. spelling errors and
proofreading was not
apparent.
Referencing and
utilizing outside
sources
The author posted
references in APA
format and cited an
one or more original
references, outside of
the assigned readings.
The author posted
references in APA
format of assigned
readings, but did not
include an additional
reference.
The author neither
utilized APA format or
referenced material
used nor cited an
outside reference.
Promotes
Discussion
The author’s post
clearly responds to the
assignment prompt,
The author’s post
responds to the
assignment prompt,
The author’s post does
not correspond with
the assignment
develops ideas but relies heavily on prompt,
cogently, organizes definitional mainly discusses
them logically and explanations and does personal opinions,
supports them through not create and develop irrelevant information,
empirical writing. The original ideas and or information is
author’s post also support them logically. presented with limited
raises question or The author’s post may logic and lack of
stimulates discussion. stimulate some development and
discussion. organization of ideas.
Does not support any
claims made.
Timely Response Assignment is posted
on or prior to due date.
Assignment is one day
late.
Assignment is two
days late.
Be advised, there are also response costs associated with specific behaviors:
• response cost of (3) points will be administered for not responding to a
peer’s post.
• response cost of (1) point will be administered for not reading all of peers’
posts.
• Discussion posts that are turned in more than two days after the due date
will not be accepted unless otherwise excused by the instructor.
Educ Psychol Rev (2017) 29:583–598
DOI 10.1007/s10648-015-9339-x
REVIEW ARTICLE
A Critical Review of Line Graphs in Behavior
Analytic Journals
Richard M. Kubina Jr.1 & Douglas E. Kostewicz2 &
Kaitlyn M. Brennan2 & Seth A. King3
Published online: 3 September 2015
# Springer Science+Business Media New York 2015
Abstract Visual displays such as graphs have played an instrumental role in psychology. One
discipline relies almost exclusively on graphs in both applied and basic settings, behavior
analysis. The most common graphic used in behavior analysis falls under the category of time
series. The line graph represents the most frequently used display for visual analysis and
subsequent interpretation and communication of exp ...
We estimate that nearly one third of news articles contain references to future events. While this information can prove crucial to understanding news stories and how events will develop for a given topic, there is currently no easy way to access this information. We propose a new task to address the problem of retrieving and ranking sentences that contain mentions to future events, which we call ranking related news predictions. In this paper, we formally define this task and propose a learning to rank approach based on 4 classes of features: term similarity, entity-based similarity, topic similarity, and temporal similarity. Through extensive evaluations using a corpus consisting of 1.8 millions news articles and 6,000 manually judged relevance pairs, we show that our approach is able to retrieve a significant number of relevant predictions related to a given topic.
Journey of The Connected Enterprise - Knowledge Graphs - Smart DataBenjamin Nussbaum
We live in an era where the world is more connected than ever before and the trajectory is such that data relationships will only continue to increase with no signs of slowing down.
Connected data is the key to your business succeeding and growing in today’s connected world.
Leading enterprises will be the ones that utilize relationship-centric technologies to leverage connections from their internal operations and supply chain to their customer and user interactions. This ability to utilize connected data to understand all the nuanced relationships within their organization will propel them forward as they act on more holistic insights.
Every organization needs a knowledge graph because connected data is an essential foundation to advancing business. Knowledge graphs provide:
- Increased visibility between internal groups
- Efficiency gains
- Cross-functional data collaboration
- Core complete and reliable business insights
- Better customer engagement
The live presentation and discussion can be found here: https://www.youtube.com/watch?v=RQGdw82rAes
Additional reading on why connected data is beneficial: https://www.graphgrid.com/why-connected-data-is-more-useful/
Connected data solutions available by Benjamin and his team via GraphGrid and AtomRain: https://www.graphgrid.com and https://www.atomrain.com
How to Design Retail Recommendation Engines with Neo4jNeo4j
Recommendations are at the core of digital transformation in retail today. Whether you’re building features such as product recommendations, promotion recommendations, personalized customer experience, or re-imagining your supply chain to meet customer demands for same day delivery — you’re facing challenges that require the ability to leverage connections from many different data sources, in real-time. There’s no better technology to meet these challenges than a native graphDB technology such as Neo4j.
Relational databases were conceived to digitize paper forms and automate well-structured business processes, and still have their uses. But RDBMS cannot model or store data and its relationships without complexity, which means performance degrades with the increasing number and levels of data relationships and data size. Additionally, new types of data and data relationships require schema redesign that increases time to market.
A native graph database like Neo4j naturally stores, manages, analyzes, and uses data within the context of connections meaning Neo4j provides faster query performance and vastly improved flexibility in handling complex hierarchies than SQL.
This webinar explains why companies are shifting away from RDBMS towards graphs to unlock the business value in their data relationships.
Slides from presentation at GraphConnect London 19/11/2013 about performing an impact analysis using Neo4J graph database in the domain of web service integration.
IBM Graph – Graph Database-as-a-Service: Managing Data and Its Relationships ...Alexander Pozdneev
The slides presented by Alexander Pozdneev at GraphHPC-2017 conference (http://www.dislab.org/GraphHPC-2017/en/agenda.php).
Graph databases are increasingly popular in managing the information where the relationships between the data entities are of highest priority. However, a technical task of deploying, managing, and maintaining a graph database on-a-premise is decoupled from the process of solving an applied problem. IBM Graph is a graph database-as-a-service available on the IBM Bluemix cloud platform-as-a-service. IBM Graph is built upon open-source components while featuring high-availability and scalability on-demand. In this talk, we will introduce the main concepts behind IBM Graph and show how to leverage its API and the Bluemix console GUI.
Discussion Post Rubric
(20) Possible Points
Category 4 Points 2 Points 0 Points
Length of Post The author’s post
consisted of 150 – 200
words.
The author’s post
consisted of 150 - 100
words.
The author’s post
consisted of 100 words
or less.
Grammar, usage,
spelling
The author’s post
contained less than 2
The author’s post
contained 3 – 4
The author’s post
contained over 5
grammar, usage, or grammar, usage, or grammar, usage, or
spelling errors. spelling errors. spelling errors and
proofreading was not
apparent.
Referencing and
utilizing outside
sources
The author posted
references in APA
format and cited an
one or more original
references, outside of
the assigned readings.
The author posted
references in APA
format of assigned
readings, but did not
include an additional
reference.
The author neither
utilized APA format or
referenced material
used nor cited an
outside reference.
Promotes
Discussion
The author’s post
clearly responds to the
assignment prompt,
The author’s post
responds to the
assignment prompt,
The author’s post does
not correspond with
the assignment
develops ideas but relies heavily on prompt,
cogently, organizes definitional mainly discusses
them logically and explanations and does personal opinions,
supports them through not create and develop irrelevant information,
empirical writing. The original ideas and or information is
author’s post also support them logically. presented with limited
raises question or The author’s post may logic and lack of
stimulates discussion. stimulate some development and
discussion. organization of ideas.
Does not support any
claims made.
Timely Response Assignment is posted
on or prior to due date.
Assignment is one day
late.
Assignment is two
days late.
Be advised, there are also response costs associated with specific behaviors:
• response cost of (3) points will be administered for not responding to a
peer’s post.
• response cost of (1) point will be administered for not reading all of peers’
posts.
• Discussion posts that are turned in more than two days after the due date
will not be accepted unless otherwise excused by the instructor.
Educ Psychol Rev (2017) 29:583–598
DOI 10.1007/s10648-015-9339-x
REVIEW ARTICLE
A Critical Review of Line Graphs in Behavior
Analytic Journals
Richard M. Kubina Jr.1 & Douglas E. Kostewicz2 &
Kaitlyn M. Brennan2 & Seth A. King3
Published online: 3 September 2015
# Springer Science+Business Media New York 2015
Abstract Visual displays such as graphs have played an instrumental role in psychology. One
discipline relies almost exclusively on graphs in both applied and basic settings, behavior
analysis. The most common graphic used in behavior analysis falls under the category of time
series. The line graph represents the most frequently used display for visual analysis and
subsequent interpretation and communication of exp ...
We estimate that nearly one third of news articles contain references to future events. While this information can prove crucial to understanding news stories and how events will develop for a given topic, there is currently no easy way to access this information. We propose a new task to address the problem of retrieving and ranking sentences that contain mentions to future events, which we call ranking related news predictions. In this paper, we formally define this task and propose a learning to rank approach based on 4 classes of features: term similarity, entity-based similarity, topic similarity, and temporal similarity. Through extensive evaluations using a corpus consisting of 1.8 millions news articles and 6,000 manually judged relevance pairs, we show that our approach is able to retrieve a significant number of relevant predictions related to a given topic.
Presentation slides for the paper 'Structural Patterns and Generative Models of Real-world Hypergraphs'. Published in KDD2020 - ACM SIGKDD International Conference on Knowedge Discovery and Data Mining
ProjectHouston’sFaults.Students willcarry out Internet res.docxbriancrawford30935
Project: Houston’s Faults.
Students will carry out Internet research on faults in and around Houston Texas. Your research should look at the following aspects related to faults.
· The origin of faults in the Houston area
· The distribution of faults in the area
· The type of faults (normal, reverse, strike slip etc.)
· How the faults impact city planning (location of airports, major highways, stadiums, city center, sewage lines etc. in relation to the major faults)
· Faults and earthquakes
· As a geoscience student, how can your knowledge of the origin, distribution and types of fault be useful to city planners?
Students will present this information in the form of a power point slide. Your power point should include all relevant information including sketches, photos, maps and should have a reference section.
EXAMPLE ON HOW YOU CAN FORMAT YOUR PRESENTATION: you will create a slide show then print it out and turn it in a black folder. You do not need to send it to me via email
1st slide Intro: What are faults? (types of faults; normal, reverse, strike slip etc)
*have figures but let them stand alone (meaning the should be on there on slide)
2nd slide Faults in Houston Texas
Origin of faults (what cause them)
Distribution (include a map of where faults are located) remember figures must stand alone)
3rd slide faults in city planning. (Stadiums, airports, major roads etc) how it affects it
Think: Hobby airport has a fault, roads have faults, city center, why are sewers where faults are, why do Houston Texas have faults but no earthquakes
POWER POINT SLIDE DUE APRIL 27TH THRUSDAY AS SOON AS YOU WALKING INTO CLASS.. Slides must be between 10 and 20 slides. *no less than 10 and nor more then 20
Abbreviated Title 1
Title
Your name here
School name here
Full course name and number
Instructor name
Date of submission
Remember the font should be 12 point, Times New Roman or Arial for everything, including the title page
Abstract
An abstract is nothing more than a summary of the main ideas. In this course, the abstract is a summary of the basic building blocks used in the research proposal. It will be slightly different than an abstract for a paper or essay.
In a paper or essay, the abstract summarizes the main points of the document. In a research proposal, the abstract summarizes the main research components (to be used) as demonstrated with the topic.
In either case, an abstract is simple. It is just a summary of the main ideas, points, or methodologies. The difference is what the author is summarizing. In other words, the reader should be able to read the brief abstract and understand what the researcher is proposing..... In 2 or 3 paragraphs, you should be able to answer the following questions in narrative form: What is the topic? What are the variables? What is the hypothesis? What is the design? What is the population/sample? What is the Data Collection Method(s)?
Title
This is your introducti.
Assignment 1case study 6.1.jpgAssignment 1case study 6.1-1.docxdeanmtaylor1545
Assignment 1/case study 6.1.jpg
Assignment 1/case study 6.1-1.jpg
Assignment 1/case study 6.1-2.jpg
Assignment 1/case study 6.1-3.jpg
Assignment 1/case study 6.1-4.jpg
Chapter6/Chapter Guides.pdf
IBM SPSS for Introductory Statistics: Use and Interpretation, 5th Ed. (Morgan, Leech, Gloeckner & Barrett) Instructor's Manual by Gene W.
Gloeckner and Don Quick
Chapter 6 – Selecting and Interpreting Inferential Statistics
Study Guide
OBJECTIVES:
The student will be able to:
1. Identify the general design classification for difference research questions.
2. Explain the distinctions of within subjects design versus between groups design
classifications.
3. Utilize a decision tree (Figure 6.1) to guide the selection of appropriate inferential
statistics (Tables 6.1-6.4).
a. Identify the research problem.
b. Identify the variables and their level of measurement.
c. Select appropriate inferential statistic.
4. Describe the relationship between difference and associational inferential statistics as a
function of the general linear model.
5. Interpret the results of a statistical test.
a. Determine whether to reject the null hypothesis.
b. Determine the direction of the effect.
c. Evaluate the size of the effect.
6. Discuss the relationship between statistical significance and practical significance.
TERMINOLOGY:
• variables
• levels of measurement
• descriptive statistics
• inferential statistics
o difference inferential statistics
o associational inferential statistics
• difference question designs
• between group designs
• within subjects design (repeated measures design)
• single factor designs
• between groups factorial designs
• mixed factorial designs
• basic (bivariate) statistics
o phi or Cramer’s V
o eta
o Pearson product moment correlation
o Kendall’s tau or Spearman rho
• complex statistics
o factorial ANOVA
o multiple regression
o discriminant analysis
o logistic regression
IBM SPSS for Introductory Statistics: Use and Interpretation, 5th Ed. (Morgan, Leech, Gloeckner & Barrett) Instructor's Manual by Gene W.
Gloeckner and Don Quick
o MANOVA
o ANCOVA
• loglinear
• general linear model
• statistical significance
o critical value
o calculated value
o statistically significant
o Sig.
• practical significance
• effect size
o r family of effect size measures
o d family of effect size measures
• confidence intervals
ASSIGNMENTS: See additional activities and extra SPSS problems for assignment examples.
Chapter6/Chapter Outlines.pdf
IBM SPSS for Introductory Statistics: Use and Interpretation, 5th Ed. (Morgan, Leech, Gloeckner & Barrett) Instructor's Manual by
Gene W. Gloeckner and Don Quick
Chapter 6 – Selecting and Interpreting Statistics
Chapter Outline
I. General Design Classifications for Difference Questions
A. Labeling difference question designs.
1. State overall type of design (e.g. between groups, within
subjects). .
Detecting Incongruity Between News Headline and Body Text via a Deep Hierarch...Seoul National University
The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19)
January 27 – February 1, 2019, Honolulu, Hawaii, USA.
https://aaai.org/Conferences/AAAI-19/
Focus on what you learned that made an impression, what may have s.docxkeugene1
Focus on what you learned that made an impression, what may have surprised you, and what you found particularly beneficial and why. Specifically:
What did you find that was really useful, or that challenged your thinking?
What are you still mulling over?
Was there anything that you may take back to your classroom?
Is there anything you would like to have clarified?
ANSWER THE ABOVE QUESTIONS BASED ON THE DOCUMENTS BELOW
Introduction & Goals
This week, we will investigate the distribution of a variable and look at ways to best see the key features of a quantitative variable’s distribution. We will look at visualizations of data, including line plots, frequency tables, stemplots, and histograms. We will hone our ability to describe key features of a distribution from visualizations and use them to compare distributions. We will begin to think about ideas for the Comparative Study by brainstorming in our project groups.
Goals
:
Reinforce the idea that data will vary
Explain what the distribution of variable is
Identify five key features of a distribution: center, spread, shape, clusters & outliers
Identify and create appropriate displays for categorical and quantitative data in one variable, including bar graphs, line plots, frequency tables, and histograms
Analyze distributions using stemplots and histograms
Recognize advantages and limitations of histograms
Begin to explore technology for use in statistics
Begin work on Comparative Study Final Project
DOW #2: How Long Is A Minute?
In week 1, we gathered data for this week’s DoW, addressing the question:
“How long is a minute to an adult?”
This week we'll:
In investigations 1 & 2, you will analyze the data with dot plots, frequency tables, stemplots, and histograms.
In Exercise B2, you will post your initial analysis and interpretation to the discussion board by Wednesday, 10 PM EST and create at least three follow-up posts by Friday, 10 PM EST.
In Exercise D2 & E2, you will post your best histogram to the discussion board by Friday, 10 PM EST. Compare the histograms and choose the one you think best represents the distribution by Sunday, 10 PM EST
Investigation 1: Seeing the Distribution
As we emphasized in Week 1,
data varies
. This point may seem trivial, but it encapsulates one of the most fundamental concepts of statistics:
variability
. Statistical Analysis is really a study of the patterns we find within this variation in the data. The pattern(s) in the variation is called the
distribution
of the variable. Much of statistics focuses on ways to represent and describe the distribution of a variable.
Activities A & B in this investigation focus on representing and describing the distribution.
Activity C introduces Excel as a tool for looking at a distribution.
Inv 1, Activity A: Patterns in the Variation
As we emphasized in Week 1,
data varies
. This point may seem trivial, but it encapsulates one of the most fundamental concepts of statistics:
variability
. Statistical Analy.
Visual Compression of Workflow Visualizations with Automated Detection of Mac...Eamonn Maguire
VIS 2013 Presentation
Paper is available here: http://www.oerc.ox.ac.uk/personal-pages/emaguire/AutoMacron.pdf
Code is available here: http://github.com/isa-tools/automacron
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
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.
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.
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/
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.
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.
"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.
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.
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.
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/
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.
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
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Visualization of Publication Impact
1. Visualization of Publication Impact
Eamonn Maguire (CERN), Javier Martin Montull (CERN), Gilles Louppe (CERN & NYU)
CERN, Geneva, Switzerland
New York University, NYC, USA
eamonn.maguire@cern.ch
@antarcticdesign
4. The Problem
When looking through a set
of papers, e.g. when
deciding on who should get a
faculty position, people look
at very coarse metrics, e.g.
the citation count for a paper
and the h-index of an author.
But these metrics don’t tell
the whole story…
5. For each paper, our
system has:
1) every reference with
its citation count; and
2) every citation with its
respective citation
count,
The Problem
6. But the only metric ever really used to evaluate a paper is its
citation count.
But it’s difficult to see the importance of papers citing this paper.
And it’s difficult to see the relative importance of a paper within
its field (consider the importance of references too).
7. The Problem
Representing all of the information just as a number would remove information.
Our goal is to provide more information…visually.
8. The Problem
The visualization needs to encode:
1) The distribution of references and citations over time;
2) The number of citations for everything;
3) Encode self citations; and
4) Allow for extension (e.g. add data).
Encoding Requirements
9. The Problem
Also, we wished to create a design that could be used in a number of
different contexts, including:
1) in a detailed view;
2) as a glyph; and
3) as a summary for an author or research field.
Visualisation Requirements
12. Design
2001
2001
the impact graph
1) Plot the paper by its date of
publication and citation count.
2) Plot all the references by their
date and citation count.
13. 2001 2001
Design the impact graph
3) Plot all the citing articles by
their date and citation count.
4) Plot the citation momentum
graph. e.g. aggregation of
number of citations in a year.
14. Design
Referenced Papers Cited by
2001
Self
Referenced Papers Cited by Self
Detailed impact graph Impact Glyph Impact Collection
18. Shape Grammar
Can one quickly see a publications impact just from the shape of the graph?
Low impact High impact
N1 N5
References
Citations
N3 N4N2
Higher Impact
None
References
Citations
Higher Impact
Lower Impact
References
Citations
Average
Average
References
Citations
Lower Impact
Higher Impact
References
Citations
Lower Impact
Lower Impact
21. Shape Grammar
We can use these shapes to reduce the visual complexity of our impact graph collection
visualisation to support higher numbers of papers.
High impact publications
24. Added to the new version on inspire, the largest high energy physics publication resource,
developed largely at CERN and used by over 43,000 physicists last month.
Usage