Complex Networks proposal
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This document outlines a student's complex networks project analyzing Twitter data related to fitness and healthy eating. Specifically, the student collected over 500,000 tweets containing the hashtags #fitness and #eatclean from nearly 80,000 unique users. The student plans to analyze this data to measure how fitness and eating behaviors spread through the social network of followers on Twitter. Related works on social contagion and sentiment analysis of social media data are also cited for context.
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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!
AI-Powered Food Delivery Transforming App Development in Saudi Arabia.pdf
In this blog post, we'll delve into the intersection of AI and app development in Saudi Arabia, focusing on the food delivery sector. We'll explore how AI is revolutionizing the way Saudi consumers order food, how restaurants manage their operations, and how delivery partners navigate the bustling streets of cities like Riyadh, Jeddah, and Dammam. Through real-world case studies, we'll showcase how leading Saudi food delivery apps are leveraging AI to redefine convenience, personalization, and efficiency.
Full-RAG: A modern architecture for hyper-personalization
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
20240609 QFM020 Irresponsible AI Reading List May 2024
Everything I found interesting about the irresponsible use of machine intelligence in May 2024
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
CAKE: Sharing Slices of Confidential Data on Blockchain
Presented at the CAiSE 2024 Forum, Intelligent Information Systems, June 6th, Limassol, Cyprus.
Synopsis: Cooperative information systems typically involve various entities in a collaborative process within a distributed environment. Blockchain technology offers a mechanism for automating such processes, even when only partial trust exists among participants. The data stored on the blockchain is replicated across all nodes in the network, ensuring accessibility to all participants. While this aspect facilitates traceability, integrity, and persistence, it poses challenges for adopting public blockchains in enterprise settings due to confidentiality issues. In this paper, we present a software tool named Control Access via Key Encryption (CAKE), designed to ensure data confidentiality in scenarios involving public blockchains. After outlining its core components and functionalities, we showcase the application of CAKE in the context of a real-world cyber-security project within the logistics domain.
Paper: https://doi.org/10.1007/978-3-031-61000-4_16
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
20240609 QFM020 Irresponsible AI Reading List May 2024
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CAKE: Sharing Slices of Confidential Data on Blockchain
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Complex Networks proposal
- 1. MY COMPLEX NETWORKS PROJECT
- 2. HOW EVERYTHING STARTED? Observation of my friend’s behavior related to food choices Observation of the summer camp obese teenagers Why people become fat? • Genetics • Money • Friends Is it a choice? What makes people eat what they eat? Why some people say that they want to lose fat but still having the same habits related to food even knowing about nutrition and knowing that they shouldn’t eat what they are eating?
- 3. NICHOLAS A. CHRISTAKIS The Spread of Obesity in a Large Social Network over 32 Years
- 4. If the obesity spreads through network, the same thing can be observed with #fitness and #eatclean behaviors?
- 5. • A special attention must be given to the word behavior because the fact of people posting something doesn’t mean that he is doing what he is saying that he is doing. • I don’t have the body mass measurements of the users of twitter.
- 6. WHAT DO I HAVE? • Tweets with the hashtags #eatclean and #fitness • Users and followers of the users • Followers that also posted a tweet with the hashtags #eatclean and #fitness
- 7. HOW MUCH DATA DO I HAVE? Tweets: 522188 ! Users: 79719
- 8. DEFINITION OF THE NETWORK: NODES AND RELATIONSHIP(S)
- 9. HOW AM I STORING THE DATA?
- 10. WHAT ELSE AM I USING? • Python • Pymongo • Tweepy • Networkx
- 11. HOW IT LOOKS LIKE (Sample data)
- 12. WHAT CAN I DO? • Sentiment analysis • Homophily measurement using sentiment analysis • Government data about obesity (Geolocalization) • Geolocalization of the users
- 13. RELATED WORKS • Theodore A. Vickey,1 Kathleen Martin Ginis, Maciej Dabrowski. Twitter classification model: the ABC of two million fitness tweets. • Morgan R. Frank, Lewis Mitchell, Peter Sheridan Dodds & Christopher M. Danforth. Happiness and the Patterns of Life: A Study of Geolocated Tweets. Scientific Reports. 3: 2625. 2013 • Johan Bollen, Bruno Goncalves, Guangchen Ruan, Huina Mao. Happiness is assortative in online social networks. Artificial Life. Vol. 17, No. 3, Pages 237-251. • Nicholas A. Christakis, James H. Fowler. The Spread of Obesity in a Large Social Network over 32 Years • Anna Chmiel, Julian Sienkiewicz, Mike Thelwall, Georgios Paltoglou, Kevan Buckley, Arvid Kappas, Janusz A. Hołyst. Collective Emotions Online and Their Influence on Community Life. • Bagozzi, Richard P;Dholakia, Utpal M. Intentional social action in virtual communities. Journal of Interactive Marketing; Spring 2002; 16, 2; ABI/INFORM Complete pg. 2 • Yuriy Hulovatyy, Sidney D’Mello, Rafael A. Calvo, and Tijana Milenković. Network analysis improves interpretation of affective physiological data. jcomplexnetw 2014 : cnu032v1-cnu032. • Apoorv Agarwal Boyi Xie Ilia Vovsha Owen Rambow Rebecca Passonneau. Sentiment Analysis of Twitter Data .Department of Computer Science Columbia University. New York, NY 10027 USA.