Market Basket Analysis Algorithm with Map/Reduce of Cloud Computing presented at PDPTA 2011 (http://www.world-academy-of-science.org/worldcomp11/ws/conferences/pdpta11)
The Data Distribution Service for Real-Time Systems (DDS) is an Object Management Group (OMG) standard for publish/subscribe designed to address the needs of a large class of mission- and business-critical distributed real-time systems and system of systems. The DDS standard was formally adopted in 2004 and in less than five years from its inception has experienced swift adoption in a wide variety of application domains. These application domains are characterized by the need to distribute high volumes of data with predictable low latencies, such as, Radar Processors, Flying and Land Drones, Combat Management Systems, Air Traffic Management, High Performance Telemetry, Large Scale Supervisory Systems, and Automated Stocks and Options Trading. Along with wide commercial adoption, the DDS Standard has been recommended and mandated as the technology for real-time data distribution by key administrations worldwide such as the US Navy, the DoD Information-Technology Standards Registry (DISR), the UK MoD, and EUROCONTROL.
This two-part Tutorial will cover most of the key aspects of DDS to ensure that you can proficiently start using it for designing or developing your next system. In brief this tutorial will get you jump-started into DDS.
Amazon EMR: Optimize Transient Clusters for Data Processing & ETL (ANT341) - ...Amazon Web Services
Amazon EMR was built for agility, enabling you to spin up and down resources for big data processing and analytics on demand, and realize the flexible potential of cloud. In this chalk talk, we discuss in detail how to efficiently start, stop, and resize your clusters for Apache Spark and Hadoop, reducing your costs, and accelerating your time to completion (TTC) for jobs. Join us to hear expert advice on how to optimize your "one-and-done" workloads.
Presentation of the paper "On Using JSON-LD to Create Evolvable RESTful Services" at the 3rd International Workshop on RESTful Design (WS-REST 2012) at WWW2012 in Lyon, France
zenoh -- the ZEro Network OverHead protocolAngelo Corsaro
This presentation introduces the key ideas behind zenoh -- an Internet scale data-centric protocol that unifies data-sharing between any kind of device including those constrained with respect to the node resources, such as computational resources and power, as well as the network.
The Data Distribution Service for Real-Time Systems (DDS) is an Object Management Group (OMG) standard for publish/subscribe designed to address the needs of a large class of mission- and business-critical distributed real-time systems and system of systems. The DDS standard was formally adopted in 2004 and in less than five years from its inception has experienced swift adoption in a wide variety of application domains. These application domains are characterized by the need to distribute high volumes of data with predictable low latencies, such as, Radar Processors, Flying and Land Drones, Combat Management Systems, Air Traffic Management, High Performance Telemetry, Large Scale Supervisory Systems, and Automated Stocks and Options Trading. Along with wide commercial adoption, the DDS Standard has been recommended and mandated as the technology for real-time data distribution by key administrations worldwide such as the US Navy, the DoD Information-Technology Standards Registry (DISR), the UK MoD, and EUROCONTROL.
This two-part Tutorial will cover most of the key aspects of DDS to ensure that you can proficiently start using it for designing or developing your next system. In brief this tutorial will get you jump-started into DDS.
Amazon EMR: Optimize Transient Clusters for Data Processing & ETL (ANT341) - ...Amazon Web Services
Amazon EMR was built for agility, enabling you to spin up and down resources for big data processing and analytics on demand, and realize the flexible potential of cloud. In this chalk talk, we discuss in detail how to efficiently start, stop, and resize your clusters for Apache Spark and Hadoop, reducing your costs, and accelerating your time to completion (TTC) for jobs. Join us to hear expert advice on how to optimize your "one-and-done" workloads.
Presentation of the paper "On Using JSON-LD to Create Evolvable RESTful Services" at the 3rd International Workshop on RESTful Design (WS-REST 2012) at WWW2012 in Lyon, France
zenoh -- the ZEro Network OverHead protocolAngelo Corsaro
This presentation introduces the key ideas behind zenoh -- an Internet scale data-centric protocol that unifies data-sharing between any kind of device including those constrained with respect to the node resources, such as computational resources and power, as well as the network.
Speaker: Jerry Reghunadh, Architect, CAPIOT Software Pvt. Ltd.
Level: 200 (Intermediate)
Track: Microservices
One of the leading assisted e-commerce players in India approached CAPIOT to rebuild their ERP system from the ground up. Their existing PHP-MySQL setup, while rich in functionality and having served them well for under half a decade, would not scale to meet future demands due to the exponential grown they were experiencing.
We built the entire system using a microservices architecture. To develop APIs we used Node.js, Express, Swagger and Mongoose, and MongoDB was used as the active data store. During the development phase, we solved several problems ranging from cross-service calls, data consistency, service discovery, and security.
One of the issues that we faced is how to effectively design and make cross-service calls. Should we implement a cross-service call for every document that we require or should we duplicate and distribute the data, reducing cross-service calls? We found a balance between these two and engineered a solution that gave us good performance.
In addition, our current system has 36 independent services. We enabled services to auto-discover and make secure calls.
We used Swagger to define our APIs first and enforce request and response validations and Mongoose as our ODM for schema validation. We also heavily depend on pre-save hooks to validate data and post-save hooks to trigger changes in other systems. This API-driven approach vastly enabled our frontend and backend teams to scrum together on a single API spec without worrying about the repercussions of changing API schemas.
What You Will Learn:
- How we used Swagger and Mongoose to off-load validations and schema enforcements. We used Swagger to define our APIs first and enforce request and response validations and Mongoose as our ODM for schema validation. We also heavily depend on pre-save hooks to validate data and post-save hooks to trigger changes in other systems. This API-driven approach vastly enabled our frontend and backend teams to scrum together on a single API spec without worrying about the repercussions of changing API schemas.
- How microservices and cross-service calls work. One of the issues that we faced is how to effectively design and make cross-service calls. Should we implement a cross-service call for every document that we require or should we duplicate and distribute the data, reducing cross-service calls? We found a balance between these two and engineered a solution that gave us good performance.
- How we implemented microservice auto discovery: Our current system has 36 independent services, so we enabled services to auto-discover and make secure calls.
Making the right data available at the right time, at the right place, securely, efficiently, whilst promoting interoperability, is a key need for virtually any IoT application. After all, IoT is about leveraging access data – that used to be unavailable – in order to improve the ability to react, manage, predict and preserve a cyber-physical system.
The Data Distribution Service (DDS) is a standard for interoperable, secure, and efficient data sharing, used at the foundation of some of the most challenging Consumer and Industrial IoT applications, such as Smart Cities, Autonomous Vehicles, Smart Grids, Smart Farming, Home Automation and Connected Medical Devices.
In this presentation we will (1) introduce the Eclipse Cyclone DDS project, (2) provide a quick intro that will get you started with Cyclone DDS, (3) present a few Cyclone DDS use cases, and (4) share the Cyclone DDS development road-map.
Software as a Service (SaaS), on demand software, is a software delivery model in which software and its associated data are hosted centrally and accessed using a thin-client, usually a web browser over the internet.
Big Data yani büyük veri nedir diyorsanız ve büyük veri analizinin ne gibi yararlar sağlayacağını merak ediyorsanız sizin için Renerald olarak bu sunumu hazırladık. Büyük veri analizleri sayesinde, stratejilerinizi bilimsel veriler ışığında geliştirip şirketinize inanılmaz artı değerler kazandırabileceksiniz.
A brief overview of caching mechanisms in a web application. Taking a look at the different layers of caching and how to utilize them in a PHP code base. We also compare Redis and MemCached discussing their advantages and disadvantages.
Learn how Amazon Redshift, our fully managed, petabyte-scale data warehouse, can help you quickly and cost-effectively analyze all your data using your existing business intelligence tools. Get an introduction to how Amazon Redshift uses massively parallel processing and scale-out architecture to ensure compute resources grow with your dataset size, and columnar, direct-attached storage to dramatically reduce I/O time. Learn how top online retailer RetailMeNot moved their largest Vertica cluster on Amazon EC2 to Amazon Redshift. See how they gain insights from clickstream, location, merchant, marketing, and operational data across desktop and mobile properties.
Even though the U.S. Department of Defense budget is shrinking and the country's military footprint worldwide is receding the need for the warfighter to have accurate and actionable intelligence has never been more critical. Data from Intelligence, Surveillance, and Reconnaissance (C4ISR) systems such as radar, image processing payloads on Unmanned Aerial Vehicles, and more will be used and fused together to provide commanders with real-time situational awareness. Each system will also need to embrace open architectures and the latest commercial standards to meet the DoD's performance, size, and cost requirements. This e-cast will discuss how embedded defense suppliers are meeting these challenges.
Speaker: Jerry Reghunadh, Architect, CAPIOT Software Pvt. Ltd.
Level: 200 (Intermediate)
Track: Microservices
One of the leading assisted e-commerce players in India approached CAPIOT to rebuild their ERP system from the ground up. Their existing PHP-MySQL setup, while rich in functionality and having served them well for under half a decade, would not scale to meet future demands due to the exponential grown they were experiencing.
We built the entire system using a microservices architecture. To develop APIs we used Node.js, Express, Swagger and Mongoose, and MongoDB was used as the active data store. During the development phase, we solved several problems ranging from cross-service calls, data consistency, service discovery, and security.
One of the issues that we faced is how to effectively design and make cross-service calls. Should we implement a cross-service call for every document that we require or should we duplicate and distribute the data, reducing cross-service calls? We found a balance between these two and engineered a solution that gave us good performance.
In addition, our current system has 36 independent services. We enabled services to auto-discover and make secure calls.
We used Swagger to define our APIs first and enforce request and response validations and Mongoose as our ODM for schema validation. We also heavily depend on pre-save hooks to validate data and post-save hooks to trigger changes in other systems. This API-driven approach vastly enabled our frontend and backend teams to scrum together on a single API spec without worrying about the repercussions of changing API schemas.
What You Will Learn:
- How we used Swagger and Mongoose to off-load validations and schema enforcements. We used Swagger to define our APIs first and enforce request and response validations and Mongoose as our ODM for schema validation. We also heavily depend on pre-save hooks to validate data and post-save hooks to trigger changes in other systems. This API-driven approach vastly enabled our frontend and backend teams to scrum together on a single API spec without worrying about the repercussions of changing API schemas.
- How microservices and cross-service calls work. One of the issues that we faced is how to effectively design and make cross-service calls. Should we implement a cross-service call for every document that we require or should we duplicate and distribute the data, reducing cross-service calls? We found a balance between these two and engineered a solution that gave us good performance.
- How we implemented microservice auto discovery: Our current system has 36 independent services, so we enabled services to auto-discover and make secure calls.
Making the right data available at the right time, at the right place, securely, efficiently, whilst promoting interoperability, is a key need for virtually any IoT application. After all, IoT is about leveraging access data – that used to be unavailable – in order to improve the ability to react, manage, predict and preserve a cyber-physical system.
The Data Distribution Service (DDS) is a standard for interoperable, secure, and efficient data sharing, used at the foundation of some of the most challenging Consumer and Industrial IoT applications, such as Smart Cities, Autonomous Vehicles, Smart Grids, Smart Farming, Home Automation and Connected Medical Devices.
In this presentation we will (1) introduce the Eclipse Cyclone DDS project, (2) provide a quick intro that will get you started with Cyclone DDS, (3) present a few Cyclone DDS use cases, and (4) share the Cyclone DDS development road-map.
Software as a Service (SaaS), on demand software, is a software delivery model in which software and its associated data are hosted centrally and accessed using a thin-client, usually a web browser over the internet.
Big Data yani büyük veri nedir diyorsanız ve büyük veri analizinin ne gibi yararlar sağlayacağını merak ediyorsanız sizin için Renerald olarak bu sunumu hazırladık. Büyük veri analizleri sayesinde, stratejilerinizi bilimsel veriler ışığında geliştirip şirketinize inanılmaz artı değerler kazandırabileceksiniz.
A brief overview of caching mechanisms in a web application. Taking a look at the different layers of caching and how to utilize them in a PHP code base. We also compare Redis and MemCached discussing their advantages and disadvantages.
Learn how Amazon Redshift, our fully managed, petabyte-scale data warehouse, can help you quickly and cost-effectively analyze all your data using your existing business intelligence tools. Get an introduction to how Amazon Redshift uses massively parallel processing and scale-out architecture to ensure compute resources grow with your dataset size, and columnar, direct-attached storage to dramatically reduce I/O time. Learn how top online retailer RetailMeNot moved their largest Vertica cluster on Amazon EC2 to Amazon Redshift. See how they gain insights from clickstream, location, merchant, marketing, and operational data across desktop and mobile properties.
Even though the U.S. Department of Defense budget is shrinking and the country's military footprint worldwide is receding the need for the warfighter to have accurate and actionable intelligence has never been more critical. Data from Intelligence, Surveillance, and Reconnaissance (C4ISR) systems such as radar, image processing payloads on Unmanned Aerial Vehicles, and more will be used and fused together to provide commanders with real-time situational awareness. Each system will also need to embrace open architectures and the latest commercial standards to meet the DoD's performance, size, and cost requirements. This e-cast will discuss how embedded defense suppliers are meeting these challenges.
Explaining implementation and analysis of two well known DFA minimisation algorithms namely Morore and Hopcroft, in Map Reduce using Hadoop. Cost analysis and complexity are described.
Please follow this link: http://dl.acm.org/citation.cfm?id=2926537
Speaking of big data analysis, what comes to mind is possibly using HDFS and MapReduce within Hadoop. But to write a MapReduce program, one must face the problem of learning how to write native java. One might wonder is it possible to use R, the most popular language adapted by data scientist, to implement MapReduce program? And through the integration or R and Hadoop, is it truly one can unleash the power of parallel computing and big data analysis?
This slide introduces how to install RHadoop step by step, and introduces how to write a MapReduce program through R. What is more, this slide will discuss whether RHadoop is really a light for big data analysis, or just another method to write MapReduce Program.
Please mail me if you found any problem toward the slide. EMAIL: tr.ywchiu@gmail.com
談到巨量資料,通常大家腦海中聯想到的就是使用Hadoop 的 MapReduce 和HDFS,但是撰寫MapReduce,則就必須要學會撰寫Java 或透過Thrift 接口才能撰寫。但R是否有辦法運行在Hadoop 上呢 ? 而使用R + Hadoop,是否就真的能結合R強大的分析功能,分析巨量資料呢 ?
本次講題將介紹如何Step by step 在Hadoop 上安裝RHadoop相關套件,並介紹如何撰寫R的MapReduce 程式。更重要的是,此次將探討使用RHadoop 是否為巨量資料分析找到一盞明燈? 或者只是另一套實作方法而已?
This presentation describes the WEP issued in the original IEEE 802.11 and points out it's weakness and how can attacks be executed. Also, it summarizes the best practices to introduce security to the Wireless enviroment.
Mouth preparation for removable partial denture/ dental education in indiaIndian dental academy
Indian Dental Academy: will be one of the most relevant and exciting training
center with best faculty and flexible training programs for dental
professionals who wish to advance in their dental practice,Offers certified
courses in Dental implants,Orthodontics,Endodontics,Cosmetic Dentistry,
Prosthetic Dentistry, Periodontics and General Dentistry.
Everyday I'm Shuffling - Tips for Writing Better Spark Programs, Strata San J...Databricks
Watch video at: http://youtu.be/Wg2boMqLjCg
Want to learn how to write faster and more efficient programs for Apache Spark? Two Spark experts from Databricks, Vida Ha and Holden Karau, provide some performance tuning and testing tips for your Spark applications
introduction to data processing using Hadoop and PigRicardo Varela
In this talk we make an introduction to data processing with big data and review the basic concepts in MapReduce programming with Hadoop. We also comment about the use of Pig to simplify the development of data processing applications
YDN Tuesdays are geek meetups organized the first Tuesday of each month by YDN in London
Is There Room For Another Elephant In TucsonAndy Lenards
Would you like to scale data-intensive tasks horizontally? Would you like an open source project that gave you that foundation?
Well, there is: Apache Hadoop. It's a Java software framework for supporting data-intensive distributed applications. The framework was inspired by Google papers on their MapReduce framework and Google File System.
Who uses Hadoop? Here's a short list: Yahoo!, A9.com, LinkedIn, Facebook, ImageShack, eHarmony, Hulu, Last.fm, and The New York Times. The highest profile user, Yahoo!, is also a major contributor to the project. They use it extensively in their web search and advertising divisions.
In this talk, titled "Is there room for another elephant in Tucson?", Andrew Lenards will tell us about Hadoop and describe how it could be applied to several practical problems, even if you aren't as big as Google.
Accelerating analytics on the Sensor and IoT Data. Keshav Murthy
Informix Warehouse Accelerator (IWA) has helped traditional
data warehousing performance to improve dramatically. Now,
IWA accelerates analytics over the sensor data stored in relational and timeseries data.
QConSF 2014 talk on Netflix Mantis, a stream processing systemDanny Yuan
Justin and I gave this talk in QCon SF 2014 about the Mantis, a stream processing system that features a reactive programming API, auto scaling, and stream locality
A Deep Dive into Structured Streaming in Apache Spark Anyscale
This presentation was given at Apache Spark Meetup in Milano by Databricks software engineer and Apache Spark contributor Burak Yavuz. It covers how to write end-to-end, fault-tolerant continuous application using Structured Streaming APIs available in Apache Spark 2.x
Apache Spark 2.0: A Deep Dive Into Structured Streaming - by Tathagata Das Databricks
“In Spark 2.0, we have extended DataFrames and Datasets to handle real time streaming data. This not only provides a single programming abstraction for batch and streaming data, it also brings support for event-time based processing, out-or-order/delayed data, sessionization and tight integration with non-streaming data sources and sinks. In this talk, I will take a deep dive into the concepts and the API and show how this simplifies building complex “Continuous Applications”.” - T.D.
Databricks Blog: "Structured Streaming In Apache Spark 2.0: A new high-level API for streaming"
https://databricks.com/blog/2016/07/28/structured-streaming-in-apache-spark.html
// About the Presenter //
Tathagata Das is an Apache Spark Committer and a member of the PMC. He’s the lead developer behind Spark Streaming, and is currently employed at Databricks. Before Databricks, you could find him at the AMPLab of UC Berkeley, researching datacenter frameworks and networks with professors Scott Shenker and Ion Stoica.
Follow T.D. on -
Twitter: https://twitter.com/tathadas
LinkedIn: https://www.linkedin.com/in/tathadas
Founding committer of Spark, Patrick Wendell, gave this talk at 2015 Strata London about Apache Spark.
These slides provides an introduction to Spark, and delves into future developments, including DataFrames, Datasource API, Catalyst logical optimizer, and Project Tungsten.
Next Generation Indexes For Big Data Engineering (ODSC East 2018)Daniel Lemire
Maximizing performance in data engineering is a daunting challenge. We present some of our work on designing faster indexes, with a particular emphasis on compressed indexes. Some of our prior work includes (1) Roaring indexes which are part of multiple big-data systems such as Spark, Hive, Druid, Atlas, Pinot, Kylin, (2) EWAH indexes are part of Git (GitHub) and included in major Linux distributions.
We will present ongoing and future work on how we can process data faster while supporting the diverse systems found in the cloud (with upcoming ARM processors) and under multiple programming languages (e.g., Java, C++, Go, Python). We seek to minimize shared resources (e.g., RAM) while exploiting algorithms designed for the single-instruction-multiple-data (SIMD) instructions available on commodity processors. Our end goal is to process billions of records per second per core.
The talk will be aimed at programmers who want to better understand the performance characteristics of current big-data systems as well as their evolution. The following specific topics will be addressed:
1. The various types of indexes and their performance characteristics and trade-offs: hashing, sorted arrays, bitsets and so forth.
2. Index and table compression techniques: binary packing, patched coding, dictionary coding, frame-of-reference.
Designing ETL Pipelines with Structured Streaming and Delta Lake—How to Archi...Databricks
Structured Streaming has proven to be the best platform for building distributed stream processing applications. Its unified SQL/Dataset/DataFrame APIs and Spark’s built-in functions make it easy for developers to express complex computations. Delta Lake, on the other hand, is the best way to store structured data because it is a open-source storage layer that brings ACID transactions to Apache Spark and big data workloads Together, these can make it very easy to build pipelines in many common scenarios. However, expressing the business logic is only part of the larger problem of building end-to-end streaming pipelines that interact with a complex ecosystem of storage systems and workloads. It is important for the developer to truly understand the business problem that needs to be solved. Apache Spark, being a unified analytics engine doing both batch and stream processing, often provides multiples ways to solve the same problem. So understanding the requirements carefully helps you to architect your pipeline that solves your business needs in the most resource efficient manner.
In this talk, I am going examine a number common streaming design patterns in the context of the following questions.
WHAT are you trying to consume? What are you trying to produce? What is the final output that the business wants? What are your throughput and latency requirements?
WHY do you really have those requirements? Would solving the requirements of the individual pipeline actually solve your end-to-end business requirements?
HOW are going to architect the solution? And how much are you willing to pay for it?
Clarity in understanding the ‘what and why’ of any problem can automatically much clarity on the ‘how’ to architect it using Structured Streaming and, in many cases, Delta Lake.
Comparing Scalable Predictive Analysis using Spark XGBoost PlatformsJongwook Woo
This paper compares the performance of scalable predictive analysis models using XGBoost in Big Data. The performance measurement is based on the training computing time and accuracy with AUR and Precision of a model. We developed XGBoost classification models with Airbnb listing dataset that predict the recommendation of the listings. The models are built in PySpark Rapids, BigDL, and H2O Sparkling with CPU and GPU on AWS EMR. We observed that BigDL with GPU is 25 – 50% faster training time than other platforms. H2O Sparkling has 5 - 7% better AUC and 0.7% better Precision than others.
Scalable Predictive Analysis and The Trend with Big Data & AIJongwook Woo
The history and the latest trend of Big Data and Scalable Predictive Analysis for large scale data set using Distributed Machine Learning and Deep Learning with GPUs in Spark and Rapids; Invited talk at IS department of Yonsei University, Korea
Introduction to Big Data and AI for Business Analytics and PredictionJongwook Woo
Big Data has been popular last 10 years using Hadoop and Spark for data analysis and prediction with large scale data sets in distributed parallel computing systems. Its platform has expanded using NoSQL DB and Search Engine as well and has been more popular along cloud computing. Then, Deep Learning has become a buzzword past several years using GPU and Big Data. It makes even small companies and labs to own supercomputers with a small amount of budgets, which is the situation of “Dream Comes True” in the IT and business. In this talk, the history and trends of Big Data and AI platforms are introduced and how predictive analysis should be presented in Business using Big Data & AI.
Introduction to Big Data and its TrendsJongwook Woo
Big Data has been popular last 10 years using Hadoop and Spark for data analysis and prediction with large scale data sets in distributed parallel computing systems. Its platform has expanded using NoSQL DB and Search Engine as well and has been more popular along cloud computing. Then, Deep Learning has become a buzzword past several years using GPU and Big Data. It makes even small companies and labs to own supercomputers with a small amount of budgets, which is the situation of “Dream Comes True” in the IT and business. In this talk, the history and trends of Big Data and AI platforms are introduced and Big Data predictive analysis should be presented.
Rating Prediction using Deep Learning and SparkJongwook Woo
Distributed Deep Learning to predict Amazon review data rating in Spark using Analytics Zoo on AWS, which is published at "Rating Prediction using Deep Learning and Spark" at The 11th Internation Conference on Internet (ICONI 2019), Hanoi, Vietnam, Dec 15 - 18 2019
Traffic Data Analysis and Prediction using Big DataJongwook Woo
- Denser traffic on Freeways 101, 405, 10
- Rush hours from 7 am to 9 am produce a lot of traffic, the heaviest traffic time start from 3pm and gets better after 6pm.
- Major areas of traffic in DTLA, Santa Monica, Hollywood
- More insights can be found with bigger dataset using this framework for analysis of traffic
- Using such data and platform can also give an opportunity to predict traffic congestions. Prediction can be performed using machine learning algorithm – Decision Forest with the accuracy of 83% for predicting the heaviest traffic jam.
Predictive Analysis of Financial Fraud Detection using Azure and Spark MLJongwook Woo
This talk aims at providing insights, performance, and architecture on Financial Fraud Detection on a mobile money transactional activity in Azure ML and Spark. We have predicted and classified the transaction as normal or fraud with a small sample and massive data set using Azure ML and Spark ML, which are traditional systems and Big Data respectively. I will present predictive analysis with several classification models experimenting in Azure and Spark ML. Besides, scalability of Spark ML will be presented for the models with different number of nodes for Spark clusters in Amazon AWS.
Whose tombs are so called Nakrang tombs in Pyungyang? By Moon SungjaeJongwook Woo
South Korea historians trained under Imperial Japan have believe that the tombs in Pyungyang belong to the Chinese Han. Dr Moon points out that the tombs have the similar remains to the northern nomadic, who might be the Hun/HyoongNo. He provides many evidence why it should not belong to the Chinese Han but the northern nomadic, who is the brother of Korean kingdoms.
Big Data Analysis in Hydrogen Station using Spark and Azure MLJongwook Woo
Decision Forest machine learning algorithm is adopted to find out the features to affect the temperature of fueling valve and controller and to predict it.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
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.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Welocme to ViralQR, your best QR code generator.ViralQR
Welcome to ViralQR, your best QR code generator available on the market!
At ViralQR, we design static and dynamic QR codes. Our mission is to make business operations easier and customer engagement more powerful through the use of QR technology. Be it a small-scale business or a huge enterprise, our easy-to-use platform provides multiple choices that can be tailored according to your company's branding and marketing strategies.
Our Vision
We are here to make the process of creating QR codes easy and smooth, thus enhancing customer interaction and making business more fluid. We very strongly believe in the ability of QR codes to change the world for businesses in their interaction with customers and are set on making that technology accessible and usable far and wide.
Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
Pricing and Packages
Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
Subscribers of ViralQR receive detailed analytics and tracking tools in light of having a view of the core values of QR code performance. Our analytics dashboard shows aggregate views and unique views, as well as detailed information about each impression, including time, device, browser, and estimated location by city and country.
So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
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.
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
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.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
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
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
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!
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/
FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf
Market Basket Analysis Algorithm with Map/Reduce of Cloud Computing
1. Market Basket Analysis Algorithm with Map/Reduce of Cloud Computing 2011 PDPTA Jongwook Woo, PhD [email_address] High-Performance Internet Computing Center (HiPIC) Computer Information Systems Department California State University, Los Angeles
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3. What is Map/Reduce Cloud Computing Cloudera HortonWorks AWS Parallel Computing