Disambiguating Advanced Computing for Humanities Researchers

•Download as PPT, PDF•

1 like•402 views

The document discusses how advanced computing can enable new opportunities in data-intensive humanities research by providing computational capabilities beyond what is ordinarily available. It outlines the types of advanced computing including clusters, grids, and middleware. It also describes application execution models, interfaces to advanced computing resources, and how this can help humanities researchers answer old questions and discover new ones through computational analysis of large datasets.

Disambiguating Advanced Computing for Humanities Researchers Baden Hughes Department of Computer Science and Software Engineering University of Melbourne [email_address]

Agenda ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Towards Data Intensive Research in the Humanities ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

A Thesis ,[object Object],[object Object],[object Object],[object Object]

Motivation for this Talk ,[object Object],[object Object],[object Object],[object Object],[object Object]

The Disambiguation Task ,[object Object],[object Object],[object Object],[object Object],[object Object]

Architectural Characteristics ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Application Execution Models ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Integration and Execution ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Interfaces ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Extending the Computational Boundaries ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Conclusion ,[object Object],[object Object],[object Object],[object Object],[object Object]

The computer technologies have rapidly developed in both software and hardware field. The complexity of software is increasing as per the market demand because the manual systems are going to become automation as well as the cost of hardware is decreasing. High Performance Computing (HPC) is very demanding technology and an attractive area of computing due to huge data processing in many applications of computing. The paper focus upon different applications of HPC and the types of HPC such as Cluster Computing, Grid Computing and Cloud Computing. It also studies, different classifications and applications of above types of HPC. All these types of HPC are demanding area of computer science. This paper also done comparative study of grid, cloud and cluster computing based on benefits, drawbacks, key areas of research, characterstics, issues and challenges.

GRID COMPUTING PRESENTATION

Ashok Mannai

Presented By Ashok.J 3 rd BCA - AVVM Sri Pushpam College, Poondi , Tanjor Slide 2: GRID COMPUTING Conceptual View Of Grid Computing ? What Is Grid Computing?: What Is Grid Computing? Grid computing is the collection of computer resources from multiple locations to reach a common goal. GRID COMPUTING Slide 4: How Grid Computing Works? GRID COMPUTING Slide 5: Types Of Grid Data Grid Collaboration Grid Network Grid Utility Grid GRID COMPUTING Computational Grid Slide 6: Grid topologies Slide 7: Intra grids A Typical intra grid topology exist within S ingle Organization, providing a basic set of grid Services Slide 8: Extra grids An Extra grid, Typically involves more than one security provider , and the level Management complexity increases Slide 9: Inter Grids An inter grid requires the dynamic integration of applications, resources and service with patterns, Customers access via WAN/ Internet Slide 10: A Simple Grid GRID COMPUTING Slide 11: Complex Inter grid GRID COMPUTING Slide 12: Grid Scheduled An application is one or more jobs that are scheduled to run a Grid GRID COMPUTING Slide 13: Advantages : Can solve larger, more complex problems in a shorter time Easier to collaborate with other organizations Make better use of existing hardware GRID COMPUTING Slide 14: Disa dvantages : Grid software and standards are still evolving Learning curve to get started Non-interactive job submission GRID COMPUTING Slide 15: BENEFITS OF GRID COMPUTING GRID COMPUTING Exploiting underutilized resources Parallel CPU capacity Virtual organizations for collaboration and virtual resources Access to additional resources Resource balancing Reliability Management Presented By Ashok.J ashokmannai0005@gmail.com

40 41INTERNATIONAL INDEXED,REFERRED,MULTILINGUAL,INTERDISCIPLINARY, MONTHLY RESEARCH JOURNAL

Grid computing

Presentaionslive.blogspot.com

The Grid means the infrastructure for the Advanced Web, for computing, collaboration and communication. The goal is to create the illusion of a simple yet large and powerful self managing virtual computer out of a large collection of connected heterogeneous systems sharing various combinations of resources. “Grid” computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and ,in some cases, high-performance orientation . We presented the Grid concept in analogy with that of an electrical power grid and Grid vision

Computation grid as a connected world

ijcsa

Grid computing or network computing is developed to make the available electric power in the similar way as it is available for the grid. For that we just plug in the power and whoever needs power, may use it. In grid computing if a system needs more power than available it can share the computing with other machines connected in a grid. In this way we can use the power of a super computer without a huge cost and the CPU cycles that were wasted previously can also be utilized. For performing grid computation in joined computers through the internet, the software must be installed which supports grid computation on each computer inside the VO. The software handles information queries, storage management, processing scheduling, authentication and data encryption to ensure information security.

"Volunteer Computing with BOINC Client-Server side" por Diamantino Cruz e Ric...

Núcleo de Electrónica e Informática da Universidade do Algarve

A Comparison of Cloud Execution Mechanisms Fog, Edge, and Clone Cloud Computing

IJECEIAES

Cloud computing is a technology that was developed a decade ago to provide uninterrupted, scalable services to users and organizations. Cloud computing has also become an attractive feature for mobile users due to the limited features of mobile devices. The combination of cloud technologies with mobile technologies resulted in a new area of computing called mobile cloud computing. This combined technology is used to augment the resources existing in Smart devices. In recent times, Fog computing, Edge computing, and Clone Cloud computing techniques have become the latest trends after mobile cloud computing, which have all been developed to address the limitations in cloud computing. This paper reviews these recent technologies in detail and provides a comparative study of them. It also addresses the differences in these technologies and how each of them is effective for organizations and developers.

Advancement in computing facilities marks back from 1960’s with introduction of mainframes. Each of the computing has one or the other issues, so keeping this in mind cloud computing was introduced. Cloud computing has its roots in older technologies such as hardware virtualization, distributed computing, internet technologies, and autonomic computing. Cloud computing can be described with two models, one is service model and second is deployment model. While providing several services, cloud management’s primary role is resource provisioning. While there are several such benefits of cloud computing, there are challenges in adopting public clouds because of dependency on infrastructure that is shared by many enterprises. In this paper, we present core knowledge of cloud computing, highlighting its key concepts, deployment models, service models, benefits as well as security issues related to cloud data. The aim of this paper is to provide a better understanding of the cloud computing and to identify important research directions in this field

Implementing K-Out-Of-N Computing For Fault Tolerant Processing In Mobile and...

IJERA Editor

Despite the advances in hardware for hand-held mobile devices, resource-intensive applications (e.g., video and imagestorage and processing or map-reduce type) still remain off bounds since they require large computation and storage capabilities.Recent research has attempted to address these issues by employing remote servers, such as clouds and peer mobile devices.For mobile devices deployed in dynamic networks (i.e., with frequent topology changes because of node failure/unavailability andmobility as in a mobile cloud), however, challenges of reliability and energy efficiency remain largely unaddressed. To the best of ourknowledge, we are the first to address these challenges in an integrated manner for both data storage and processing in mobilecloud, an approach we call k-out-of-n computing. In our solution, mobile devices successfully retrieve or process data, in the mostenergy-efficient way, as long as k out of n remote servers are accessible. Through a real system implementation we prove the feasibilityof our approach. Extensive simulations demonstrate the fault tolerance and energy efficiency performance of our framework in largerscale networks.

Grid computing

Dikshita_Viradia

Bt9002 grid computing 1

Techglyphs

Applications of SOA and Web Services in Grid Computingyht4ever

CYBER INFRASTRUCTURE AS A SERVICE TO EMPOWER MULTIDISCIPLINARY, DATA-DRIVEN S...

ijcsit

In supporting its large scale, multidisciplinary scientific research efforts across all the university campuses and by the research personnel spread over literally every corner of the state, the state of Nevada needs to build and leverage its own Cyber infrastructure. Following the well-established as-a-service model, this state-wide Cyber infrastructure that consists of data acquisition, data storage, advanced instruments, visualization, computing and information processing systems, and people, all seamlessly linked together through a high-speed network, is designed and operated to deliver the benefits of Cyber infrastructure-as-aService (CaaS).There are three major service groups in this CaaS, namely (i) supporting infrastructural services that comprise sensors, computing/storage/networking hardware, operating system, management tools, virtualization and message passing interface (MPI); (ii) data transmission and storage services that provide connectivity to various big data sources, as well as cached and stored datasets in a distributed storage backend; and (iii) processing and visualization services that provide user access to rich processing and visualization tools and packages essential to various scientific research workflows. Built on commodity hardware and open source software packages, the Southern Nevada Research Cloud(SNRC)and a data repository in a separate location constitute a low cost solution to deliver all these services around CaaS. The service-oriented architecture and implementation of the SNRC are geared to encapsulate as much detail of big data processing and cloud computing as possible away from end users; rather scientists only need to learn and access an interactive web-based interface to conduct their collaborative, multidisciplinary, dataintensive research. The capability and easy-to-use features of the SNRC are demonstrated through a use case that attempts to derive a solar radiation model from a large data set by regression analysis.

Grid Computing (An Up-Coming Technology)

LJ PROJECTS

Security and privacy issues of fog

Rezgar Mohammad

Cloud versus cloud

Masoud Gholami

Syllabus cse

Prakash Palanisamy

Cs6703 grid and cloud computing book

kaleeswaranme

Emerging cloud computing paradigm vision, research challenges and development...

eSAT Publishing House

IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology

F2CDM: Internet of Things for Healthcare Network Based Fog-to-Cloud and Data-...

Istabraq M. Al-Joboury

Internet of Things (IoT) evolves very rapidly over time, since everything such as sensors/actuators linked together from around the world with use of evolution of ubiquitous computing through the Internet. These devices have a unique IP address in order to communicate with each other and transmit data with features of wireless technologies. Fog computing or so called edge computing brings all Cloud features to embedded devices at edge network and adds more features to servers like pre-store data of Cloud, fast response, and generate overhasty users reporting. Fog mediates between Cloud and IoT devices and thus enables new types of computing and services. The future applications take the advantage of combing the two concepts Fog and Cloud in order to provide low delay Fog-based and high capacity of storage Cloud-based. This paper proposes an IoT architecture for healthcare network based on Fog to Cloud and Data in Motion (F2CDM). The proposed architecture is designed and implemented over three sites: Site 1 contains the embedded devices layer, Site 2 consists of the Fog network layer, while Site 3 consists of the Cloud network. The Fog layer is represented by a middleware server in Al-Nahrain University with temporary storage such that the data lives inside for 30 min. During this time, the selection of up-normality in behavior is send to the Cloud while the rest of the data is wiped out. On the other hand, the Cloud stores all the incoming data from Fog permanently. The F2CDM works using Message Queue Telemetry Transport (MQTT) for fast response. The results show that all data can be monitored from the Fog in real time while the critical data can be monitored from Cloud. In addition, the response time is evaluated using traffic generator called Tsung. It has been found that the proposed architecture reduces traffic on Cloud network and provides better data analysis.

International Journal of Engineering Research and Development

IJERD Editor

Electrical, Electronics and Computer Engineering, Information Engineering and Technology, Mechanical, Industrial and Manufacturing Engineering, Automation and Mechatronics Engineering, Material and Chemical Engineering, Civil and Architecture Engineering, Biotechnology and Bio Engineering, Environmental Engineering, Petroleum and Mining Engineering, Marine and Agriculture engineering, Aerospace Engineering.

A review on orchestration distributed systems for IoT smart services in fog c...

IJECEIAES

This paper provides a review of orchestration distributed systems for IoT smart services in fog computing. The cloud infrastructure alone cannot handle the flow of information with the abundance of data, devices and interactions. Thus, fog computing becomes a new paradigm to overcome the problem. One of the first challenges was to build the orchestration systems to activate the clouds and to execute tasks throughout the whole system that has to be considered to the situation in the large scale of geographical distance, heterogeneity and low latency to support the limitation of cloud computing. Some problems exist for orchestration distributed in fog computing are to fulfil with high reliability and low-delay requirements in the IoT applications system and to form a larger computer network like a fog network, at different geographic sites. This paper reviewed approximately 68 articles on orchestration distributed system for fog computing. The result shows the orchestration distribute system and some of the evaluation criteria for fog computing that have been compared in terms of Borg, Kubernetes, Swarm, Mesos, Aurora, heterogeneity, QoS management, scalability, mobility, federation, and interoperability. The significance of this study is to support the researcher in developing orchestration distributed systems for IoT smart services in fog computing focus on IR4.0 national agenda.

The Riisk and Challllenges off Clloud Computtiing

IJERA Editor

Cloud computing is a computing technology aiming to share storage, computation, and services transparently among a massive users. Current cloud computing systems pose serious limitation to protecting the confidentiality of user data. Since the data share and stored is presented in unencrypted forms to remote machines owned and operated by third party service providers despite it sensitivity (example contact address, mails), the risks of disclosing user confidential data by service providers may be quite high and the risk of attacking cloud storage by third party is also increasing. The purpose of this study is to review researches done on this technology, identify the security risk and explore some techniques for protecting users‟ data from attackers in the cloud.

IRJET- Fog Route:Distribution of Data using Delay Tolerant Network

IRJET Journal

3. the grid new infrastructure

Dr Sandeep Kumar Poonia

Grid computingBeethika Sarangi

Analyzing the Difference of Cluster, Grid, Utility & Cloud Computing

IOSRjournaljce

: Virtualization and cloud computing is creating a fundamental change in computer architecture, software and tools development, in the way we store, distribute and consume information. In the recent era of autonomic computing it comes the importance and need of basic concepts of having and sharing various hardware and software and other resources & applications that can manage themself with high level of human guidance. Virtualization or Autonomic computing is not a new to the world, but it developed rapidly with Cloud computing. In this paper there give an overview of various types of computing. There will be discussion on Cluster, Grid computing, Utility & Cloud Computing. Analysis architecture, differences between them, characteristics , its working, advantages and disadvantages

Unit 2 3 1 Costs Of ProductionCorey Topf

Johan Ronnestam. Keynote. Webbdagarna 2012.

Johan Ronnestam

What's hot

Core of Cloud Computing

IJERA Editor

Implementing K-Out-Of-N Computing For Fault Tolerant Processing In Mobile and...

IJERA Editor

Grid computing

Dikshita_Viradia

Bt9002 grid computing 1

Techglyphs

Applications of SOA and Web Services in Grid Computingyht4ever

CYBER INFRASTRUCTURE AS A SERVICE TO EMPOWER MULTIDISCIPLINARY, DATA-DRIVEN S...

ijcsit

Grid Computing (An Up-Coming Technology)

LJ PROJECTS

Security and privacy issues of fog

Rezgar Mohammad

Cloud versus cloud

Masoud Gholami

Syllabus cse

Prakash Palanisamy

Cs6703 grid and cloud computing book

kaleeswaranme

Emerging cloud computing paradigm vision, research challenges and development...

eSAT Publishing House

F2CDM: Internet of Things for Healthcare Network Based Fog-to-Cloud and Data-...

Istabraq M. Al-Joboury

International Journal of Engineering Research and Development

IJERD Editor

A review on orchestration distributed systems for IoT smart services in fog c...

IJECEIAES

The Riisk and Challllenges off Clloud Computtiing

IJERA Editor

IRJET- Fog Route:Distribution of Data using Delay Tolerant Network

IRJET Journal

3. the grid new infrastructure

Dr Sandeep Kumar Poonia

Grid computingBeethika Sarangi

Analyzing the Difference of Cluster, Grid, Utility & Cloud Computing

IOSRjournaljce

What's hot (20)

Core of Cloud Computing

Implementing K-Out-Of-N Computing For Fault Tolerant Processing In Mobile and...

Grid computing

Bt9002 grid computing 1

Applications of SOA and Web Services in Grid Computing

CYBER INFRASTRUCTURE AS A SERVICE TO EMPOWER MULTIDISCIPLINARY, DATA-DRIVEN S...

Grid Computing (An Up-Coming Technology)

Security and privacy issues of fog

Cloud versus cloud

Syllabus cse

Cs6703 grid and cloud computing book

Emerging cloud computing paradigm vision, research challenges and development...

F2CDM: Internet of Things for Healthcare Network Based Fog-to-Cloud and Data-...

International Journal of Engineering Research and Development

A review on orchestration distributed systems for IoT smart services in fog c...

The Riisk and Challllenges off Clloud Computtiing

IRJET- Fog Route:Distribution of Data using Delay Tolerant Network

3. the grid new infrastructure

Grid computing

Analyzing the Difference of Cluster, Grid, Utility & Cloud Computing

Viewers also liked

Unit 2 3 1 Costs Of ProductionCorey Topf

Johan Ronnestam. Keynote. Webbdagarna 2012.

Johan Ronnestam

2nd Trimester SpongesCorey Topf

Versie 3 Nv Iad2 0910 Q1 Les 4 Patterns For MobileHans Kemp

2nd Trimester SpongesCorey Topf

Tips for Using Semi-ColonsCorey Topf

Legal aspects of data gathering and information exchangeStevenSegaert

Unit 2 3 1 Costs Of ProductionCorey Topf

Unit 2Corey Topf

Visuelereisdoororganisatielandv2 1225371301186079 8

roemen

0708 Iad1 Werkgroep1

Hans Kemp

Zappos - eBay Talk - 04-22-08

zappos

Minor User Experience EnglishHans Kemp

Object Reuse and Exchange (ORE) : Experience in the Open Language Archives Co...

Baden Hughes

User Created Content deel II

Sanoma Netherlands

Elasticity 1Corey Topf

1011q1 design for mobile les 1 the carry principleHans Kemp

Week8 SpongesCorey Topf

Analysis of social computing applications in the EU

Sanoma Netherlands

Unbearable vocabularyCorey Topf

Viewers also liked (20)

Unit 2 3 1 Costs Of Production

Johan Ronnestam. Keynote. Webbdagarna 2012.

2nd Trimester Sponges

Versie 3 Nv Iad2 0910 Q1 Les 4 Patterns For Mobile

2nd Trimester Sponges

Tips for Using Semi-Colons

Legal aspects of data gathering and information exchange

Unit 2 3 1 Costs Of Production

Unit 2

Visuelereisdoororganisatielandv2 1225371301186079 8

0708 Iad1 Werkgroep1

Zappos - eBay Talk - 04-22-08

Minor User Experience English

Object Reuse and Exchange (ORE) : Experience in the Open Language Archives Co...

User Created Content deel II

Elasticity 1

1011q1 design for mobile les 1 the carry principle

Week8 Sponges

Analysis of social computing applications in the EU

Unbearable vocabulary

Similar to Disambiguating Advanced Computing for Humanities Researchers

kantorNSF-NIJ-ISI-03-06-04.pptbutest

Paper id 25201431IJRAT

Hughes RDAP11 Data Publication Repositories

ASIS&T

Open Archives Initiative Object Reuse and Exchange

lagoze

GridComputing-an introduction.ppt

NileshkuGiri

Multilayered paper prototyping for user concept modeling

UKOLN (dev), University of Bath

Cloud and Bid data Dr.VK.pdf

kalai75

Anusua Trivedi, Data Scientist at Texas Advanced Computing Center (TACC), UT ...

MLconf

Building a Recommender System for Publications using Vector Space Model and Python:In recent years, it has become very common that we have access to large number of publications on similar or related topics. Recommendation systems for publications are needed to locate appropriate published articles from a large number of publications on the same topic or on similar topics. In this talk, I will describe a recommender system framework for PubMed articles. PubMed is a free search engine that primarily accesses the MEDLINE database of references and abstracts on life-sciences and biomedical topics. The proposed recommender system produces two types of recommendations – i) content-based recommendation and (ii) recommendations based on similarities with other users’ search profiles. The first type of recommendation, viz., content-based recommendation, can efficiently search for material that is similar in context or topic to the input publication. The second mechanism generates recommendations using the search history of users whose search profiles match the current user. The content-based recommendation system uses a Vector Space model in ranking PubMed articles based on the similarity of content items. To implement the second recommendation mechanism, we use python libraries and frameworks. For the second method, we find the profile similarity of users, and recommend additional publications based on the history of the most similar user. In the talk I will present the background and motivation for these recommendation systems, and discuss the implementations of this PubMed recommendation system with example. This talk will cover, via live demo & code walk-through, the key lessons we’ve learned while building such real-world software systems over the past few years. We’ll incrementally build a hybrid machine learned model for fraud detection, combining features from natural language processing, topic modeling, time series analysis, link analysis, heuristic rules & anomaly detection. We’ll be looking for fraud signals in public email datasets, using Python & popular open-source libraries for data science and Apache Spark as the compute engine for scalable parallel processing.

grid computingelliando dias

CyberistructureLab Southwest

SciDB : Open Source Data Management System for Data-Intensive Scientific Anal...

San Diego Supercomputer Center

Hedstrom Infrastructureguest2c9ba28e

Metadata: Digital Humanties

Matthew Miguez

Dataintensivesulfath

Opportunities and Challenges for Running Scientific Workflows on the Cloud

lyingcom

Re-Engineering Databases using Meta-Programming Technology

Gihan Wikramanayake

12575474.ppt

Dr. Thippeswamy S.

Possible Worlds Explorer: Datalog & Answer Set Programming for the Rest of Us

Bertram Ludäscher

many-task computingHarry Sunarsa

An asynchronous replication model to improve data available into a heterogene...Alexander Decker

Similar to Disambiguating Advanced Computing for Humanities Researchers (20)

kantorNSF-NIJ-ISI-03-06-04.ppt

Paper id 25201431

Hughes RDAP11 Data Publication Repositories

Open Archives Initiative Object Reuse and Exchange

GridComputing-an introduction.ppt

Multilayered paper prototyping for user concept modeling

Cloud and Bid data Dr.VK.pdf

Anusua Trivedi, Data Scientist at Texas Advanced Computing Center (TACC), UT ...

grid computing

Cyberistructure

SciDB : Open Source Data Management System for Data-Intensive Scientific Anal...

Hedstrom Infrastructure

Metadata: Digital Humanties

Dataintensive

Opportunities and Challenges for Running Scientific Workflows on the Cloud

Re-Engineering Databases using Meta-Programming Technology

12575474.ppt

Possible Worlds Explorer: Datalog & Answer Set Programming for the Rest of Us

many-task computing

An asynchronous replication model to improve data available into a heterogene...

Recently uploaded

DevOps and Testing slides at DASA Connect

Kari Kakkonen

Bits & Pixels using AI for Good.........

Alison B. Lowndes

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.

Accelerate your Kubernetes clusters with Varnish Caching

Thijs Feryn

Encryption in Microsoft 365 - ExpertsLive Netherlands 2024

Albert Hoitingh

Knowledge engineering: from people to machines and back

Elena Simperl

De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...

Product School

UiPath Test Automation using UiPath Test Suite series, part 4

DianaGray10

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

To Graph or Not to Graph Knowledge Graph Architectures and LLMs

Paul Groth

Epistemic Interaction - tuning interfaces to provide information for AI support

Alan 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.

The Art of the Pitch: WordPress Relationships and Sales

Laura 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.

From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...

Product School

GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...

James Anderson

Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management. The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM). Speakers: Bob Boule Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle. Gopinath Rebala Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.

Securing your Kubernetes cluster_ a step-by-step guide to success !

KatiaHIMEUR1

Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster. However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks. In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.

From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...

Product School

UiPath Test Automation using UiPath Test Suite series, part 3

DianaGray10

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.

Essentials of Automations: Optimizing FME Workflows with Parameters

Safe Software

Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place. Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects. Here’s what you’ll gain: - Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows. - Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy. - Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency. - Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity. We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic. Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.

AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...

Product School

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

Recently uploaded (20)