DATA SCIENCE Lesson 2 Parallelism Computing Data Processing Performance Measu...Jean-Antoine Moreau
Ā
Data Science DATA SCIENCE Parallelism Computing Data Processing Performance Measures Modeling Conference Jean-Antoine Moreau
https://sites.google.com/site/jammooc/
Copyright managed by the ADAGP www.adagp.fr
DATA SCIENCE Lesson 4 Data Science Predictive Method Parsing Process Topic Mo...Jean-Antoine Moreau
Ā
DATA SCIENCE Lecture 4 Data Science Predictive Method Parsing Process Topic Modeling Nash equilibrium Machine learning Schelling Model conference Jean-Antoine Moreau
https://sites.google.com/site/jammooc/
Copyright managed by the ADAGP www.adagp.fr
DATA SCIENCE Lesson 5 Data Science Predictive Modeling and Modelling Methodol...Jean-Antoine Moreau
Ā
This document is a lecture by Jean-Antoine Moreau on predictive modeling and geographic information systems. It discusses modeling methodologies including inductive and deductive approaches. It also describes the components of a geographic information system including databases, mapping, analysis and modeling systems. Predictive techniques like neural networks and their applications to business and geographic information systems are also covered.
DATA SCIENCE Lesson 2 Parallelism Computing Data Processing Performance Measu...Jean-Antoine Moreau
Ā
Data Science DATA SCIENCE Parallelism Computing Data Processing Performance Measures Modeling Conference Jean-Antoine Moreau
https://sites.google.com/site/jammooc/
Copyright managed by the ADAGP www.adagp.fr
DATA SCIENCE Lesson 4 Data Science Predictive Method Parsing Process Topic Mo...Jean-Antoine Moreau
Ā
DATA SCIENCE Lecture 4 Data Science Predictive Method Parsing Process Topic Modeling Nash equilibrium Machine learning Schelling Model conference Jean-Antoine Moreau
https://sites.google.com/site/jammooc/
Copyright managed by the ADAGP www.adagp.fr
DATA SCIENCE Lesson 5 Data Science Predictive Modeling and Modelling Methodol...Jean-Antoine Moreau
Ā
This document is a lecture by Jean-Antoine Moreau on predictive modeling and geographic information systems. It discusses modeling methodologies including inductive and deductive approaches. It also describes the components of a geographic information system including databases, mapping, analysis and modeling systems. Predictive techniques like neural networks and their applications to business and geographic information systems are also covered.
The document discusses information system architecture and modeling. It describes using the Unified Modeling Language (UML) to define, specify, structure and integrate information system architectural elements. UML uses various views or models, such as logical, component, process and deployment views, to describe different aspects of the information system and its architecture. The document also discusses using UML to model business processes and software architecture.
A short introduction to EMF Views: dealing with several interrelated EMF models
Video/demo available from http://emfviews.jdvillacalle.com/examples#ea_views
This document provides an introduction to an optimization course for data science. It discusses how optimization methods are important for data science applications like predictive analytics and prescriptive analytics. It provides an example of using a polynomial interpolation model and cross-validation to estimate daily energy production from an energy community. The goal is to optimally size a battery for the energy community based on energy predictions and price signals. The course will cover algorithms for solving optimization problems that arise in fitting machine learning models and other data science applications.
Tools for Discrete Time Control; Application to Power SystemsOlivier Teytaud
Ā
3 main algorithms from the state of the art:
- Model Predictive Control
- Stochastic Dynamic Programming
- Direct Policy Search
==> and our proposal, a modified Direct Policy Search
termed Direct Value Search
Collaboro - EclipseCon France 2013 - Ignite Talks SessionHugo Bruneliere
Ā
Collaboro is an approach and supporting Eclipse tool that enables collaborative definition of domain-specific languages (DSLs). The tool allows both language developers and users to work together in defining and evolving a DSL. Key features of the Collaboro tool include version control of DSL definitions, tracking collaborators' proposals and changes, and facilitating decision making. Current work is focused on improving support for graphical and remote collaboration, as well as generating initial implementations of defined DSLs. Collaboro has been used to define languages like the ATL transformation language and MoDisco modeling framework.
This document contains a lesson plan for a course on problem solving and design using ICT tools. It includes the following key points:
- An overview of the course schedule with topics like the internet, word processing, collaboration, and presentations
- Descriptions of the components of a computer system including the CPU, RAM, hardware, operating system, and applications
- Examples of important concepts in computer science history like Moore's Law and the development of hardware from room-sized computers to integrated circuits
- Explanations of early user interfaces like command line interfaces, graphical user interfaces pioneered by Xerox PARC and Engelbart, and the evolution to modern operating systems like Windows
- Discussions of current topics including
The document discusses Six Sigma, which is presented as both a metric and methodology for quality improvement and management. Six Sigma aims to reduce variability in processes, improve customer satisfaction, and increase profits through defining problems, measuring processes, analyzing data, innovating solutions, and controlling results. It can be combined with approaches like Lean Management and integrated with quality systems like ISO 9000. The key steps of the Six Sigma DMAIC methodology are outlined.
Artificial Intelligence on Data Centric PlatformStratio
Ā
Digital Transformation starts with data. What if a solution existed that put data at the center, in a single place, serving all applications around it? This training will include a demonstration in a distributed data-centric platform which provides a data intelligence layer, composed of artificial intelligence models able to make use of a whole companyās data.
Nowadays, one of the most innovative techniques in the realm of artificial intelligence is Deep Neural Nets. Among the many applications, language modelling, machine translation and image generation are receiving particular attention. Deep nets are also powerful in predictive modelling ambits such as stock pricing and the energy industry. We will address a few case studies modeled with TensorFlow, running on Stratioās data-centric product in a distributed cluster.
By: Fernando Velasco
practicing what you never preached: sorting and discarding from a practical ...FIAT/IFTA
Ā
This document outlines a process for selecting and discarding physical media as part of an archival digitization and preservation project. It involves 3 main steps: 1) documentation work to analyze the collections and properties, 2) physical inspection of media to verify condition and contents, and 3) technical examination of any remaining doubtful cases. Criteria are provided for determining what materials should be kept based on factors like uniqueness, quality, and role in digitization. Guidelines are given for different media types, especially film and video, regarding hierarchies of quality and combinations of formats. The goal is to retain the highest quality and most important materials while discarding redundant, obsolete, or too degraded copies.
This presentation provides an overview and introduction to using the Neuroinformatics Platform and XNAT database. It discusses the goals of the platform in standardizing data sharing and storage. It then demonstrates how to navigate the XNAT interface, create projects and user accounts, upload common file types like MRI and EEG data, run quality control pipelines, and access data processing tools. The overall aim is to familiarize users with the basic functions and best practices for working with the Neuroinformatics Platform.
Collaboro - Community-Driven Language DevelopmentJavier Canovas
Ā
Software development processes are becoming more collaborative, trying to integrate end-users as much as possible. The idea is to advance towards a community-driven process where all actors (both technical and non- technical) work together to ensure that the system-to-be will satisfy all expectations. This seems specially appropriate in the field of Domain-Specific Languages (DSLs) typically designed to facilitate the development of software for a particular domain. DSLs offer constructs closer to the vocabulary of the domain which simplifies the adoption of the DSL by end-users. Interestingly enough, the development of DSLs is not a collaborative process itself. In this sense, the goal of this paper is to propose a collaborative infrastructure for the development of DSLs where end-users have a direct and active participation in the evolution of the language. This infrastructure is based on Collaboro, a DSL to represent change proposals, possible solutions and comments arisen during the development and evolution of a language.
Data recovery is the process of salvaging data from damaged, failed, corrupted, or inaccessible storage media. It involves recovering lost or deleted files, as well as addressing issues like logical damage, physical damage, or data overwritten multiple times. Key techniques include data scanning tools, commercial recovery programs, magnetic force microscopy to detect remnant magnetization, and overwriting data in specific patterns to securely delete it. Proper techniques and care must be taken to avoid further loss or damage during recovery.
The biggest challenge in performance tuning is identifying the root cause of the bottleneck. Once you find it, the fix often becomes trivial. However, this detective work takes patience, skills, and effort, so we often attempt to guess the cause, by trying out tentative fixes. The result: messy code, waste of time and money, and frustration. During this talk you will learn how to correctly zoom in on the bottleneck using three levels of profiling: distributed tracing with Zipkin, metrics with Micrometer, and profiling with the Java Flight Recorder already built into your JVM. Weāll focus on the latter and learn how to read a flame graph to trace some common issues of backend systems like connection/thread pool starvation, time-consuming aspects, hot methods, and lock contention, even if these occur in library code you did not write.
The document discusses information system architecture and modeling. It describes using the Unified Modeling Language (UML) to define, specify, structure and integrate information system architectural elements. UML uses various views or models, such as logical, component, process and deployment views, to describe different aspects of the information system and its architecture. The document also discusses using UML to model business processes and software architecture.
A short introduction to EMF Views: dealing with several interrelated EMF models
Video/demo available from http://emfviews.jdvillacalle.com/examples#ea_views
This document provides an introduction to an optimization course for data science. It discusses how optimization methods are important for data science applications like predictive analytics and prescriptive analytics. It provides an example of using a polynomial interpolation model and cross-validation to estimate daily energy production from an energy community. The goal is to optimally size a battery for the energy community based on energy predictions and price signals. The course will cover algorithms for solving optimization problems that arise in fitting machine learning models and other data science applications.
Tools for Discrete Time Control; Application to Power SystemsOlivier Teytaud
Ā
3 main algorithms from the state of the art:
- Model Predictive Control
- Stochastic Dynamic Programming
- Direct Policy Search
==> and our proposal, a modified Direct Policy Search
termed Direct Value Search
Collaboro - EclipseCon France 2013 - Ignite Talks SessionHugo Bruneliere
Ā
Collaboro is an approach and supporting Eclipse tool that enables collaborative definition of domain-specific languages (DSLs). The tool allows both language developers and users to work together in defining and evolving a DSL. Key features of the Collaboro tool include version control of DSL definitions, tracking collaborators' proposals and changes, and facilitating decision making. Current work is focused on improving support for graphical and remote collaboration, as well as generating initial implementations of defined DSLs. Collaboro has been used to define languages like the ATL transformation language and MoDisco modeling framework.
This document contains a lesson plan for a course on problem solving and design using ICT tools. It includes the following key points:
- An overview of the course schedule with topics like the internet, word processing, collaboration, and presentations
- Descriptions of the components of a computer system including the CPU, RAM, hardware, operating system, and applications
- Examples of important concepts in computer science history like Moore's Law and the development of hardware from room-sized computers to integrated circuits
- Explanations of early user interfaces like command line interfaces, graphical user interfaces pioneered by Xerox PARC and Engelbart, and the evolution to modern operating systems like Windows
- Discussions of current topics including
The document discusses Six Sigma, which is presented as both a metric and methodology for quality improvement and management. Six Sigma aims to reduce variability in processes, improve customer satisfaction, and increase profits through defining problems, measuring processes, analyzing data, innovating solutions, and controlling results. It can be combined with approaches like Lean Management and integrated with quality systems like ISO 9000. The key steps of the Six Sigma DMAIC methodology are outlined.
Artificial Intelligence on Data Centric PlatformStratio
Ā
Digital Transformation starts with data. What if a solution existed that put data at the center, in a single place, serving all applications around it? This training will include a demonstration in a distributed data-centric platform which provides a data intelligence layer, composed of artificial intelligence models able to make use of a whole companyās data.
Nowadays, one of the most innovative techniques in the realm of artificial intelligence is Deep Neural Nets. Among the many applications, language modelling, machine translation and image generation are receiving particular attention. Deep nets are also powerful in predictive modelling ambits such as stock pricing and the energy industry. We will address a few case studies modeled with TensorFlow, running on Stratioās data-centric product in a distributed cluster.
By: Fernando Velasco
practicing what you never preached: sorting and discarding from a practical ...FIAT/IFTA
Ā
This document outlines a process for selecting and discarding physical media as part of an archival digitization and preservation project. It involves 3 main steps: 1) documentation work to analyze the collections and properties, 2) physical inspection of media to verify condition and contents, and 3) technical examination of any remaining doubtful cases. Criteria are provided for determining what materials should be kept based on factors like uniqueness, quality, and role in digitization. Guidelines are given for different media types, especially film and video, regarding hierarchies of quality and combinations of formats. The goal is to retain the highest quality and most important materials while discarding redundant, obsolete, or too degraded copies.
This presentation provides an overview and introduction to using the Neuroinformatics Platform and XNAT database. It discusses the goals of the platform in standardizing data sharing and storage. It then demonstrates how to navigate the XNAT interface, create projects and user accounts, upload common file types like MRI and EEG data, run quality control pipelines, and access data processing tools. The overall aim is to familiarize users with the basic functions and best practices for working with the Neuroinformatics Platform.
Collaboro - Community-Driven Language DevelopmentJavier Canovas
Ā
Software development processes are becoming more collaborative, trying to integrate end-users as much as possible. The idea is to advance towards a community-driven process where all actors (both technical and non- technical) work together to ensure that the system-to-be will satisfy all expectations. This seems specially appropriate in the field of Domain-Specific Languages (DSLs) typically designed to facilitate the development of software for a particular domain. DSLs offer constructs closer to the vocabulary of the domain which simplifies the adoption of the DSL by end-users. Interestingly enough, the development of DSLs is not a collaborative process itself. In this sense, the goal of this paper is to propose a collaborative infrastructure for the development of DSLs where end-users have a direct and active participation in the evolution of the language. This infrastructure is based on Collaboro, a DSL to represent change proposals, possible solutions and comments arisen during the development and evolution of a language.
Data recovery is the process of salvaging data from damaged, failed, corrupted, or inaccessible storage media. It involves recovering lost or deleted files, as well as addressing issues like logical damage, physical damage, or data overwritten multiple times. Key techniques include data scanning tools, commercial recovery programs, magnetic force microscopy to detect remnant magnetization, and overwriting data in specific patterns to securely delete it. Proper techniques and care must be taken to avoid further loss or damage during recovery.
The biggest challenge in performance tuning is identifying the root cause of the bottleneck. Once you find it, the fix often becomes trivial. However, this detective work takes patience, skills, and effort, so we often attempt to guess the cause, by trying out tentative fixes. The result: messy code, waste of time and money, and frustration. During this talk you will learn how to correctly zoom in on the bottleneck using three levels of profiling: distributed tracing with Zipkin, metrics with Micrometer, and profiling with the Java Flight Recorder already built into your JVM. Weāll focus on the latter and learn how to read a flame graph to trace some common issues of backend systems like connection/thread pool starvation, time-consuming aspects, hot methods, and lock contention, even if these occur in library code you did not write.
Similar to DATA SCIENCE Lesson 3 Data Architectures Data Processing Modeling -Algorithm - Method conference Jean-Antoine Moreau (20)
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
Ā
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
A high-Speed Communication System is based on the Design of a Bi-NoC Router, ...DharmaBanothu
Ā
The Network on Chip (NoC) has emerged as an effective
solution for intercommunication infrastructure within System on
Chip (SoC) designs, overcoming the limitations of traditional
methods that face significant bottlenecks. However, the complexity
of NoC design presents numerous challenges related to
performance metrics such as scalability, latency, power
consumption, and signal integrity. This project addresses the
issues within the router's memory unit and proposes an enhanced
memory structure. To achieve efficient data transfer, FIFO buffers
are implemented in distributed RAM and virtual channels for
FPGA-based NoC. The project introduces advanced FIFO-based
memory units within the NoC router, assessing their performance
in a Bi-directional NoC (Bi-NoC) configuration. The primary
objective is to reduce the router's workload while enhancing the
FIFO internal structure. To further improve data transfer speed,
a Bi-NoC with a self-configurable intercommunication channel is
suggested. Simulation and synthesis results demonstrate
guaranteed throughput, predictable latency, and equitable
network access, showing significant improvement over previous
designs
Blood finder application project report (1).pdfKamal Acharya
Ā
Blood Finder is an emergency time app where a user can search for the blood banks as
well as the registered blood donors around Mumbai. This application also provide an
opportunity for the user of this application to become a registered donor for this user have
to enroll for the donor request from the application itself. If the admin wish to make user
a registered donor, with some of the formalities with the organization it can be done.
Specialization of this application is that the user will not have to register on sign-in for
searching the blood banks and blood donors it can be just done by installing the
application to the mobile.
The purpose of making this application is to save the userās time for searching blood of
needed blood group during the time of the emergency.
This is an android application developed in Java and XML with the connectivity of
SQLite database. This application will provide most of basic functionality required for an
emergency time application. All the details of Blood banks and Blood donors are stored
in the database i.e. SQLite.
This application allowed the user to get all the information regarding blood banks and
blood donors such as Name, Number, Address, Blood Group, rather than searching it on
the different websites and wasting the precious time. This application is effective and
user friendly.
Supermarket Management System Project Report.pdfKamal Acharya
Ā
Supermarket management is a stand-alone J2EE using Eclipse Juno program.
This project contains all the necessary required information about maintaining
the supermarket billing system.
The core idea of this project to minimize the paper work and centralize the
data. Here all the communication is taken in secure manner. That is, in this
application the information will be stored in client itself. For further security the
data base is stored in the back-end oracle and so no intruders can access it.
Height and depth gauge linear metrology.pdfq30122000
Ā
Height gauges may also be used to measure the height of an object by using the underside of the scriber as the datum. The datum may be permanently fixed or the height gauge may have provision to adjust the scale, this is done by sliding the scale vertically along the body of the height gauge by turning a fine feed screw at the top of the gauge; then with the scriber set to the same level as the base, the scale can be matched to it. This adjustment allows different scribers or probes to be used, as well as adjusting for any errors in a damaged or resharpened probe.
Applications of artificial Intelligence in Mechanical Engineering.pdfAtif Razi
Ā
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
This study Examines the Effectiveness of Talent Procurement through the Imple...DharmaBanothu
Ā
In the world with high technology and fast
forward mindset recruiters are walking/showing interest
towards E-Recruitment. Present most of the HRs of
many companies are choosing E-Recruitment as the best
choice for recruitment. E-Recruitment is being done
through many online platforms like Linkedin, Naukri,
Instagram , Facebook etc. Now with high technology E-
Recruitment has gone through next level by using
Artificial Intelligence too.
Key Words : Talent Management, Talent Acquisition , E-
Recruitment , Artificial Intelligence Introduction
Effectiveness of Talent Acquisition through E-
Recruitment in this topic we will discuss about 4important
and interlinked topics which are
Digital Twins Computer Networking Paper Presentation.pptxaryanpankaj78
Ā
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.