Government boost for data technology researchJohn Davis
As companies become more high-tech, generate larger quantities of data, seek ever larger banks of storage facilities and turn to innovations like the cloud, it seems clear that the future belongs to those who can use this technology best.
Quontra solutions is your premier online IT educational destination in UK. It provides online IT courses like Selenium , Hadoop ,CCNA ,Cloud Computing ,Business Analyst and Many other IT courses. All the courses are designed by experienced instructors and designers. Hadoop is a free, Java-based programming framework that supports the processing of large data sets in a distributed computing environment there is an urgent need for IT professional to keep themselves in trend with Hadoop and Big Data technologies
.
Quontra Specialties :
***All the courses are designed by Experienced Instructors and Designers.
***. Trainers are not limited to the syllabus, they explain off –the-shelf content also.
*** 24X7 technical support team .
***Unlimited access to all recorded sessions ,available after every live class.
***Syllabus built based on professional standards and employer insights.
***Trainers are Certified Experts in their corresponding field and they bring years of industry experience in to the training classes
Government boost for data technology researchJohn Davis
As companies become more high-tech, generate larger quantities of data, seek ever larger banks of storage facilities and turn to innovations like the cloud, it seems clear that the future belongs to those who can use this technology best.
Quontra solutions is your premier online IT educational destination in UK. It provides online IT courses like Selenium , Hadoop ,CCNA ,Cloud Computing ,Business Analyst and Many other IT courses. All the courses are designed by experienced instructors and designers. Hadoop is a free, Java-based programming framework that supports the processing of large data sets in a distributed computing environment there is an urgent need for IT professional to keep themselves in trend with Hadoop and Big Data technologies
.
Quontra Specialties :
***All the courses are designed by Experienced Instructors and Designers.
***. Trainers are not limited to the syllabus, they explain off –the-shelf content also.
*** 24X7 technical support team .
***Unlimited access to all recorded sessions ,available after every live class.
***Syllabus built based on professional standards and employer insights.
***Trainers are Certified Experts in their corresponding field and they bring years of industry experience in to the training classes
Data Mining with big data total ieee project and entire files.Kinnudj Amee
abstract, literature survey, implementaion, sample code, html code, project description, bibilography, conclusion, result, modules, uml diagrams, design, and etc.
There are as many views and definitions of Data Mining as there are people working in and on the topic. Confusion reigns and people ask; what is it; why do we need it; and isn’t it just Data Mining rebranded? In this slide deck and presentation we set the scene an highlight the differences and need for Data Mining in order to give a framework for case studies and future projects.
So - why do we need it?
The economic, industrial, commercial, social, political and sustainability problems we face cannot be successfully addressed using the management techniques and models largely inherited from the Industrial Revolution. The world no longer appears infinite in resources, slow paced, linear and stable. We now see the limitations; feel the impact of rapid change; and we can conceptualize the non-linear and unstable nature of it all! We are also starting to comprehend the scale and the need for machine assistance.
Modeling our situation !
Sophisticated computer models for weather systems are now complemented by ecological, economic, conflict and resource modeling of varying depth and accuracy. However, the key is always the accuracy and coverage of the primary data. We started with modest databases and data mining, but they mostly proved inadequate, and we are now amassing vast databases on every aspect of life - people, planet and machines. This ‘BIG DATA’ explosion demands a rethink of how, what, and where we gather data; the way we analyze and model; and the way we make decisions.
So - what is the big difference?
Data Mining was limited, planer, simple, linear and constrained to a few relationships amongst people: what they did, where they went, who they knew and so on. In contrast; Big Data is unbounded, spans all peoples and machines in all domains and activities with application to every aspect of life, business, industry, government and sustainability etc. It also takes into account the non-linear nature of relationships and events.
“Big Data is an almost unconscious outcome of the desire and need to sustain all peoples on a rapidly smaller looking planet”
Yes, we face a data deluge and big data seems to be largely about how to deal with it. But 99% of what has been written about big data is focused on selling hardware and services. The truth is that until the concept of big data can be objectively defined, any measurements, claims of success, quantifications, etc. must be viewed skeptically and with suspicion. While both the need for and approaches to these new requirements are faced by virtually every organization, jumping into the fray ill-prepared has (to date) reproduced the same dismal IT project results.
The very real, very rapid, very great increases in data of all forms (charts showing data types and volume increases)
Challenges faced by virtually all data management programs
Means by which big data techniques can compliment existing data management practices
Necessary but insufficient pre-requisites to exploiting big data techniques
Prototyping nature of practicing big data techniques
You can sign up for future Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/
for getting the library resources fro the libraries entire world, the important tool is Library catalogues. every can browse all most all the world literature through WorldCat fro the INTERNET.
Big data is used to describe a massive volume of both structured and unstructured data that is so large that it's difficult to process using traditional database and software techniques. In most enterprise scenarios the data is too big or it moves too fast or it exceeds current processing capacity. The term big data is believed to have originated with Web search companies who had to query very large distributed aggregations of loosely-structured data.
Data Mining with big data total ieee project and entire files.Kinnudj Amee
abstract, literature survey, implementaion, sample code, html code, project description, bibilography, conclusion, result, modules, uml diagrams, design, and etc.
There are as many views and definitions of Data Mining as there are people working in and on the topic. Confusion reigns and people ask; what is it; why do we need it; and isn’t it just Data Mining rebranded? In this slide deck and presentation we set the scene an highlight the differences and need for Data Mining in order to give a framework for case studies and future projects.
So - why do we need it?
The economic, industrial, commercial, social, political and sustainability problems we face cannot be successfully addressed using the management techniques and models largely inherited from the Industrial Revolution. The world no longer appears infinite in resources, slow paced, linear and stable. We now see the limitations; feel the impact of rapid change; and we can conceptualize the non-linear and unstable nature of it all! We are also starting to comprehend the scale and the need for machine assistance.
Modeling our situation !
Sophisticated computer models for weather systems are now complemented by ecological, economic, conflict and resource modeling of varying depth and accuracy. However, the key is always the accuracy and coverage of the primary data. We started with modest databases and data mining, but they mostly proved inadequate, and we are now amassing vast databases on every aspect of life - people, planet and machines. This ‘BIG DATA’ explosion demands a rethink of how, what, and where we gather data; the way we analyze and model; and the way we make decisions.
So - what is the big difference?
Data Mining was limited, planer, simple, linear and constrained to a few relationships amongst people: what they did, where they went, who they knew and so on. In contrast; Big Data is unbounded, spans all peoples and machines in all domains and activities with application to every aspect of life, business, industry, government and sustainability etc. It also takes into account the non-linear nature of relationships and events.
“Big Data is an almost unconscious outcome of the desire and need to sustain all peoples on a rapidly smaller looking planet”
Yes, we face a data deluge and big data seems to be largely about how to deal with it. But 99% of what has been written about big data is focused on selling hardware and services. The truth is that until the concept of big data can be objectively defined, any measurements, claims of success, quantifications, etc. must be viewed skeptically and with suspicion. While both the need for and approaches to these new requirements are faced by virtually every organization, jumping into the fray ill-prepared has (to date) reproduced the same dismal IT project results.
The very real, very rapid, very great increases in data of all forms (charts showing data types and volume increases)
Challenges faced by virtually all data management programs
Means by which big data techniques can compliment existing data management practices
Necessary but insufficient pre-requisites to exploiting big data techniques
Prototyping nature of practicing big data techniques
You can sign up for future Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/
for getting the library resources fro the libraries entire world, the important tool is Library catalogues. every can browse all most all the world literature through WorldCat fro the INTERNET.
Big data is used to describe a massive volume of both structured and unstructured data that is so large that it's difficult to process using traditional database and software techniques. In most enterprise scenarios the data is too big or it moves too fast or it exceeds current processing capacity. The term big data is believed to have originated with Web search companies who had to query very large distributed aggregations of loosely-structured data.
Data Science Innovations : Democratisation of Data and Data Science suresh sood
Data Science Innovations : Democratisation of Data and Data Science covers the opportunity of citizen data science lying at the convergence of natural language generation and discoveries in data made by the professions, not data scientists.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
1. INTRODUCTION
Along with the above example, the era of Big Data has arrived. Every day, 2.5 quintillion bytes
of data are created and 90 percent of the data in the world today were produced within the past
two years. Our capability for data generation has never been so powerful and enormous ever
since the invention of the information technology in the early 19th century. As another example,
on 4 October 2012, the first presidential debate between President Barack Obama and Governor
Mitt Romney triggered more than 10 million tweets within 2 hours. Among all these tweets, the
specific moments that generated the most discussions actually revealed the public interests, such
as the discussions about medicare and vouchers. Such online discussions provide a new means to
sense the public interests and generate feedback in realtime, and are mostly appealing compared
to generic media, such as radio or TV broadcasting. Another example is Flickr, a public picture
sharing site, which received 1.8 million photos per day, on average, from February to March
2012. Assuming the size of each photo is 2 megabytes (MB), this requires 3.6 terabytes (TB)
storage every single day. Indeed, as an old saying states: “a picture is worth a thousand words,”
the billions of pictures on Flicker are a treasure tank for us to explore the human society, social
events, public affairs, disasters, and so on, only if we have the power to harness the enormous
amount of data. The above examples demonstrate the rise of Big Data applications where data
collection has grown tremendously and is beyond the ability of commonly used software tools to
capture, manage, and process within a “tolerable elapsed time.” The most fundamental challenge
for Big Data applications is to explore the large volumes of data and extract useful information
or knowledge for future actions. In many situations, the knowledge extraction process has to be
very efficient and close to real time because storing all observed data is nearly infeasible. For
example, the square kilometer array (SKA) in radio astronomy consists of 1,000 to 1,500 15-
meter dishes in a central 5-km area. It provides 100 times more sensitive vision than any existing
radio telescopes, answering fundamental questions about the Universe. However, with a 40
gigabytes (GB)/second data volume, the data generated from the SKA are exceptionally large.
Although researchers have confirmed that interesting patterns, such as transient radio anomalies
can be discovered from the SKA data, existing methods can only work in an offline fashion and
are incapable of handling this Big Data scenario in real time. As a result, the unprecedented data
volumes require an effective data analysis and prediction platform to achieve fast response and
real-time classification for such Big Data.