These slides are about parallel sorting algorithms. In which four types of sorting algorithms are discussed with the comparison between their sequential and parallel ways. The four algorithms which are included are: Bubble sort, merge sort, Bitonic sort and Shear sort.
These slides are about parallel sorting algorithms. In which four types of sorting algorithms are discussed with the comparison between their sequential and parallel ways. The four algorithms which are included are: Bubble sort, merge sort, Bitonic sort and Shear sort.
The MapReduce model popularized by Google has successfully been utilized in several scientific applications. We investigated whether this approach can be flourishingly applied to DNA Sequence Alignment.
In particular, algorithms for both perfect matching and sequence alignment are presented.
This is a little presentation for those interested in learning C#. I find it useful to present this to new clients to see where they are at in the the programming curve.
The MapReduce model popularized by Google has successfully been utilized in several scientific applications. We investigated whether this approach can be flourishingly applied to DNA Sequence Alignment.
In particular, algorithms for both perfect matching and sequence alignment are presented.
This is a little presentation for those interested in learning C#. I find it useful to present this to new clients to see where they are at in the the programming curve.
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.
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.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
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.
1. Gandhinagar Institute of Technology
SUBJECT – CD (2170701)
Non-predictive Parser
Prepared By-
Tarj Mehta (170120107074)
Guided By – Prof. Archana Singh
2. Non-predictive parser
•It is a top-down parser, so it builds the parse tree
from top to bottom starting from non-terminal.
•It is also known as recursive-descent parser as it
uses a set of recursive procedures to scan its input.
•This parsing technique may involve backtracking:
that is making repeated scan of its input.
4. Example
• Consider the grammar given below:
S cAd
A ab | a
• Consider the input string: w = c a d
input pointer
Step-1: S cAd
S if (input pointer == descent pointer)
increment descent pointer by 1
c A d increment input pointer by 1
Descent pointer
5. • Step-2: w = c a d
input pointer
S A is non-terminal so expand it
c A d
descent pointer
• A ab | a Now,
S input pointer == descent pointer
incrementing both pointers in next
c A d step
a b
descent pointer
6. • Step-3: w = c a d
input pointer
S
c A d
a b
descent pointer
Here, input pointer != descent pointer
Now backtracking to the immediate non-terminal
7. • Step – 4: w = c a d
input pointer
S input pointer == descent pointer
incrementing both the pointers
c A d
a
descent pointer
Now, S
w = c a d
c A d
input pointer
Here, a
input pointer == descent pointer
descent pointer
8. • As both the pointers are equal and all the elements of input string
have been parsed, we can say that the string has been successfully
parsed.
• The final parse tree can be given as follows:
S
c A d
a
• The given grammar was small to solve, but in case of big grammar
the non-predictive parser technique becomes very long.
• Hence to over come this, predictive parser was introduced.
