Raman Pal is seeking a challenging position in a reputed organization where he can utilize his subject knowledge, communication, and technical skills. He has a PG Diploma in Advanced Big Data Analytics from NIELIT Calicut and a B.Tech in Computer Science from Internationl Institute of Technology & Managment. His academic projects include a challan system app, a gadget information website built with WordPress, and a hotel management system built with Java and Netbeans. His key skills include adopting new concepts, enjoying computing and technical design, undertaking detailed work, problem solving, and good explanation skills.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Adjusting primitives for graph : SHORT REPORT / NOTES
Raman pal Resume
1. CURRICULUM VITAE
Raman Pal
Email:-
raman.datascience@gmail.co
m
Mobile Number
+91 8860244587
+91 8447499891
LinkedIn
https://www.linkedin.com/i
n/raman-pal/
Github
https://github.com/Ramanpal1
Skype Name
live:2024a731509644fe
Objective:-
Obtaining a challenging position in a reputed
organization where I can utilize my Subject
knowledge, Communications and technical
skills for the development of the organization
and my career.
Basic Qualification:-
PG Diploma (Advanced Big Data Analytics)
from NIELIT Calicut, Kerala. First
Division(80%) in 2019
B.Tech(CSE) from Internationl Institute of
Technology & Managment, Murthal Affiliated to
DCRUST University. First Division(67.9%), 2018.
12th (59.69%)in (PCM) from CBSE. in 2014.
10th
(70.3%) from CBSE. in 2011.
Academic Project
1. Project Title: - Challan System
• A Challan app is designed on java use with
eclipse IDE to interact to the peoples and
pay challan online.
• Police man generate challan use this app.
• It is designed for Police man and peoples to pay
challan online.
Duration: 3 Months
2. Key Skills:
• Adopting new concepts
for studies and
responsibilities.
• Enjoy computing and
technical design.
• Ability to undertake
detailed and
elaborate work.
• Ability to identify, analyze
and solve problems.
• Easily get involved
with the new Faces.
• Good explanation skills.
2) Project Title: - www.gadgetclubs.com
This website is developed to give
correct information about gadget.
Website is created through online
CMS wordpress .
It give information about latest gadget,
automibiles, latest android apps.
Duration: 3 Months
3. Project Title: - Hotel Management System
• This Software is designed on java use with
Netbeans IDE to.fill all details of peoples.
• A seperate admin interface for managing the
hotel
• Various login-ids for employees alotted
by the admin.
• Computer based registration of users.
• User can choose single room, double
room and shows its price depends on the
users stay in a room .
Duration: 4 Months
4. Project Title: - Honey Bees Detection with
CNN
• This project for health detection of honeybee
is by using CNN-Convolution Neural Network
in which, bee subspecies and bee health will
be taken in consideration.
• In this project we create two different
CNN models bees subspecies nd bee
health classification.
• Virtulaziation of data using
Python. Duration: 1Month
3. Personal Information:-
Fathers Name : Ved Prakash
DOB: 09-12-1995
Sex : Male
Marital Status :Unmarried
Languages Known:-
English ,Hindi
Nationality :- Indian
Permanent Address:-
H.No.317
Village: Haiderpur
Dist: Delhi
State: Delhi
Pin Code: 110088
Software Skills:-
• CC++Python(DataVisualization)/
HTMLMySQLRHadoop(Pig Hive Sqoop
YarnSpark)Tableau Machine
LearningWeka Wordpress.
• Linux commands.
• Digital Marketing Traning in NIIM,
Janakpuri Delhi.
• Core Java Traning in TATA CMC. Rohini Delhi.
• Workshop in Ethical Hacking from Vidyavilla
foundation in IIT,Delhi.
• OS - Windows (‘98 – ‘10)| Linux | MS DOS |
BASIC | IOS | UNIX.
• Other Software’s - Wordpress, Netbeans,
Eclipse, Oracle, MS Office,Weka.
Place: Delhi
.
(Raman pal)
