how to spy on whatsapp messages without target phone freeWasweem Akaram
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how to spy on whatsapp messages without target phone freeWasweem Akaram
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How We Read Digitally: ebookcraft 2018 research study - Noah Genner & Monique...BookNet Canada
Join us on a journey into the thoughts, feelings, and habits of the ebook reader. From preferences for devices and ebook providers to how they use search tools and accessibility features, we asked, they answered, and now we're sharing those findings with you. If you've ever wanted to know more about the people you design ebooks for, you won't want to miss this presentation.
Battle of Gangiri-Heavy Price paid by HM 6 Dragoon Guards for Gallantry Agha A
Battle of Gangiri-Heavy Price paid by HM 6 Dragoon Guards for Gallantry https://www.academia.edu/52632772/Battle_of_Gangiri_Heavy_Price_paid_by_HM_6_Dragoon_Guards_for_Gallantry via @academia
How We Read Digitally: ebookcraft 2018 research study - Noah Genner & Monique...BookNet Canada
Join us on a journey into the thoughts, feelings, and habits of the ebook reader. From preferences for devices and ebook providers to how they use search tools and accessibility features, we asked, they answered, and now we're sharing those findings with you. If you've ever wanted to know more about the people you design ebooks for, you won't want to miss this presentation.
Battle of Gangiri-Heavy Price paid by HM 6 Dragoon Guards for Gallantry Agha A
Battle of Gangiri-Heavy Price paid by HM 6 Dragoon Guards for Gallantry https://www.academia.edu/52632772/Battle_of_Gangiri_Heavy_Price_paid_by_HM_6_Dragoon_Guards_for_Gallantry via @academia
WHY PAKISTAN ARMY OR INDIAN ARMY CAN NEVER PRODUCE A MUSTAFA KAMAL- SOMETHING...Agha A
WHY PAKISTAN ARMY OR INDIAN ARMY CAN NEVER PRODUCE A MUSTAFA KAMAL- SOMETHING SERIOUSLY WRONG IN THE GENES
April 2020
DOI: 10.13140/RG.2.2.20723.27689
Project: MILITARY HISTORY
Agha H Amin
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.
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.
