Feudal Europe was divided into kingdoms ruled by kings who derived their power from God. Society was strictly stratified with the king and higher nobility such as dukes and counts at the top governing with help from the Catholic Church. Beneath them were the lower nobility of knights and lesser landowners and the lower clergy of priests and monks. At the bottom were the unprivileged commoners like peasants and craftsmen who worked the lands and paid taxes in exchange for protection from nobles they were bound to through systems of servitude and vassalage.
Created by María Jesús Campos, teacher of Social Studies, History and Geography in a bilingual section in Madrid (Spain).
learningfromhistory.wikispaces.com
learningfromgeography.wikispaces.com
Created by María Jesús Campos, teacher of Social Studies, History and Geography in a bilingual section in Madrid (Spain).
learningfromhistory.wikispaces.com
learningfromgeography.wikispaces.com
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.
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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
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.
2. Society in the early middle ages | Social Pyramid
The KING
The higher nobility
and the higher clergy
Unprivileged classes
Peasants
Serfs
Craftsmen
The lower nobility
and the lower clergy
3. Society in the early middle ages | The King
The KING
Feudal Europe was fragmented into numerous kingdoms
The Kings considered that their power came from God.
The King governed with the help of the Curia Regis
(the Pope, Bishops and Nobles)
4. Society in the early middle ages | The higher nobility and clergy
The higher nobility
and the higher clergy
The higher nobility composed of the direct vassals of the
King, such as dukes, counts, marquises and barons. They
lived in castles, where the population took refuge.
The higher clergy included the Pope, bishops, and the
abbots and abbesses of the great monasteries. They
enjoyed sizable fiefdoms and revenues.
5. Society in the early middle ages | The lower nobility and clergy
The lower nobility
and the lower clergy
The lower nobility was composed of lesser nobles, such
as knights or people who could own a horse and
weapons of war.
The lower clergy included priest and the monks and nuns
of the monasteries
6. Society in the early middle ages | Unprivileged classes
Unprivileged classes
The commoners work and carried out the necessary tasks
to maintain and feed the other groups.
They are the only group that work and pay taxes.
They can established relationships of servitude with the
lords. The lord gave protection and permission to work on
the demesne, in return they gave to the lord a portion of
his harvest and pay signorial rights.
7. Society in the early middle ages | Relations
SERVITUDE
VASSALAGE
8. Society in the early middle ages | Relations
Each group gave protection to all
people who work its lands and pay
taxes for it.
The commoners (peasants,
craftsmen…) work the lands and
pay taxes to keep the kingdom
