"The White Knight" is a fantasy novel written by M. R. Pritchard, first published in 2011. The story follows a young boy named Gavin who embarks on a journey filled with magical creatures, epic battles, and a quest to rescue the kidnapped princess of his kingdom. It blends elements of adventure, friendship, and the classic battle between good and evil.
A **Riemannian submersion** is a specific type of mathematical structure that arises in differential geometry. It involves two Riemannian manifolds and a smooth map between them that preserves certain geometric properties. More formally, let \( (M, g_M) \) and \( (N, g_N) \) be two Riemannian manifolds, where \( g_M \) and \( g_N \) are their respective Riemannian metrics.
Bluetooth mesh networking is a wireless communication protocol that facilitates communication between multiple devices in a mesh network structure. It extends the capabilities of traditional Bluetooth technology by allowing many devices to communicate with each other over a larger area, rather than relying on a single point-to-point connection. ### Key Features of Bluetooth Mesh Networking: 1. **Mesh Topology**: Unlike traditional Bluetooth connections, which are typically one-to-one, Bluetooth mesh allows devices (nodes) to relay messages to one another.
An optical mesh network is a type of communication network that uses optical fibers to transmit data. In this architecture, multiple interconnected nodes (or routers) form a mesh topology, allowing for flexible and efficient data routing. Here are some key features and characteristics of optical mesh networks: 1. **Topology**: Unlike traditional hierarchical networks, a mesh topology offers multiple pathways for data to travel between nodes. This enhances redundancy, reliability, and overall network resilience.
Scalable Source Routing (SSR) is a routing paradigm designed primarily for scenarios in which traditional routing methods may face challenges related to scalability, efficiency, and flexibility. It is often associated with large, dynamic networks, such as those found in mobile ad hoc networks (MANETs) or sensor networks.
The Serval Project is an initiative aimed at providing communication solutions in areas with limited or no infrastructure, particularly in remote, rural, or disaster-stricken regions. The project focuses on enabling mobile communication using a decentralized mesh network approach. Key features of the Serval Project include: 1. **Mesh Networking**: The project allows devices to connect directly to one another without relying on traditional cellular networks or the internet, creating a self-organizing network that can expand as more devices join.
TerraNet AB is a technology company based in Sweden that specializes in developing solutions for wireless communication and networking. The company focuses on creating innovative technologies for various applications, including machine-to-machine (M2M) communication, the Internet of Things (IoT), and smart city infrastructure. One of TerraNet's notable technologies is its proprietary communication platform, which is designed to enable devices to communicate directly with one another without the need for traditional cellular networks.
Bayesian statisticians are practitioners of Bayesian statistics, a statistical framework that interprets probability primarily as a measure of belief or uncertainty about the state of the world. This approach contrasts with frequentist statistics, which interprets probability in terms of long-run frequencies of events. Key concepts in Bayesian statistics include: 1. **Prior Probability**: This represents the initial belief about a parameter before observing any data.
Bayes linear statistics is an approach to statistical modeling and inference that combines principles of Bayesian statistics with a linear perspective on uncertainty. It focuses on updating beliefs in light of new evidence, and while it typically employs the structure of a Bayesian framework, it allows for a more intuitive interpretation of the uncertainty associated with parameters and predictions. ### Key Features of Bayes Linear Statistics: 1. **Linear Expectation**: Bayes linear statistics emphasizes the use of linear combinations of expectations.
Bayesian Vector Autoregression (BVAR) is a statistical method used for capturing the linear relationships among multiple time series variables over time. It combines the principles of vector autoregression (VAR) with Bayesian statistical techniques, allowing for more flexible modeling and inference, particularly in the presence of uncertainty and smaller sample sizes.
The Ensemble Kalman Filter (EnKF) is an advanced variant of the Kalman Filter, which is used for estimating the state of a dynamic system from noisy observations. The EnKF is particularly useful for high-dimensional, nonlinear systems, and it is widely applied in fields such as meteorology, oceanography, engineering, and environmental monitoring.
In Bayesian statistics, a hyperprior is a prior distribution placed on the hyperparameters of another distribution, which is itself the prior for the parameters of a model. To clarify, the Bayesian framework involves using prior distributions to quantify our beliefs about parameters before observing data. When these parameters have their own parameters, which we don't know and want to estimate, we refer to those as hyperparameters. The distribution assigned to these hyperparameters is what's known as a hyperprior.
Subjectivism is a philosophical theory that emphasizes the role of individual perspectives, feelings, and experiences in the formation of knowledge, truth, and moral values. It asserts that our understanding and interpretation of the world are inherently shaped by our subjective experiences, rather than by an objective reality that exists independently of individuals. There are several forms of subjectivism, including: 1. **Epistemological Subjectivism**: This suggests that knowledge is contingent upon the individual's perceptions and experiences.
Posterior probability is a fundamental concept in Bayesian statistics. It refers to the probability of a hypothesis (or event) given observed evidence. In simpler terms, it's the updated probability of a certain outcome after considering new data.
Robust Bayesian analysis is an approach within the Bayesian framework that aims to provide inference that is not overly sensitive to prior assumptions or model specifications. Traditional Bayesian analysis relies heavily on prior distributions and the chosen model, which can lead to results that are sensitive to the assumptions made. If the prior is misspecified or the model fails to capture the true underlying data-generating process, the conclusions drawn from the analysis can be misleading.
WinBUGS (Bayesian Inference Using Gibbs Sampling) is a software package designed for the analysis of Bayesian models using Markov Chain Monte Carlo (MCMC) methods. It allows users to specify a wide range of statistical models in a flexible manner and then perform inference using Bayesian techniques. Key features of WinBUGS include: 1. **Model Specification**: Users can define complex statistical models using a straightforward programming language specifically designed for Bayesian analysis.
Lewis's triviality result, primarily associated with philosopher David Lewis, pertains to the topic of modal realism and the nature of possible worlds. In particular, it addresses the challenges of modal discourse—how we talk about what is possible, necessary, or contingent—and offers insights into the interpretation of these modalities. The result can be characterized as follows: 1. **Modal Realism**: Lewis argued for a form of modal realism, which posits that all possible worlds are as real as the actual world.
Inanna is an ancient Sumerian goddess, one of the most important deities in the Mesopotamian pantheon. She is associated with various aspects, including love, beauty, fertility, war, and political power. Inanna's dual nature embodies both nurturing and fierce qualities, reflecting the complexities of human experience.
David S. Moore is a notable statistician and educator, primarily recognized for his contributions to the field of statistics, particularly in the area of statistical education and data analysis. He is also known for his authorship of several influential textbooks, including "Introduction to the Practice of Statistics," which is widely used in introductory statistics courses. Moore's work has emphasized the importance of understanding data and using statistical methods to analyze real-world situations, and he has been involved in promoting the teaching of statistics in academia.
Pinned article: ourbigbook/introduction-to-the-ourbigbook-project
Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
Intro to OurBigBook
. Source. We have two killer features:
- topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculusArticles of different users are sorted by upvote within each article page. This feature is a bit like:
- a Wikipedia where each user can have their own version of each article
- a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.Figure 1. Screenshot of the "Derivative" topic page. View it live at: ourbigbook.com/go/topic/derivativeVideo 2. OurBigBook Web topics demo. Source. - local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
- to OurBigBook.com to get awesome multi-user features like topics and likes
- as HTML files to a static website, which you can host yourself for free on many external providers like GitHub Pages, and remain in full control
Figure 2. You can publish local OurBigBook lightweight markup files to either OurBigBook.com or as a static website.Figure 3. Visual Studio Code extension installation.Figure 5. . You can also edit articles on the Web editor without installing anything locally. Video 3. Edit locally and publish demo. Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension. - Infinitely deep tables of contents:
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact