This document discusses a method called Q2 learning that combines qualitative and quantitative representations for machine learning. Q2 learning aims to overcome qualitative errors that numerical learners can make. It works by first inducing qualitative constraints from data, then enforcing these constraints in numerical learning to ensure qualitatively consistent predictions. This approach has been shown to improve predictions while also providing clearer model interpretations. The document outlines techniques like QUIN for inducing constraints and QFILTER for enforcing them numerically. It also provides examples of applying Q2 learning to problems in various domains.
This document discusses the definition, diagnosis, risk stratification, and management of ST-elevation myocardial infarction (STEMI). It covers:
1. Defining STEMI and the revised definition of myocardial infarction.
2. Risk stratifying STEMI patients based on ECG and biomarker results as well as factors like prior history and complications.
3. The goals of rapid diagnosis, restoration of perfusion through medical or mechanical means like thrombolysis or primary PCI, and achieving door-to-drug/balloon times to salvage myocardium.
Dokumen tersebut membahas tentang perilaku konsumen dan teori-teori yang melandasinya. Teori-teori tersebut meliputi hukum nilai guna marginal yang semakin menurun, hukum Gossen I dan II, serta faktor-faktor yang mempengaruhi perilaku konsumen seperti pendapatan, harga, selera, dan status sosial.
Berlin Hyp is preparing to launch the first green covered bond. In this special sponsored report, published by The Covered Bond Report, Berlin Hyp and its partners discuss the germination of the idea, the product's potential, and how it fits into wider ESG and SRI trends in the capital markets.
O documento descreve os principais componentes do sistema Common Rail para injeção de combustível em motores a diesel, incluindo a bomba de alta pressão, o rail, válvulas reguladoras de pressão, injetores e sensores. O sistema permite o controle eletrônico da quantidade de combustível injetado e do momento da injeção.
The document summarizes the use of data assimilation methods to correct hydrological model forecasts based on measurements. It presents an example using the CATHY model and assimilating streamflow measurements to correct for uncertainties in initial conditions and atmospheric forcings. It also discusses applications to coupled hydrogeophysical inversion, and using data assimilation at the Landscape Evolution Observatory to estimate spatially distributed hydraulic conductivity fields based on sensor measurements under rainfall experiments.
The document presents an assessment of a post-stack Q estimation algorithm called Q-est. It tests the tool on synthetic and real seismic data. The key findings are: (1) Q-est successfully recovers assumed Q fields from synthetic data with 16% error; (2) Estimated Q fields from real data show lateral consistency and correlate with geological features; (3) Q compensation using estimated fields improves resolution and recovers amplitudes better than using a single Q value.
Modelling and Control of Drinkable Water Networks. Presentation at the 1st technical workshop of the FP7 research project EFFINET in Limassol, Cyprus, 5-6 June 2013. The main developments within WP2 are presented: Understanding the water demand patterns, development of time-series models for the water demand, formulation and solution of Model Predictive Control (MPC) problems for the water network and quantification of the effect that the prediction errors have on the optimal solution and on the closed-loop behaviour of the controlled system.
This document discusses the definition, diagnosis, risk stratification, and management of ST-elevation myocardial infarction (STEMI). It covers:
1. Defining STEMI and the revised definition of myocardial infarction.
2. Risk stratifying STEMI patients based on ECG and biomarker results as well as factors like prior history and complications.
3. The goals of rapid diagnosis, restoration of perfusion through medical or mechanical means like thrombolysis or primary PCI, and achieving door-to-drug/balloon times to salvage myocardium.
Dokumen tersebut membahas tentang perilaku konsumen dan teori-teori yang melandasinya. Teori-teori tersebut meliputi hukum nilai guna marginal yang semakin menurun, hukum Gossen I dan II, serta faktor-faktor yang mempengaruhi perilaku konsumen seperti pendapatan, harga, selera, dan status sosial.
Berlin Hyp is preparing to launch the first green covered bond. In this special sponsored report, published by The Covered Bond Report, Berlin Hyp and its partners discuss the germination of the idea, the product's potential, and how it fits into wider ESG and SRI trends in the capital markets.
O documento descreve os principais componentes do sistema Common Rail para injeção de combustível em motores a diesel, incluindo a bomba de alta pressão, o rail, válvulas reguladoras de pressão, injetores e sensores. O sistema permite o controle eletrônico da quantidade de combustível injetado e do momento da injeção.
The document summarizes the use of data assimilation methods to correct hydrological model forecasts based on measurements. It presents an example using the CATHY model and assimilating streamflow measurements to correct for uncertainties in initial conditions and atmospheric forcings. It also discusses applications to coupled hydrogeophysical inversion, and using data assimilation at the Landscape Evolution Observatory to estimate spatially distributed hydraulic conductivity fields based on sensor measurements under rainfall experiments.
The document presents an assessment of a post-stack Q estimation algorithm called Q-est. It tests the tool on synthetic and real seismic data. The key findings are: (1) Q-est successfully recovers assumed Q fields from synthetic data with 16% error; (2) Estimated Q fields from real data show lateral consistency and correlate with geological features; (3) Q compensation using estimated fields improves resolution and recovers amplitudes better than using a single Q value.
Modelling and Control of Drinkable Water Networks. Presentation at the 1st technical workshop of the FP7 research project EFFINET in Limassol, Cyprus, 5-6 June 2013. The main developments within WP2 are presented: Understanding the water demand patterns, development of time-series models for the water demand, formulation and solution of Model Predictive Control (MPC) problems for the water network and quantification of the effect that the prediction errors have on the optimal solution and on the closed-loop behaviour of the controlled system.
The document discusses several examples of modeling and uncertainty quantification:
1) Weather and climate modeling involves coupling complex multi-physics models that contain uncertainties in inputs, numerical approximations, and sensor measurements. The goal is to assimilate data to quantify uncertain initial conditions and parameters and make predictions with quantified uncertainties.
2) Pressurized water reactor (PWR) modeling involves multi-scale, multi-physics models with large numbers of uncertain inputs and parameters. Quantifying these uncertainties and understanding their impact on important outputs like peak operating temperature and CRUD buildup is challenging.
3) HIV and epidemic models have many uncertain parameters that cannot be directly measured. Bayesian inference and MCMC sampling are used to quantify parameter uncertainties and make predictions with
Streaming Model Transformations by Complex Event ProcessingIstván Dávid
This document discusses streaming model transformations using complex event processing. It proposes a language for defining complex event patterns and streaming transformation rules. A prototype runtime executes the transformations reactively in response to events. An evaluation on a gesture recognition case study demonstrates the feasibility of processing over 24,000 complex events per second.
This document describes the construction and selection of single sampling quick switching variables systems for given control limits that involve minimum sum of risks. It provides the procedure for finding the single sampling quick switching variables system that has the minimum sum of producer's and consumer's risk for a specified acceptable quality level and limiting quality level. A table is constructed that can be used to select a quick switching variables sampling system for given values of AQL and LQL that has the minimum sum of risks. The document also discusses how to design a quick switching variables sampling system with an unknown standard deviation that involves minimum sum of risks.
This document describes the construction and selection of single sampling quick switching variables systems for given control limits that involve minimum sum of risks. It provides the procedure for finding the single sampling quick switching variables system that has the minimum sum of producer's and consumer's risk for a specified acceptable quality level and limiting quality level. A table is constructed that can be used to select a quick switching variables sampling system for given values of AQL and LQL that has the minimum sum of risks. The document also discusses how to design a quick switching variables sampling system with an unknown standard deviation that involves minimum sum of risks.
The document provides background on supercomputing and introduces the shallow water equations model of wave motion. It summarizes the mathematical model, numerical model using Lax-Wendroff method, sample programs in MATLAB, Java and C/MPI, and results showing the model accurately simulates experimental wave tank behavior.
The document provides background on supercomputing and introduces the shallow water equations model for simulating wave motion. It describes:
1) The mathematical shallow water equations model for conserving mass and momentum over time.
2) The numerical Lax-Wendroff method used to solve the equations, including predictor-corrector steps.
3) Sample programs implementing the method in languages like C/MPI, Java, and MATLAB to model wave behavior in 1D and 2D.
We investigated the applicability and efficiency of the MLMC approach for the Henry-like problem with uncertain porosity, permeability, and recharge. These uncertain parameters were modeled by random fields with three independent random variables. The numerical solution for each random realization was obtained using the well-known ug4 parallel multigrid solver. The number of required random samples on each level was estimated by computing the decay of the variances and computational costs for each level. We also computed the expected value and variance of the mass fraction in the whole domain, the evolution of the pdfs, the solutions at a few preselected points $(t,\bx)$, and the time evolution of the freshwater integral value. We have found that some QoIs require only 2-3 of the coarsest mesh levels, and samples from finer meshes would not significantly improve the result. Note that a different type of porosity may lead to a different conclusion.
The results show that the MLMC method is faster than the QMC method at the finest mesh. Thus, sampling at different mesh levels makes sense and helps to reduce the overall computational cost.
A summary of ongoing research we have been working on at the University of Washington. I gave this in August 2011 at Georgia Tech. My take on how signal processing shapes the projects of UbiComp, turning a novel idea into a robust reality.
This document discusses various techniques for measuring flow in closed conduit systems such as pipes. It describes direct measurement techniques including volume/weight measurements and velocity-area integration. It also covers indirect measurement techniques using differential pressure like the Pitot tube, Venturi meter, orifice plate, and elbow meter. Additional meter types discussed include electromagnetic, turbine, vortex, displacement, ultrasonic, acoustic Doppler, laser Doppler, and particle tracking flow meters. Examples are provided for some techniques.
"Streamflow prediction in River Rhine: Exploring combinations of bias-correct...Jan Verkade
This document explores bias correction of temperature, precipitation, and streamflow predictions for the Rhine River. It finds that bias correcting temperature and precipitation predictions improves their accuracy by 20-60% and 20-30% respectively, but does not consistently translate to improved streamflow prediction accuracy. Preserving the spatial and cross-variable dependencies between predictions is important for streamflow skill. Future work will focus on determining whether the benefits of bias correcting forcing inputs are maintained after also bias correcting streamflow predictions.
Pre- and Post-Selection Paradoxes, Measurement-Disturbance and Contextuality ...Matthew Leifer
1) The document discusses pre-selection, post-selection, and measurements in quantum mechanics, highlighting several paradoxes that can arise.
2) It shows that while these "logical PPS paradoxes" do not necessarily imply theories must be contextual, there is a related proof of contextuality for each paradox when pre- and post-selection projectors are not orthogonal.
3) The author conjectures that the existence of logical PPS paradoxes, combined with an "uncertainty principle" constraint, would imply contextuality and discusses open questions about applications in quantum information theory.
1) The document describes the development, verification, and validation of a responsive boundary model.
2) Verification was performed using manufactured solutions and grid convergence studies to evaluate spatial and temporal discretization errors.
3) Validation compared model predictions of helium plume interferometry data to experimental measurements, analyzing sources of error and sensitivity.
4) Results showed good agreement between computation and experiment, demonstrating the model captured important physical phenomena.
Efficient Simulations for Contamination of Groundwater Aquifers under Uncerta...Alexander Litvinenko
1. Solved time-dependent density driven flow problem with uncertain porosity and permeability in 2D and 3D
2. Computed propagation of uncertainties in porosity into the mass fraction.
3. Computed the mean, variance, exceedance probabilities, quantiles, risks.
4. Such QoIs as the number of fingers, their size, shape, propagation time can be unstable
5. For moderate perturbations, our gPCE surrogate results are similar to qMC results.
6. Used highly scalable solver on up to 800 computing nodes,
1) The document presents a Bayesian hierarchical model to predict chlorophyll a levels in the New River Estuary using water quality data from 8 monitoring stations collected monthly since 2007.
2) It describes handling missing data through multiple imputation, and building a two-level hierarchical model with stations at level 1 and estuarine sections at level 2.
3) The results show the station and section coefficients from the hierarchical model, indicating the effects of various physical and chemical attributes on chlorophyll a levels across the estuary.
This document discusses biostatistics in bioequivalence studies. It covers:
1) The importance of biostatistics in designing and analyzing bioequivalence trials, as well as distinguishing between correlation and causation.
2) Key biostatistical concepts for bioequivalence studies including descriptive statistics, parametric assumptions of normality and homoscedasticity, study designs, and tests of significance.
3) Details on sample size calculation and determining the number of subjects needed in a bioequivalence study based on factors like variability, equivalence bounds, type I and II error rates.
This document summarizes the CoCoA algorithm for distributed optimization. CoCoA uses a primal-dual framework to solve machine learning problems efficiently when data is distributed across multiple machines. It allows local machines to immediately apply updates to their local dual variables, while averaging the local primal updates over a small number of machines. CoCoA guarantees convergence, requires low communication, and can be implemented in just a few lines of code in systems like Spark. It improves upon mini-batch approaches by handling methods beyond stochastic gradient descent and avoiding issues with stale updates.
This document discusses computational simulations of chaotic systems and the challenges of sensitivity analysis and optimization for such systems. It introduces the concept of Least Squares Shadowing as a solution, which formulates the problem as a least squares problem without an initial condition to avoid the divergence of solutions seen in traditional sensitivity analysis of chaotic systems. Algorithms for solving the Least Squares Shadowing problem are also presented.
This document provides an overview of sparse statistical modelling techniques. It begins by defining sparse statistical models as those with only a small number of nonzero parameters. It then outlines several sparse modelling methods, including sparse linear models, sparse PCA, sparse SVD, sparse CCA, and sparse LDA. For each method, it provides a brief mathematical formulation and discusses how sparsity is introduced through penalization terms. It also includes examples applying several of these techniques to both simulated and real-world genomic data.
Este documento analiza el modelo de negocio de YouTube. Explica que YouTube y otros sitios de video online representan un nuevo modelo de negocio para contenidos audiovisuales debido al cambio en los hábitos de consumo causado por las nuevas tecnologías. Describe cómo YouTube aprovecha la participación de los usuarios para mejorar continuamente y atraer una audiencia diferente a la de los medios tradicionales.
The document discusses several examples of modeling and uncertainty quantification:
1) Weather and climate modeling involves coupling complex multi-physics models that contain uncertainties in inputs, numerical approximations, and sensor measurements. The goal is to assimilate data to quantify uncertain initial conditions and parameters and make predictions with quantified uncertainties.
2) Pressurized water reactor (PWR) modeling involves multi-scale, multi-physics models with large numbers of uncertain inputs and parameters. Quantifying these uncertainties and understanding their impact on important outputs like peak operating temperature and CRUD buildup is challenging.
3) HIV and epidemic models have many uncertain parameters that cannot be directly measured. Bayesian inference and MCMC sampling are used to quantify parameter uncertainties and make predictions with
Streaming Model Transformations by Complex Event ProcessingIstván Dávid
This document discusses streaming model transformations using complex event processing. It proposes a language for defining complex event patterns and streaming transformation rules. A prototype runtime executes the transformations reactively in response to events. An evaluation on a gesture recognition case study demonstrates the feasibility of processing over 24,000 complex events per second.
This document describes the construction and selection of single sampling quick switching variables systems for given control limits that involve minimum sum of risks. It provides the procedure for finding the single sampling quick switching variables system that has the minimum sum of producer's and consumer's risk for a specified acceptable quality level and limiting quality level. A table is constructed that can be used to select a quick switching variables sampling system for given values of AQL and LQL that has the minimum sum of risks. The document also discusses how to design a quick switching variables sampling system with an unknown standard deviation that involves minimum sum of risks.
This document describes the construction and selection of single sampling quick switching variables systems for given control limits that involve minimum sum of risks. It provides the procedure for finding the single sampling quick switching variables system that has the minimum sum of producer's and consumer's risk for a specified acceptable quality level and limiting quality level. A table is constructed that can be used to select a quick switching variables sampling system for given values of AQL and LQL that has the minimum sum of risks. The document also discusses how to design a quick switching variables sampling system with an unknown standard deviation that involves minimum sum of risks.
The document provides background on supercomputing and introduces the shallow water equations model of wave motion. It summarizes the mathematical model, numerical model using Lax-Wendroff method, sample programs in MATLAB, Java and C/MPI, and results showing the model accurately simulates experimental wave tank behavior.
The document provides background on supercomputing and introduces the shallow water equations model for simulating wave motion. It describes:
1) The mathematical shallow water equations model for conserving mass and momentum over time.
2) The numerical Lax-Wendroff method used to solve the equations, including predictor-corrector steps.
3) Sample programs implementing the method in languages like C/MPI, Java, and MATLAB to model wave behavior in 1D and 2D.
We investigated the applicability and efficiency of the MLMC approach for the Henry-like problem with uncertain porosity, permeability, and recharge. These uncertain parameters were modeled by random fields with three independent random variables. The numerical solution for each random realization was obtained using the well-known ug4 parallel multigrid solver. The number of required random samples on each level was estimated by computing the decay of the variances and computational costs for each level. We also computed the expected value and variance of the mass fraction in the whole domain, the evolution of the pdfs, the solutions at a few preselected points $(t,\bx)$, and the time evolution of the freshwater integral value. We have found that some QoIs require only 2-3 of the coarsest mesh levels, and samples from finer meshes would not significantly improve the result. Note that a different type of porosity may lead to a different conclusion.
The results show that the MLMC method is faster than the QMC method at the finest mesh. Thus, sampling at different mesh levels makes sense and helps to reduce the overall computational cost.
A summary of ongoing research we have been working on at the University of Washington. I gave this in August 2011 at Georgia Tech. My take on how signal processing shapes the projects of UbiComp, turning a novel idea into a robust reality.
This document discusses various techniques for measuring flow in closed conduit systems such as pipes. It describes direct measurement techniques including volume/weight measurements and velocity-area integration. It also covers indirect measurement techniques using differential pressure like the Pitot tube, Venturi meter, orifice plate, and elbow meter. Additional meter types discussed include electromagnetic, turbine, vortex, displacement, ultrasonic, acoustic Doppler, laser Doppler, and particle tracking flow meters. Examples are provided for some techniques.
"Streamflow prediction in River Rhine: Exploring combinations of bias-correct...Jan Verkade
This document explores bias correction of temperature, precipitation, and streamflow predictions for the Rhine River. It finds that bias correcting temperature and precipitation predictions improves their accuracy by 20-60% and 20-30% respectively, but does not consistently translate to improved streamflow prediction accuracy. Preserving the spatial and cross-variable dependencies between predictions is important for streamflow skill. Future work will focus on determining whether the benefits of bias correcting forcing inputs are maintained after also bias correcting streamflow predictions.
Pre- and Post-Selection Paradoxes, Measurement-Disturbance and Contextuality ...Matthew Leifer
1) The document discusses pre-selection, post-selection, and measurements in quantum mechanics, highlighting several paradoxes that can arise.
2) It shows that while these "logical PPS paradoxes" do not necessarily imply theories must be contextual, there is a related proof of contextuality for each paradox when pre- and post-selection projectors are not orthogonal.
3) The author conjectures that the existence of logical PPS paradoxes, combined with an "uncertainty principle" constraint, would imply contextuality and discusses open questions about applications in quantum information theory.
1) The document describes the development, verification, and validation of a responsive boundary model.
2) Verification was performed using manufactured solutions and grid convergence studies to evaluate spatial and temporal discretization errors.
3) Validation compared model predictions of helium plume interferometry data to experimental measurements, analyzing sources of error and sensitivity.
4) Results showed good agreement between computation and experiment, demonstrating the model captured important physical phenomena.
Efficient Simulations for Contamination of Groundwater Aquifers under Uncerta...Alexander Litvinenko
1. Solved time-dependent density driven flow problem with uncertain porosity and permeability in 2D and 3D
2. Computed propagation of uncertainties in porosity into the mass fraction.
3. Computed the mean, variance, exceedance probabilities, quantiles, risks.
4. Such QoIs as the number of fingers, their size, shape, propagation time can be unstable
5. For moderate perturbations, our gPCE surrogate results are similar to qMC results.
6. Used highly scalable solver on up to 800 computing nodes,
1) The document presents a Bayesian hierarchical model to predict chlorophyll a levels in the New River Estuary using water quality data from 8 monitoring stations collected monthly since 2007.
2) It describes handling missing data through multiple imputation, and building a two-level hierarchical model with stations at level 1 and estuarine sections at level 2.
3) The results show the station and section coefficients from the hierarchical model, indicating the effects of various physical and chemical attributes on chlorophyll a levels across the estuary.
This document discusses biostatistics in bioequivalence studies. It covers:
1) The importance of biostatistics in designing and analyzing bioequivalence trials, as well as distinguishing between correlation and causation.
2) Key biostatistical concepts for bioequivalence studies including descriptive statistics, parametric assumptions of normality and homoscedasticity, study designs, and tests of significance.
3) Details on sample size calculation and determining the number of subjects needed in a bioequivalence study based on factors like variability, equivalence bounds, type I and II error rates.
This document summarizes the CoCoA algorithm for distributed optimization. CoCoA uses a primal-dual framework to solve machine learning problems efficiently when data is distributed across multiple machines. It allows local machines to immediately apply updates to their local dual variables, while averaging the local primal updates over a small number of machines. CoCoA guarantees convergence, requires low communication, and can be implemented in just a few lines of code in systems like Spark. It improves upon mini-batch approaches by handling methods beyond stochastic gradient descent and avoiding issues with stale updates.
This document discusses computational simulations of chaotic systems and the challenges of sensitivity analysis and optimization for such systems. It introduces the concept of Least Squares Shadowing as a solution, which formulates the problem as a least squares problem without an initial condition to avoid the divergence of solutions seen in traditional sensitivity analysis of chaotic systems. Algorithms for solving the Least Squares Shadowing problem are also presented.
This document provides an overview of sparse statistical modelling techniques. It begins by defining sparse statistical models as those with only a small number of nonzero parameters. It then outlines several sparse modelling methods, including sparse linear models, sparse PCA, sparse SVD, sparse CCA, and sparse LDA. For each method, it provides a brief mathematical formulation and discusses how sparsity is introduced through penalization terms. It also includes examples applying several of these techniques to both simulated and real-world genomic data.
Similar to Using Qualitative Knowledge in Numerical Learning (20)
Este documento analiza el modelo de negocio de YouTube. Explica que YouTube y otros sitios de video online representan un nuevo modelo de negocio para contenidos audiovisuales debido al cambio en los hábitos de consumo causado por las nuevas tecnologías. Describe cómo YouTube aprovecha la participación de los usuarios para mejorar continuamente y atraer una audiencia diferente a la de los medios tradicionales.
The defense was successful in portraying Michael Jackson favorably to the jury in several ways:
1) They dressed Jackson in ornate costumes that conveyed images of purity, innocence, and humility.
2) Jackson was shown entering the courtroom as if on a red carpet, emphasizing his celebrity status.
3) Jackson appeared vulnerable, childlike, and in declining health during the trial, eliciting sympathy from jurors.
4) Defense attorney Tom Mesereau effectively presented a coherent narrative of Jackson as a victim and portrayed Neverland as a place of refuge, undermining the prosecution's arguments.
Michael Jackson was born in 1958 in Gary, Indiana and rose to fame in the 1960s as the lead singer of The Jackson 5, topping music charts in the 1970s. As a solo artist in the 1980s, his album Thriller broke music records. In the 1990s and 2000s, Jackson faced several legal issues related to child abuse allegations while continuing to release music. He married Lisa Marie Presley and Debbie Rowe and had two children before his death in 2009.
Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...butest
This document appears to be a list of popular books from various authors. It includes over 150 book titles across many genres such as fiction, non-fiction, memoirs, and novels. The books cover a wide range of topics from politics to cooking to autobiographies.
The prosecution lost the Michael Jackson trial due to several key mistakes and weaknesses in their case:
1) The lead prosecutor, Thomas Sneddon, was too personally invested in the case against Jackson, having pursued him for over a decade without success.
2) Sneddon's opening statement was disorganized and weak, failing to effectively outline the prosecution's case.
3) The accuser's mother was not credible and damaged the prosecution's case through her erratic testimony, history of lies and con artist behavior.
4) Many prosecution witnesses were not credible due to prior lawsuits against Jackson, debts owed to him, or having been fired by him. Several witnesses even took the Fifth Amendment.
Here are three examples of public relations from around the world:
1. The UK government's "Be Clear on Cancer" campaign which aims to raise awareness of cancer symptoms and encourage early diagnosis.
2. Samsung's global brand marketing and sponsorship activities which aim to increase brand awareness and favorability of Samsung products worldwide.
3. The Brazilian government's efforts to improve its international image and relations with other countries through strategic communication and diplomacy.
The three most important functions of public relations are:
1. Media relations because the media is how most organizations reach their key audiences. Strong media relationships are crucial.
2. Writing, because written communication is at the core of public relations and how most information is
Michael Jackson Please Wait... provides biographical information about Michael Jackson including his birthdate, birthplace, parents, height, interests, idols, favorite foods, films, and more. It discusses his background, career highlights including influential albums like Thriller, and films he appeared in such as The Wiz and Moonwalker. The document contains photos and details about Jackson's life and illustrious music career.
The MYnstrel Free Press Volume 2: Economic Struggles, Meet Jazzbutest
The document discusses the process of manufacturing celebrity and its negative byproducts. It argues that celebrities are rarely the best in their individual pursuits like singing, dancing, etc. but become famous due to being products of a system controlled by wealthy elites. This system stifles opportunities for worthy artists and creates feudalism. The document also asserts that manufactured celebrities should not be viewed as role models due to behaviors like drug abuse and narcissism that result from the celebrity-making process.
Michael Jackson was a child star who rose to fame with the Jackson 5 in the late 1960s and early 1970s. As a solo artist in the 1970s and 1980s, he had immense commercial success with albums like Off the Wall, Thriller, and Bad, which featured hit singles and groundbreaking music videos. However, his career and public image were plagued by controversies related to allegations of child sexual abuse in the 1990s and 2000s. He continued recording and performing but faced ongoing media scrutiny into his private life until his death in 2009.
Social Networks: Twitter Facebook SL - Slide 1butest
The document discusses using social networking tools like Twitter and Facebook in K-12 education. Twitter allows students and teachers to share short updates and can be used to give parents a window into classroom activities. Facebook allows targeted advertising that could be used to promote educational activities. Both tools could help facilitate communication between schools and communities if used properly while managing privacy and security concerns.
Facebook has over 300 million active users who log on daily, and allows brands to create public profile pages to interact with users. Pages are for brands and organizations only, while groups can be made by any user about any topic. Pages do not show admin names and have no limits on fans, while groups display admin names and are limited to 5,000 members. Content on pages should aim to provoke action from subscribers and establish a regular posting schedule using a conversational tone.
Executive Summary Hare Chevrolet is a General Motors dealership ...butest
Hare Chevrolet is a car dealership located in Noblesville, Indiana that has successfully used social media platforms like Twitter, Facebook, and YouTube to create a positive brand image. They invest significant time interacting directly with customers online to foster a sense of community rather than overtly advertising. As a result, Hare Chevrolet has built a large, engaged audience on social media and serves as a model for how brands can use online presences strategically.
Welcome to the Dougherty County Public Library's Facebook and ...butest
This document provides instructions for signing up for Facebook and Twitter accounts. It outlines the sign up process for both platforms, including filling out forms with name, email, password and other details. It describes how the platforms will then search for friends and suggest people to connect with. It also explains how to search for and follow the Dougherty County Public Library page on both Facebook and Twitter once signed up. The document concludes by thanking participants and providing a contact for any additional questions.
Paragon Software announces the release of Paragon NTFS for Mac OS X 8.0, which provides full read and write access to NTFS partitions on Macs. It is the fastest NTFS driver on the market, achieving speeds comparable to native Mac file systems. Paragon NTFS for Mac 8.0 fully supports the latest Mac OS X Snow Leopard operating system in 64-bit mode and allows easy transfer of files between Windows and Mac partitions without additional hardware or software.
This document provides compatibility information for Olympus digital products used with Macintosh OS X. It lists various digital cameras, photo printers, voice recorders, and accessories along with their connection type and any notes on compatibility. Some products require booting into OS 9.1 for software compatibility or do not support devices that need a serial port. Drivers and software are available for download from Olympus and other websites for many products to enable use with OS X.
To use printers managed by the university's Information Technology Services (ITS), students and faculty must install the ITS Remote Printing software on their Mac OS X computer. This allows them to add network printers, log in with their ITS account credentials, and print documents while being charged per page to funds in their pre-paid ITS account. The document provides step-by-step instructions for installing the software, adding a network printer, and printing to that printer from any internet connection on or off campus. It also explains the pay-in-advance printing payment system and how to check printing charges.
The document provides an overview of the Mac OS X user interface for beginners, including descriptions of the desktop, login screen, desktop elements like the dock and hard disk, and how to perform common tasks like opening files and folders. It also addresses frequently asked questions for Windows users switching to Mac OS X, such as where documents are stored, how to save or find documents, and what the equivalent of the C: drive is in Mac OS X. The document concludes with sections on file management tasks like creating and deleting folders, organizing files within applications, using Spotlight search, and an overview of the Dashboard feature.
This document provides a checklist for securing Mac OS X version 10.5, focusing on hardening the operating system, securing user accounts and administrator accounts, enabling file encryption and permissions, implementing intrusion detection, and maintaining password security. It describes the Unix infrastructure and security framework that Mac OS X is built on, leveraging open source software and following the Common Data Security Architecture model. The checklist can be used to audit a system or harden it against security threats.
This document summarizes a course on web design that was piloted in the summer of 2003. The course was a 3 credit course that met 4 times a week for lectures and labs. It covered topics such as XHTML, CSS, JavaScript, Photoshop, and building a basic website. 18 students from various majors enrolled. Student and instructor evaluations found the course to be very successful overall, though some improvements were suggested like ensuring proper software and pairing programming/non-programming students. The document also discusses implications of incorporating web design material into existing computer science curriculums.
10. PREDICTING WATER LEVEL WITH M5 11.25 10.0 8.75 6.25 7.5 Initial_ouflow =12.5 Qualitatively incorrect – water level cannot increase M5 prediction
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12. Q 2 LEARNING AIMS AT OVERCOMING THESE DIFFICULTIES
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18. HOW CAN WE DESCRIBE QUALITATIVE PROPERTIES ? We can use concepts from field of qualitative reasoning in AI Related terms: Qualitative physics, Naive physics, Qualitative modelling
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26. THIS REASONING IS VALID FOR ALL CONTAINERS OF ANY SHAPE AND SIZE, REGARDLESS OF ACTUAL NUMBERS!
37. INDUCED QUALITATIVE TREE FOR z = x 2 - y 2 + noise z= M -,+ ( x,y) z= M -,- ( x,y) z= M +,+ ( x , y) z= M +,- ( x,y) 0 > 0 > 0 0 > 0 0 y x y
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39. Q2Q Qualitative to Quantitative Transformation
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42. RESPECTING MQCs NUMERICALLY z = M +,+ (x,y) requires: If x 1 < x 2 and y 1 < y 2 then z 1 < z 2 (x 2 , y 2 ) (x 1 , y 1 ) x y
43. QFILTER AN APPROACH TO Q2Q TRANSFORMATION Šuc and Bratko, ECML ’03
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47. QFILTER APPLIED TO WATER OUTFLOW Qualitative constraint that applies to water outflow: h = M -,+ (time, InitialOutflow) This could be supplied by domain expert, or induced from data by QUIN
73. CARRIAGE CONTROL QUIN: dX des = f(X, , d ) M - ( X ) M + ( ) X < 20.7 X < 60.1 M + ( X ) yes yes no no First the trolley velocity is increasing From about middle distance from the goal until the goal the trolley velocity is decreasing At the goal reduce the swing of the rope (by acceleration of the trolley when the rope angle increases)
74. CARRIAGE CONTROL: dX des = f(X, , d ) M - ( X ) M + ( ) X < 20.7 X < 60.1 X < 29.3 M + ( X ) d < -0.02 M - ( X ) M -,+ ( X , ) M +,+,- ( X, , d ) yes yes yes yes no no no no Enables reconstruction of individual differences in control styles Operator S Operator L
80. Robot Arm Domain Y 1 Y 2 Two-link, two-joint robot arm Link 1 extendible: L 1 [2, 10] Y 1 = L 1 sin( 1 ) Y 2 = L 1 sin( 1 ) + 5 sin( 1 + 2 ) 1 2 Four learning problems: A: Y 1 = f(L 1 , 1 ) B: Y 2 = f(L 1 , 1 , 2 , sum , Y 1 ) C: Y 2 = f(L 1 , 1 , 2 , sum ) D: Y 2 = f(L 1 , 1 , 2 ) L 1 Derived attribute sum = 1 + 2 Difficulty for Q 2
81. Robot Arm: LWR and Q 2 at different noise levels Q 2 outperforms LWR with all four learning problems (at all three noise levels) A 0, 5, 10% n. | B 0, 5, 10% n. | C 0, 5, 10% n. | D 0, 5, 10% n.
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83. UCI and Dynamic Domains: LWR compared to Q 2 Similar results with other two base-learners. Q 2 significantly better than base-learners in 18 out of 24 comparisons (24 = 8 datasets * 3 base-learners)
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Editor's Notes
I’ll give an example of the learning problem for QUIN algorithm. The red points on the picture are example points for the fn. z=… And this are noisy example – QUIN has to be able to learn from noisy data. We can see some qualitatively similar regions: there are 4 qual. different regions. This examples are the learning examples for QUIN: Z is the class var., and x and y are the attributes.
I’ll give an example of the learning problem for QUIN algorithm. The red points on the picture are example points for the fn. z=… And this are noisy example – QUIN has to be able to learn from noisy data. We can see some qualitatively similar regions: there are 4 qual. different regions. This examples are the learning examples for QUIN: Z is the class var., and x and y are the attributes.
From this learning examples, QUIN induces the following qual.tree that defines the partition of the attribute space into the areas with common behaviour of the class variable. In the leaves are QCFs. For example, the rightmost leaf that applies when x and y are both positive says that z is ... We say that z is …
A basic alg. for learning of q.trees uses MDL to learn …QCF, that is QCF that fits the examples best. To learn a qual. tree. a top-down greedy alg., that is similar to dec.tree learning algorithms, is used:… QUIN is heuristic improvement of this basic algorithm that considers also the consistency and prox…
Given results for ZooChange are multiplied by 1000 (actual values are 1000 times smaller)
The improvements of Q2 are even more obvious on INTEC wheel model. The blue line denotes the time behavior of toe angle alpha on the most difficult test trace.
The red line is alpha predicted by LWR.
and the orange line, alpha predicted by M5.
The green line corresponds to Q2 prediction learned from the same data. Q2 clearly has the best numerical fit. Also with other state-of-the-art numerical predictors qualitative errors are clearly visible.
To evaluate accuracy benefits of Q2 learning we compared Because Qfilter optimaly adjusts a base-learner’s predictions to be consistent with a qualitative tree, the differences… We experimented with 3 base-learners: {it RRE} is the root mean squared error normalized by the root mean squared error of average class value. Using our implementation of model and regression trees.
Now I wll describe the experiments with 5 UCI and 3 Dyanmic Domains We used the 5 smallest data sets from the UCI repository with the majority of continuous attributes. A reason for choosing these data sets is also that Quinlan gives results of M5 and several other regression methods on these data sets, which enables a better comparison of $Q^2$ to other methods. The other three data sets are from dynamic domains where QUIN has typically been previously applied to explain the underlying control skill and to use the induced qualitative models to control a dynamic system. Until now, it was not possible to measure the numerical accuracy of the learned qualitative trees or compare it to other learning methods. Data set {em AntiSway} was used in reverse-engineering of an industrial gantry crane controller. This so-called {em anti-sway crane} is used in metallurgical companies to reduce the swing of the load and increase the productivity of transportation of slabs. Data sets {em CraneSkill1} and {em CraneSkill2} are the logged data of two experienced human operators controlling a crane simulator. Such control traces are typically used to reconstruct the underlying operator's control skill. The learning task is to predict the velocity of a crane trolley given the position of the trolley, rope angle and its velocity.
The graph gives the RREs of LWR and Q2 in these 8 datasets using 10CV. Q 2 is much better in all domains, except in AutoMPG domain.