Esmaeilzade sampling
•Download as PPTX, PDF•
2 likes•2,380 views
This document discusses different sampling techniques used in population surveys including simple random sampling, systematic sampling, stratified sampling, cluster sampling, convenience sampling, and quota sampling. It provides examples of how to calculate the sample size for each technique and notes the advantages and disadvantages of each.
Report
Share
Report
Share
Recommended
Pavement design method
The document contains the input parameters and results of a pavement design analysis using a linear elastic layered system model. The analysis was performed for a 3-layer pavement system with different thicknesses and moduli for each layer, under a single load group with a contact pressure of 120 psi. The results show the radial and vertical displacements, stresses, and strains at 4 radial coordinate points within each layer for the given loading condition.
Kaggle Amazon Contest
Slides for my talk at Open Data Science Meetup #1 at Minsk
https://www.youtube.com/watch?v=l43hszLm-SU&index=3
An Overview of HDF-EOS (Part 1)
HDF AND HDF-EOS WORKSHOP II (1998)
Source: http://hdfeos.org/workshops/ws02/presentations/ilg1/ilg1.ppt
Time series representations for better data mining
The document discusses time series representations, which can be used to reduce dimensionality, remove noise, and emphasize patterns in time series data. It introduces the TSrepr R package, which implements various time series representation methods like PAA, DWT, DFT, and SAX. It allows creating representation matrices from multiple time series and provides functions for normalization, windowing, and extending the package with custom representations. Time series representations help with tasks like clustering, classification, and forecasting of time series data.
Java 8 Concurrency Updates
This document summarizes new concurrency features in Java 8 including parallel streams, ConcurrentHashMap improvements, Striped64 for lock-free counting, CompletableFuture for asynchronous programming, and @Contended annotation for avoiding false sharing. It also discusses best practices for using parallel streams and new concurrent collection classes like ConcurrentHashMap.
Contrastive Divergence Learning
1) The document discusses contrastive divergence learning, a method for training probabilistic models using gradient descent.
2) It involves using Markov chain Monte Carlo sampling to approximate gradients that are intractable, by running a short Markov chain to move model samples from the data distribution to the model distribution.
3) There is a potential for bias compared to true maximum likelihood learning, as contrastive divergence approximates minimizing the Kullback-Leibler divergence between the data and model after one step of MCMC, rather than the full distributions.
Sloshing-aware MPC for upper stage attitude control
We present a novel modeling
methodology to derive a nonlinear dynamical model which
adequately describes the effect of fuel sloshing on the attitude dynamics of a spacecraft. We model the impulsive thrusters using mixed logic and dynamics leading to a hybrid formulation.
We design a hybrid model predictive control scheme for the
attitude control of a launcher during its long coasting period,
aiming at minimising the actuation count of the thrusters.
report_1
The document reports on an experiment to determine the critical compression load of an aluminum alloy bar. The bar was 300mm long with a 25mm diameter and 1mm thickness. It was tested on a machine that applied increasing loads until failure. The bar failed at a maximum load of 2404N. Calculations determined the theoretical critical load to be 42936N and theoretical critical stress to be 327MPa, which is close to the experimental value of 318MPa with a 2.83% error.
Recommended
Pavement design method
The document contains the input parameters and results of a pavement design analysis using a linear elastic layered system model. The analysis was performed for a 3-layer pavement system with different thicknesses and moduli for each layer, under a single load group with a contact pressure of 120 psi. The results show the radial and vertical displacements, stresses, and strains at 4 radial coordinate points within each layer for the given loading condition.
Kaggle Amazon Contest
Slides for my talk at Open Data Science Meetup #1 at Minsk
https://www.youtube.com/watch?v=l43hszLm-SU&index=3
An Overview of HDF-EOS (Part 1)
HDF AND HDF-EOS WORKSHOP II (1998)
Source: http://hdfeos.org/workshops/ws02/presentations/ilg1/ilg1.ppt
Time series representations for better data mining
The document discusses time series representations, which can be used to reduce dimensionality, remove noise, and emphasize patterns in time series data. It introduces the TSrepr R package, which implements various time series representation methods like PAA, DWT, DFT, and SAX. It allows creating representation matrices from multiple time series and provides functions for normalization, windowing, and extending the package with custom representations. Time series representations help with tasks like clustering, classification, and forecasting of time series data.
Java 8 Concurrency Updates
This document summarizes new concurrency features in Java 8 including parallel streams, ConcurrentHashMap improvements, Striped64 for lock-free counting, CompletableFuture for asynchronous programming, and @Contended annotation for avoiding false sharing. It also discusses best practices for using parallel streams and new concurrent collection classes like ConcurrentHashMap.
Contrastive Divergence Learning
1) The document discusses contrastive divergence learning, a method for training probabilistic models using gradient descent.
2) It involves using Markov chain Monte Carlo sampling to approximate gradients that are intractable, by running a short Markov chain to move model samples from the data distribution to the model distribution.
3) There is a potential for bias compared to true maximum likelihood learning, as contrastive divergence approximates minimizing the Kullback-Leibler divergence between the data and model after one step of MCMC, rather than the full distributions.
Sloshing-aware MPC for upper stage attitude control
We present a novel modeling
methodology to derive a nonlinear dynamical model which
adequately describes the effect of fuel sloshing on the attitude dynamics of a spacecraft. We model the impulsive thrusters using mixed logic and dynamics leading to a hybrid formulation.
We design a hybrid model predictive control scheme for the
attitude control of a launcher during its long coasting period,
aiming at minimising the actuation count of the thrusters.
report_1
The document reports on an experiment to determine the critical compression load of an aluminum alloy bar. The bar was 300mm long with a 25mm diameter and 1mm thickness. It was tested on a machine that applied increasing loads until failure. The bar failed at a maximum load of 2404N. Calculations determined the theoretical critical load to be 42936N and theoretical critical stress to be 327MPa, which is close to the experimental value of 318MPa with a 2.83% error.
report_2_v2
The document analyzes the aerodynamic characteristics of the FX 63-137 airfoil using XFOIL software. XFOIL was used to generate lift and drag curves across a range of angles of attack and calculate coefficients like lift curve slope, maximum lift, and minimum drag. These results were then compared to wind tunnel data from the Stuttgarter Profilkatalog, finding some differences, especially at high angles of attack. The document includes figures of the results and tables comparing the XFOIL and experimental values.
HMPC for Upper Stage Attitude Control
This document describes a hybrid model predictive control approach for attitude control of spacecraft using impulsive thrusters. The approach models the spacecraft dynamics and minimum impulse effects of the thrusters. It formulates the control problem as minimizing a cost function over future inputs while satisfying the hybrid dynamics and constraints, such as a limit on total thruster actuations. Simulations show the hybrid MPC achieves higher pointing accuracy, lower thruster usage, and better disturbance rejection compared to traditional PD and LQR controllers.
Devansh
This document summarizes research on general profit scheduling on parallel processors. It discusses how profit functions can be parameterized to incorporate various metrics like weighted flow time. It presents solutions for special profit functions using dynamic programming formulations. The solutions are extended to handle multiple machines using a similar DP approach. Generalizations like jobs having different processing times on different machines and non-zero release times are also discussed. Reductions from general scheduling problems to geometric set cover problems are explained. Further work directions on improving approximations for these problems are mentioned.
射頻電子實驗手冊 [實驗6] 阻抗匹配模擬
This document discusses using the Smith Chart tool in ADS (Advanced Design System) for impedance matching circuits at different frequency ranges. It covers defining the source and load impedances on the Smith Chart, using the Z-Chart and Y-Chart variations, examining the Q factor on the Smith Chart, and designing basic matching networks like L-sections and T-sections directly on the Smith Chart in ADS.
ALPSチュートリアル
1. ALPS (Applications and Libraries for Physics Simulations) is an open source software project that provides a framework for large-scale simulations of quantum many-body systems using quantum Monte Carlo and other numerical techniques.
2. It contains libraries and applications for lattice models, quantum lattice models, and other physics simulations. Models can be defined through XML files and simulations run using the simplemc program.
3. Results such as magnetization and specific heat are output in XML format and can be analyzed using the Python analysis module or visualized using ParaView.
2019 CtD: A hybrid deep learning approach to vertexing
This document presents a hybrid deep learning approach for vertex finding using 1D convolutional neural networks. It describes generating 1D kernel densities from tracking information, building target distributions, and using a CNN architecture with an adjustable cost function to optimize the false positive rate versus efficiency. The approach achieves 93.87% efficiency with a 0.251 false positive rate on test data. Future work includes incorporating additional xy information and exploring full 2D kernel densities.
HOW 2019: Machine Learning for the Primary Vertex Reconstruction
The document describes a machine learning approach for primary vertex reconstruction in high-energy physics experiments. A hybrid method is proposed that uses a 1D convolutional neural network to analyze histograms produced from tracking data. The network is able to find primary vertices with high efficiency and tunable false positive rates, demonstrating the potential of machine learning for this task. Future work involves adding more tracking information and iterating between track association and vertex finding to improve performance.
2019 IML workshop: A hybrid deep learning approach to vertexing
A hybrid deep learning approach is proposed for vertex finding using 1D convolutional neural networks on kernel density estimates from tracking data. The approach generates 1D histograms from 3D tracking data and uses a CNN to classify primary vertex positions. In a proof-of-concept on simulated data, it achieves primary vertex finding efficiencies and false positive rates comparable to traditional algorithms, with tunable efficiency-false positive tradeoffs. Future work includes incorporating additional tracking features, associating tracks to vertices, and deploying the inference engine for the LHCb trigger.
QR Factorizations and SVDs for Tall-and-skinny Matrices in MapReduce Architec...
This document summarizes Austin Benson's presentation on QR factorizations and SVDs for tall-and-skinny matrices in MapReduce architectures. It discusses how communication-avoiding TSQR and indirect/direct TSQR algorithms can be implemented in MapReduce frameworks to compute QR factorizations and SVDs of large matrices in a distributed, parallel manner. It also compares the performance of different MapReduce algorithms for computing QR on various sized matrices.
ACAT 2019: A hybrid deep learning approach to vertexing
This document presents a hybrid deep learning approach for vertex finding in high-energy physics experiments. It uses a 1D convolutional neural network to analyze kernel density estimates of track information in order to identify primary vertex positions. The approach achieves primary vertex finding efficiencies of 88-94% with low false positive rates comparable to traditional algorithms. The authors demonstrate tuning of the efficiency-false positive rate tradeoff and discuss plans to improve performance by incorporating additional track information and iterative refinement.
Ejerciciooo3
This document analyzes the linear regression between hours worked (x) and units produced (y) at a workshop. It provides the correlation coefficient (0.953994158), scatter plot of the data, and calculations to determine the regression line equation and test for significance of the linear relationship. The t-statistic calculated (10.06071375) is greater than the critical value (2.228), indicating there is a statistically significant linear relationship between hours worked and units produced.
射頻電子 - [第六章] 低雜訊放大器設計
This document discusses the design of low-noise amplifiers. It begins with an overview of the basic structure of transmitters and receivers in wireless communication systems. It then reviews the relationships between power and gain and introduces the concept of the available power gain circle. The document discusses a design method for amplifiers that does not require simultaneous conjugate matching of both ports. It also covers noise theory for two-port networks and the fixed noise figure circle. The key points are utilizing available power gain circles and fixed noise figure circles to design amplifiers through tradeoffs between gain and noise on the Smith chart.
Presupuesto del ordenador (1)
This document contains a list of items and their quantities, descriptions, unit prices, and total prices. It includes computer components like a case, motherboard, graphics card, and accessories such as a webcam, mouse, keyboard, and printer. The total price of all items is over 2,300 euros.
Distributed solution of stochastic optimal control problem on GPUs
Stochastic optimal control problems arise in many
applications and are, in principle,
large-scale involving up to millions of decision variables. Their
applicability in control applications is often limited by the
availability of algorithms that can solve them efficiently and within
the sampling time of the controlled system.
In this paper we propose a dual accelerated proximal
gradient algorithm which is amenable to parallelization and
demonstrate that its GPU implementation affords high speed-up
values (with respect to a CPU implementation) and greatly outperforms
well-established commercial optimizers such as Gurobi.
library(tidyr) and library(ggplot2)
The document loads libraries and plots data from the mtcars dataset. It uses gather() to reshape the data and plot mpg vs other variables like hp, cyl, and wt, facetted by each variable. It then plots mpg vs each variable with stat_smooth() added.
Math cad fourier analysis (jcb-edited)
This document discusses Fourier analysis and the Fourier transform. It illustrates generating a signal as the superposition of three harmonic components and plotting the individual time histories. The components are summed to form a more complex signal. The signal is then converted to a digital format and the fast Fourier transform is calculated. Plotting the signal in the frequency domain makes the three harmonic components easier to identify compared to the original time domain signal with added noise.
Bellman ford Algorithm
The document describes the Bellman-Ford algorithm for finding the shortest paths in a graph. It begins by defining the shortest path problem and describing applications that can be modeled as shortest path problems, such as network routing. It then explains that Bellman-Ford can find single-source shortest paths in graphs with positive or negative edge weights, unlike Dijkstra's algorithm which only works for positive edges. The core of the algorithm uses relaxation to iteratively update the shortest path estimates over multiple rounds until convergence. Pseudocode is provided to demonstrate how the relaxation process is repeated for all edges |V|-1 times to find a shortest path from the source node to all other nodes.
polar-cap-power
This document summarizes how ultra-low frequency (ULF) hydromagnetic power is typically characterized in the deep polar cap. It presents median power values as a function of frequency band, magnetic field direction, location, and local time using data from multiple polar cap stations including AGO5, AGO6, SPA, and MCM. Graphs of median-relative spectra are shown for AGO5 at 87°S CGMLat to illustrate the visualization techniques.
Renewable energy course#02 gen
This document provides information about power patterns in Colorado during winter, wind turbine performance prediction theories, and the fields required to contribute to wind energy technology. It summarizes:
1) A typical winter day in Colorado sees power demand peak in the morning and evening with lower demand during the day, while wind power generation is highest during the night and midday.
2) Common theories for predicting vertical axis wind turbine performance include single stream tube, multiple stream tube, and fixed wake models.
3) Developing contributions to wind energy requires expertise in many disciplines including fluid dynamics, materials science, engineering, programming, and business/policy areas.
Renewable energy course#02
This document discusses vertical axis wind turbine (VAWT) performance prediction theories and a single stream tube model for VAWTs. It presents the angle of attack equation for the single stream tube model assuming zero tilt angle. It also provides the iterative equation used to determine the induction factor and the power equation that is integrated over a full rotation to predict average power. The document indicates that understanding and integrating various engineering disciplines is required to make meaningful contributions to wind turbine research and development.
Multirate dtsp
This document provides an overview of multirate digital signal processing using filter banks and subband processing. It describes:
1) How signals are split into multiple frequency bands or subbands using an analysis filter bank and then downsampled.
2) Individual subband processing such as coding/compression can then be applied.
3) The subbands are then reconstructed using upsampling and a synthesis filter bank to combine the signals back into the original sampling rate.
4) Perfect reconstruction filter banks can be designed to remove aliasing introduced during downsampling to accurately reconstruct the original signal up to a delay.
Efficient Implementation of Self-Organizing Map for Sparse Input Data
This document describes improvements made to the self-organizing map (SOM) algorithm to make it more efficient for sparse, high-dimensional input data. The key contributions are a sparse SOM (Sparse-Som) and sparse batch SOM (Sparse-BSom) algorithm that exploit the sparseness of the data to reduce computational complexity from O(TMD) to O(TMd), where d is the number of non-zero dimensions. Sparse-Som speeds up the BMU search and weight update phases, while Sparse-BSom further allows for efficient parallelization. Experiments show Sparse-Som and Sparse-BSom train significantly faster than standard SOM on sparse datasets, with comparable or better quality
More Related Content
What's hot
report_2_v2
The document analyzes the aerodynamic characteristics of the FX 63-137 airfoil using XFOIL software. XFOIL was used to generate lift and drag curves across a range of angles of attack and calculate coefficients like lift curve slope, maximum lift, and minimum drag. These results were then compared to wind tunnel data from the Stuttgarter Profilkatalog, finding some differences, especially at high angles of attack. The document includes figures of the results and tables comparing the XFOIL and experimental values.
HMPC for Upper Stage Attitude Control
This document describes a hybrid model predictive control approach for attitude control of spacecraft using impulsive thrusters. The approach models the spacecraft dynamics and minimum impulse effects of the thrusters. It formulates the control problem as minimizing a cost function over future inputs while satisfying the hybrid dynamics and constraints, such as a limit on total thruster actuations. Simulations show the hybrid MPC achieves higher pointing accuracy, lower thruster usage, and better disturbance rejection compared to traditional PD and LQR controllers.
Devansh
This document summarizes research on general profit scheduling on parallel processors. It discusses how profit functions can be parameterized to incorporate various metrics like weighted flow time. It presents solutions for special profit functions using dynamic programming formulations. The solutions are extended to handle multiple machines using a similar DP approach. Generalizations like jobs having different processing times on different machines and non-zero release times are also discussed. Reductions from general scheduling problems to geometric set cover problems are explained. Further work directions on improving approximations for these problems are mentioned.
射頻電子實驗手冊 [實驗6] 阻抗匹配模擬
This document discusses using the Smith Chart tool in ADS (Advanced Design System) for impedance matching circuits at different frequency ranges. It covers defining the source and load impedances on the Smith Chart, using the Z-Chart and Y-Chart variations, examining the Q factor on the Smith Chart, and designing basic matching networks like L-sections and T-sections directly on the Smith Chart in ADS.
ALPSチュートリアル
1. ALPS (Applications and Libraries for Physics Simulations) is an open source software project that provides a framework for large-scale simulations of quantum many-body systems using quantum Monte Carlo and other numerical techniques.
2. It contains libraries and applications for lattice models, quantum lattice models, and other physics simulations. Models can be defined through XML files and simulations run using the simplemc program.
3. Results such as magnetization and specific heat are output in XML format and can be analyzed using the Python analysis module or visualized using ParaView.
2019 CtD: A hybrid deep learning approach to vertexing
This document presents a hybrid deep learning approach for vertex finding using 1D convolutional neural networks. It describes generating 1D kernel densities from tracking information, building target distributions, and using a CNN architecture with an adjustable cost function to optimize the false positive rate versus efficiency. The approach achieves 93.87% efficiency with a 0.251 false positive rate on test data. Future work includes incorporating additional xy information and exploring full 2D kernel densities.
HOW 2019: Machine Learning for the Primary Vertex Reconstruction
The document describes a machine learning approach for primary vertex reconstruction in high-energy physics experiments. A hybrid method is proposed that uses a 1D convolutional neural network to analyze histograms produced from tracking data. The network is able to find primary vertices with high efficiency and tunable false positive rates, demonstrating the potential of machine learning for this task. Future work involves adding more tracking information and iterating between track association and vertex finding to improve performance.
2019 IML workshop: A hybrid deep learning approach to vertexing
A hybrid deep learning approach is proposed for vertex finding using 1D convolutional neural networks on kernel density estimates from tracking data. The approach generates 1D histograms from 3D tracking data and uses a CNN to classify primary vertex positions. In a proof-of-concept on simulated data, it achieves primary vertex finding efficiencies and false positive rates comparable to traditional algorithms, with tunable efficiency-false positive tradeoffs. Future work includes incorporating additional tracking features, associating tracks to vertices, and deploying the inference engine for the LHCb trigger.
QR Factorizations and SVDs for Tall-and-skinny Matrices in MapReduce Architec...
This document summarizes Austin Benson's presentation on QR factorizations and SVDs for tall-and-skinny matrices in MapReduce architectures. It discusses how communication-avoiding TSQR and indirect/direct TSQR algorithms can be implemented in MapReduce frameworks to compute QR factorizations and SVDs of large matrices in a distributed, parallel manner. It also compares the performance of different MapReduce algorithms for computing QR on various sized matrices.
ACAT 2019: A hybrid deep learning approach to vertexing
This document presents a hybrid deep learning approach for vertex finding in high-energy physics experiments. It uses a 1D convolutional neural network to analyze kernel density estimates of track information in order to identify primary vertex positions. The approach achieves primary vertex finding efficiencies of 88-94% with low false positive rates comparable to traditional algorithms. The authors demonstrate tuning of the efficiency-false positive rate tradeoff and discuss plans to improve performance by incorporating additional track information and iterative refinement.
Ejerciciooo3
This document analyzes the linear regression between hours worked (x) and units produced (y) at a workshop. It provides the correlation coefficient (0.953994158), scatter plot of the data, and calculations to determine the regression line equation and test for significance of the linear relationship. The t-statistic calculated (10.06071375) is greater than the critical value (2.228), indicating there is a statistically significant linear relationship between hours worked and units produced.
射頻電子 - [第六章] 低雜訊放大器設計
This document discusses the design of low-noise amplifiers. It begins with an overview of the basic structure of transmitters and receivers in wireless communication systems. It then reviews the relationships between power and gain and introduces the concept of the available power gain circle. The document discusses a design method for amplifiers that does not require simultaneous conjugate matching of both ports. It also covers noise theory for two-port networks and the fixed noise figure circle. The key points are utilizing available power gain circles and fixed noise figure circles to design amplifiers through tradeoffs between gain and noise on the Smith chart.
Presupuesto del ordenador (1)
This document contains a list of items and their quantities, descriptions, unit prices, and total prices. It includes computer components like a case, motherboard, graphics card, and accessories such as a webcam, mouse, keyboard, and printer. The total price of all items is over 2,300 euros.
Distributed solution of stochastic optimal control problem on GPUs
Stochastic optimal control problems arise in many
applications and are, in principle,
large-scale involving up to millions of decision variables. Their
applicability in control applications is often limited by the
availability of algorithms that can solve them efficiently and within
the sampling time of the controlled system.
In this paper we propose a dual accelerated proximal
gradient algorithm which is amenable to parallelization and
demonstrate that its GPU implementation affords high speed-up
values (with respect to a CPU implementation) and greatly outperforms
well-established commercial optimizers such as Gurobi.
library(tidyr) and library(ggplot2)
The document loads libraries and plots data from the mtcars dataset. It uses gather() to reshape the data and plot mpg vs other variables like hp, cyl, and wt, facetted by each variable. It then plots mpg vs each variable with stat_smooth() added.
Math cad fourier analysis (jcb-edited)
This document discusses Fourier analysis and the Fourier transform. It illustrates generating a signal as the superposition of three harmonic components and plotting the individual time histories. The components are summed to form a more complex signal. The signal is then converted to a digital format and the fast Fourier transform is calculated. Plotting the signal in the frequency domain makes the three harmonic components easier to identify compared to the original time domain signal with added noise.
Bellman ford Algorithm
The document describes the Bellman-Ford algorithm for finding the shortest paths in a graph. It begins by defining the shortest path problem and describing applications that can be modeled as shortest path problems, such as network routing. It then explains that Bellman-Ford can find single-source shortest paths in graphs with positive or negative edge weights, unlike Dijkstra's algorithm which only works for positive edges. The core of the algorithm uses relaxation to iteratively update the shortest path estimates over multiple rounds until convergence. Pseudocode is provided to demonstrate how the relaxation process is repeated for all edges |V|-1 times to find a shortest path from the source node to all other nodes.
polar-cap-power
This document summarizes how ultra-low frequency (ULF) hydromagnetic power is typically characterized in the deep polar cap. It presents median power values as a function of frequency band, magnetic field direction, location, and local time using data from multiple polar cap stations including AGO5, AGO6, SPA, and MCM. Graphs of median-relative spectra are shown for AGO5 at 87°S CGMLat to illustrate the visualization techniques.
Renewable energy course#02 gen
This document provides information about power patterns in Colorado during winter, wind turbine performance prediction theories, and the fields required to contribute to wind energy technology. It summarizes:
1) A typical winter day in Colorado sees power demand peak in the morning and evening with lower demand during the day, while wind power generation is highest during the night and midday.
2) Common theories for predicting vertical axis wind turbine performance include single stream tube, multiple stream tube, and fixed wake models.
3) Developing contributions to wind energy requires expertise in many disciplines including fluid dynamics, materials science, engineering, programming, and business/policy areas.
Renewable energy course#02
This document discusses vertical axis wind turbine (VAWT) performance prediction theories and a single stream tube model for VAWTs. It presents the angle of attack equation for the single stream tube model assuming zero tilt angle. It also provides the iterative equation used to determine the induction factor and the power equation that is integrated over a full rotation to predict average power. The document indicates that understanding and integrating various engineering disciplines is required to make meaningful contributions to wind turbine research and development.
What's hot (20)
2019 CtD: A hybrid deep learning approach to vertexing
2019 CtD: A hybrid deep learning approach to vertexing
HOW 2019: Machine Learning for the Primary Vertex Reconstruction
HOW 2019: Machine Learning for the Primary Vertex Reconstruction
2019 IML workshop: A hybrid deep learning approach to vertexing
2019 IML workshop: A hybrid deep learning approach to vertexing
QR Factorizations and SVDs for Tall-and-skinny Matrices in MapReduce Architec...
QR Factorizations and SVDs for Tall-and-skinny Matrices in MapReduce Architec...
ACAT 2019: A hybrid deep learning approach to vertexing
ACAT 2019: A hybrid deep learning approach to vertexing
Distributed solution of stochastic optimal control problem on GPUs
Distributed solution of stochastic optimal control problem on GPUs
Similar to Esmaeilzade sampling
Multirate dtsp
This document provides an overview of multirate digital signal processing using filter banks and subband processing. It describes:
1) How signals are split into multiple frequency bands or subbands using an analysis filter bank and then downsampled.
2) Individual subband processing such as coding/compression can then be applied.
3) The subbands are then reconstructed using upsampling and a synthesis filter bank to combine the signals back into the original sampling rate.
4) Perfect reconstruction filter banks can be designed to remove aliasing introduced during downsampling to accurately reconstruct the original signal up to a delay.
Efficient Implementation of Self-Organizing Map for Sparse Input Data
This document describes improvements made to the self-organizing map (SOM) algorithm to make it more efficient for sparse, high-dimensional input data. The key contributions are a sparse SOM (Sparse-Som) and sparse batch SOM (Sparse-BSom) algorithm that exploit the sparseness of the data to reduce computational complexity from O(TMD) to O(TMd), where d is the number of non-zero dimensions. Sparse-Som speeds up the BMU search and weight update phases, while Sparse-BSom further allows for efficient parallelization. Experiments show Sparse-Som and Sparse-BSom train significantly faster than standard SOM on sparse datasets, with comparable or better quality
Compressed learning for time series classification
This document proposes a compressed learning framework for time series classification using sparse envelope representations. It introduces compressed sensing concepts and describes creating a sparse envelope for time series by thresholding around the mean and standard deviation. A classification framework is developed using linear SVMs in the compressed domain. Experimental results on benchmark datasets demonstrate effectiveness of the envelope representations compared to state-of-the-art methods, as well as efficiency gains from compression. Real-world case studies on smart home applications show promising identification performance from envelope-based classifiers on sensor time series data.
GTC Taiwan 2017 GPU 平台上導入深度學習於半導體產業之 EDA 應用
A deep learning model using convolutional neural networks is proposed for lithography hotspot detection. The model takes layout clip images as input and outputs a prediction of hotspot or non-hotspot. It uses several convolutional and pooling layers to automatically learn features from the images without manual feature engineering. Evaluation shows the deep learning model achieves higher accuracy than previous shallow learning methods that rely on manually designed features.
Complex models in ecology: challenges and solutions
This document discusses complex models in ecology and solutions for Bayesian analysis of complex hierarchical models. It introduces data cloning as a method that allows using Bayesian Markov chain Monte Carlo tools for frequentist inference on complex models. Data cloning replicates the data to increase the effective sample size, improving mixing and reducing the need for long runs. The document also discusses using high-performance computing to parallelize MCMC for faster inference on complex models through techniques like distributing chains across nodes.
Tdm fdm
Frequency division multiplexing (FDM) divides the available bandwidth into non-overlapping frequency bands, with each band carrying a separate signal. Time division multiplexing (TDM) divides signals into different time slots to share the same frequency channel. TDM samples voice frequency signals at 8 kHz and quantizes each sample to 8 bits, requiring 64 kbps per voice channel. A 32-channel PCM system using TDM requires 2 Mbps of bandwidth and can carry more voice channels than FDM with the same bandwidth.
sequencea.ppt
Sequence data mining techniques can be used to analyze ordered sets of elements where the order is important. Some key techniques include classifying entire sequences, clustering sequences based on similarity, and finding repeated patterns. These techniques require adapting traditional mining methods to handle variable sequence lengths and order. Specific sequence mining tasks include partial sequence classification, sequence segmentation, and predicting the next element of a sequence. These techniques have applications in domains like intrusion detection, computational biology, and customer behavior analysis.
Histograms in 12c era
Oracle database 12c introduced several improvements on histograms, this session focuses on what's changed and how those changes address past concerns
Dsp&a
Digital signal processing involves sampling an analog signal, converting it to digital form using quantization and encoding, and then processing the digital signal using a digital signal processor chip. A digital signal processor chip contains a processor, memory, and functional units optimized for common signal processing tasks like convolution. It uses techniques like pipelining to process instructions in parallel and improve performance for tasks like filtering signals.
Convolution Neural Network Lecture Slides
This document provides an overview of convolutional neural networks (CNNs) for image and video recognition. It discusses that CNNs have greatly improved image classification accuracy on ImageNet over the years. CNNs consist of convolutional layers that apply filters to extract features, pooling layers that reduce the spatial size, and fully connected layers for classification. Training involves tuning parameters through backpropagation, while inference uses a trained model for classification. Example networks discussed include AlexNet, VGG16, GoogLeNet and ResNet, which contain increasing numbers of parameters and computational operations.
Hy 523
The document describes a system with 4 CPUs that can communicate with each other and access shared memory in parallel. Each CPU has its own instruction memory and can access any of the shared data memories through an interconnection system. A USB interface allows one of the CPUs to input and output video and audio files from an external device for decoding. The system is designed to maximize parallelism and efficiency while minimizing power consumption.
Presentació renovables
This document discusses systems for monitoring and controlling renewable energy plants. It covers various architectures for wind turbine and solar plant monitoring including control systems, communications networks, and data standards. Concepts around the IEC 61400-25 standard are explained for modeling wind turbine data. Various signal processing techniques are presented for fault detection in generators and gearboxes including relevant fault frequencies. Condition monitoring technologies are outlined along with classification algorithms like SVM. Finally, an integrated smart operations management platform called SmartOpex is introduced.
presentazione
This document summarizes the results of a study on classifying tables in HTML documents as genuine or non-genuine tables. It describes the dataset, features considered for the classification including layout, content type and word group features. It discusses various machine learning models tested - SVM, Decision Tree, Random Forest, Adaboost and Neural Networks. It provides the optimal parameters determined for each model and compares their performance on the table classification task based on accuracy, F1 score and confusion matrices.
Neural network
This document provides an overview of neural networks and related topics. It begins with an introduction to neural networks and discusses natural neural networks, early artificial neural networks, modeling neurons, and network design. It then covers multi-layer neural networks, perceptron networks, training, and advantages of neural networks. Additional topics include fuzzy logic, genetic algorithms, clustering, and adaptive neuro-fuzzy inference systems (ANFIS).
presentation-final
The document describes a project using one-class support vector machines to detect inflight engine shutdown abnormalities. The team analyzed flight data containing 200 variables from 35,000 flights provided by NASA, selecting 14 variables. They tested a two-class SVM approach but found it did not perform well with abundant normal data. Therefore, they used a one-class SVM for novelty detection, which trains only on normal data. Their best model used a Laplace kernel, 800 normal training samples, and hyperparameters tuned for high accuracy on both normal and abnormal test flights.
Time Series Analysis and Mining with R
This document discusses time series analysis techniques in R, including decomposition, forecasting, clustering, and classification. It provides examples of decomposing the AirPassengers dataset, forecasting with ARIMA models, hierarchical clustering on synthetic control chart data using Euclidean and DTW distances, and classifying the control chart data using decision trees with DWT features. Accuracy of over 88% was achieved on the classification task.
02-11-2005.ppt
This document provides an overview of echo state networks (ESNs), a training method for recurrent neural networks. It begins with a primer on recurrent neural networks and their properties. It then introduces ESNs, explaining that they exploit the dynamics of a fixed "reservoir" network to model temporal patterns while only training the output weights. The rest of the document provides examples of using ESNs, including generating tones, implementing delays, and identifying nonlinear systems. It explains how ESNs can be trained offline using linear regression to minimize error between the network's outputs and training targets.
IARE_DSP_PPT.pptx
This document provides an introduction to digital signal processing. It discusses how signals can be represented digitally by sampling analog signals and converting them to sequences of numbers. This allows signals to be processed using digital processors. Some key benefits of digital signal processing include accuracy, repeatability, flexibility, and easy implementation of nonlinear and time-varying operations in software. The document covers topics such as sampling, analog-to-digital conversion, reconstruction, discrete-time signals and systems, linearity, time-invariance, and examples of basic sequences like sinusoidal, exponential, and geometric sequences.
CIFAR-10 for DAWNBench: Wide ResNets, Mixup Augmentation and "Super Convergen...
Summary of models and methods used for DAWNBench CIFAR-10 Challenge. Starting with an review of ResNets from high level architecture, we review Basic vs Bottleneck blocks, pre-activation blocks and Wide Resets. After a brief mention of PyramidNet, ResNext and DenseNet models, we look at regularization techniques such as Mixup. And we finish with a review of Cyclical Learning Rates, and the phenomenon of "Super Convergence".
MXNet Gluon API was used for the implementations.
Similar to Esmaeilzade sampling (20)
Efficient Implementation of Self-Organizing Map for Sparse Input Data
Efficient Implementation of Self-Organizing Map for Sparse Input Data
Compressed learning for time series classification
Compressed learning for time series classification
Complex models in ecology: challenges and solutions
Complex models in ecology: challenges and solutions
CIFAR-10 for DAWNBench: Wide ResNets, Mixup Augmentation and "Super Convergen...
CIFAR-10 for DAWNBench: Wide ResNets, Mixup Augmentation and "Super Convergen...
Recently uploaded
STUDY ON THE DEVELOPMENT STRATEGY OF HUZHOU TOURISM
ABSTRACT: Huzhou has rich tourism resources, as early as a considerable development since the reform and
opening up, especially in recent years, Huzhou tourism has ushered in a new period of development
opportunities. At present, Huzhou tourism has become one of the most characteristic tourist cities on the East
China tourism line. With the development of Huzhou City, the tourism industry has been further improved, and
the tourism degree of the whole city has further increased the transformation and upgrading of the tourism
industry. However, the development of tourism in Huzhou City still lags far behind the tourism development of
major cities in East China. This round of research mainly analyzes the current development of tourism in
Huzhou City, on the basis of analyzing the specific situation, pointed out that the current development of
Huzhou tourism problems, and then analyzes these problems one by one, and put forward some specific
solutions, so as to promote the further rapid development of tourism in Huzhou City.
KEYWORDS:Huzhou; Travel; Development
HMS Facebook Stories All V1 06092024.docx
The conversations on Facebook from the Herringswell Manor School group from 2009 to the first half of 2024
LORRAINE ANDREI_LEQUIGAN_HOW TO USE TELEGRAM
Telegram is a messaging platform that ushers in a new era of communication. Available for Android, Windows, Mac, and Linux, Telegram offers simplicity, privacy, synchronization across devices, speed, and powerful features. It allows users to create their own stickers with a user-friendly editor. With robust encryption, Telegram ensures message security and even offers self-destructing messages. The platform is open, with an API and source code accessible to everyone, making it a secure and social environment where groups can accommodate up to 200,000 members. Customize your messenger experience with Telegram's expressive features.
Maximize Your Twitch Potential!..........
Sign up now and start your journey to Twitch stardom!
https://www.sociocosmos.com/product-category/twitch/
EASY TUTORIAL OF HOW TO USE G-TEAMS BY: FEBLESS HERNANE
Using Google Teams (G-Teams) is simple. Start by opening the Google Teams app on your phone or visiting the G-Teams website on your computer. Sign in with your Google account. To join a meeting, click on the link shared by the organizer or enter the meeting code in the "Join a Meeting" section. To start a meeting, click on "New Meeting" and share the link with others. You can use the chat feature to send messages and the video button to turn your camera on or off. G-Teams makes it easy to connect and collaborate with others!
HOW TO USE FACEBOOK _ by Clarissa Credito
This tutorial presentation provides a step-by-step guide on how to use Facebook, the popular social media platform. In simple and easy-to-understand language, this presentation explains how to create a Facebook account, connect with friends and family, post updates, share photos and videos, join groups, and manage privacy settings. Whether you're new to Facebook or just need a refresher, this presentation will help you navigate the features and make the most of your Facebook experience.
UR BHATTI ACADEMY AND ONLINE COURSES.pdf
UR BHatti Academy dedicated to providing the finest IT courses training in the world. Under the guidance of experienced trainer Usman Rasheed Bhatti, we have established ourselves as a professional online training firm offering unparalleled courses in Pakistan. Our academy is a trailblazer in Dijkot, being the first institute to officially provide training to all students at their preferred schedules, led by real-world industry professionals and Google certified staff.
Your LinkedIn Success Starts Here.......
In order to make a lasting impression on your sector, SocioCosmos provides customized solutions to improve your LinkedIn profile.
https://www.sociocosmos.com/product-category/linkedin/
快速办理(BCR毕业证书)加州大学河滨分校毕业证文凭证书一模一样
学校原件一模一样【微信：741003700 】《(BCR毕业证书)加州大学河滨分校毕业证文凭证书》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
快速办理(worcester毕业证书)伍斯特大学毕业证PDF成绩单一模一样
学校原件一模一样【微信：741003700 】《(worcester毕业证书)伍斯特大学毕业证PDF成绩单》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
原版制作(Hull毕业证书)赫尔大学毕业证Offer一模一样
学校原件一模一样【微信：741003700 】《(Hull毕业证书)赫尔大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Dominate Reddit Discussions.............
Dominate Reddit Discussions: Become a top Reddit influencer with our proven methods. Learn More.
https://www.sociocosmos.com/product-category/reddit/
Recently uploaded (13)
STUDY ON THE DEVELOPMENT STRATEGY OF HUZHOU TOURISM
STUDY ON THE DEVELOPMENT STRATEGY OF HUZHOU TOURISM
EASY TUTORIAL OF HOW TO USE G-TEAMS BY: FEBLESS HERNANE
EASY TUTORIAL OF HOW TO USE G-TEAMS BY: FEBLESS HERNANE
Transportation_Channel_Investor_Presentation_April_2024_ Final .pdf
Transportation_Channel_Investor_Presentation_April_2024_ Final .pdf
Esmaeilzade sampling
- 5.
- 7. -Simple Random Sampling -(convenience ) -Stratified sampling) -(Cluster sampling ) -(Systematic sampling) -(quota )
- 8. Simple Random Sampling) (Systematic sampling) Stratified sampling) (Cluster sampling )
- 9.
- 12.
- 14. (Systematic)
- 15.
- 16.
- 19. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 31 34 35 36 37 38 39 40 41 42 43 44 45 16 17 18 19 20 21 22 23 24 25 26 27 28 46 47 48 49 50 51 52 53 54 55 ……..
- 21. - - - -
- 22.
- 23.
- 25. • • •
- 26. cluster sampling
- 27. - - - -
- 29. Example of cluster sampling Section 4 Section 5 Section 3 Section 2Section 1 Sampling techniques
- 31.
- 32.
- 33.
- 36.
- 38.
- 40. - - - -
- 41. power
- 43. ( ) ( ) max mini ix x2 6 /s 2 5 1 0 667 6
- 44. -N -N -N -N
- 46. ( / ) ( ) /n 2 2 2 1 96 40 245 9 246 5
- 47. N ( ) ( ) ( ) N z n N d z 2 2 1 2 2 2 2 1 2 1 ( / ) ( / ) ( / ) ( / ) ( / ) n 2 2 2 2 2 240 1 96 1 2 90 239 0 03 1 96 1 2
- 48. N ( )z pq n d 2 1 2 2 pp p q1 /p 0 5 p
- 49. ( / ) ( / )( / ) ( / ) n 2 2 1 96 0 21 0 79 256 0 05
- 50. N ( ) ( ) ( ) N z pq n N d z pq 2 1 2 2 2 1 2 1 ( / ) ( / ) ( / ) ( / ) ( / ) n 2 2 2 2 2 150 1 96 0 5 97 149 0 06 1 96 0 5 p
- 51. 51 S N P dd= ( ) N pq S N d 2 2 2 1 2
- 52. -
- 53.