Spiking Neural Networks
Advantages and limitations
SNNs are formed by neuron models that communicate by sequences of spikes.
They offer plausible models of neuronal mechanisms and neuron behaviors.
They are powerful tools for analysis and understanding of elementary processes in the brain.
Computationally more powerful than perceptrons and sigmoidal gates.
However, they do not produce abstract , clearly decomposable , and interpretable representations of a problem .
Deep neural networks
Desiderata for Learning AI
Ability to learn, complex, highly-varying functions.
Ability to learn with little human input low-level, intermediate, and high-level representations.
Ability to learn from a very large set of examples.
Ability to learn from mostly unlabeled data.
Ability to exploit the synergies present across a large number of tasks, i.e. multi-task learning.
In the limit of a large number of tasks and when future tasks are not known ahead of time, strong unsupervised learning (i.e. capturing the statistical structure in the observed data) is an important element of the solution.
Y. Bengio. Learning deep architectures for AI. Foundations and trends in Machine Learning. 2.1. Pp. 1-127. 2009.
There are a number of classes of DNNs. These are among the best known.
Deep Neural Networks
Goals
Automatically discover problem representations of different complexity from the lowest level features to highest level concepts.
Being able to scale to very large problems.
Provide interpretable representations of the problem.
Allow multi-task solving by re-using modular components of the network.
Be robust to different transformations of the original training data.
Characteristics
Are composed of multiple processing layers to learn representations of data with multiple levels of abstraction.
Once the architecture has been defined, they require very little engineering by hand .
Exploit the property that many natural signals are compositional hierarchies , in which higher-level features are obtained by composing lower-level ones.
Good features can be learned automatically using a general-purpose learning procedure.
They heavily depend on local optimization methods to tune their parameters.
Deep Neural Networks
Shallow and Deep Neural Networks
R. Salakhutdinov. Learning deep generative models. Annual Review of Statistics and Its Application. Vol. 2. Pp. 361-385. 2015.
Deep Neural Networks
Components
Structure: Characterized by a combination of:
Activation functions.
Layers.
Loss functions.
Activation functions : Using a combination of the inputs, determines whether the neuron is activated (fired).
Sigmoid
tahn
ReLU, ELU, Leaky ELU, etc.
Layers : Determine how the neurons are organized. Fully connected, recurrent, dropouts, convolutional and pooling.
Loss functions : Establishes the criterion to evaluate the quality of NN model. Mean square error, cross-entropy loss, etc.
Activation Functions
Sigmoid linear unit
One of the most widely used activation functions today.
\( f(x) = \frac{1}{1+e^{-x}} \)
It is nonlinear in nature.
The output of the activation function is always going to be in range \((0,1) \).
It has the problem of the vanishing gradients .
Activation Functions
tanh
\( f(x) = \frac{2}{1-e^{-2x}} \)
It is similar to the sigmoid function.
Squashes numbers to range [-1,1].
It is zero centered.
It destroys information about the gradient when it is saturated.
The gradient is stronger for tanh than sigmoid (derivatives are steeper).
Activation Functions
Rectifier linear unit (ReLU)
\(f(x) = max(0,x) \)
More biologically plausible.
It is nonlinear in nature.
Converges much faster than other functions, e.g., sigmoid and tanh.
Computationally efficient
The gradient can get toward zero.
Deep Neural Networks
Deep network architecture
Composed of multiple levels of non-linear operations
As a model they integrate the steps of feature selection and feature understanding.
Can learn decomposable representations of complex patterns into simpler patterns.
They are organized as hierarchical features, from simpler patterns in the initial layers to more complex patterns in subsequent layers.
Shallow neural networks
A shallow network has less number of hidden layers.
The number of parameters required to fit a function should be in general higher.
They are usually very homogeneous in terms of the activation functions they use.
R. Salakhutdinov. Learning deep generative models. Annual Review of Statistics and Its Application. Vol. 2. Pp. 361-385. 2015.
Deep neural networks
More applications
Predicting the activity of potential drug molecules.
Analyzing particle accerator data.
Reconstructing brain circuits.
Predicting the effects of mutations in non-coding DNA on gene expression and disease.
DNNs applications
Object detection, speech recognition, and machine translation.
Generate artistic images with different styles.
Clustering patterns of gene expressions .
Sentiment analysis fusioning different modalities.
H. Wang, B. Raj, and E. P. Xing. On the Origin of Deep Learning. arXiv preprint arXiv:1702.07800. 2017.
Y. LeCun, Y. Bengio, and G. Hinton. Deep learning. Nature 521.7553 (2015): 436-444. 2015.
The application of deep neural networks are multiple.
These are only some few examples.
Deep neural networks
Types of DNNs
Deep Belief Nets (DBNs).
Deep Boltzmann Machines (DBMs).
AutoEncoders (AEs).
Convolutional Neural Networks (CNN).
Recurrent Neural Networks (RNNs) and LSTM.
Generative Adversarial Networks (GAN).
f
H. Wang, B. Raj, and E. P. Xing.On the Origin of Deep Learning. arXiv preprint arXiv:1702.07800. 2017.
There are a number of classes of DNNs. These are among the best known.
Boltzmann machines
Boltzmann Machine probabilities
x=(v,h) \(E(x)\) \(e^{-E(x)}\) \(p(x)\)
000 0 1 1/95
001 -log(2) 2 2/95
010 -log(2) 2 2/95
011 -3log(2) 8 8/95
100 -log(2) 2 2/95
101 -3log(2) 8 8/95
110 -3log(2) 8 8/95
111 -6log(2) 64 64/95
\(\sum\) 95 1.0
Exercise
Compute marginal probabilities \(p(x_1)\) and \(p(x_1,x_2)\)
Compute conditional probabilities \(p(x_1|x_2)\) and \(p(x_3|x_2)\)
Compute factorizations \(q(x) = \prod_i p(x_i) \) and \(r(x) = p(x_1) p(x_2,x_3)\)
Energy function
\[
\begin{align}
E(v,h) &=& -\sum_i v_ib_i -\sum_k h_k d_k -\sum_{i,j} v_iv_jw_{i,j} \\
&=& -\sum_{i,k} v_ih_k w_{i,k} -\sum_{k,l} h_kh_lw_{k,l}
\end{align}
\]
Weight matrix
\[
W = \begin{pmatrix}
0& log(2) & log(2)\\
log(2)& 0& log(2)\\
log(2)& log(2)& 0\\
\end{pmatrix}
\]
Assumptions
\(b_i,h_i=log(2) \; \forall i \)
\(W_{i,j}=log(2) \; \forall i,j \)
Boltzmann machines
Boltzmann Machine probabilities
x=(v,h) \(E(x)\) \(e^{-E(x)}\) \(p(x)\)
000 0 1 1/95
001 -log(2) 2 2/95
010 -log(2) 2 2/95
011 -3log(2) 8 8/95
100 -log(2) 2 2/95
101 -3log(2) 8 8/95
110 -3log(2) 8 8/95
111 -6log(2) 64 64/95
\(\sum\) 95 1.0
Exercise
Compute marginal probabilities \(p(x_1)\) and \(p(x_1,x_2)\)
Compute conditional probabilities \(p(x_1|x_2)\) and \(p(x_3|x_2)\)
Compute factorizations \(q(x) = \prod_i p(x_i) \) and \(r(x) = p(x_1) p(x_2,x_3)\)
Univariate Marginal probabilities
\[
\begin{align}
p(x_i) &= \sum_{x'|x'_i=x_i} p(x') \\
p(x_1=0) &= p(000) + p(001) + p(010) + p(011) \\
&= 1/95 + 2/95 + 2/95 + 8/95 \\
&= 13/95 \\
p(x_1=1) &= p(100) + p(101) + p(110) + p(111) \\
&= 2/95 + 8/95 + 8/95 + 64/95 \\
&= 82/95
\end{align}
\]
Bivariate Marginal probabilities
\[
\begin{align}
p(x_i,x_j) &= \sum_{x'|x'_i=xi,x'_j=x_j} p(x') \\
p(x_1,x_2=00) &= p(000) + p(001) = 3/95 \\
p(x_1,x_2=01) &= p(010) + p(011) = 10/95 \\
p(x_1,x_2=10) &= p(100) + p(101) = 10/95 \\
p(x_1,x_2=11) &= p(110) + p(111) = 72/95
\end{align}
\]
Boltzmann machines
Boltzmann Machine probabilities
x=(v,h) \(E(x)\) \(e^{-E(x)}\) \(p(x)\)
000 0 1 1/95
001 -log(2) 2 2/95
010 -log(2) 2 2/95
011 -3log(2) 8 8/95
100 -log(2) 2 2/95
101 -3log(2) 8 8/95
110 -3log(2) 8 8/95
111 -6log(2) 64 64/95
\(\sum\) 95 1.0
Exercise
Compute marginal probabilities \(p(x_1)\) and \(p(x_1,x_2)\)
Compute conditional probabilities \(p(x_1|x_2)\)
Compute factorizations \(q(x) = \prod_i p(x_i) \) and \(r(x) = p(x_1) p(x_2,x_3)\)
Conditional probabilities
\[
\begin{align}
p(x_i|x_j) &= \frac{p(x_i,x_j)}{p(x_j)} \\
p(x_1|x_2) &= \frac{p(x_1,x_2)}{p(x_2)} \\
p(x_1=0|x_2=0) &= \frac{p(x_1=0,x_2=0)}{p(x_2)=0} = \frac{3/95}{13/95} = 3/13 \\
p(x_1=1|x_2=0) &= \frac{p(x_1=1,x_2=0)}{p(x_2)=0} = \frac{10/95}{13/95} = 10/13 \\
p(x_1=0|x_2=1) &= \frac{p(x_1=0,x_2=1)}{p(x_2)=1} = \frac{10/95}{82/95} = 10/82 \\
p(x_1=1|x_2=1) &= \frac{p(x_1=1,x_2=1)}{p(x_2)=1} = \frac{10/95}{22/95} = 72/82 \\
\end{align}
\]
Boltzmann machines
Boltzmann Machine probabilities
x=(v,h) \(E(x)\) \(e^{-E(x)}\) \(p(x)\)
000 0 1 1/95
001 -log(2) 2 2/95
010 -log(2) 2 2/95
011 -3log(2) 8 8/95
100 -log(2) 2 2/95
101 -3log(2) 8 8/95
110 -3log(2) 8 8/95
111 -6log(2) 64 64/95
\(\sum\) 95 1.0
Exercise
Compute marginal probabilities \(p(x_1)\) and \(p(x_1,x_2)\)
Compute conditional probabilities \(p(x_1|x_2)\)
Compute factorizations \(q(x) = \prod_i p(x_i) \) and \(r(x) = p(x_1) p(x_2,x_3)\)
Factorizations
x=(v,h) \(p(x)\) \(\prod_i p(x_i) \) \(p(x_1)p(x_2,x_3)\)
000 1/95 (13/95)*(13/95)*(13/95) (13/95)(3/95)
001 2/95 (13/95)*(13/95)*(82/95) (13/95)(10/95)
010 2/95 (13/95)*(82/95)*(13/95) (13/95)(10/95)
011 8/95 (13/95)*(82/95)*(82/95) (13/95)(72/95)
100 2/95 (82/95)*(13/95)*(13/95) (82/95)(3/95)
101 8/95 (82/95)*(13/95)*(82/95) (82/95)(10/95)
110 8/95 (82/95)*(82/95)*(13/95) (82/95)(10/95)
111 64/95 (82/95)*(82/95)*(82/95) (82/95)(72/95)
\(\sum\) 1.0 1.0 1.0


CV19Locator API
For Developers
The CV19Locator API obtains case data from the GitHub of the Johns Hopkins University Center for Systems Science and Engineering.
This public API allows developers to avoid the hassle of having to parse through .csv files and come up with arduous implementations to sort through case data by location.
Postman documentation will be available soon!
Current available endpoints (copy-paste these URLs into your browser or Postman):
http://cv19location.com/API/series/global/confirmed
Obtains time series global data on confirmed cases.
http://cv19location.com/API/series/global/deaths
Obtains time series global data on fatal cases.
http://cv19location.com/API/series/global/recovered
Obtains time series global data on recovered cases.
http://cv19location.com/API/series/US/confirmed
Obtains time series US data on confirmed cases.
http://cv19location.com/API/series/US/deaths
Obtains time series US data on fatal cases.
http://cv19location.com/API/uifcountries
Obtains country codes and population data on countries/provinces/counties.
(This page is a work in progress.)


Preparation time
over 2 hours
Cooking time
30 mins to 1 hour
Serves
Makes 3
Dietary
Paul Hollywood shares his secrets for the perfect pizza – here with a tasty topping of fig, prosciutto and gorgonzola.
For the pizza dough, mix the flour, salt, olive oil, yeast and water together in a bowl.
Turn the dough out onto an oiled work surface and knead for 5-10 minutes, or until the dough is smooth and elastic. Cut off a small piece of the dough and stretch part of it as thinly as you can. If you can see the shadow of your fingers through the dough - the light should shine through the dough like a window pane - without the dough tearing, it is ready to prove.
Shape the dough into a ball and tip into a bowl.
Cover with a damp tea towel and leave to rise for an hour.
Divide the mix into three balls. Roll out on a floured surface into circles. Place each circle on a flat baking tray or a plastic chopping board dusted with semolina (so the pizza can be easily transferred to the oven later).
Place a pizza stone or an upturned baking tray into the oven and heat the oven to 220C/425F/Gas 7 (in a non-fan oven).
For the topping, cover the bases with the onion slices and sprinkle on the crumbled gorgonzola. Lay the ham and fig quarters on top and dust with the pecorino.
Drizzle over a little olive oil and a sprinkle of balsamic vinegar. Season with salt and freshly ground black pepper.
When ready to bake, slide the pizza directly onto the hot pizza stone or baking tray and bake in the oven for 8-10 minutes, or until the base is golden-brown and the topping is bubbling.
Serve with rocket leaves on top.


a little bit about me
Hey! My name is Kirandeep and I'm a web developer with a passion for front end development and design. I'm currently a student at Lambton College pursuing a degree in Computer Programming . I aspire towards a career that will allow me to channel my creativity through crafting beautiful software and engaging experiences.
When I am not in computer , I like to be close to nature or workout to remain fit.
What i do
DESIGN
Design isn't just what a product looks like and feels like on the outside. Design encompasses the internal functionality of a product as well as the overall user experience. I strive to design interfaces and experiences that people can enjoy on all digital mediums.
development
With a strong foundation in Computer Science, I am passionate about Web design and development. As I grow as a developer, I hope to write clean, readable code that can be used by others and leveraged to create beautiful software.
Goals
I would like to bring my full potential into the work environment. Keeping in mind to fullfill all the requirements that my position demands. Also I actively seek out new technologies and stay up to date on industry trends and advancements.
technologies i have worked with
I've been doing web development for quiet a time now , and I'm always eager to learn more in this fast paced industry.
my projects
(More coming soon ... )
Get In Touch
Whether you have an idea for a project or just want to chat, feel free to shoot me an email!


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SdFat
|
StdioStream implements a minimal stdio stream. More...
#include <StdioStream.h>
Public Member Functions | |
| void | clearerr () |
| int | fclose () |
| int | feof () |
| int | ferror () |
| int | fflush () |
| int | fgetc () |
| char * | fgets (char *str, size_t num, size_t *len=0) |
| bool | fopen (const char *path, const char *mode) |
| int | fputc (int c) |
| int | fputs (const char *str) |
| size_t | fread (void *ptr, size_t size, size_t count) |
| int | fseek (int32_t offset, int origin) |
| int32_t | ftell () |
| size_t | fwrite (const void *ptr, size_t size, size_t count) |
| int | getc () |
| size_t | print (char c) |
| size_t | print (const char *str) |
| size_t | print (const __FlashStringHelper *str) |
| size_t | print (double val, uint8_t prec=2) |
| size_t | print (float val, uint8_t prec=2) |
| template<typename T > | |
| size_t | print (T val) |
| int | printDec (char n) |
| int | printDec (signed char n) |
| int | printDec (unsigned char n) |
| int | printDec (int16_t n) |
| int | printDec (uint16_t n) |
| int | printDec (int32_t n) |
| int | printDec (uint32_t n) |
| int | printDec (double value, uint8_t prec) |
| int | printDec (float value, uint8_t prec) |
| int | printField (double value, char term, uint8_t prec=2) |
| int | printField (float value, char term, uint8_t prec=2) |
| template<typename T > | |
| int | printField (T value, char term) |
| int | printHex (uint32_t n) |
| int | printHexln (uint32_t n) |
| size_t | println () |
| size_t | println (double val, uint8_t prec=2) |
| size_t | println (float val, uint8_t prec=2) |
| template<typename T > | |
| size_t | println (T val) |
| int | putc (int c) |
| int | putCRLF () |
| bool | rewind () |
| StdioStream () | |
| int | ungetc (int c) |
Private Member Functions | |
| uint32_t | available () |
| void | clearError () |
| void | clearWriteError () |
| bool | close () |
| bool | contiguousRange (uint32_t *bgnBlock, uint32_t *endBlock) |
| bool | createContiguous (FatFile *dirFile, const char *path, uint32_t size) |
| bool | createContiguous (const char *path, uint32_t size) |
| uint32_t | curCluster () const |
| uint32_t | curPosition () const |
| bool | dirEntry (dir_t *dir) |
| uint16_t | dirIndex () |
| uint32_t | dirSize () |
| void | dmpFile (print_t *pr, uint32_t pos, size_t n) |
| bool | exists (const char *path) |
| int16_t | fgets (char *str, int16_t num, char *delim=0) |
| uint8_t | fileAttr () const |
| uint32_t | fileSize () const |
| uint32_t | firstBlock () |
| uint32_t | firstCluster () const |
| uint8_t | getError () |
| bool | getName (char *name, size_t size) |
| void | getpos (FatPos_t *pos) |
| bool | getSFN (char *name) |
| bool | getWriteError () |
| bool | isDir () const |
| bool | isFile () const |
| bool | isHidden () const |
| bool | isLFN () const |
| bool | isOpen () const |
| bool | isReadOnly () const |
| bool | isRoot () const |
| bool | isRoot32 () const |
| bool | isRootFixed () const |
| bool | isSubDir () const |
| bool | isSystem () const |
| void | ls (uint8_t flags=0) |
| void | ls (print_t *pr, uint8_t flags=0, uint8_t indent=0) |
| bool | mkdir (FatFile *dir, const char *path, bool pFlag=true) |
| bool | open (FatFileSystem *fs, const char *path, oflag_t oflag) |
| bool | open (FatFile *dirFile, uint16_t index, oflag_t oflag) |
| bool | open (FatFile *dirFile, const char *path, oflag_t oflag) |
| bool | open (const char *path, oflag_t oflag=O_RDONLY) |
| bool | openNext (FatFile *dirFile, oflag_t oflag=O_RDONLY) |
| bool | openRoot (FatVolume *vol) |
| int | peek () |
| bool | printCreateDateTime (print_t *pr) |
| int | printField (int16_t value, char term) |
| int | printField (uint16_t value, char term) |
| int | printField (int32_t value, char term) |
| int | printField (uint32_t value, char term) |
| size_t | printFileSize (print_t *pr) |
| bool | printModifyDateTime (print_t *pr) |
| size_t | printName () |
| size_t | printName (print_t *pr) |
| size_t | printSFN (print_t *pr) |
| int | read () |
| int | read (void *buf, size_t nbyte) |
| int8_t | readDir (dir_t *dir) |
| bool | remove () |
| bool | rename (FatFile *dirFile, const char *newPath) |
| bool | rmdir () |
| bool | rmRfStar () |
| bool | seekCur (int32_t offset) |
| bool | seekEnd (int32_t offset=0) |
| bool | seekSet (uint32_t pos) |
| void | setpos (FatPos_t *pos) |
| bool | sync () |
| bool | timestamp (FatFile *file) |
| bool | timestamp (uint8_t flags, uint16_t year, uint8_t month, uint8_t day, uint8_t hour, uint8_t minute, uint8_t second) |
| bool | truncate (uint32_t length) |
| FatVolume * | volume () const |
| int | write (const char *str) |
| int | write (uint8_t b) |
Static Private Member Functions | |
| static FatFile * | cwd () |
| static void | dateTimeCallback (void(*dateTime)(uint16_t *date, uint16_t *time)) |
| static void | dateTimeCallbackCancel () |
| static uint8_t | dirName (const dir_t *dir, char *name) |
| static bool | legal83Char (uint8_t c) |
| static void | printFatDate (uint16_t fatDate) |
| static void | printFatDate (print_t *pr, uint16_t fatDate) |
| static void | printFatTime (uint16_t fatTime) |
| static void | printFatTime (print_t *pr, uint16_t fatTime) |
| static bool | remove (FatFile *dirFile, const char *path) |
| static bool | setCwd (FatFile *dir) |
StdioStream implements a minimal stdio stream.
StdioStream does not support subdirectories or long file names.
|
inline |
Constructor
|
inline |
Clear the stream's end-of-file and error indicators.
| int StdioStream::fclose | ( | ) |
Close a stream.
A successful call to the fclose function causes the stream to be flushed and the associated file to be closed. Any unwritten buffered data is written to the file; any unread buffered data is discarded. Whether or not the call succeeds, the stream is disassociated from the file.
Copyright (c) 2011-2018 Bill Greiman This file is part of the SdFat library for SD memory cards.
MIT License
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
 IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
|
inline |
Test the stream's end-of-file indicator.
|
inline |
Test the stream's error indicator.
| int StdioStream::fflush | ( | ) |
Flush the stream.
If stream is an output stream or an update stream in which the most recent operation was not input, any unwritten data is written to the file; otherwise the call is an error since any buffered input data would be lost.
|
inline |
Get a byte from the stream.
| char * StdioStream::fgets | ( | char * | str, |
| size_t | num, | ||
| size_t * | len = 0 |
||
| ) |
Get a string from a stream.
The fgets function reads at most one less than the number of characters specified by num from the stream into the array pointed to by str. No additional characters are read after a new-line character (which is retained) or after end-of-file. A null character is written immediately after the last character read into the array.
| [out] | str | Pointer to an array of where the string is copied. |
| [in] | num | Maximum number of characters including the null character. |
| [out] | len | If len is not null and fgets is successful, the length of the string is returned. |
| bool StdioStream::fopen | ( | const char * | path, |
| const char * | mode | ||
| ) |
Open a stream.
Open a file and associates the stream with it.
| [in] | path | file to be opened. |
| [in] | mode | a string that indicates the open mode. |
| "r" or "rb" | Open a file for reading. The file must exist. |
| "w" or "wb" | Truncate an existing to zero length or create an empty file for writing. |
| "wx" or "wbx" | Create a file for writing. Fails if the file already exists. |
| "a" or "ab" | Append; open or create file for writing at end-of-file. |
| "r+" or "rb+" or "r+b" | Open a file for update (reading and writing). |
| "w+" or "w+b" or "wb+" | Truncate an existing to zero length or create a file for update. |
| "w+x" or "w+bx" or "wb+x" | Create a file for update. Fails if the file already exists. |
| "a+" or "a+b" or "ab+" | Append; open or create a file for update, writing at end-of-file. |
The character 'b' shall have no effect, but is allowed for ISO C standard conformance.
Opening a file with append mode causes all subsequent writes to the file to be forced to the then current end-of-file, regardless of intervening calls to the fseek function.
When a file is opened with update mode, both input and output may be performed on the associated stream. However, output shall not be directly followed by input without an intervening call to the fflush function or to a file positioning function (fseek, or rewind), and input shall not be directly followed by output without an intervening call to a file positioning function, unless the input operation encounters end-of-file.
|
inline |
Write a byte to a stream.
| [in] | c | the byte to be written (converted to an unsigned char). |
| int StdioStream::fputs | ( | const char * | str | ) |
Write a string to a stream.
| [in] | str | a pointer to the string to be written. |
| size_t StdioStream::fread | ( | void * | ptr, |
| size_t | size, | ||
| size_t | count | ||
| ) |
Binary input.
Reads an array of up to count elements, each one with a size of size bytes.
| [out] | ptr | pointer to area of at least (size*count) bytes where the data will be stored. |
| [in] | size | the size, in bytes, of each element to be read. |
| [in] | count | the number of elements to be read. |
| int StdioStream::fseek | ( | int32_t | offset, |
| int | origin | ||
| ) |
Set the file position for the stream.
| [in] | offset | number of offset from the origin. |
| [in] | origin | position used as reference for the offset. It is specified by one of the following constants. |
SEEK_SET - Beginning of file.
SEEK_CUR - Current position of the file pointer.
SEEK_END - End of file.
| int32_t StdioStream::ftell | ( | ) |
Get the current position in a stream.
| size_t StdioStream::fwrite | ( | const void * | ptr, |
| size_t | size, | ||
| size_t | count | ||
| ) |
Binary output.
Writes an array of up to count elements, each one with a size of size bytes.
| [in] | ptr | pointer to (size*count) bytes of data to be written. |
| [in] | size | the size, in bytes, of each element to be written. |
| [in] | count | the number of elements to be written. |
|
inline |
Get a byte from the stream.
getc and fgetc are equivalent but getc is in-line so it is faster but require more flash memory.
|
inline |
Write a character.
| [in] | c | the character to write. |
|
inline |
Write a string.
| [in] | str | the string to be written. |
| size_t StdioStream::print | ( | const __FlashStringHelper * | str | ) |
Print a string stored in flash memory.
| [in] | str | the string to print. |
|
inline |
Print a floating point number.
| [in] | prec | Number of digits after decimal point. |
| [in] | val | the number to be printed. |
|
inline |
Print a floating point number.
| [in] | prec | Number of digits after decimal point. |
| [in] | val | the number to be printed. |
|
inline |
Print a number.
| [in] | val | the number to be printed. |
|
inline |
Print a char as a number.
| [in] | n | number to be printed. |
| int StdioStream::printDec | ( | signed char | n | ) |
print a signed 8-bit integer
| [in] | n | number to be printed. |
|
inline |
Print an unsigned 8-bit number.
| [in] | n | number to be print. |
| int StdioStream::printDec | ( | int16_t | n | ) |
Print a int16_t
| [in] | n | number to be printed. |
| int StdioStream::printDec | ( | uint16_t | n | ) |
print a uint16_t.
| [in] | n | number to be printed. |
| int StdioStream::printDec | ( | int32_t | n | ) |
Print a signed 32-bit integer.
| [in] | n | number to be printed. |
| int StdioStream::printDec | ( | uint32_t | n | ) |
Write an unsigned 32-bit number.
| [in] | n | number to be printed. |
|
inline |
Print a double.
| [in] | value | The number to be printed. |
| [in] | prec | Number of digits after decimal point. |
| int StdioStream::printDec | ( | float | value, |
| uint8_t | prec | ||
| ) |
Print a float.
| [in] | value | The number to be printed. |
| [in] | prec | Number of digits after decimal point. |
|
inline |
Print a number followed by a field terminator.
| [in] | value | The number to be printed. |
| [in] | term | The field terminator. |
| [in] | prec | Number of digits after decimal point. |
|
inline |
Print a number followed by a field terminator.
| [in] | value | The number to be printed. |
| [in] | term | The field terminator. |
| [in] | prec | Number of digits after decimal point. |
|
inline |
Print a number followed by a field terminator.
| [in] | value | The number to be printed. |
| [in] | term | The field terminator. |
| int StdioStream::printHex | ( | uint32_t | n | ) |
Print HEX
| [in] | n | number to be printed as HEX. |
|
inline |
Print HEX with CRLF
| [in] | n | number to be printed as HEX. |
|
inline |
Write a CR/LF.
|
inline |
Print a floating point number followed by CR/LF.
| [in] | val | the number to be printed. |
| [in] | prec | Number of digits after decimal point. |
|
inline |
Print a floating point number followed by CR/LF.
| [in] | val | the number to be printed. |
| [in] | prec | Number of digits after decimal point. |
|
inline |
Print an item followed by CR/LF
| [in] | val | the item to be printed. |
|
inline |
Write a byte to a stream.
putc and fputc are equivalent but putc is in-line so it is faster but require more flash memory.
| [in] | c | the byte to be written (converted to an unsigned char). |
|
inline |
Write a CR/LF.
| bool StdioStream::rewind | ( | ) |
Set position of a stream to the beginning.
The rewind function sets the file position to the beginning of the file. It is equivalent to fseek(0L, SEEK_SET) except that the error indicator for the stream is also cleared.
| int StdioStream::ungetc | ( | int | c | ) |
Push a byte back into an input stream.
| [in] | c | the byte (converted to an unsigned char) to be pushed back. |
One character of push-back is guaranteed. If the ungetc function is called too many times without an intervening read or file positioning operation on that stream, the operation may fail.
A successful intervening call to a file positioning function (fseek, fsetpos, or rewind) discards any pushed-back characters for the stream.


| boxCox {car} | R Documentation |
Computes and optionally plots profile log-likelihoods for the parameter of the
Box-Cox power family, the Yeo-Johnson power family, or for either of the parameters in a bcnPower family. This is a slight generalization of the
boxcox
function in the MASS package that allows for families of
transformations other than the Box-Cox power family. the boxCox2d
function
produces a contour
plot of the two-dimensional likelihood profile for the bcnPower family.
boxCox(object, ...) ## Default S3 method: boxCox(object, lambda = seq(-2, 2, 1/10), plotit = TRUE, interp = plotit, eps = 1/50, xlab=NULL, ylab=NULL, family="bcPower", param=c("lambda", "gamma"), gamma=NULL, grid=TRUE, ...) ## S3 method for class 'formula' boxCox(object, lambda = seq(-2, 2, 1/10), plotit = TRUE, family = "bcPower", param = c("lambda", "gamma"), gamma = NULL, grid = TRUE, ...) ## S3 method for class 'lm' boxCox(object, lambda = seq(-2, 2, 1/10), plotit = TRUE, ...) boxCox2d(x, ksds = 4, levels = c(0.5, 0.95, 0.99, 0.999), main = "bcnPower Log-likelihood", grid=TRUE, ...)
object |
a formula or fitted model object of class |
lambda |
vector of values of lambda, with default (-2, 2) in steps of 0.1, where the profile log-likelihood will be evaluated. |
plotit |
logical which controls whether the result should be plotted; default |
interp |
logical which controls whether spline interpolation is used. Default to
|
eps |
Tolerance for lambda = 0; defaults to 0.02. |
xlab |
defaults to |
ylab |
defaults to |
family |
Defaults to |
param |
Relevant only to |
gamma |
For use when the |
grid |
If TRUE, the default, a light-gray background grid is put on the graph. |
... |
additional arguments passed to the |
x |
An object created by a call to |
ksds |
Contour plotting of the log-likelihood surface will cover plus of minus |
levels |
Contours will be drawn at the values of levels. For example, |
main |
Title for the contour plot |
The boxCox
function is an elaboration of the boxcox
function in the
MASS package. The first 7 arguments are the same as in boxcox
, and if the argument family="bcPower"
is used, the result is essentially identical to the function in MASS. Two additional families are the yjPower
and bcnPower
families that allow a few values of the response to be non-positive.
The bcnPower family has two parameters: a power lambda and a start or location parameter gamma, and the boxCox
function can be used to obtain a profile log-likelihood for either parameter with lambda as the default. Alternatively, the boxCox2d
function can be used to get a contour plot of the profile log-likelihood.
Both functions ae designed for their side effects of drawing a graph. The boxCox
function returns a list of the lambda (or possibly, gamma) vector and the computed profile log-likelihood vector,
invisibly if the result is plotted. If plotit=TRUE
plots log-likelihood vs
lambda and indicates a 95% confidence interval about the maximum observed value of
lambda. If interp=TRUE
, spline interpolation is used to give a smoother plot.
Sanford Weisberg<EMAIL_ADDRESS>Box, G. E. P. and Cox, D. R. (1964) An analysis of transformations. Journal of the Royal Statisistical Society, Series B. 26 211-46.
Cook, R. D. and Weisberg, S. (1999) Applied Regression Including Computing and Graphics. Wiley.
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Hawkins, D. and Weisberg, S. (2017) Combining the Box-Cox Power and Generalized Log Transformations to Accomodate Nonpositive Responses In Linear and Mixed-Effects Linear Models South African Statistics Journal, 51, 317-328.
Weisberg, S. (2014) Applied Linear Regression, Fourth Edition, Wiley.
Yeo, I. and Johnson, R. (2000) A new family of power transformations to improve normality or symmetry. Biometrika, 87, 954-959.
boxcox
, yjPower
, bcPower
, bcnPower
,
powerTransform
, contour
with(trees, boxCox(Volume ~ log(Height) + log(Girth), data = trees, lambda = seq(-0.25, 0.25, length = 10))) data("quine", package = "MASS") with(quine, boxCox(Days ~ Eth*Sex*Age*Lrn, lambda = seq(-0.05, 0.45, len = 20), family="yjPower"))


Welcome to Andela BuildForSDG 2020 challenge
Welcome once again. We are glad to have you here. you can try out our COVID-19 estimator to generate your statistical data such as :
impact
severe impact
No of bed available etc
Welcome once again. We are glad to have you here. you can try out our COVID-19 estimator to generate your statistical data such as :
impact
severe impact
No of bed available etc


James Cameron’s multi Oscar Winning epic action/sci-fi masterpiece, TERMINATOR 2: JUDGMENT DAY will return to cinemas from August 29th in a breath-taking new 3D conversion overseen by James Cameron himself.
To celebrate the new release Marty & Conor are giving away €500 to the person who can do the best Arnie Terminator 2 impersonation. Send in a video of you doing your best line from the movie APP them on 087 18 18 100.
Along with the €500 that will be given away on “Judgement Day: August 29”, there is also 5 runner up merch packs up for grabs which include a Quad -Blu-ray bundle: Robocop, Total Recall, Non-Stop – Official T2 t-shirt and tickets to see TERMINATOR 2: JUDGMENT DAY 3D
Having originally hit screens in 1991, complete with groundbreaking special effects, TERMINATOR 2: JUDGMENT DAY became Arnold Schwarzenegger’s most iconic role to date, as well as one of the most quotable scripts of the decade. This brand new 3D version will blast the seminal blockbuster into the 21st century and introduce it to a brand new generation of fans.


WITNESS LIST Appropriations Committee (Subcommittee on Job Classification) March 30, 1998-1:00P Information Technology Personnel On: Edge, Joanne (DPRS) Kelli Dan (SAO) Lauderdale, Mary (DPS) Majek, Mark (Sm State Agency Tsk Frc) Williams, Debra (RRC) Williamson, Diana (DHS)


---
layout: page
title: "telnet://tw2002"
description: "TradeWars 2002"
header-img: "img/header/tradewars-2002.png"
---
According to Wikipedia:
What is Trade Wars 2002?
Trade Wars is a series of popular computer games dating back to the early days of personal computing. Inspired by Hunt the Wumpus, the board game Risk, and the original space trader game Star Trader, Trade Wars was the first multiplayer game of the space trader genre. During the height of its popularity in the early 1990s, Trade Wars was the preeminent BBS game, played by tens of thousands of users around the world.
Released in 1986, TradeWars was among the earliest multiplayer online games. As of 2013, TradeWars has been hosted on over 21,000 different sites in 59 different countries, with some sites hosting the game continuously for over 25 years. In 1995, when there were 400 active MUD sites, TradeWars was running on over 14,000 different sites. That same year, when popular MUD LambdaMOO hosted 10,000 players, over 70,000 played TradeWars.
Connecting to the Trade Wars 2002 (tw2002) server is accomplished over telnet. This can be accomplished via the command line (terminal) or a telnet client.
Click here to launch game or connect manually to telnet tw2002.jdstraughan.com
on port 2002
.
Full command
telnet tw2002.jdstraughan.com 2002
The best way to get started is to just hop in a game and start playing around. When you get lost, you can alway view the menu by sending a?
.
There is still an active forum for TW2002, many guides, tutorials, the infamous TradeWars Bible, and in-game help. TradeWars even has an active Twitter account!
The default settings on Mac terminals have issues that impact gameplay.
First, you will need to set the backspace character to be recognized by the game. Follow the instructions here to update terminal.
Next, you will want to need to add a terminal profile to properly parse the ANSI graphics in the game. Follow this tutorial to configure your Terminal app.I will continue to make updates to this page as time allows. This was a super quick write-up to get the game server announced, and this guide could use some help. You are welcome submit pull requests via the GitHub repository. Happy trading, and see you at the Stardock!


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a+(b+c)=(a+b)+c
represents which one of the following properties:
Associative
Notice that on the left side of the equation the parentheses indicate to add the b
and the c
before you add the a
.
On the right side of the equation, we first add a
and b
before adding c
.
The order of the variables has not changed but the groupings (what's inside the parentheses) have.
The groups have changed, and another word for a group is association.The above equation demonstrates the Associative Property of addition.
A+(B+C)=(A+B)+C
represents which one of the following properties:
Associative
On the left side of the equation, the parentheses indicate to add the B and the C before you add the A. On the right side of the equation, we first add the A and the B before adding the C.
Notice that the order of the numbers inside the parentheses has not changed but the groupings (what's inside the parentheses) have.
Evaluating the left side:
A+(B+C)=ASSOCIATIVE_RESULT
Evaluating the right side, the result is the same:
(A+B)+C=ASSOCIATIVE_RESULT
The groups have changed, and another word for a group is association. The equation demonstrates the Associative Property.
Which one of the equations on the right represents the Associative Property of addition?
a+(b+c)=(a+b)+c
value
The Associative Property should not be confused with the Commutative Property, in which the sequence or order of numbers is changed.
In contrast to the Commutative Property, the Associative Property justifies rearranging our parentheses. For example, adding (4+2)+3
is equivalent to adding 4+(2+3)
and represents the Associative Property.
a+(b+c)=(a+b)+c
demonstrates the Associative Property.
a+b=b+a
represents which one of the following properties:
Commutative
As this equation implies, changing the order of a
and b
will not change the end result.
This property should not be confused with the Associative Property, in which groupings (what's inside the parentheses) are changed.
This equation demonstrates the Commutative Property. The following sentence may help you to remember this property: The commuting distance is the same in either direction, from school to home or home to school.
A+B=B+A
represents which one of the following properties:
Commutative
This property should not be confused with the Associative Property, in which the order of operations is changed.
As this equation implies, changing the order of A and B doesn't change the end result.
Evaluating the left side:
A+B=COMMUTATIVE_RESULT
Evaluating the right side, the result is the same:
B+A=COMMUTATIVE_RESULT
This equation demonstrates the Commutative Property. The following sentence may help you to remember this property: The commuting distance is the same in either direction, from school to home or home to school.
Which one of the equations on the right represents the Commutative Property of addition?
a+b=b+a
value
According to the Commutative Property, the order of the numbers doesn't matter.
The Commutative Property should not be confused with the Associative Property, in which you change the groupings (what is contained inside the parentheses).
The following sentence may help you to remember the Commutative Property: "The commuting distance is the same in either direction, from school to home or home to school."
a+b=b+a
demonstrates the Commutative Property.
a+b(c+d)=a+bc+bd
represents which one of the following properties:
Distributive
On the left side of the equation, b
is multiplied by the sum of c
and d
.
On the right side of the equation, we first multiply b
by c
and d
individually and then add their products.
We say that multiplication distributes b
over addition of c
and d
, and this equation demonstrates the Distributive Property.
A+B(C+D)=A+(B)(C)+(B)(D)
represents which one of the following properties:
Distributive
On the left side of the equation, B
is multiplied by the sum of C
and D
. On the right side of the equation, we first multiply B
by C
and D
individually and then add their products.
Evaluating the left side:
A+B(C+D)=DISTRIBUTIVE_RESULT
Evaluating the right side, the result is the same:
A+(B)(C)+(B)(D)=DISTRIBUTIVE_RESULT
We say that multiplication distributes B
over addition of C
and D
and so this is called the Distributive Property.
Which one of the equations on the right represents the Distributive Property of addition?
a+b(c+d)=a+bc+bd
value
In the correct answer, on the left side the equation b
is multiplied by the sum of c
and d
.
On the right side of this equation, we first multiply b
by c
and d
individually and then add their products.
In this equation, b
gets distributed to c
and d
, and so we call this the Distributive Property.
a+b(c+d)=a+bc+bd
represents the Distributive Property.


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San Francisco
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
Los Angelas
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
New York
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
Lake Tahoe
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
Hawaii
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.


Hide a gif for others to discover while you look for gifs of your own. You're like a modern-day Indiana Jones! Tip: Drag an image from your toolbelt!


Immerse yourself into the other side of the world right from your living room.
360 Degrees Camera that works live on the internet with absolute high picture quality and low latency!
Along will the app, you will have a totally different immersive experience.
App available in Autumn 2016!
Feel free to email us for more information!


So I wanted to learn more about HTML
and I took a code acadmy course
and I took a code acadmy course
and some of it was easy but some of it was hard
I also saw this online and tried my best to recreate the image using Javascript but I did have to do some extensive googling to figure out some parts. But I thought it was cool so I put it here.


This is a freighter port and not for cruising yachts, however access is permitted if hiding from a typhoon, or for a mechanical emergency.
Position 34° 37'32.82N, 138° 08'29.39E
There are no floating docks, just giant concrete walls that you can tie to. The walls, especially when the winds push you into them, are hard on your fenders. There is no shore power, and no water.
Last updated September 2009.


Photos: Baby Trump Balloon Stabbed 'Beyond Repair' Amid POTUS Alabama Visit
This is not for the first time a balloon caricature of Trump wearing a diaper and holding a cellphone in his hand has been vandalized during protests. This time, however, observers suggest that the damage is irreparable.
US President Donald Trump appeared in Tuscaloosa, Alabama, on Saturday, attending a Alabama-Louisiana State football game alongside several local Republican lawmakers.
In contrast to reports of a warm welcome for POTUS at the game, his floating caricature - 'Baby Trump' balloon - was not so lucky, as it was knifed by a protester in a park located close to the site where the University of Alabama football game was held.
According to multiple reports, the man who "attacked" Baby Trump has been arrested. Twitterians shared photos and video of the alleged arrest.


{% extends "base.html" %} {% load staticfiles %} {% block script %} {% endblock %} {% block content %}
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_A_Map_of_the_World_ (R) ** 1/2 (out of ****)
Sigourney Weaver's portrayal of an Iowa farm wife/school nurse accused of child abuse is indeed worthy of all the accolades it has received, most notably a Golden Globe nomination. The role of Alice Goodwin is an exceedingly difficult one; her portrayer must have enough of a dark side to make the accusations plausible while at the same time remain likable enough to make the audience care. Weaver's achievement is not only pulling off the balance but making a real person.
Unfortunately, Scott Elliott's film as a whole is far less convincing. _A_Map_of_the_World_ is the second in the new subgenre of drama I call "the Oprah film": a woman faces adversity of a domestic nature in a story usually coming from a novel on Oprah's book club list. That should tell you how gooey with sentiment the film is, not to mention the outcome of the entire affair. Nonetheless, Weaver and the rest of the stellar cast--which also includes Julianne Moore, David Strathairn, Arliss Howard, and ChloŽ Sevigny--do their best, even while saddled with some very "movie" dialogue (e.g., a sobbing Moore laments, "It's amazing how much a person can cry!").
Michael Dequina<EMAIL_ADDRESS>|<EMAIL_ADDRESS>|<EMAIL_ADDRESS>|<EMAIL_ADDRESS>Mr. Brown's Movie Site: http://welcome.to/mrbrown CinemaReview Magazine: http://www.CinemaReview.com on ICQ: #25289934 | on AOL Instant Messenger: MrBrown23
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


India warming CMIP forcings temperature data different CRU observed RCP. increase climate trends historical simulations mean {border-style IMD surface change future px;} #ffffff;} models shows trend using Climate GHG century forcings. years Figure changes forcing shown India. compared global model natural GHGs emission period Data heat increases relative sets (–) anthropogenic century, end version (Fig. Fig. However, Indian bias century. cooling ensemble scenarios variability (Figure (IDL) Clim. Interactive Language RCP Table confidence created data. direct estimated expected external followed gridded http://www.harrisgeospatial.com/docs/whats_new_in_.html). level maximum projections px; region seasonal significant spatial {font-family AA, Himalayan NAT RCP., analysis annual contribution correlation effect font-size grid increased individual near negative regression software used (). Change Historical Nature Research central considered double; emissions higher highest historic human larger minimum observational observations projected rare rate simulations, (e.g., ./s--- LU. NAT, National Res. Temperature [], aerosols border-color border-width cold consistent decreases distribution events extreme extremes high indicate indicates indirect lines models. parts point radiation regional regions respectively. scenarios. solid; studies time variation variations warming. {font-style {font-weight (i.e., (–), . K/decade Anthropogenic Commons Creative Department Earth’s GHGs, India, LU, Lett. Surface Taylor addition, atmosphere atmospheric available based biases bold computed contributed correlations courier; difference em; experiments factors fall forcings, grid.. included large material means models, noticed past periods plotted pt;} recent regions) results robust role series simulation solid temperatures temporal understanding use values winter year


Enthusiasm!!!! Wooooo, Yayyyyyy!
Enthusiasm is superly duperly super duper important, no matter what you are doing. Cleaning up that wine stain on the carpet won't be boring and stressful if you are enthusiastic about it. Own that carpet! Destroy that stain and triumph with a fresh and clean floor for your feet to comfortably rest upon. Seriously tho, if you are enthusiastic while doing any task/learning, you won't even consider being bored and wasting time. You are way more eager to learn and pay attention. Eager + Fun + Learning = Awesome Knowledge Retention (based on a Personal Study on Myself).
So, what was the last thing someone asked me for advice on? What to get for dinner, and I said Chinese. Does that relate to my enthusiasm value above?  I haven't had Chinese food (frozen doesn't count) in over 9 months so I was SUPER EXCITED about this. And guess what?? Chinese was consumed shortly after. WIN WIN.
Can my values help mediate stereotype threat? THEY SURE CAN.  Think those people are going to make fun of you for those AWESOME new Pokemon Velcro shoes that light up when you walk?  Rock them Pokemon shoes.


SIR NOD
Celtic-daft Rod Stewart curls up in Hoops top after performing at Memories That Matter charity bash in London
by Oliver NortonSIR ROD Stewart curled up in bed after setting the dance-floor alight with his missus.
The rock-star, 74, performed at the Memories That Matter charity bash in London to raise money for the Teenage Cancer Trust.
He also showed off his moves with wife and model Penny Lancaster, 48, who joined him on the floor.
She later took to Instagram and posted an image of her hubby in bed with his favourite Celtic top on.
She wrote: “The Celtic loving boy having a lay in after an incredible night, raising 1 million for @teenage_cancer.
“Now he’s off to Manchester for his first show of the UK tour ending just before Christmas.”
Sir Rod is set to perform three sell out shows at the SSE Hydro in Glasgow this week (on November 26, 28 and 30).
We told how Celtic-daft Sir Rod revealed his oldest brother is a Rangers fan – and that his dad has a Light Blues player named on his grave.
The rocker told how sibling Robert is a dedicated Gers supporter – but he says the pair “don’t have fights about it”.
He also said that ex-Ibrox and Scotland defender Eric Caldow is engraved on his father’s grave.


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Kim Ryder
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Kim is a software developer in Microsoft. She works in ASP.NET MVC Team and collaborates with other teams.
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Colophon
kaidez.com was created by Kai Gittens using the following tools:
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title: 'Colophon « kaidez.com'
author: Kai Gittens
layout: default
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tags: [kaidez]
---
kaidez.com was created by Kai Gittens using the following tools:
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Posts on kaidez.com are written in Markdown within HTML5-based templates, with Liquid tags lending a helping hand. The site's source code is open source and freely available on GitHub.
On the development level, kaidez.com site dependencies are managed by Bower.
kaidez.com is proudly hosted on a LAMP stack provided by Media Temple. Static assets are hosted via MaxCDN.
kaidez.com doesn't care much about being viewed properly on Internet Explorer 8 and lower.


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We forecast that the workforce demand over a five-year period to produce and market the drone would be intensive. Right now, there is a growing demand in the prosumer market and our drone would theoretically provide more lift than a regular propeller-driven drone. Production should be easy to implement because the aeronautic design we used does not deviate much from what outs in the market as of right now. This would most certainly make the prosumer drone market more competitive by having two different types of drones out there that both function well and provide different benefits.
Paul G. Allen School of Computer Science and Engineering, University of Washington
The program gives you the broad education necessary to understand and to impact global, economic, environmental, and society through robotics engineering solutions. The course is an undergraduate course that mainly focuses on the basics of robotics and its implementation into society. This relates to our NCT Technical Application because it’s about robotics and we are building one.
John D. Odegard School of Aerospace Sciences
University of North Dakota
Located in Phoenix, North Dakota, the John D. Odegard School of Aerospace Sciences is one of the first universities to offer Unmanned Aircraft System
Operations as a Major. Centering on aviation applications, the Undergraduate Program in Unmanned Aircraft Systems aims to educate students in the operations, procedures, and regulations of the American National Airspace System. By working in team and directly applying various science and engineering principles, the program aims for the students to develop an understanding of the aviation industry and help to contribute to it effectively.
Title: Physics Principals in Robotics
Instead of limiting the course material to resolving around the magnus effect, this program would take a broader approach. This primarily project-based program would focus on having students apply physics principles in the field of robotics. An example of a project would be our own magnus effect drone. The goal of the program is for students to try experimenting with different designs for robots and to consider the different opportunities offered by utilizing these different principles. Another example would be entirely wind-powered robots. Part of the program would resolve around coding and another part would focus on construction and team management. Hopefully, this program could inspire some experimentation and contribution in the field of robotics.


Planet of the Apes * * (out of * * * * )
Directed by Tim Burton. Cast: Mark Wahlberg, Helena Bonham Carter, Tim Roth, Estella Warren, Michael Clarke Duncan, Kris Kristofferson, Paul Giamatti, Cary-Hiroyuki Tagawa, David Warner, Lisa Marie, Charlton Heston, Linda Harrison. 2001 - 119 minutes Rated PG-13 (for violence). Reviewed by Dustin Putman, July 27, 2001.
One of the most visionary filmmakers working today is, unquestionably, Tim Burton. Interested in telling strange and unusual tales with a grand helping of imagination and wonder to spare, Burton is a groundbreaking director whose stamp seems to be all over his films, from 1985's "Pee Wee's Big Adventure," to 1988's "Beetlejuice," to 1989's "Batman," to 1990's "Edward Scissorhands," to 1996's "Mars Attacks!," to 1999's "Sleepy Hollow." In each of his movies, he is equipped with startlingly innovative production designs and haunting music scores from Burton regular Danny Elfman. In a nutshell, when one goes to see "A Tim Burton Film," one is sure to walk out having seen something they have never seen before.
That being said, "Planet of the Apes," a re-imagining of the cult 1968 hit that spawned four sequels, is the most uneven motion picture Tim Burton has ever had the misfortune of directing. In fact, it doesn't particularly even seem like something that should go on his filmography next to everything else he has been involved with. Elfman's signature excellent score is still here, to be sure, but the movie is nearly devoid of inventive thought or human connection (whether it involve actual homosapiens or apes). Although nowhere near as badly handled or haphazardly constructed, "Planet of the Apes" remains Tim Burton's version of "Battlefield Earth."
Set in 2029, astronaut Leo Davidson (Mark Wahlberg) crash-lands his one-person space pod on an unidentified planet where apes are the superior life form over human beings, who are treated as slaves and animals. Immediately captured by General Thade (Tim Roth) and his gang of human-hating apes, Leo manages to promptly escape, along with a few of the other captured people, including the beautiful Daena (Estella Warren). Aided by ape-woman Ari (Helena Bonham Carter), who believes humans and primates should coexist as equals, the escapees begin their journey to a place called the "Forbidden Zone," where they hope to reach salvation.
Murkily plotted and slightly written, by William Broyles Jr., Lawrence Konner, and Mark D. Rosenthal, "Planet of the Apes" is a marginally ambitious sci-fi adventure that feels like it could have used another rewrite. Very little seems to happen in its 119-minute running time, and what does is merely passable--unexciting, frequently uninvolving, and just sort of there.
Also desperately lacking in character development, the film never allows you to grow attached to anyone onscreen (with one exception), and so you stop caring and become impatient. The talent roster is certainly impressive, especially for such a big-budget film, but not much is done with any one of them. Mark Wahlberg (2000's "The Perfect Storm") is an arresting actor who is, nonetheless, vapid as Leo Davidson. Nothing is learned about Leo in the course of the film, and Wahlberg's performance seems akin to a mirage--he just doesn't seem to be playing at the usual top of his game. Tim Roth (2000's "Lucky Numbers") disappears behind layers of Rick Baker's flawless ape makeup, as the villainous Thade, and with his human identity also goes a memorable presence. As for the sultry Estella Warren (2001's "Driven"), she is horribly put to waste as the human Daena, who says very little, and seems to be thinking even less. At the climax, we are led to believe that she has fallen for Leo, and it is one of the most laughably unwarranted film romances to come around the pike in some time. Had as much work been done in giving the people a little more personality as was spent on the Oscar-bound makeup, there might have been a little more material to chew on.
Thank goodness for small favors. Helena Bonham Carter (1999's "Fight Club") is the aforementioned one exception to the character problems, and she is a standout. As the determined, earnest Ari, Carter paints her role with just the right shading of emotion, longing, and hopefulness, and the results are dynamite. When all is said and done, it is Carter's sparkling turn that should get the much-earned credit.
Feeling obligated to one-up its 1968 predecessor, "Planet of the Apes" has two separate plot twists at the end. The first one is more or less predictable, and anyone with a sharp eye will be able to spot the setup during the early scene where Leo crashes his pod on the planet. The second twist appears at the very end, and it is almost enraging in how little sense it actually makes. While the undiscriminating viewer may think it is "cool" and move on, put up to a split second of closer scrutiny unveils it to not only be illogical, but also pointless. Tim Burton may have reimagined the older "Planet of the Apes" for his current version, but the outcome was not necessarily for the better.
- Copyright 2001 by Dustin Putman
Visit my brand-new web site: TheMovieBoy.com
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hello, this is S.Mothikha.usually people think that my name is different and unique but it is a common name in hindi ,which means pearl.
I'm a upcoming graduate in the stream of computer science and engineering
.
born on 02-august at chennai,tamilnadu,india.I completed my schooling in chennai.
I have a huge intrest towards drawing.
My strength is that ,i have a positive attitude and can complete the given work in a perfect manner
Moreover i can face all the challenges. I consider my weakness to be as ,i have a trouble in saying "No".


Chapter 14 Respiration kinetics at the sediment-water interface
Chapter summary:
14.1 The spatial scale of redox sequence in wetlands
In Chapter 8 we presented the theoretical cascade of redox reactions in wetlands. The redox cascade was simplified in a series of well identified spatial zones in which an electron acceptor would be at play. It is the imbalance between the supply and demand of the electron acceptors that defined the zones themselves, and also the direction of concentration gradients and fluxes of electron acceptors and byproducts of respiration (see Figure 8.15). For illustration purposes, the depth and extent of each of the redox layer appeared the same and of several centimeter thick. But is that so, and does it matter?
14.2 Deriving of \(O_2\) microprofile equation in sediment
The hypothesis given is that the volumetric respiration rates are constant, which means that the volumetric respiration rates are of zero order rates with respect to dioxygen in the water column. The dimensions of this rate are \([M.L^{-3}.T^{-1}]\). The instructions given are that the x axis is tilted upward, contrary to what was done in class. The method to derive this equation is to calculate a mass balance for an elementary volume of sediment. Let us take this elementary volume as being a straight parallelepiped of height \(dx\) and of flux surface area \(A\).
This mass balance can be calculated two different ways. The mass \(\Delta M\) of oxygen removed during \(\Delta t\) is equal to the absolute difference in the downward flux of oxygen \(J(x+dx)\) at \(x+dx\) minus that \(J(x)\) at \(x\). The difference between what was done in class is that both \(J(x+dx)\) and \(J(x)\) are negative this time and the absolute value of \(J(x+dx)\) is greater than that \(J(x)\). So \(\Delta M\), which must be positive, can be calculated as:
\[\begin{equation} \Delta M = \left[ J(x) - J(x+dx) \right].A. \Delta t \end{equation}\]
This is opposite from what was done in class, where the axis was pointing downward.
The mass of oxygen removed \(\Delta M\) can also be calculated from the volumetric removal rate \(R_0\) during \(\Delta t\) such that
\[\begin{equation} \Delta M = R_0 . A . dx . \Delta t \end{equation}\]
Combining these two equations yields
\[\begin{equation} \left[J(x) - J(x+dx)\right].A. \Delta t = R_0 . A . dx . \Delta t \end{equation}\]
Rearranging the equation yields:
\[\begin{equation} \frac{J(x+dx) - J(x)}{dx} = -R_0 \end{equation}\]
Interestingly, this expression is the same one as that seen in class. Taking the limit of this equation when \(dx \to 0\)
\[\begin{equation} \lim_{dx\to 0} \frac{J(x+dx) - J(x)}{dx} = -R_0 \end{equation}\]
yields the derivative of the flux such that
\[\begin{equation} \frac{dJ}{dx} = -R_0 \end{equation}\]
For the expression of the flux down, we use Fick’s law
\[\begin{equation} J(x) = -D\frac{dc}{dx} \end{equation}\]
where \(\frac{dc}{dx}\) is the \(O_2\) concentration (\(c\)) concentration gradient with respect to \(x\), and \(D\) is the diffusivity coefficient. The sign of this equation does not change regardless of the direction of \(x\). Indeed, for a positive \(dx\), the oxygen concentration increases, so \(dc>0\). As a result, \(\frac{dc}{dx}>0\). As result, \(-D\frac{dc}{dx}<0\), i.e., \(J(x)<0\), which is correct using this direction for the axis. The derivative of the flux can thus be written as:
\[\begin{equation} \frac{dJ}{dx} = -D\frac{d^2c}{dx^2} \end{equation}\]
Putting everything back together yields:
\[\begin{equation} \frac{d^2c}{dx^2} = \frac{R_0}{D} \\[7pt] \end{equation}\]
Taking the integral a first time yields:
\[\begin{equation} \int_{}^{} \frac{d^2c}{dx^2} = \frac{dc}{dx} = \frac{R_0}{D}x + a \\[7pt] \end{equation}\]
and finally
\[\begin{equation} c(x) = \frac{R_0}{2D}x^2 + ax +b \\[7pt] \end{equation}\]
where \(a,b,c\) are variables to be determined.
To do so, one looks at the conditions at the boundaries. At \(x=0\), \(c(0) = c_0\), hence \(b = c_0\). At depth \(x = L\) (\(L\) is negative here because the x axis is reversed), both \(c(L) = 0\), and, \(\frac{dc}{dx}(L) = 0\) because the profile is a parabola. One can thus write, using the derivative \(\frac{dc}{dx}(L) = 0\) at the boundary:
\[\begin{equation} 0 = \frac{R_0}{D}L + a \\[7pt] or \\[7pt] a = -\frac{R_0}{D}L \end{equation}\]
Using \(c(L) = 0\) boundary condition:
\[\begin{equation} 0 = \frac{R_0}{2D}L^2 - \frac{R_0}{D}L^2 + c_0 \\[7pt] or \\[7pt] 0 = -\frac{R_0}{2D}L^2 + c_0\\[7pt] and \\[7pt] \frac{R_0}{2D}L^2 = c_0 \end{equation}\]
\[\begin{equation} L^2 = \frac{2c_0D}{R_0}\\[7pt] and \\[7pt] L = -\sqrt{\frac{2c_0D}{R_0}} \end{equation}\]
Because \(L\) is negative. Thus
\[\begin{equation} a = -\frac{R_0}{D} \times -\sqrt{\frac{2c_0D}{R_0}}\\[7pt] a = \sqrt{\frac{2c_0R_0}{D}}\\[7pt] \end{equation}\]
Hence the final equation
\[\begin{equation} \boxed{ c(x) = \frac{R_0}{2D}x^2 +\sqrt{\frac{2c_0R_0}{D}}x +c_0 \\[7pt] } \end{equation}\]
It is possible to verify the answer by replacing \(x\) in the equation derived in class by \(-x\).
14.3 Equation of the downward flux at the sediment-water interface (10 points)
The general expression of the flux down is given by Fick’s law:
\[\begin{equation} J(x) = -D\frac{dc}{dx} \end{equation}\]
From the equation of \(c(x)\), one can calculate the derivative of \(c(x)\)
\[\begin{equation} \frac{dc}{dx} = \frac{R_0}{D}x +\sqrt{\frac{2c_0R_0}{D}} \end{equation}\]
Hence:
\[\begin{equation} J(x) = -R_0x -\sqrt{2c_0R_0D} \end{equation}\]
The downward flux of oxygen at the sediment water interface, which one may call Sediment Oxygen Demand (SOD), corresponds to \(J(x=0)\).
\[\begin{equation} \boxed{ SOD= -\sqrt{2c_0R_0D} } \end{equation}\]
As expected, the flux is negative compared to the direction of the axis. This verification confirms the result obtained.


{% extends 'base.html' %} {% block title %}Recommended Events{% endblock %} {% block content %}
(based on your job search progress)
About the event: {{new_dict[event_key][1]}}.....


Nielsen to split its media, ads unit into 2 separate publicly traded firms
The move, which is backed by one of its biggest shareholders Elliott Management, sent the company's shares up 5% in premarket trading
by ReutersNielsen Holdings Plc said on Thursday it had decided to split the market research firm into two publicly traded companies.
The company's two franchises Global Media business that caters to media and advertising clients and Global Connect business that provides research data to consumer goods companies will become two separate units, Nielsen said in a statement.
The move, which is backed by one of its biggest shareholders Elliott Management, sent the company's shares up 5% in premarket trading.


@(email: String, firstName: String, lastName: String) @views.html.common.main("RESOLVEWebIDE - Registration", null) {
Login Username: @email
First name: @firstName
Last name: @lastName


Gained experience from projects such as operating system kernel implementation, socket programming, web development, sophisticated computer graphics algorithm implementation and practical application development. Now is diving deep in real-world problems in computing industry. TECHNICAL SKILLS: Programming Languages: Java, C, Python, Go, Lua, PHP, JavaScript, Assembly Language(x86) Platform/Libraries: Unix, Linux, Windows, Android, MATLAB, openCV/openGL Java Framework: Retrofit, Spring Analysis Tools: Wireshark, Volatility, OllyDbg, IDA Game Engine: Cocos2d-x, Corona
This is my blog at the first time -- random stuff
This is my second blog
My hobbies include
hobbiesComputer science


Welcome one and all to my website. Here are a few fun facts about me!
- I can play the guitar very well but have never had passion to play untill recently.
- I really enjoy fishing alone.
- I have competed in some tournaments for super smash bros melee
- For some reason my legs are super flexiable despite never stretching or doing yoga.
- I was on varsity swim team the first year I tried swim and dive in highschool


Warriors
Build your tribe with these epic warriors.
Build your tribe with these epic warriors.
Description: Description
Generation: Generation
Realm: Realm
Faction: Faction
Level: Level
Attack: Attack
Defense: Defend
Strategy: Strategy
Win Count: Win Count
Loss Count: Loss Count


Writing the perfect first sentence is damn near impossible. I’ve written two novels, a handful of short stories, and too many blog posts to count. Each time I started writing, I stared at a blank page for several minutes before conceding to the fact that, no, I still hadn’t figured out a way to avoid fudging my opening sentence the first time I write it.
For me, web development is the exact same way. Starting a project from scratch is by far the most intimidating part of the whole process. Even though I know I’ll end up rewriting and refactoring my code, my brain tells me that I’ve got to figure out everything before I can even begin. Why? The hell if I know.
I created this blog 7 months ago. Before that, I played with the idea of creating a dev blog for at least a month. You’ll notice that, 2/3 of a year after my brain gave birth to the original idea, it’s just now deciding to really do something about it.
“Why are you blaming your brain? You control your brain.
 Secondly, I’m not trying to fool anyone. Think about it: How often do you want to do something, but not actually do it? Hmm, doesn’t sound like you’re in complete control, now does it?
“But who is controlling my brain if not me? If I’m not my brain, what am I? What does it mean to be me? WHAT IS LIFE?”
Woah. Woah. Take a breath. There will be plenty of time for existential question in later chapters. This chapter is simply an introduction. As you can see, I’m trying out a different format from other web dev blogs. I’ve got two reason for this:
- Gimmicks motivate me
- I haven’t figured out what I’m trying to accomplish
I’m hoping that, as I refine this format, it will become more clear what exactly I want to achieve with this blog. This is definitely a rough start (meta posts are pointless when you don’t have an audience), but that’s the whole idea of this chapter. It’s a beginning, and beginnings are rough. Every. Single. Time.

I’m Mike Cornish. This is devStory.


"You might belong in Gryffindor,
Where dwell the brave at heart,
Their daring, nerve, and chivalry
Set Gryffindors apart"
"You might belong in Gryffindor,
Where dwell the brave at heart,
Their daring, nerve, and chivalry
Set Gryffindors apart"
The Gryffindor house emphasised the traits of courage as well as "daring, nerve, and chivalry and thus its members were generally regarded as brave, though sometimes to the point of recklessness. Some Gryffindors had also been noted to be short-tempered. Notably, Gryffindor house contributed many members to Dumbledore's Army and the Order of the Phoenix,although this may have been because the main members made it a point not to associate with other houses.
Gryffindor corresponded roughly to the element of fire, and it was for this reason that the colours scarlet and gold were chosen to represent the house.The colour of fire corresponded to that of a lion as well, with scarlet representing the mane and tail and gold representing the coat.
They take every oppurtunity and try to make best out of it . Because of this nature members of other houses, particularly Slytherin, sometimes felt that Gryffindors engaged in "pointless heroics".
Like Hufflepuffs, Gryffindor are highly determined. Their determination, however, is more self-focused. They will use their strong work ethic to fulfill their ambition and advance their own position. While this may seem self-absorbed, Slytherins recognise that by focusing on self-improvement, they can become better friends and family members and be more useful to society as a whole.
Godric Gryffindor (fl. c. 993) was an English wizard and one of the four founders of Hogwarts School of
Witchcraft and Wizardry. He was great friends with Salazar Slytherin, but opposed him when he later
thought that they should not accept Muggle-born students at Hogwarts. It is unknown when he died. In his
honour Gryffindor's birthplace became known as Godric's Hollow. Godric Gryffindor's portrait still
remains at Hogwarts.Read
more


EVOLUTION Reviewed by Jerry Saravia July 3rd, 2001
The beauty of comedy is that there are no rules and, quite simply, rules are made to be broken in the comedic arena. Director Ivan Reitman is often aware of this, as evidenced by his crude though subtly funny "Junior" and, his biggest hit, "Ghostbusters." Both films redefined the boundaries of good taste by imbuing crudeness with cleverness rather than cheap, desperate gags a'la "Austin Powers" that only serve to make the audience puke. Consider Arnold Schwarzeneger as a pregnant man in "Junior," a premise that is otherwise ripe for gross-out humor. Instead that film built its premise with wit and engaging repartee between Schwarzeneger and Danny DeVito.
"Evolution" does the same thing, imbuing crudeness with cleverness. The premise deals with a community college science teacher (and former scientist), Ira Kane (David Duchovny), who partners with a sharp, jocose scientist, Harry Block (Orlando Jones), to investigate a flaming meteor that has burned a hole through the ground into an underground cavern. Kane's class goes on a field trip to discover and study this meteor only to find some strange atmosphere has developed at an accelerated rate, not to mention some expanding and evolving wormlike creatures. Kane and Block realize this is no ordinary meteor - it is a fertile ground for alien creatures. At first, the creatures seem harmless in the form of butterflies until they later evolve into flying dinosaurs, raging blue monkeys and some shapeless matter in the form of large intestines.
The only way to approach "Evolution" is by checking your brain at the entrance door of the cinema before the first reel is projected. It is a one-note joke movie to be sure but it has moments of eye-opening special-effects, shrewd one-liners and moments where you will literally jump out of your seat. It mostly pokes fun at "Independence Day" right down to the climax involving those humongous intestines where a central digestive tract is the target for destruction - the expansive mass even looks like a spaceship. Mostly, the screenplay by David Diamond, David Weissman and Don Jakoby focuses on bodily functions and sexual entendres, as well as creepy monsters hiding inside harmless looking alien slugs and such. Many of the sexual entendres center around Julianne Moore as an assistant to a soldier-scientist (Ted Levine) - she is regarded at one point as an "icy goddess in desperate need of some humping." Speaking of the ravishing Moore, it is nice to see her as a clumsy woman who keeps tripping over objects every once in a while.
"Evolution" is cutesy nonsense and often quite funny and engaging. It is actually a breath of fresh air as compared to the gross-out humor so reminiscent of most comedies nowadays - wit and some dry humor are this film's virtues. As for performances, Duchvony and Jones make a delightful pair and Moore is lots of fun to watch - nice to see her handle comedy for a change in contrast with her dramatic roles. Only Ted Levine seems a little out of his element as the straight-faced soldier scientist, Dr. Woodman, who doesn't want Kane anywhere near these aliens.
"Evolution" is not as frantically funny or as visually inventive as Reitman's "Ghostbusters," but it will suffice in what has been a dry couple of years of laughless comedies.
For more reviews, check out JERRY AT THE MOVIES at http://moviething.com/members/movies/faust/JATMindex.shtml
E-mail me with any questions, comments or general complaints at<EMAIL_ADDRESS>or at<EMAIL_ADDRESS>========== X-RAMR-ID: 28926 X-Language: en X-RT-ReviewID: 237111 X-RT-TitleID: 1108206 X-RT-SourceID: 875 X-RT-AuthorID: 1314
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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Chapter 6 A Complete Example with Visualizations
In this section we exercise a typical standard use of SOMDisco and demonstrate how the supporting SOM visualization functions can be used to aid inference and cluster extraction from a trained SOM. The SOM is unique among vector quantizers in that it possesses a predefined output topology (typically 2-d, as is our setting) which can be harnessed to compactly express the information learned by an SOM for easy inspection.
For speed, all custom SOM visualizations are predicated on R’s base::plot
functionality (vs., e.g., ggplot). Each of the visualization functions demonstrated in this section are intended to work together (via plot layering) to allow simultaneous representation of multiple learned SOM quantities. Many customization options exist for the visualization functions; their individual help menus explain this optionality.
To begin, we will setup a new SOM object for SHGR training:
# Initialize a 20x20 SOM with hexagonal lattice
mysom = SOM$new()
mysom$initialize_SOM(SHGR$X, 20, 20, "hex")
## Setting lattice quantities
## ++ calculating lattice (x,y) coordinates ... done
## ++ calculating neuron lattice adjacencies ... done
## ++ calculating geodesic lattice distances between neurons ... done
## ++ assigning geodesic lattice distances to distlist ... done
## ++ calculating lattice tile vertices ... done
## ----------------------------------------------------------------
## Setting training data
## ----------------------------------------------------------------
## Setting network ranges
## ++ external = [-115.19, 1347.57]
## ++ internal = [0.00, 1.00]
## ++ change defaults via $set_netrng
## ----------------------------------------------------------------
## Initializing prototypes to random uniform
## ++ to set a particular random seed call set.seed() and then $set_W_runif()
## ++ to set to specific values call $set_W()
## ----------------------------------------------------------------
## Initializing prototype win frequencies to equiprobable
## ++ to set to specific values call $set_p(values)
## ----------------------------------------------------------------
## Setting default learning rates
## Storing the annealing schedule as:
## t alpha beta gamma sigma
## 16384 0.50 0.05 0.01 3
## 81920 0.25 0.03 0.00 2
## 163840 0.10 0.01 0.00 1
## 409600 0.05 0.01 0.00 1
## 1638400 0.01 0.00 0.00 1
## ++ change via $get_LRAS and $set_LRAS
## ----------------------------------------------------------------
# For reproducibility, re-initialize the prototypes with a given seed
set.seed(123)
mysom$set_W_runif()
The lattice can be immediately visualized after initialization.
# Setup an SOM plot window
vis_som_setup(SOM=mysom, lattice_coords = T)
# Add the lattice tiles as polygons
vis_som_tiles(SOM=mysom, add=T)
# Add the neurons as points
vis_som_neurons(SOM = mysom, add = T)
The SOM visualizations are intended to be setup via a call to vis_som_setup
then further augmented: in this case with the lattice tiles (whose shape is dependent upon lattice_type
: squares for “grid” types, and hexagons for “hex” types) and neurons. Most visualization functions have an add
argument, which if set to FALSE
will call vis_som_setup
internally (thus bypassing the need to explicitly layer the functions with individual calls).
We set the SOM to monitor every 10,000 steps and train for 500,000 steps:
mysom$set_monitoring_freq(10000)
mysom$train_SOM(500000, SHGR$X)
## SOM Training:
## ++ Reporting every 10000, monitoring every 10000steps
## 1 2 3 4 5 6 7 8
## 9 10 11 12 13 14 15 16
## 17 18 19 20 21 22 23 24
## 25 26 27 28 29 30 31 32
## 33 34 35 36 37 38 39 40
## 41 42 43 44 45 46 47 48
## 49 50
## End Training (current age = 500000)
## ----------------------------------------------------------------
## SOM Recall:
## ++ finding BMUs of data ... done
## ++ building CADJ matrix ... done
## ++ setting RF_size ... done
## ++ calculating SOM Entropy ... done
## ++ populating RF_members ... done
## ++ setting lattice fences ... done
If monitoring is activated, the quantities discussed in Section WHERE? can be visualized after training:
The top panel displays a heatmap of the RF_size
of each prototype’s Receptive Field. White tiles correspond to empty Receptive Fields, black to low and light blue to high RF_size
; combined, this is the mU-Matrix visualization of [6] Clusters in these data are readily visible, separated by areas of “dead” neurons, which do not represent any training data. The lower panel plots the RMSQE, QSI and Entropy (recorded every 10k training steps) vs training age. While RMSQE and Entropy have been somewhat stable over most of the current age of the SOM QSI has not, indicating further training may be beneficial. We continue training another 500k steps and re-create the monitoring visualization:
# Train another 500k steps and view the resulting age
mysom$train_SOM(500000, SHGR$X)
## SOM Training:
## ++ Reporting every 10000, monitoring every 10000steps
## 1 2 3 4 5 6 7 8
## 9 10 11 12 13 14 15 16
## 17 18 19 20 21 22 23 24
## 25 26 27 28 29 30 31 32
## 33 34 35 36 37 38 39 40
## 41 42 43 44 45 46 47 48
## 49 50
## End Training (current age = 1000000)
## ----------------------------------------------------------------
## SOM Recall:
## ++ finding BMUs of data ... done
## ++ building CADJ matrix ... done
## ++ setting RF_size ... done
## ++ calculating SOM Entropy ... done
## ++ populating RF_members ... done
## ++ setting lattice fences ... done
mysom$age
## [1] 1e+06
# Visualize Training
vis_som_training(SOM = mysom, vis.SOM = T, vis.mtr = T)
After training we can assess the organization of the lattice by plotting the 100-d SOM prototype vectors in their respective lattice tiles:
# Setup the lattice tiles
vis_som_setup(SOM = mysom, lattice_coords = T)
vis_som_tiles(SOM = mysom, add = T)
# Add the prototype vectors in lattice situ
vis_som_prototypes(SOM=mysom, add=T)
Clusters of similar prototype shapes are readily apparent, confirming the organization of this SOM.
We can explore these apparent clusters with the CONNvis visualization which requires the TopoRNet
package to be installed as well. Using the CONN
matrix just learned we define a TRN
object and compute the CONNvis statistics
mytrn = TRN$new()
mytrn$set_input_topo(mysom$W, mysom$CONN())
## Setting Input Space Topos
## ++ storing vertices ... done
## ++ storing edge list ... done
mytrn$set_output_topo(mysom$nu_xy, mysom$nu_ADJ)
## Setting Output Space Topos
## ++ storing vertices ... done
## ++ storing edge list ... done
## ++ computing folding lengths of forward network mapping ... done
## ++ computing folding lengths of backward network mapping ...
## Warning in mytrn$set_output_topo(mysom$nu_xy, mysom$nu_ADJ): NAs introduced by
## coercion to integer range
## done
## ++ computing topology preserving radius ... done
mytrn$set_CONNvis()
## CONNvis parameterization:++ computing local ranks ... done
## ++ computing local rank stats ... done
## ++ computing global ranks ... done
## ++ computing global rank stats ... done
## ++ computing output topology length stats ... done
which are passed, along with our trained SOM, to the function vis_som_CONNvis
:
CONNvis ranks each CONN
edge by local and global topological importance, indicated by color (red, blue, green, yellow, grayscale) and line width. As recognized above, many clusters are readily apparent on the SOM with the mU-Matrix visualization alone. CONNvis has further revealed evidence of separation of large clusters in the middle-left and middel-right of the SOM.
Since these training data are labeled we can project the data labels through the learned SOM mapping to expand the CONNvis findings.
Visualizations involving labels require an additional data frame known as a color table or ctab
to function which controls the coloring of each character label found in the dataset. The ctab
should be a data frame with columns label
(listing the distinct character labels) and color
giving a hex color code (or R color name) corresponding to each label. The SHGR data is packaged with the following color table:
head(SHGR$ctab)
## label color
## 1 A #0F52BA
## 2 B #FF7417
## 3 C #4CBB17
## 4 D #ED2939
## 5 E #B660CD
## 6 F #FFF200
which can be visualized via
With a color table set, the label distribution in each prototype’s Receptive Field can be visualized on the lattice as a proportional pie chart in each lattice tile:
# Setup the lattice tiles
vis_som_setup(SOM = mysom, lattice_coords = T)
vis_som_tiles(SOM = mysom, add = T)
# View the mapped label distribution
vis_som_labeldist(SOM=mysom, ctab=SHGR$ctab, add=T)
The neighborhoods on the SOM appear to be meaningful, with the majority of prototype Receptive Fields containing data of the same label. There is some visible mixing of labels in the RFs of “boundary prototypes” which sit between neighboring clusters, which is to be expected for data of any complexity. Often, an analyst may only care about the plurality winning label within each Receptive Field, which can be viewed by “painting” the SOM tiles with their corresponding label color, and annotating each tile with its label:
# Setup the lattice tiles, colored by prototype label
vis_som_setup(SOM = mysom, lattice_coords = T)
vis_som_label(SOM = mysom, ctab = SHGR$ctab, add = T)
# Annotate the tiles with the label
vis_som_annotate(SOM = mysom, add = T, text = mysom$RF_label)
The propagated labels display roughly the same prototype clustering as suggested by the CONNvis above, confirming both our suggested clustering and the quality of the SHGR labeling.
References
[6] E. Merényi, A. Jain, and T. Villmann, “Explicit magnification control of self-organizing maps for ‘forbidden’ data,” IEEE Transactions on Neural Networks, vol. 18, no. 3, pp. 786–797, 2007.


Before Change
current_file_version = get_hspy_format_version(f)
global default_version
if current_file_version > default_version:
warnings.warn(
"This file was written using a newer version of the " +
"HyperSpy hdf5 file format. I will attempt to load it, but, " +
"if I fail, it is likely that I will be more successful at " +
"this and other tasks if you upgrade me.")
experiments = []
exp_dict_list = []
if "Experiments" in f:
After Change
current_file_version = get_hspy_format_version(f)
global default_version
if current_file_version > default_version:
warnings.warn(
"This file was written using a newer version of the "
"HyperSpy hdf5 file format. I will attempt to load it, but, "
"if I fail, it is likely that I will be more successful at "
"this and other tasks if you upgrade me.")
experiments = []
exp_dict_list = []
if "Experiments" in f:


--- layout: page title: About header-img: "img/about-bg.png" ---
I'm currently learning to code at flatironschool.com. I love superheroes and coding.


Package-level declarations
Types
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PaymentMethodNonce representing a PayPal account.
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Exception for whenever the browser has returned an 'error' in its response.
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interface PayPalBrowserSwitchResultCallback
Callback for receiving result of onBrowserSwitchResult.
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Represents the parameters that are needed to start the PayPal Checkout flow
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Used to tokenize PayPal accounts.
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Represents the PayPal credit financing response.
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The currency and amount in a PayPal credit financing response
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interface PayPalFlowStartedCallback
Callback for receiving result of requestOneTimePayment and requestBillingAgreement and tokenizePayPalAccount.
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interface PayPalListener
Implement this interface to receive PayPal result notifications.
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The payment intent in the PayPal Checkout flow
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Represents the parameters that are needed to tokenize a PayPal account.
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Represents the parameters that are needed to start the PayPal Vault flow