#include <arg.hpp>
Public Types | |
| typedef QStringList | NamesList |
| Type of the list of argument's names. | |
| typedef QList< QChar > | FlagsList |
| Type of the list of argument's flags. | |
Public Member Functions | |
| virtual bool | isRequired () const =0 |
| virtual bool | isDefined () const =0 |
| virtual bool | isWithValue () const =0 |
| virtual void | check (const QChar &delimiter, FlagsList &alreadyKnownFlags, NamesList &alreadyKnownNames) const =0 |
| Check correctness of the names, flags and so on before parsing. | |
| virtual void | check () const =0 |
| Check correctness of the state of the argument after parsing. | |
| virtual const FlagsList & | flags () const |
| virtual const NamesList & | names () const |
| virtual QString | description () const =0 |
| virtual QString | longDescription () const =0 |
| If long description is empty it's better to return description(). | |
| virtual QtArgIface * | giveArgument (const QChar &flag)=0 |
| Should return pointer to the QtArgIface if this argument know how to do it, usually returns "this" if he does. | |
| virtual QtArgIface * | giveArgument (const QString &name)=0 |
| Should return pointer to the QtArgIface if this argument know how to do it, usually returns "this" if he does. | |
| virtual const QtArgCmdLineIface::QtArgumentsList & | arguments () const =0 |
| Usually returns list with "this" pointer or list with all handled arguments. | |
| virtual void | checkConstraint () const =0 |
| Check correctness of the argument constraint. | |
| virtual QString | getUsageString (const NamesList &namesList) const |
| Should return "USAGE" string for this argument. | |
| virtual QString | getHelpString (const NamesList &namesList) const |
| Should return "HELP" string for this argument. | |
Protected Member Functions | |
| QtArgIface (const NamesList &names, const FlagsList &flags) | |
| virtual int | process (QtArgCmdLineContext &context)=0 |
| Process argument. | |
| virtual void | visit (QtArgCmdLineContext &context)=0 |
| Process with visitor. | |
Protected Attributes | |
| FlagsList | m_flags |
| Flag of the argument. If defined. | |
| NamesList | m_names |
| List of the names of the argument. | |
Friends | |
| class | QtArgCmdLine |
Should be implemented by every class wanted to be an argument.
| names | Names of the argument. |
| flags | Flags of the argument. |
| virtual bool QtArgIface::isRequired | ( | ) | const [pure virtual] |
| virtual bool QtArgIface::isDefined | ( | ) | const [pure virtual] |
| virtual bool QtArgIface::isWithValue | ( | ) | const [pure virtual] |
| virtual void QtArgIface::check | ( | const QChar & | delimiter, | |
| FlagsList & | alreadyKnownFlags, | |||
| NamesList & | alreadyKnownNames | |||
| ) | const [pure virtual] |
Check correctness of the names, flags and so on before parsing.
| delimiter | Delimiter character. |
| alreadyKnownFlags | All known flags in every argument. |
| alreadyKnownNames | All known names in every argument. |
Implemented in QtXorArg.
| const QtArgIface::FlagsList & QtArgIface::flags | ( | ) | const [inline, virtual] |
| const QtArgIface::NamesList & QtArgIface::names | ( | ) | const [inline, virtual] |
| virtual QString QtArgIface::description | ( | ) | const [pure virtual] |
| virtual QString QtArgIface::longDescription | ( | ) | const [pure virtual] |
If long description is empty it's better to return description().
| virtual QtArgIface* QtArgIface::giveArgument | ( | const QChar & | flag | ) | [pure virtual] |
Should return pointer to the QtArgIface if this argument know how to do it, usually returns "this" if he does.
If this argument handles another arguments with flag flag than he should return pointer to this argument.
| Pointer | to the QtArgIface if flag flag determines this argument. | |
| NULL | if flag flag doesn't determine this argument. |
| flag | Is a flag that returned argument should own. If this argument doesn't own this flag or sub-arguments don't own this flag then returned value should be null-pointer. |
| virtual QtArgIface* QtArgIface::giveArgument | ( | const QString & | name | ) | [pure virtual] |
Should return pointer to the QtArgIface if this argument know how to do it, usually returns "this" if he does.
If this argument handles another arguments with name name than he should return pointer to this argument.
| Pointer | to the QtArgIface if name name determines this argument. | |
| NULL | if name name doesn't determine this argument. |
| name | Is a name that returned argument should own. If this argument doesn't own this name or sub-arguments don't own this name then returned value should be null-pointer. |
| virtual const QtArgCmdLineIface::QtArgumentsList& QtArgIface::arguments | ( | ) | const [pure virtual] |
| virtual void QtArgIface::checkConstraint | ( | ) | const [pure virtual] |
Check correctness of the argument constraint.
| QtArgContraintNotObservedEx | if constraint didn't observed. |
Implemented in QtArg, QtMultiArg, and QtXorArg.
| QString QtArgIface::getUsageString | ( | const NamesList & | namesList | ) | const [inline, virtual] |
Should return "USAGE" string for this argument.
For example: "-a%afterFlags%--arg %value%", where "%value%" is QtArgHelpPrinterIface::argValue and "%afterFlags%" is QtArgHelpPrinterIface::afterFlags.
| namesList | Names of all available arguments. |
| QString QtArgIface::getHelpString | ( | const NamesList & | namesList | ) | const [inline, virtual] |
Should return "HELP" string for this argument.
For spaces you have to use string constants from QtArgHelpPrinterIface interface.
| namesList | Names of all available arguments. |
| virtual int QtArgIface::process | ( | QtArgCmdLineContext & | context | ) | [protected, pure virtual] |
Process argument.
Can throw exceptions.
| context | Command line context. |
Implemented in QtArg, QtMultiArg, and QtXorArg.
| virtual void QtArgIface::visit | ( | QtArgCmdLineContext & | context | ) | [protected, pure virtual] |


--- layout: post mathjax: true comments: true date: 2012-12-09 title: [Project Euler] #25 Solution excerpt: | This page presents a Ruby solution to Project Euler Problem 25. tags: - project euler problem 25 solution - project euler problem 25 answer - project euler problem 25 ruby ---
The Fibonacci sequence is defined by the recurrence relation:
\[F_n = F_{n−1} + F_{n−2} \text{ where } F_1 = 1 \text{ and } F_2 = 1\]Hence the first 12 terms will be:
\[ \begin{aligned} F_1 &= 1 \\\\ F_2 &= 1 \\\\ F_3 &= 2 \\\\ F_4 &= 3 \\\\ F_5 &= 5 \\\\ F_6 &= 8 \\\\ F_7 &= 13 \\\\ F_8 &= 21 \\\\ F_9 &= 34 \\\\ F_{10} &= 55 \\\\ F_{11} &= 89 \\\\ F_{12} &= 144 \end{aligned} \]The 12th term, \(F_{12}\), is the first term to contain three digits.
What is the first term in the Fibonacci sequence to contain 1000 digits?
4782


--- layout: altpage title: "About" description: "A brief biography" header-img: "img/treeview.jpg" ---
This site is dedicated to computer science education.
Hello, my name is Eddie Rangel. I am a Software Engineer, teacher, and all around Californian. I am also a husband and father. We currently reside in Bakersfield, CA.
I was born and raised in Bakersfield, CA. I attended local schools in East Bakersfield and graduated from Highland High School. My first semester of my post secondary education started at Bakersfield College. After completing one semester and then withdrawing/failing my second semester, I enlisted in the United States Navy. I served on board the U.S.S Ramage (DDG-61) as an Operations Specialist where I worked in the Combat Information Center. I was on board during the completion of a Mediterraean Deployment in support of the campain in Kosovo. After I separated from the service, I was more focused and had a better sense of direction with what I wanted from college. In the Spring of 2002 I restarted on my academic career at Bakersfield College and have been on my current journey ever since.
I taught my first course as an Adjunct at the Delano Campus with a former collegue where we created a course around the fundamentals of Georgraphic Information Systems. I returned in the Fall of 2014 teaching in the Computer Science Department at the main BC campus. I have also taught as a Lecturer in the Computer & Electrical Engineering and Computer Science Department at CSUB.


Name: pick
Input: Object of class catalogue and constant or element.
Output: Entry of data type text.
Definition: Short description of the function, style of the old system manual
Argumentlist:
Argument No 1 (required) Object name.
Argument No 2 (required)
This argument can accept different types of value.
Argument No 3 (optional) Keyword:
Argument No 4 (optional) Number.
Argument No 5 (optional) Object name.
Discussion: Detailed explanation and examples


[ERROR] [FATAL]: could not create task: origami.v86
Linux is not enabled on your device. Use vmc enable from the shell to enable linux on your device.


Quiz #3 - Course Review
View Solutions
As the final quiz in the course, this was easily the most difficult one yet. How'd you do? If any of the questions left you twiddling your thumbs, be sure to revisit the applicable lesson in the course for another viewing!


This package gives you the exact first four permutation moments for the most commonly used quadratic form statistics, which need not be positive definite. The extension of this work to quadratic forms greatly expands the utility of density approximations for these problems, including for high-dimensional applications, where the statistics must be extreme in order to exceed stringent testing thresholds. Approximate p-values are obtained by matching the exact moments to the Pearson family of distributions using the PearsonDS package.
| Version: | 1.0 |
| Imports: | PearsonDS |
| Published: | 2014-07-15 |
| Author: | Yi-Hui Zhou |
| Maintainer: | Yi-Hui Zhou <yihui_zhou at ncsu.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | quad results |
| Reference manual: | quad.pdf |
| Package source: | quad_1.0.tar.gz |
| Windows binaries: | r-devel: quad_1.0.zip, r-release: quad_1.0.zip, r-oldrel: quad_1.0.zip |
| OS X binaries: | r-release: quad_1.0.tgz, r-oldrel: quad_1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=quad to link to this page.


Gyan-NamChain
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A chord diagram
represents flows or connections between several entities (called nodes
). Each entity is represented by a fragment on the outer part of the circular layout
. Then, arcs
are drawn between each entities. The size of the arc is proportional to the importance of the flow.
Here is an example displaying the number of people migrating from one country to another. Data used comes from this scientific publication from Gui J. Abel.
# Libraries
library(tidyverse)
library(viridis)
library(patchwork)
library(hrbrthemes)
library(circlize)
library(chorddiag) #devtools::install_github("mattflor/chorddiag")
# Load dataset from github
data <- read.table("https://raw.githubusercontent.com/holtzy/data_to_viz/master/Example_dataset/13_AdjacencyDirectedWeighted.csv", header=TRUE)
# short names
colnames(data) <- c("Africa", "East Asia", "Europe", "Latin Ame.", "North Ame.", "Oceania", "South Asia", "South East Asia", "Soviet Union", "West.Asia")
rownames(data) <- colnames(data)
# I need a long format
data_long <- data %>%
rownames_to_column %>%
gather(key = 'key', value = 'value', -rowname)
# parameters
circos.clear()
circos.par(start.degree = 90, gap.degree = 4, track.margin = c(-0.1, 0.1), points.overflow.warning = FALSE)
par(mar = rep(0, 4))
# color palette
mycolor <- viridis(10, alpha = 1, begin = 0, end = 1, option = "D")
mycolor <- mycolor[sample(1:10)]
# Base plot
chordDiagram(
x = data_long,
grid.col = mycolor,
transparency = 0.25,
directional = 1,
direction.type = c("arrows", "diffHeight"),
diffHeight = -0.04,
annotationTrack = "grid",
annotationTrackHeight = c(0.05, 0.1),
link.arr.type = "big.arrow",
link.sort = TRUE,
link.largest.ontop = TRUE)
# Add text and axis
circos.trackPlotRegion(
track.index = 1,
bg.border = NA,
panel.fun = function(x, y) {
xlim = get.cell.meta.data("xlim")
sector.index = get.cell.meta.data("sector.index")
# Add names to the sector.
circos.text(
x = mean(xlim),
y = 3.2,
labels = sector.index,
facing = "bending",
cex = 0.8
)
# Add graduation on axis
circos.axis(
h = "top",
major.at = seq(from = 0, to = xlim[2], by = ifelse(test = xlim[2]>10, yes = 2, no = 1)),
minor.ticks = 1,
major.tick.percentage = 0.5,
labels.niceFacing = FALSE)
}
)
Note: this plot is made using the circlize library, and very strongly inspired from the Migest package from Gui J. Abel. Read more about this story here.
Chord diagrams are eye catching and quite popular in data visualization. They allow to visualize weigthed
relationships between several entities. They are adapted for several specific situations that slightly modify the output and the way to read them:
Flow. This is the example decribed in the chord diagram above. But two ways to represent it:
Bipartite: nodes are grouped in a few categories. Connections go between categories but not within categories. In my opinion sankey diagrams are more adapted in this situation.
Note: this section is under construction.
Interactivity is a real plus to make the chord diagram understandable. In the example below, you can hover a specific group to highlight all its connections.
library(chorddiag)
m <- matrix(c(11975, 5871, 8916, 2868,
1951, 10048, 2060, 6171,
8010, 16145, 8090, 8045,
1013, 990, 940, 6907),
byrow = TRUE,
nrow = 4, ncol = 4)
haircolors <- c("black", "blonde", "brown", "red")
dimnames(m) <- list(have = haircolors,
prefer = haircolors)
groupColors <- c("#000000", "#FFDD89", "#957244", "#F26223")
chorddiag(m, groupColors = groupColors, groupnamePadding = 20)
Note: this example comes from the chorddiag package documentation.
The R and Python graph galleries are 2 websites providing hundreds of chart example, always providing the reproducible code. Click the button below to see how to build the chart you need with your favorite programing language.
R graph gallery Python gallery
Any thoughts on this? Found any mistake? Disagree? Please drop me a word on twitter or in the comment section below:
A work by Yan Holtz for data-to-viz.com


Troubleshooting¶
Missing .so error when running tensorflow¶
ensure LD_LIBRARY_PATH is correct
My GPU is suddenly not avilable (Ubuntu)¶
If your GPU was working previously, but suddenly is not accessable the the system. The following script may help the script at `scripts/fix_gpu.sh`
may help.
Testing GPU¶
Check if torch is detecting the GPU
python -c “import torch; print(torch.cuda.is_available());”
Running Atari Environment on Windows¶
If you get this error:
FileNotFoundError: Could not find module '..\atari_py\ale_interface\ale_c.dll' (or one of its dependencies). Try using the full path with constructor syntax.------------
Reinstall Atari from here: https://github.com/Kojoley/atari-py/releases


I don't understand people who ride with earbuds. The city's murmur and roar, birds chriping, the wind in my ears are a big part of the fun.
8/23/2010, 7:26:55 PM
Favs: 0
Retweets: 0
link--- layout: tweet ---
I don't understand people who ride with earbuds. The city's murmur and roar, birds chriping, the wind in my ears are a big part of the fun.
8/23/2010, 7:26:55 PM
Favs: 0
Retweets: 0
link


|
DMA Friends
2.0
|
Public Member Functions | |
| __construct ($apiKey) | |
| testConnection () | |
| getMemberID ($email) | |
| request ($verb, $endpoint, array $params=[]) | |
| __call ($method, $arguments) | |
Public Attributes | |
| const | MEMBER_STATUS_SUBSCRIBED = 'subscribed' |
| const | MEMBER_STATUS_UNSUBSCRIBED = 'unsubscribed' |
| const | MEMBER_STATUS_CLEANED = 'cleaned' |
| const | MEMBER_STAUTS_PENDING = 'pending' |
Protected Member Functions | |
| getClient () | |
Basic client to access Mailchimp api. All calls are asynchronous therefore they return a promise.
| DMA\Friends\Classes\Mailchimp\BaseMailchimpClient::__construct | ( | $apiKey | ) |
| $apiKey | stirng Mailchimp api key to user |
| DMA\Friends\Classes\Mailchimp\BaseMailchimpClient::__call | ( | $method, | |
| $arguments | |||
| ) |
| string | $method | |
| array | $arguments |
| Exception |
| DMA\Friends\Classes\Mailchimp\BaseMailchimpClient::getMemberID | ( | ) |
| DMA\Friends\Classes\Mailchimp\BaseMailchimpClient::testConnection | ( | ) |
| const DMA\Friends\Classes\Mailchimp\BaseMailchimpClient::MEMBER_STATUS_SUBSCRIBED = 'subscribed' |
Notes: Use member status as follow


{% load flowcells %}
{% count_barcode_reads object as num_barcodes %}
{% if num_barcodes > 0 and not object.index_histograms.all %}
No index statistics found so far.
Thus, we cannot compare sample sheet with real data.
Thus, only sanity checks (e.g., unique names and adapters) will be performed.
{% endif %}
#
Name
Project ID
Organism
i7 Kit
i7 Seq
i5 Kit
i5 Seq
Lanes
CC
{% if flowcell_libraries %}
{% for item in flowcell_libraries %}
{% include "flowcells/_library_item.html" %}
{% endfor %}
{% else %}


{% extends "base.html" %} {% block title %}404 - File Not Found {% endblock %} {% block content %}
We searched high and low
but your file eludes us still
Enjoy this haiku


styleAPP
First name:
Number:
booking_time:
task:
Attendant:
Select a person:
Peter Griffin
Lois Griffin
Glenn Quagmire
Joseph Swanson
Address:
Reserve
View Gallery
View Appointment
Contact Salon
styleAPP: Make a reservation with our salon today, at the comfort of your home!!!


Deals: Don't Miss These Exciting Official Nintendo UK Store Black Friday Bargains
Grab yourself a bargain
by Nintendo Life StaffYup, it's that time of year once again, folks! Black Friday is just around the corner and retailers are going big with deals all over the place. The Nintendo Official UK Store is no different, and we've rounded up the very best offers going for you below.
You'll find Nintendo Switch consoles, including the new Switch Lite, Nintendo 2DS XL consoles, a whole lot of games and accessories, free Labo kits, and plenty more besides, all placed under some tempting new deals. Feel free to take a browse through:
Black Friday Nintendo Switch & 2DS XL Hardware Deals
2DS XL Console + 2 Games + Accessory
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The Legend of Zelda: Link's Awakening + Red Rupee Lamp Pack
Nintendo Switch LEGO Game Pack
The Legend of Zelda: Breath of the Wild Pack
Nintendo Switch Co-Op Game Pack
Luigi's Mansion 3 & Boo Glow-in-the-Dark T-Shirt Pack
Taiko no Tatsujin: Drum ‘n’ Fun!
Starlink: Battle for Atlas Starter Pack
Wolfenstein: Youngblood Deluxe Edition
Super Mario Party + Mario Cap
Super Smash Bros. Ultimate + Battled Pad - Pikachu
Splatoon 2 Pack
Mario Kart 8 Deluxe Pack
Mortal Kombat 11 + Pixel Pals Lamp - Raiden
Yoshi's Crafted World + Yoshi's Rubber Keychain
Rayman Legends: Definitive Edition
Black Friday Accessory Deals
Super Mario Acorn Plains Figure set
Nintendo Classic Mini Deluxe Travel Case
Nintendo Switch Battle Pad - Luigi
NES Controller - Rubber Keychain
Nintendo Switch Battle Pad - Princess Peach
Nintendo Switch Analog Stick Caps - Super Mario
Black Friday Nintendo Clothing Deals
Luigi Cap
The Legend Of Zelda - Men's Hoody
Pokémon Ash and Pikachu Christmas Jumper
Donkey Kong Banana Print T-Shirt - Grey
Star Fox Zero Character T-Shirt - Multi
Fire Emblem Echoes: Shadows of Valentia T-Shirt
Star Fox Team Logo T-Shirt - Black
Splatoon SquidForce T-Shirt - Yellow
The Legend Of Zelda Link's Belts T-Shirt - Khaki
Donkey Kong All Over Print T-Shirt - Multi
Splatoon Firefin 8-Bit FishFry T-Shirt - Grey
Pokémon Pikachu All Over Jumper
Super Mario Odyssey Cappy Hat
Super Mario Luigi L Logo T-Shirt - Green
Pokemon All Over Pikachu Print T-Shirt - Black
Luigi L Logo Green Hoodie
Pokemon I Choose You Pokeball T-Shirt - Black
Super Mario Cap
Black Friday Nintendo - All Other Deals
Nintendo Game Boy Backpack
Pokémon Bulbasaur + Poké Ball Soft Toy
Pokémon My Friend Pikachu Soft Toy
Pokémon Squirtle + Dive Ball Soft Toy
Super Mario Lamp
Yoshi's Egg Coin Pouch
Super Mario Odyssey - Cappy Keychain
NES Controller - Metal Keychain
Nintendo Big NES Controller Backpack
Pokémon Team Rocket Gym Bag
Team Rocket Backpack
Pixel Pals Lamp: Mortal Kombat Edition - Raiden
Super Mario Hat - Rubber 3D Keychain
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Maps and Movement
Basic Movement
Move D6 squares. If you roll a 1, also take a Grit. (You may use this immediately to avoid exceeding your Max Grit.)
Use one Grit to move +1D6 squares.
Diagonals are allowed unless the wall blocks the corner.
Optional Rule Fixed Movement: Move 4 spaces per turn. (Continue to roll movement die for the purpose of recovering grit.
Escape
Roll D6 for Escape to move away from an enemy model.
Roll once per turn and keep the roll in case you move next to other enemies later in your movement.
KO'd
A hero may drag a KO'd hero at the cost of 2 MP per square (instead of the usual 1/square). Must in the same or adjacent square.
Large (L) Models
Large (L) and bigger models may push through other models.
- Enemy models may only displace smaller enemy models.
- Hero models (i.e. Sumo) may only displace smaller hero models.
- Swap spaces with displaced model.
Extra-Large (XL) Models
XL models pick one square under their base as the 'anchor' from which movement is calculated.
XL models can overlap walls so long as half their base is on the map.
When pushing through other models, the displaced model may move 2 or more squares as needed.
Map Tiles
If you are on a puzzle connector (half-square) you are considered to be on both tiles.
Barriers
Thick white lines are barriers.
-
Cannot move across barriers unless:
- You can also move through other models
- You can fly
- You are XL or larger
- Does not block line of sight
- Does not affect adjacency rules (e.g. Escape rolls)
- Does not block melee attacks
- Does not block bombs
Exertion Token [Heroes Only]
-
Gain 1 Exertion token when starting activation completely inside a barrier.
- If 3+ tokens, take D6 Wounds, ignoring Defense and Armor.
- Remove 1 Exertion token when starting activation outside of a barrier.
Lava Spaces
- Lava spaces have a Dodge value such as 5+.
- When Heroes enter a Lava square, Test Agility (Dodge) to avoid taking D3 Burning tokens.
- Enemies are not affected when moving normally.
- Enemies take D3 Burning tokens if knocked into a Lava Square by a Hero.
Gateways
Movement through gateways is instantons, as if the squares are adjacent.
Melee Attacks
Melee attacks through gates work as if adjacent.
Line of Sight
You may only trance line-of-sight through a gateway if you are standing next to it.
Lantern
The lantern works through a gateway as if the tiles were adjacent.


Check your inbox.
We've emailed you instructions for setting your password. You should receive the email shortly!
{% extends 'base.html' %} {% block title %}Email Sent{% endblock %} {% block content %}
Check your inbox.
We've emailed you instructions for setting your password. You should receive the email shortly!


The bug led to improper computation of custom spectral indices in the case that their formula included addition or subtraction operations on reflectance values (e.g., something like \(\frac{(\rho_{NIR}+0.1)}{\rho_{Red}}\), with \(\rho\) indicating a reflectance).
Values of the following Additional Spectral Indices selectable using the MODIStsp GUI:
, in the case that the Apply Scale/Offset option was set to “No”
Values of any custom spectral indexes added by the user, in case they included additive or subtractive coefficients.
, in the case that the Apply Scale/Offset option was set to “No”
Values of spectral indexes available in MODIS HDF images as original sds layers (e.g., EVI in MOD13Q1)
Values of any additional / custom spectral indexes in case they did not include additive or subtractive coefficients, or the Apply Scale/Offset option was set to “Yes”
The bug is now fixed on the GitHub version. A patched release will be made available on CRAN as soon as possible.
Unfortunately, if you have time series processed with the old version falling in the “What is affected” category, there’s nothing you can do, save for reprocessing them.
We are truly sorry for the problem, which somehow managed to slip under the radar until now. We hope it will not bring you too much trouble!
This is so basic that can easily go unnoticed. So it’s better to document it…
MODIS reflectances are stored in HDF layers as integers with a 10000 scale factor (e.g., a 0.1 reflectance is stored as 1000). If you need to “manually” compute an index such as SAVI:
\(SAVI = \frac{(\rho_{NIR} - \rho_{Red})}{(\rho_{NIR} + \rho_{Red} + 0.5)} * (1 + 0.5)\)).
starting from MODIS reflectances, you must take care of multiplying the MODIS data by 10E-4 beforehand. Your formula then becomes:
\(SAVI = \frac{(0.0001 * b2_{NIR} - 0.0001 * b1_{Red})}{0.0001 * b2_{NIR} + 0.0001 * b1_{Red} + 0.5} * (1 + 0.5)\)).
, otherwise the additive constants (in this case, the \(+ 0.5\) in the denominator) would be made practically irrelevant.


PrivacyRegulation
- legislation_sector : String
The identifier of the set of legislation rules this rule\nbelongs to e.g. the UK data protection act.
- Private Information Source : String
The source of the private data
- Private Information Type : String
The type of private information; e.g. is it information that identifies the user (e.g. id number)? is it location information about the user? Is it about their activities?
- Enum:
- Identification
- Shared Identification
- Geographic
- Temporal
- Network and relationships
- Objects
- Behavioural
- Beliefs
- Measurements
- Action : String
The action being carried out on the data
- Required Consent : String
The type of consent that must be followed
- Enum:
- opt-in
- opt-out


About Jim Corbett National Park
Jim Corbett National Park, which is a part of the larger Corbett Tiger Reserve,
a Project Tiger Reserve lies in the Nainital district of Uttarakhand.
The magical landscape of Corbett is well known and fabled for its tiger richness.
Established in the year 1936 as Hailey National Park, Corbett has the glory of being
India's oldest and most prestigious National Park. It is also being honored as the place
where Project Tiger was first launched in 1973. This unique tiger territory is best known
as the father who gave birth of the Project Tiger in India to protect the most endangered
species and the Royal of India called Tigers.
Spans over an extent of 520 square kilometers, its whole area comprises of hills, marshy depressions, riverine belts, grasslands and large lake. It is among the few tiger reserves in India that allows overnight stays in the lap of the National Park. Nature watch and wildlife viewing in the park is done in an open four wheeler Jeep and on elephant back. Sheltering a healthy population of tigers and rare species like Otters and the endemic fish eating crocodile, the national park is one of the most sought after destinations for the wildlife buffs. Dhikala, situated at the border of the extensive Patil Dun valley, is the most popular destination in Corbett because of its superb location and sheer abundance of wildlife present.
If you love bird watching then Corbett is virtual haven for such tourists. Corbett
and its adjoining area is a home to more than 650 species of residents and migratory birds.
Particularly Dhikala is fine place to look for birds of prey, more than over 50 species of
raptors alone shows the healthy biodiversity of the area. Their multiplex behavior is
intriguing and their varied songs are very much pleasing to the ear. In a nutshell,
this finest national park of India is well known for rich and varied wildlife including royal
Bengal tiger, elephant, four to five species of deer and rich birdlife.
The Tourist Zones:
In order to promote tourism in the region Corbett National Park has been divided into five different zones. These are the marked buffer or core area of the park where visitors can be part of wildlife safari and can enjoy the intriguing behavior of the animals with bare eyes at proximity.
Bijrani Safari Zone :
Bijrani Zone is very popular tourist's hub because of its abundant natural beauty and open grasslands. The entry gate of the zone is located at only 01 Km from Ramnagar city.
Jhirna Safari Zone :
Jhirna is another important tourist zone in the Jim Corbett National park that is open for tourist round the year. Jhirna Gate is located at 16 km from Ramnagar city.
Dhela Safari Zone :
Dhela is a new eco tourism zone in Corbett National Park included in tiger reserve zone in November 2014. This is the only area in the reserve's buffer zone open to tourists in CTR. The zone is retaining the attention of large number of tourist because of its wealthy flora and fauna, open throughout the year, located at an approximate distance of 13 Km from Ramnagar City.
Dhikala Zone :
Being the largest and most varied zone in Corbett, Dhikala is famous for its abundant natural beauty as well as offering the best sight for exotic fauna. The entry gate is 18 km away from Ramnagar city. Night stay inside the Dhikala Tourism Zone is highly recommended for the hard core wildlife enthusiasts.
Durga Devi Zone :
Located on the north-eastern boundary of the Jim Corbett National Park, Durga Devi zone is the heaven on planet earth for those who are fond of bird watching. Entry gate is located at an approximate distance of 36 km from Ramnagar city.
Sitabani Buffer Zone :
Sitabani Zone doesn't fall under the Corbett Tiger Reserve area. If you are fond of serene ambiance of the natural beauty, must visit Sitabani area.
Right Season to Plan Your Visit to Jim Corbett National Park
Winter Season - Within October to February


Poems of Emily Brontë
by Emily Brontë
Faith and Despondency
Additional Information
- Year Published: 1846
- Language: English
- Country of Origin: England
- Source: Bronte, A., Bronte, C., and Bronte, E. (1846). Poems by Currer, Ellis, and Acton Bell. London, England: Aylott and Jones.
-
Readability:
- Flesch–Kincaid Level: 8.0
- Word Count: 488
- Genre: Poetry
- Keywords: death
- ✎ Cite This
Downloads
“The winter wind is loud and wild,
Come close to me, my darling child;
Forsake thy books, and mateless play;
And, while the night is gathering gray,
We’ll talk its pensive hours away;—
“Ierne, round our sheltered hall
November’s gusts unheeded call;
Not one faint breath can enter here
Enough to wave my daughter’s hair,
And I am glad to watch the blaze
Glance from her eyes, with mimic rays;
To feel her cheek, so softly pressed,
In happy quiet on my breast,
“But, yet, even this tranquillity
Brings bitter, restless thoughts to me;
And, in the red fire’s cheerful glow,
I think of deep glens, blocked with snow;
I dream of moor, and misty hill,
Where evening closes dark and chill;
For, lone, among the mountains cold,
Lie those that I have loved of old.
And my heart aches, in hopeless pain,
Exhausted with repinings vain,
That I shall greet them ne’er again!”
“Father, in early infancy,
When you were far beyond the sea,
Such thoughts were tyrants over me!
I often sat, for hours together,
Through the long nights of angry weather,
Raised on my pillow, to descry
The dim moon struggling in the sky;
Or, with strained ear, to catch the shock,
Of rock with wave, and wave with rock;
So would I fearful vigil keep,
And, all for listening, never sleep.
But this world’s life has much to dread,
Not so, my Father, with the dead.
“Oh! not for them, should we despair,
The grave is drear, but they are not there;
Their dust is mingled with the sod,
Their happy souls are gone to God!

Ah! my dear father, tell me why?
For, if your former words were true,
How useless would such sorrow be;
As wise, to mourn the seed which grew
Unnoticed on its parent tree,
Because it fell in fertile earth,
And sprang up to a glorious birth—
Struck deep its root, and lifted high
Its green boughs in the breezy sky.
"But, I’ll not fear, I will not weep
For those whose bodies rest in sleep,—
I know there is a blessed shore,
Opening its ports for me and mine;
And, gazing Time’s wide waters o’er,
I weary for that land divine,
Where we were born, where you and I
Shall meet our dearest, when we die;
From suffering and corruption free,
Restored into the Deity.”
“Well hast thou spoken, sweet, trustful child!
And wiser than thy sire;
And worldly tempests, raging wild,
Shall strengthen thy desire—
Thy fervent hope, through storm and foam,
Through wind and ocean’s roar,
To reach, at last, the eternal home,
The steadfast, changeless shore!”


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The <input type="date">
defines a date picker. The resulting value includes the year, month, and day.
Tip: Always add the <label> tag for best accessibility practices!
Example:
Show a date control:
<form action="/action_page.php">
<label for="birthday">Birthday:</label>
<input type="date" id="birthday" name="birthday">
<input type="submit">
</form>
Note: type="date" is not supported in Safari or Internet Explorer 11 (or earlier).


Client for the 'Orcid.org' 'API' (<https://orcid.org/>). Functions included for searching for people, searching by 'DOI', and searching by 'Orcid' 'ID'.
| Version: | 0.4.0 |
| Imports: | crul (≥ 0.5.0), httr, fauxpas, jsonlite (≥ 1.5), xml2 (≥ 1.1.1), tibble (≥ 1.3.0), data.table |
| Suggests: | testthat, knitr |
| Published: | 2018-02-11 |
| Author: | Scott Chamberlain [aut, cre] |
| Maintainer: | Scott Chamberlain <myrmecocystus at gmail.com> |
| BugReports: | https://github.com/ropensci/rorcid/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/ropensci/rorcid |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| In views: | WebTechnologies |
| CRAN checks: | rorcid results |
| Reference manual: | rorcid.pdf |
| Vignettes: |
Introduction to the rorcid package |
| Package source: | rorcid_0.4.0.tar.gz |
| Windows binaries: | r-devel: rorcid_0.4.0.zip, r-release: rorcid_0.4.0.zip, r-oldrel: rorcid_0.4.0.zip |
| OS X binaries: | r-release: rorcid_0.4.0.tgz, r-oldrel: rorcid_0.4.0.tgz |
| Old sources: | rorcid archive |
Please use the canonical form https://CRAN.R-project.org/package=rorcid to link to this page.


Sporting Life Premier League Weekly Podcast: Tom Carnduff, George Pitts and Dale Tempest joined by Paul Parker
by Sporting LifeSporting Life's Tom Carnduff and George Pitts are joined by Sky Bet's Dale Tempest to review all the latest Premier League events.
Duncan Ferguson had an immediate impact at Everton as they beat Chelsea 3-1 at Goodison Park. Should he get the job on a full-time basis? Or is it important that they don't get carried away in the moment?
It's been a great week for Manchester United after they secured bragging rights in the derby. We hear from former United defender Paul Parker who gives us his thoughts on the current situation.
Leicester keep on winning. Are they serious title contenders? Or would you back Liverpool going the entire season unbeaten?
We discuss all that and much more.


Paragrafo 2
Paragrafo 3
Paragrafo 4
Paragrafo 1
Your files have downloaded successfully into the My Downloads folder.
Currently using 36% of your storage space.


11. kolo
Cardiff vs Brighton
Huddersfield vs West Ham
Leicester vs Burnley
Newcastle vs Bournemouth
Southampton vs Watford
Crystal Palace vs Spurs
Liverpool vs Fulham
Chelsea vs Everton
Arsenal vs Wolves
Man City vs Man Utd
12. kolo
Brighton vs Leicester
Everton vs Cardiff
Fulham vs Southampton
Man Utd vs Crystal Palace
Watford vs Liverpool
Watford vs Liverpool
West Ham vs Man City
Spurs vs Chelsa
Bournemuth vs Arsenal
Wolves vs Huddersfield
13. kolo
Burnley vs Newcastle
Cardiff vs Wolves
Crystal Palace vs Burnley
Huddersfield vs Brighton
Leicester vs Watford
Man City vs Bournemouth
Newcastle vs West Ham
Southampton vs Man Utd
Chelsea vs Fulham
Arsenal vs Spurs
14. kolo
Liverpool vs Everton
Bournemouth vs Huddersfield
Brighton vs Crystal Palace
West Ham vs Cardiff
Watford vs Man City
Burnley vs Liverpool
Everton vs Newcastle
Wolves vs Chelsea
Man Utd vs Arsenal
Spurs vs Southampton


After Step 1 has completed. The program will begin scanning the OU website for available downloads.
Note: this may take some time.
Since progress is hard to gauge at this step, a 'marquee' progress bar continually updates. Additionally, any update messages are displayed in a 'running log'. These are both pictured below in Figure 2.
Once the program has finished gathering a list of new content, it is compared against the items in your library.
If you would like to cancel: click on the Stop button. This will abandon the download process (your user profile will be signed-out) and you will have to start again from Step 1.


{% load static %}
Below are examples of ten "tell-tale" features that the AI-generated images tend to exhibit.
Again, these images feature the faces of people who do not exist.
The features are divided into three categories: Background, Asymmetry, and Abnormalities.
Note that perhaps none of these features will appear on a given AI-generated image.
Note also that these are not the only features that can be used to distinguish the AI-generated images.
The features are a guide; it is important to also apply an element of common sense.
In the main question sequence, you will be tested on your ability to distinguish these images from images of faces of people who do exist.
You will be quizzed on your memory of these signs later.
Please study these carefully.


Easily create or join a local nanny share with Hapu
Hapu is Airbnb for nanny share. Share your home, nanny and costs and create new flexible, affordable solutions in childcare.
See Hapu in action (27 seconds)
Hapu is Airbnb for nanny share. Share your home, nanny and costs and create new flexible, affordable solutions in childcare.
See Hapu in action (27 seconds)
Wednesday, Thursday, Friday - 7:30 - 5:30
You have a fantastic home, a fantastic nanny and wouldn't cutting your costs in half be, well, fantastic?! If only it was easy to connect with other parents to share your costs? Well now it is, with Hapy! Hapu means tribe and it's our foundational 3 tribal principles that empowers you to create and manage your own tribe. A tribe that together has the power to create new affordable solutions in childcare that work for you and your community.
Ready to get started?Leave us your name and email and we'll update you as soon as a share becomes available in your area!
Sometimes it's hard enough just sharing a restaurant bill. Try sharing that bill week in, week out and you might encounter more than a few snares. But not with Hapu. Simply set your rates and our automated payment system takes care of the rest. You need never talk money or who owes what.
Read how Bridget's share (without Hapu) ended over $15Childcare is for the long term. And you need a framework you can count on that gives your share long term viability and success. That's why we've defined Hapu around our three tribal principles: clearly defined process, transparency over money and equility of participation.
Read how Hapu's tribal background defines our appWith the Hapu daily diary your nanny will be able to update you and your sharers with photos and commentary of the day. You and the sharers will receive notifications and you'll be able to login to view the daily adventures of your little ones. We can't wait!
Takes less than 5 minutes to get started
Create Your Nanny Share
Takes less than 5 minutes


9.1 Prove that Universal Instantiation is sound and that Existential Instantiation produces an inferentially equivalent knowledge base.
9.2 From ${Likes}({Jerry},{IceCream})$ it seems reasonable to infer ${\exists,x\;\;} {Likes}(x,{IceCream})$. Write down a general inference rule, , that sanctions this inference. State carefully the conditions that must be satisfied by the variables and terms involved.
9.3 Suppose a knowledge base contains just one sentence, $\exists,x\ {AsHighAs}(x,{Everest})$. Which of the following are legitimate results of applying Existential Instantiation?
${AsHighAs}({Everest},{Everest})$.
${AsHighAs}({Kilimanjaro},{Everest})$.
${AsHighAs}({Kilimanjaro},{Everest}) \land {AsHighAs}({BenNevis},{Everest})$\ (after two applications).
9.4 For each pair of atomic sentences, give the most general unifier if it exists:
$P(A,B,B)$, $P(x,y,z)$.
$Q(y,G(A,B))$, $Q(G(x,x),y)$.
${Older}({Father}(y),y)$, ${Older}({Father}(x),{John})$.
${Knows}({Father}(y),y)$, ${Knows}(x,x)$.
9.5 For each pair of atomic sentences, give the most general unifier if it exists:
$P(A,A,B)$, $P(x,y,z)$.
$Q(y,G(A,B))$, $Q(G(x,x),y)$.
${Older}({Father}(y),y)$, ${Older}({Father}(x),{Jerry})$.
${Knows}({Father}(y),y)$, ${Knows}(x,x)$.
9.6 [subsumption-lattice-exercise]Consider the subsumption lattices shown in Figure subsumption-lattice-figure (page subsumption-lattice-figure).
Construct the lattice for the sentence ${Employs}({Mother}({John}),{Father}({Richard}))$.
Construct the lattice for the sentence ${Employs}({IBM},y)$ (“Everyone works for IBM”). Remember to include every kind of query that unifies with the sentence.
Assume that indexes each sentence under every node in its subsumption lattice. Explain how should work when some of these sentences contain variables; use as examples the sentences in (a) and (b) and the query ${Employs}(x,{Father}(x))$.
9.7 [fol-horses-exercise]Write down logical representations for the following sentences, suitable for use with Generalized Modus Ponens:
Horses, cows, and pigs are mammals.
An offspring of a horse is a horse.
Bluebeard is a horse.
Bluebeard is Charlie’s parent.
Offspring and parent are inverse relations.
Every mammal has a parent.
9.8 These questions concern concern issues with substitution and Skolemization.
Given the premise ${\forall,x\;\;} {\exists,y\;\;} P(x,y)$, it is not valid to conclude that ${\exists,q\;\;} P(q,q)$. Give an example of a predicate $P$ where the first is true but the second is false.
Suppose that an inference engine is incorrectly written with the occurs check omitted, so that it allows a literal like $P(x,F(x))$ to be unified with $P(q,q)$. (As mentioned, most standard implementations of Prolog actually do allow this.) Show that such an inference engine will allow the conclusion ${\exists,y\;\;} P(q,q)$ to be inferred from the premise ${\forall,x\;\;} {\exists,y\;\;} P(x,y)$.
Suppose that a procedure that converts first-order logic to clausal form incorrectly Skolemizes ${\forall,x\;\;} {\exists,y\;\;} P(x,y)$ to $P(x,Sk0)$—that is, it replaces $y$ by a Skolem constant rather than by a Skolem function of $x$. Show that an inference engine that uses such a procedure will likewise allow ${\exists,q\;\;} P(q,q)$ to be inferred from the premise ${\forall,x\;\;} {\exists,y\;\;} P(x,y)$.
A common error among students is to suppose that, in unification, one is allowed to substitute a term for a Skolem constant instead of for a variable. For instance, they will say that the formulas $P(Sk1)$ and $P(A)$ can be unified under the substitution ${ Sk1/A }$. Give an example where this leads to an invalid inference.
9.9 This question considers Horn KBs, such as the following: $$\begin{array}{l} P(F(x)) {\:\;{\Rightarrow}\:\;}P(x)\ Q(x) {\:\;{\Rightarrow}\:\;}P(F(x))\ P(A)\ Q(B) \end{array}$$ Let FC be a breadth-first forward-chaining algorithm that repeatedly adds all consequences of currently satisfied rules; let BC be a depth-first left-to-right backward-chaining algorithm that tries clauses in the order given in the KB. Which of the following are true?
FC will infer the literal $Q(A)$.
FC will infer the literal $P(B)$.
If FC has failed to infer a given literal, then it is not entailed by the KB.
BC will return ${true}$ given the query $P(B)$.
If BC does not return ${true}$ given a query literal, then it is not entailed by the KB.
9.10 [csp-clause-exercise]Explain how to write any given 3-SAT problem of arbitrary size using a single first-order definite clause and no more than 30 ground facts.
9.11 Suppose you are given the following axioms:
- $0 \leq 3$.
- $7 \leq 9$.
- ${\forall,x\;\;} \; \; x \leq x$.
- ${\forall,x\;\;} \; \; x \leq x+0$.
- ${\forall,x\;\;} \; \; x+0 \leq x$.
- ${\forall,x,y\;\;} \; \; x+y \leq y+x$.
- ${\forall,w,x,y,z\;\;} \; \; w \leq y$ $\wedge$ $x \leq z$ ${\:\;{\Rightarrow}\:\;}$ $w+x \leq y+z$.
- ${\forall,x,y,z\;\;} \; \; x \leq y \wedge y \leq z \: {\:\;{\Rightarrow}\:\;}\: x \leq z$
Give a backward-chaining proof of the sentence $7 \leq 3+9$. (Be sure, of course, to use only the axioms given here, not anything else you may know about arithmetic.) Show only the steps that leads to success, not the irrelevant steps.
Give a forward-chaining proof of the sentence $7 \leq 3+9$. Again, show only the steps that lead to success.
9.12 Suppose you are given the following axioms:
$0 \leq 4$.
$5 \leq 9$.
${\forall,x\;\;} \; \; x \leq x$.
${\forall,x\;\;} \; \; x \leq x+0$.
${\forall,x\;\;} \; \; x+0 \leq x$.
${\forall,x,y\;\;} \; \; x+y \leq y+x$.
${\forall,w,x,y,z\;\;} \; \; w \leq y$ $\wedge$ $x \leq z {\:\;{\Rightarrow}\:\;}$ $w+x \leq y+z$.
${\forall,x,y,z\;\;} \; \; x \leq y \wedge y \leq z \: {\:\;{\Rightarrow}\:\;}\: x \leq z$
Give a backward-chaining proof of the sentence $5 \leq 4+9$. (Be sure, of course, to use only the axioms given here, not anything else you may know about arithmetic.) Show only the steps that leads to success, not the irrelevant steps.
Give a forward-chaining proof of the sentence $5 \leq 4+9$. Again, show only the steps that lead to success.
9.13 A popular children’s riddle is “Brothers and sisters have I none, but that man’s father is my father’s son.” Use the rules of the family domain (Section kinship-domain-section on page kinship-domain-section) to show who that man is. You may apply any of the inference methods described in this chapter. Why do you think that this riddle is difficult?
9.14 Suppose we put into a logical knowledge base a segment of the U.S. census data listing the age, city of residence, date of birth, and mother of every person, using social security numbers as identifying constants for each person. Thus, George’s age is given by $ { Age } ( \mbox {{ 443 }} - { 65 } - { 1282 }} , {56}) $. Which of the following indexing schemes S1–S5 enable an efficient solution for which of the queries Q1–Q4 (assuming normal backward chaining)?
9.15 [standardize-failure-exercise]One might suppose that we can avoid the problem of variable conflict in unification during backward chaining by standardizing apart all of the sentences in the knowledge base once and for all. Show that, for some sentences, this approach cannot work. (Hint: Consider a sentence in which one part unifies with another.)
9.16 In this exercise, use the sentences you wrote in Exercise fol-horses-exercise to answer a question by using a backward-chaining algorithm.
Draw the proof tree generated by an exhaustive backward-chaining algorithm for the query ${\exists,h\;\;}{Horse}(h)$, where clauses are matched in the order given.
What do you notice about this domain?
How many solutions for $h$ actually follow from your sentences?
Can you think of a way to find all of them? (Hint: See @Smith+al:1986.)
9.17 [bc-trace-exercise]Trace the execution of the backward-chaining algorithm in Figure backward-chaining-algorithm (page backward-chaining-algorithm) when it is applied to solve the crime problem (page west-problem-page). Show the sequence of values taken on by the ${goals}$ variable, and arrange them into a tree.
9.18 The following Prolog code defines a predicate P. (Remember that uppercase terms are variables, not constants, in Prolog.)
P(X,[X|Y]).
P(X,[Y|Z]) :- P(X,Z).
Show proof trees and solutions for the queries P(A,[2,1,3]) and P(2,[1,A,3]).
What standard list operation does P represent?
9.19 The following Prolog code defines a predicate P. (Remember that uppercase terms are variables, not constants, in Prolog.)
P(X,[X|Y]).
P(X,[Y|Z]) :- P(X,Z).
Show proof trees and solutions for the queries P(A,[1,2,3]) and P(2,[1,A,3]).
What standard list operation does P represent?
9.20 This exercise looks at sorting in Prolog.
Write Prolog clauses that define the predicate sorted(L), which is true if and only if list L is sorted in ascending order.
Write a Prolog definition for the predicate perm(L,M), which is true if and only if L is a permutation of M.
Define sort(L,M) (M is a sorted version of L) using perm and sorted.
Run sort on longer and longer lists until you lose patience. What is the time complexity of your program?
Write a faster sorting algorithm, such as insertion sort or quicksort, in Prolog.
9.21 [diff-simplify-exercise]This exercise looks at the recursive application of rewrite rules, using logic programming. A rewrite rule (or demodulator in terminology) is an equation with a specified direction. For example, the rewrite rule $x+0 \rightarrow x$ suggests replacing any expression that matches $x+0$ with the expression $x$. Rewrite rules are a key component of equational reasoning systems. Use the predicate rewrite(X,Y) to represent rewrite rules. For example, the earlier rewrite rule is written as rewrite(X+0,X). Some terms are primitive and cannot be further simplified; thus, we write primitive(0) to say that 0 is a primitive term.
Write a definition of a predicate simplify(X,Y), that is true when Y is a simplified version of X—that is, when no further rewrite rules apply to any subexpression of Y.
Write a collection of rules for the simplification of expressions involving arithmetic operators, and apply your simplification algorithm to some sample expressions.
Write a collection of rewrite rules for symbolic differentiation, and use them along with your simplification rules to differentiate and simplify expressions involving arithmetic expressions, including exponentiation.
9.22 This exercise considers the implementation of search algorithms in Prolog. Suppose that successor(X,Y) is true when state Y is a successor of state X; and that goal(X) is true when X is a goal state. Write a definition for solve(X,P), which means that P is a path (list of states) beginning with X, ending in a goal state, and consisting of a sequence of legal steps as defined by successor. You will find that depth-first search is the easiest way to do this. How easy would it be to add heuristic search control?
9.23 Suppose a knowledge base contains just the following first-order Horn clauses:
$$ Ancestor(Mother(x),x) $$ $$ Ancestor(x,y) \land Ancestor(y,z) \implies Ancestor(x,z) $$
Consider a forward chaining algorithm that, on the $j$th iteration, terminates if the KB contains a sentence that unifies with the query, else adds to the KB every atomic sentence that can be inferred from the sentences already in the KB after iteration $j-1$.
For each of the following queries, say whether the algorithm will (1) give an answer (if so, write down that answer); or (2) terminate with no answer; or (3) never terminate.
$Ancestor(Mother(y),John)$
$Ancestor(Mother(Mother(y)),John)$
$Ancestor(Mother(Mother(Mother(y))),Mother(y))$
$Ancestor(Mother(John),Mother(Mother(John)))$
Can a resolution algorithm prove the sentence $\lnot Ancestor(John,John)$ from the original knowledge base? Explain how, or why not.
Suppose we add the assertion that $\lnot(Mother(x){{,=,}}x)$ and augment the resolution algorithm with inference rules for equality. Now what is the answer to (b)?
9.24 Let $\cal L$ be the first-order language with a single predicate $S(p,q)$, meaning “$p$ shaves $q$.” Assume a domain of people.
Consider the sentence “There exists a person $P$ who shaves every one who does not shave themselves, and only people that do not shave themselves.” Express this in $\cal L$.
Convert the sentence in (a) to clausal form.
Construct a resolution proof to show that the clauses in (b) are inherently inconsistent. (Note: you do not need any additional axioms.)
9.25 How can resolution be used to show that a sentence is valid? Unsatisfiable?
9.26 Construct an example of two clauses that can be resolved together in two different ways giving two different outcomes.
9.27 From “Horses are animals,” it follows that “The head of a horse is the head of an animal.” Demonstrate that this inference is valid by carrying out the following steps:
Translate the premise and the conclusion into the language of first-order logic. Use three predicates: ${HeadOf}(h,x)$ (meaning “$h$ is the head of $x$”), ${Horse}(x)$, and ${Animal}(x)$.
Negate the conclusion, and convert the premise and the negated conclusion into conjunctive normal form.
Use resolution to show that the conclusion follows from the premise.
9.28 From “Sheep are animals,” it follows that “The head of a sheep is the head of an animal.” Demonstrate that this inference is valid by carrying out the following steps:
Translate the premise and the conclusion into the language of first-order logic. Use three predicates: ${HeadOf}(h,x)$ (meaning “$h$ is the head of $x$”), ${Sheep}(x)$, and ${Animal}(x)$.
Negate the conclusion, and convert the premise and the negated conclusion into conjunctive normal form.
Use resolution to show that the conclusion follows from the premise.
9.29 [quantifier-order-exercise]Here are two sentences in the language of first-order logic:
(A) ${\forall,x\;\;} {\exists,y\;\;} ( x \geq y )$
(B) ${\exists,y\;\;} {\forall,x\;\;} ( x \geq y )$
Assume that the variables range over all the natural numbers $0,1,2,\ldots, \infty$ and that the “$\geq$” predicate means “is greater than or equal to.” Under this interpretation, translate (A) and (B) into English.
Is (A) true under this interpretation?
Is (B) true under this interpretation?
Does (A) logically entail (B)?
Does (B) logically entail (A)?
Using resolution, try to prove that (A) follows from (B). Do this even if you think that (B) does not logically entail (A); continue until the proof breaks down and you cannot proceed (if it does break down). Show the unifying substitution for each resolution step. If the proof fails, explain exactly where, how, and why it breaks down.
Now try to prove that (B) follows from (A).
9.30 Resolution can produce nonconstructive proofs for queries with variables, so we had to introduce special mechanisms to extract definite answers. Explain why this issue does not arise with knowledge bases containing only definite clauses.
9.31 We said in this chapter that resolution cannot be used to generate all logical consequences of a set of sentences. Can any algorithm do this?


A portable hygienic pattern matcher.
This is a full superset of the popular match
package by Andrew Wright, written in fully portable syntax-rules
and thus preserving hygiene.
The most notable extensions are the ability to use non-linear
patterns - patterns in which the same identifier occurs multiple
times, tail patterns after ellipsis, and the experimental tree patterns.
Patterns are written to look like the printed representation of
the objects they match. The basic usage is
(match expr (pat body ...) ...)
where the result of expr
is matched against each pattern in
turn, and the corresponding body is evaluated for the first to
succeed. Thus, a list of three elements matches a list of three
elements.
(let ((ls (list 1 2 3))) (match ls ((1 2 3) #t)))
=> #t
If no patterns match an error is signalled. Identifiers will match anything, and make the corresponding binding available in the body.
(match (list 1 2 3) ((a b c) b))
=> 2
If the same identifier occurs multiple times, the first instance
will match anything, but subsequent instances must match a value
which is equal?
to the first.
(match (list 1 2 1) ((a a b) 1) ((a b a) 2))
=> 2
The special identifier _
matches anything, no matter how
many times it is used, and does not bind the result in the body.
(match (list 1 2 1) ((_ _ b) 1) ((a b a) 2))
=> 1
To match a literal identifier (or list or any other literal), use
quote
.
(match 'a ('b 1) ('a 2))
=> 2
Analogous to its normal usage in scheme, quasiquote
can
be used to quote a mostly literally matching object with selected
parts unquoted.
(match (list 1 2 3) (`(1 ,b ,c) (list b c)))
=> (2 3)
Often you want to match any number of a repeated pattern. Inside
a list pattern you can append ...
after an element to
match zero or more of that pattern (like a regexp Kleene star).
(match (list 1 2) ((1 2 3 ...) #t))
=> #t
(match (list 1 2 3) ((1 2 3 ...) #t))
=> #t
(match (list 1 2 3 3 3) ((1 2 3 ...) #t))
=> #t
Pattern variables matched inside the repeated pattern are bound to a list of each matching instance in the body.
(match (list 1 2) ((a b c ...) c))
=> ()
(match (list 1 2 3) ((a b c ...) c))
=> (3)
(match (list 1 2 3 4 5) ((a b c ...) c))
=> (3 4 5)
More than one ...
may not be used in the same list, since
this would require exponential backtracking in the general case.
However, ...
need not be the final element in the list,
and may be succeeded by a fixed number of patterns.
(match (list 1 2 3 4) ((a b c ... d e) c))
=> ()
(match (list 1 2 3 4 5) ((a b c ... d e) c))
=> (3)
(match (list 1 2 3 4 5 6 7) ((a b c ... d e) c))
=> (3 4 5)
___
is provided as an alias for ...
when it is
inconvenient to use the ellipsis (as in a syntax-rules template).
The ..1
syntax is exactly like the ...
except
that it matches one or more repetitions (like a regexp "+").
(match (list 1 2) ((a b c ..1) c))
ERROR: match: "no matching pattern"
(match (list 1 2 3) ((a b c ..1) c))
=> (3)
The boolean operators and
, or
and not
can be used to group and negate patterns analogously to their
Scheme counterparts.
The and
operator ensures that all subpatterns match.
This operator is often used with the idiom (and x pat)
to
bind x
to the entire value that matches pat
(c.f. "as-patterns" in ML or Haskell). Another common use is in
conjunction with not
patterns to match a general case
with certain exceptions.
(match 1 ((and) #t))
=> #t
(match 1 ((and x) x))
=> 1
(match 1 ((and x 1) x))
=> 1
The or
operator ensures that at least one subpattern
matches. If the same identifier occurs in different subpatterns,
it is matched independently. All identifiers from all subpatterns
are bound if the or
operator matches, but the binding is
only defined for identifiers from the subpattern which matched.
(match 1 ((or) #t) (else #f))
=> #f
(match 1 ((or x) x))
=> 1
(match 1 ((or x 2) x))
=> 1
The not
operator succeeds if the given pattern doesn't
match. None of the identifiers used are available in the body.
(match 1 ((not 2) #t))
=> #t
The more general operator ?
can be used to provide a
predicate. The usage is (? predicate pat ...)
where
predicate
is a Scheme expression evaluating to a predicate
called on the value to match, and any optional patterns after the
predicate are then matched as in an and
pattern.
(match 1 ((? odd? x) x))
=> 1
The field operator =
is used to extract an arbitrary
field and match against it. It is useful for more complex or
conditional destructuring that can't be more directly expressed in
the pattern syntax. The usage is (= field pat)
, where
field
can be any expression, and should result in a
procedure of one argument, which is applied to the value to match
to generate a new value to match against pat
.
Thus the pattern (and (= car x) (= cdr y))
is equivalent
to (x . y)
, except it will result in an immediate error
if the value isn't a pair.
(match '(1 . 2) ((= car x) x))
=> 1
(match 4 ((= square x) x))
=> 16
The record operator $
is used as a concise way to match
records defined by SRFI-9 (or SRFI-99). The usage is
($ rtd field ...)
, where rtd
should be the record
type descriptor specified as the first argument to
define-record-type
, and each field
is a subpattern
matched against the fields of the record in order. Not all fields
must be present.
(let ()
(define-record-type employee
(make-employee name title)
employee?
(name get-name)
(title get-title))
(match (make-employee "Bob" "Doctor")
(($ employee n t) (list t n))))
=> ("Doctor" "Bob")
For records with more fields it can be helpful to match them by
name rather than position. For this you can use the @
operator, originally a Gauche extension:
(let ()
(define-record-type employee
(make-employee name title)
employee?
(name get-name)
(title get-title))
(match (make-employee "Bob" "Doctor")
((@ employee (title t) (name n)) (list t n))))
=> ("Doctor" "Bob")
The set!
and get!
operators are used to bind an
identifier to the setter and getter of a field, respectively. The
setter is a procedure of one argument, which mutates the field to
that argument. The getter is a procedure of no arguments which
returns the current value of the field.
(let ((x (cons 1 2))) (match x ((1 . (set! s)) (s 3) x)))
=> (1 . 3)
(match '(1 . 2) ((1 . (get! g)) (g)))
=> 2
The new operator ***
can be used to search a tree for
subpatterns. A pattern of the form (x *** y)
represents
the subpattern y
located somewhere in a tree where the path
from the current object to y
can be seen as a list of the
form (x ...)
. y
can immediately match the current
object in which case the path is the empty list. In a sense it's
a 2-dimensional version of the ...
pattern.
As a common case the pattern (_ *** y)
can be used to
search for y
anywhere in a tree, regardless of the path
used.
(match '(a (a (a b))) ((x *** 'b) x))
=> (a a a)
(match '(a (b) (c (d e) (f g))) ((x *** 'g) x))
=> (a c f)
(match expr (pattern . body) ...)
(match expr (pattern (=> failure) . body) ...)
The result of expr
is matched against each pattern
in
turn, according to the pattern rules described in the previous
section, until the the first pattern
matches. When a match is
found, the corresponding body
s are evaluated in order,
and the result of the last expression is returned as the result
of the entire match
. If a failure
is provided,
then it is bound to a procedure of no arguments which continues,
processing at the next pattern
. If no pattern
matches,
an error is signalled.
(match-lambda (pattern . body) ...)
Shortcut for lambda
+ match
. Creates a
procedure of one argument, and matches that argument against each
clause.
(match-lambda* (pattern . body) ...)
Similar to match-lambda
. Creates a procedure of any
number of arguments, and matches the argument list against each
clause.
(match-let ((var value) ...) . body)
(match-let loop ((var init) ...) . body)
Matches each var to the corresponding expression, and evaluates
the body with all match variables in scope. Raises an error if
any of the expressions fail to match. Syntax analogous to named
let can also be used for recursive functions which match on their
arguments as in match-lambda*
.
(match-letrec ((var value) ...) . body)
Similar to match-let
, but analogously to letrec
matches and binds the variables with all match variables in scope.
(match-let* ((var value) ...) body ...)
Similar to match-let
, but analogously to let*
matches and binds the variables in sequence, with preceding match
variables in scope.


BoxStack
Classic
Game Over!
Play Again?


jMath.nonlinear
Class RootFinding
java.lang.Object
jMath.nonlinear.RootFinding
public class RootFinding
- extends java.lang.Object
|
Method Summary |
static double |
fzero(Function1Var f,
double a,
double b)
computes zero of funciton f in interval [a,b] where a sign change must exist
somewhere between a and b |
static double |
fzero(Function1Var f,
double a,
double b,
double t)
fzero seeks the root of a function F(X) in an interval [A,B] using Brent's Method
Discussion:
The interval [A,B] must be a change of sign interval for F. |
| Methods inherited from class java.lang.Object |
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
RootFinding
public RootFinding()
fzero
public static double fzero(Function1Var f,
double a,
double b,
double t)
- fzero seeks the root of a function F(X) in an interval [A,B] using Brent's Method
Discussion:
The interval [A,B] must be a change of sign interval for F.
That is, F(A) and F(B) must be of opposite signs. Then
assuming that F is continuous implies the existence of at least
one value C between A and B for which F(C) = 0.
The location of the zero is determined to within an accuracy
of 6 * MACHEPS * abs ( C ) + 2 * T.
Modified:
17 Feb. 2010
Author:
Original FORTRAN77 version by Richard Brent
JAVA version by S. Andrew Ning
Reference:
Richard Brent,
Algorithms for Minimization Without Derivatives,
Dover, 2002,
ISBN: 0-486-41998-3,
LC: QA402.5.B74.
Parameters:
Input, real A, B, the endpoints of the change of sign interval.
Input, real T, a positive error tolerance.
Input, real value = F ( x ), the name of a user-supplied
function which evaluates the function whose zero is being sought.
Output, real VALUE, the estimated value of a zero of
the function F.
fzero
public static double fzero(Function1Var f,
double a,
double b)
- computes zero of funciton f in interval [a,b] where a sign change must exist
somewhere between a and b
- Parameters:
f
- a
- b
-
- Returns:


Cultural Blog
Thinking Style
June 4th, 2015
What's my thinking style? Abstract Sequential According to my thinking style, what's hard for me is having too little time to deal with a subject thoroughly. I find that especially true in DBC. However, I've realized that there are effective ways to improve results with proper time management such as time boxing. My learning style suggests that I prefer to follow a plan, which is true. Books are organized in this linear fashion, and I do find that I learn effectively following along in a book. I definitely have a growth mindset. I actually took part of the Learning to Learn course that was recommended as an optional resource. I intend to finish that course to improve my learning style in general.


You will have 75 seconds to answer the following code-related questions. Keep in mind that incorrect answers will penalize your score and decrease your time by 10 seconds. Good Luck!


Stories of Asia is a storytelling media platform founded in 2019 to empower the Asian community with a voice. By featuring workplace and business stories, we seek to inspire, share lessons and change perceptions in the market.
Learn more about us here!
82 Playfair Rd, #10-01 D’Lithium, Singapore 368001


---
layout: post
title: People - Project ETHOS
---
# ETHOS developers at the University of Iceland
|
Dr Jesús Zavala Franco (PI) Associate Professor, Faculty of Physical Sciences, University of Iceland PhD, 2007, Universidad Nacional Autónoma de México email<EMAIL_ADDRESS>website: https://notendur.hi.is/~jzavala/index.html |
|
Sebastian Bohr PhD student, Faculty of Physical Sciences, University of Iceland email<EMAIL_ADDRESS>website: |
|
Jan Burger PhD student, Faculty of Physical Sciences, University of Iceland email<EMAIL_ADDRESS>website: |
|
Dr Mark Lovell Postdoctoral Fellow, Faculty of Physical Sciences, University of Iceland email<EMAIL_ADDRESS>|
|
Dr Chaichalit Srisawat Postdoctoral Fellow, Faculty of Physical Sciences, University of Iceland PhD, 2015, University of Sussex email<EMAIL_ADDRESS>|
|
Prof Torsten Bringmann Professor, Department of Physics, University of Oslo PhD, 2005, University of Stockholm email<EMAIL_ADDRESS>website: http://www.mn.uio.no/fysikk/english/people/aca/troms/ |
|
Dr Francis-Yan Cyr-Racine Postdoctoral Fellow, Department of Physics, Harvard University PhD, 2012, University of British Columbia email<EMAIL_ADDRESS>website: http://users.physics.harvard.edu/~fcyrraci/index.html |
|
Prof Christoph Pfrommer Professor, Leibniz Institute for Astrophysics Potsdam PhD, 2005, Max Planck Institute for Astrophysics email<EMAIL_ADDRESS>website: http://www.cita.utoronto.ca/~pfrommer/ |
|
Dr Kris Sigurdson Associate Professor, Department of Physics and Astronomy, University of British Columbia PhD, 2005, California Institute of Technology email<EMAIL_ADDRESS>website: http://www.phas.ubc.ca/~krs/ |
|
Dr Mark Vogelsberger Assistant Professor, Department of Physics, MIT PhD, 2010, Max Planck Institute for Astrophysics email<EMAIL_ADDRESS>website: http://web.mit.edu/physics/people/faculty/vogelsberger_mark.html |


--- title: Decoder keywords: fastai sidebar: home_sidebar summary: "Functions to set up the dynamic decoders for use in the dynamic U-Net architecture. In particular, we utilize PyTorch hooks here." description: "Functions to set up the dynamic decoders for use in the dynamic U-Net architecture. In particular, we utilize PyTorch hooks here." ---
We need to automatically construct the Decoder using the architecture given in the encoder. To do so, we'll define some helper layers as nn.Module
s.
ConvLayer
is just a general form of a convolution, ReLU, and batch normalization layer in sequence, with some empirical bets practices (e.g. initializing using $\frac{1}{\sqrt{5}}$ for all the weights in the convolutional layer, as per the FastAI course).ConcatLayer
is just a thin wrapper on the torch.cat
function that concatenates all inputs along the channel dimension, assuming inputs are image batches, i.e. they have shape (batch size, num channels, height, width).LambdaLayer
is just a thin wrapper of a generic lambda functionupconv2x2
is a utility function for setting up convolutions that upsample an image. As mentioned above, in the U-Net architecture, we first concatenate the encoder output with the corresponding decoder input, so that when we upsample an image (i.e. from $(h, w)$ in size to $(2h, 2w)$ in size), we always have 2 times the amount of information (in this case, from having two times the number of channels). Accordingly, we will always convolve using an atrous convolution (where we dilate the kernel, rather than inserting 0s in the input to the convolutional layer), followed by the actual upsampling operation (using bilinear upsampling).Note: these functions remain exposed for now, but the goal is to not need them to be exposed.
Some specifics in how the decoder is coordinated (here, the first layer means the input encoding layer of the encoder, and the last layer indicates the last layer in the encoder). These details are not super important, and are probably understandable if you inspect the U-Net architecture image more closely.
conv3x3
before upsampling, then fed through a regular conv3x3
two times, then a conv1x1
to output the right number of channels for segmentation outputconv3x3
that first halves number of channels to upsample, then a regular conv3x3
DecoderConnect
class.Again, these details don't particularly matter, unless you're implementing the architecture yourself. The important point is that upsampling always happens after a concatenation of the encoder's output with the corresponding input to the corresponding level of the decoder.
As a quick sanity check, we can initialize this to make sure everything is in order.
#example
model = DecoderConnect(512, (7, 7))
#example
model


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Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 4
Soak eight small wooden skewers for ten minutes in cold water.
Place the mince, garlic, coriander and cumin into a bowl and season well with salt and freshly ground black pepper. Mix together well, then divide the mixture into eight equal portions.
Press each portion of the mince mixture around a wooden skewer to form a sausage, three quarters the length of the skewer, then place onto a plate in the fridge to chill.
Heat a griddle pan until hot. Place the skewers onto the griddle and cook for 2-3 minutes on each side, or until completely cooked through.
Heat a separate frying pan until hot. Add the fig slices and fry on each side for 30 seconds.
Remove the figs and set aside, then add the halloumi and cook on each side for one minute, or until golden-brown all over.
Whisk the lemon juice, olive oil, salt and freshly ground black pepper together in a clean bowl, then add the salad leaves. Toss well to coat.
To serve, place arrange slices of fig and halloumi onto the centre of each plate. Place a pile of the dressed salad leaves on top, then top each dish with two koftas. Drizzle over a little of the remaining dressing and serve.


WITNESS LIST Judicial Affairs Committee October 26, 2000-1:30P Appellate Redistricting On: Hinojosa, Justice Federico G. (Self) Seerden, Chief Justice Robert J. (Self) Appellate Redistricting & Oversight On: Schneider, Chief Justice Michael (Self and First Court of Appeals) Oversight: Child Support On: Baldwin, Howard (OAGCSED)


Executives
President
As one of the founding members of BSys and a Software Engineering student with a Health Science background, I'm excited to bring a taste of biotech to Concordia's student base! My main interest is currently in the OpenBCI and variations in electrode placement, but I'll help you get set up with whatever inspires you most.
Vice-President
VP and one of the founders of the club. Currently pursuing a Bachelor's Degree in Software Engineering at Concordia University. His passion is what makes him strive to learn as much as he can about every aspects of computer science. He is always jumping (literally) at any occasions to learn and develop new skills. As a great teammate and helper, he is looking to contribute as much as he can so that BSYS becomes a leader in Biosystems developments (and to make the world a better place).
VP Finance
Our VP Finance, description to come!
VP Communications
Our VP Communications, description to come!


src/interfaces/IDetector.ts
Interface used to configure, load and get detections from the camera.
Methods |
| destroy |
destroy()
|
|
Defined in src/interfaces/IDetector.ts:28
|
|
This function takes care of appropriately tearing down the detector instance by unregistering all previously setup subscriptions. In case the detector has been configured to generate detection data without streaming main, then this method will make sure the camera stops generating detection events and stops it's internal streaming.
Returns :
Promise<void>
A void function. |
| init |
init()
|
|
Defined in src/interfaces/IDetector.ts:15
|
|
Convenience function for setting detection and/or framing data event listeners.
Returns :
Promise<void>
A void function. |
| on | ||||||||||||
on(message: string, callback: any)
|
||||||||||||
|
Defined in src/interfaces/IDetector.ts:39
|
||||||||||||
|
EventEmitter
Parameters :
Returns :
any
|
| once | ||||||||||||
once(message: string, callback: any)
|
||||||||||||
|
Defined in src/interfaces/IDetector.ts:50
|
||||||||||||
|
EventEmitter
Parameters :
Returns :
any
|
| removeAllListeners | ||||||||
removeAllListeners(message: string)
|
||||||||
|
Defined in src/interfaces/IDetector.ts:71
|
||||||||
|
EventEmitter
Parameters :
Returns :
any
|
| removeListener | ||||||||||||
removeListener(message: string, callbackFn: any)
|
||||||||||||
|
Defined in src/interfaces/IDetector.ts:62
|
||||||||||||
|
EventEmitter on the caught event.
Parameters :
Returns :
any
|
In order to use the detector interface you need to make sure that the autozoom feature is enabled on the camera (see the ICnnControl interface for documentation on how to do it).
The detector interface allows you to subscribe to detection and/or framing data from the camera. From version 0.4.0 we support getting detection data from Detector without having to stream the camera on the host machine.
NOTE that this is the default behavior now.
It is still possible to get detections the old way, where you only get detection when streaming the camera on the host machine. We show you below how to do that!
/*
We suppose that the sdk has been initialized and autozoom feature is enabled
and running.
*/
...
/**
* Get an instance of detector implementation from the
* camera manager.
*/
const detector = cameraManager.getDetector();
// Always call `init`
await detector.init();
/*
Detector class implements EventEmitter and therefore implements
all the event emitter methods. Below we show how to listen
to detector events such as DETECTIONS and FRAMING.
*/
detector.on('DETECTIONS', (detectionList) => {
// Process the array
});
detector.on('FRAMING', (framingInfo) => {
// Process framing info
});
/**
* When you are done, call `destroy` method to properly teardown
* the detection instance.
*/
await detector.destroy();
...
!! NOTE !! When tearing down your application which is using the detector object, it is important that you call destroy
method before closing the host application. Not doing so will leave the camera streaming internally after you have closed the application which might lead to confusion. The camera will stop generating detection data at some point when it detects that no host application is consuming its data. However, it is strongly recommended to properly teardown the detector instance from the host application.
If you would like to configure the detector so that you get detection events only and only when the user starts streaming the camera on the host machine, then the following code sinppet illustrates how to do just that:
...
/**
* The `getDetector` method accepts options documented on
* `IDetectorOpts` interface. One of the options allows you
* to configure the detector to get detection only when
* camera is streaming on the host machine. This option is
* called `DOWS` short for Detections Only When Streaming.
*/
const detector = await cameraManager.getDetector({
DOWS: true,
});
// Call init
await detector.init();
// Setup detection event listener
detector.on('DETECTIONS', (detectionList) => {
// Your code here
});
// Teardown
await detector.destroy();
...
The detector class can emit the following events:
| Event | Description |
|---|---|
DETECTIONS |
Subscribe to this event to get detections from the camera. At the moment only the People class is supported from the detector. |
FRAMING |
Subscribe to this event to get information about the framing. Framing data consists of a property called bbox which contains the coordinates (x, y, width and height) representing the framing data. The framer configuration on the camera will always make sure that the perfect framing of the people in the view is selected. |
export default interface IDetector {
/**
* Convenience function for setting detection and/or
* framing data event listeners.
*
* @returns {Promise<any>} A void function.
* @memberof IDetector
*/
init(): Promise<void>;
/**
* This function takes care of appropriately tearing down the
* detector instance by unregistering all previously setup
* subscriptions. In case the detector has been configured
* to generate detection data without streaming main, then
* this method will make sure the camera stops generating
* detection events and stops it's internal streaming.
*
* @returns {Promise<void>} A void function.
* @memberof IDetector
*/
destroy(): Promise<void>;
/**
* EventEmitter `on` listener. It is used for emitting detector events
* such as DETECTOR_START, DETECTOR_STOP, DETECTIONS etc. The list of
* detector events together with all the other camera events can be found in the `Events.ts` class.
*
* @param {string} message The message use to setup the listener for.
* @param {*} callback A callback used to perform actions on the caught event.
* @memberof IDetector
*/
on(message: string, callback: any);
/**
* EventEmitter `once` listener. Similar to the `#on` function,
* instead here the listener is invoked only once and that is
* the first time the message is emitted from the `Detector` implementation class.
*
* @param {string} message The message use to setup the listener for
* @param {*} callback A callback used to perform actions on the caught event.
* @memberof IDetector
*/
once(message: string, callback: any);
/**
* EventEmitter `removeListener` method. Unregisters any event listeners
* setup on the detector class (that is either the detection or framing
* data event listeners).
*
* @param {string} message The message used to setup the listener
* @param {*} callbackFn The callback function used to perform actions
* on the caught event.
* @memberof IDetector
*/
removeListener(message: string, callbackFn: any);
/**
* EventEmitter `removeAllListeners` method. Unregisters all event
* listeners setup on the given message name.
*
* @param {string} message The message used to setup the listeners
* @memberof IDetector
*/
removeAllListeners(message: string);
}


What does it mean to be human?
Submitted to the Big History Project on the aforementioned topic:
The Petty Thief
Created for the high school competition TSA as a suspense video. We even composed the music for this one!
Saving Private Pen
Also created for TSA, in 48 hours at an on-site competition:
The Call
Also created for TSA, in 48 hours at an on-site competition:
The Final Con
Also created for TSA, also a suspense video:
Note: essentially all of these videos were made as joint projects with my close friend, Praveen Jayakumar


Notes / Domino upgrade cheat sheet
Over time I've written a number of entries related to Domino upgrades, Domino administration and helped many customers to succeed in implementing the latest versions. This entry summarizes what works and provides links to the relevant articles and information serving as a convenient entry point. It is linked in the sidebar and I will keep it current.
Just to be clear: this post mentions several commercial offerings from IBM Business Partners. You need to evaluate for yourself how an investment into these offerings makes sense for you.
As usual YMMV
- Make sure you know how the ideal Domino upgrade looks like
- You need a plan, a project plan. Head over to MindPlan and get your version of a mindmapping cum project planning Notes composite application
- First make yourself knowledgeable by browsing the IBM Fixlist. It is always a good idea to know what is coming
- If you plan to jump versions, you should be on the latest patch level of your current version. IBM Fix Central provides the latest patches to get you there
- Visit Upgrade Central to get the latest recommendation
- Make sure you build a high performance Domino server for best user experience
- If that server is a new one, you can minimise your downtime when upgrading
- Revisit you Replication and Routing Architecture. It might be just fine, it might need some TLC
- If your Domino server runs on Windows you need to take care of disk fragmentation. Use OpenNTF's DominoDefrag or the commercially supported DefragNSF. If you run Notes clients on Windows, fragmentation is an issue there too. DefragNSF has a client module to take care of that
- When rolling out your client upgrades you need to rethink your installation location and installation type (I strongly advocate shared install), especially when you want to be Windows7 compliant. Smart Upgrade can't change location or type, so you want to invest into the Panagenda Marvel Client or the BCC Client genie for upgrade, roaming and management
- Disk fragmentation is an issue on your clients too. The minimum you can do about it is to incorporate a defragmentation run while installing using the free MyDiskDefrag. Better you look for continous defragmentation. Both DefragNSF and the Panagenda Marvel Client support continuous client defrag. You can also consider to use MyDefragGUI which provides a screen saver that defrags whenever your machine is idle (Added March 09, 2011)
- Revisit your eMail retention policies. Once you understand the difference between Backup and Archival, you might consider an eMail life cycle solution like the iQ.Suite
- If you would like to optimise your infrastructure and benchmark it against thousands of other installations, give TrustFactory a call and schedule a Health Check
- To improve the quality of web mail (both your use of webmail and the Internet eMail going in and out) consider Geniisoft's iFidelity plug-in for your Domino server
- While cleaning out your installation you might want to bring some order to your group names. It saves a lot of administrative time. To switch your user administration into auto-pilot mode consider HASDL FiRM, the Federated identity and Resource Management
- Give your users the opportunity to share ideas and deploy IdeJam by Elguji
- Last not least. Make your users more productive! Adopt GTD (after you read the book) and deploy the eProductivity template
Just to be clear: this post mentions several commercial offerings from IBM Business Partners. You need to evaluate for yourself how an investment into these offerings makes sense for you.
As usual YMMV
Posted by Stephan H Wissel on 18 December 2010 | Comments (1) | categories: Show-N-Tell Thursday


Each PrimeNG theme exports its own color palette.
Colors are exported as CSS variables and used with the standard var syntax such as var(--text-color).
These are common variables used throughout the theme.
| Variable | Description |
|---|---|
| --text-color | Font text color. |
| --text-secondary-color | Muted font text color with a secondary level. |
| --primary-color | Primary color of the theme. |
| --primary-color-text | Text color when background is primary color. |
| --font-family | Font family of the theme. |
A palette consists of 9 colors where each color provides tints/shades from 50 to 900.
In addition, a theme brings a special palette called surfaces that can be used as the base when designing the surface layers and separators.


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But one thing is certain: from now until August 17, STORY is all about COOL – from how it looks and tastes to what it feels like. We’ve teamed up with Quirky and GE to put a coolly inventive spin on things. They’ll be introducing us to a Aros, a smart new air conditioner that tracks users’ habits and budget, to automatically maintain the perfect at-home temperature.


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Home
2 User Manual > 2.4 Functions > 2.4.3 Function Name Parameters
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Functions can have two parameter lists: a <name> parameter list (enclosed in []) and
a regular parameter list (enclosed in ()).
The name parameter list is used in a number of different ways.
-
It can be used as a generic parameter list.
For example a sort function could take a name parameter that is the type
of elements to be sorted and regular parameter that is an array of
elements of that type.
(Note that since @x:Act has dynamic typing, this extra type parameter is not
really required since the element type could be found just by looking at the regular
parameter. Even so, there are cases where making the type an explicit parameter
helps to write clearer code.)
-
Another kind of generic parameter list can be seen in the Units type.
-
Since @x:Act has a stack-based execution model, there are no function closures
that exists after the scope instance where the function declaration was executed
has exited.
Since name parameters tightly bound as part of the function name, they can
serve as kind of closure mechanism (see curry).
-
Iterators use the regular parameter list to pass
in the loop body function, so other parameters to the iterator must
be passed as name parameters.


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Psalms 119:132
Look thou upon me, and be merciful unto me, as thou usest to do unto those that love thy name.


I’m a Full Stack Web Developer and US Navy Veteran that’s self-driven and skilled at building responsive web applications from front to back. I’m passionate about giving ideas life, learning new technologies, and working with a motivated team. I’m known amongst team members for having a strong work ethic, openness, and attention to detail, no matter the complexity of the project. On my free time I like to workout and bowl.
This application provides the user who wants to take an interest in hiking or biking trails with information and advice to help them make the best approach.
Try to beat the randomly given number that's give at the start of the game. Each crystal is assigned a number. Each time you click on a crystal the number is added together. Your total must equal the randomly given number to win. If your number exceeds the given number, you lose. Good luck!
Cool web applicaton to test your knowlege of JavaScript. You'll only have 10 seconds to answer each question.
Applion that allows you to create a train, destination, and up to date arrival time. Users can also Delete the train.
LIRI is like iPhone's SIRI. However, while SIRI is a Speech Interpretation and Recognition Interface, LIRI is a Language Interpretation and Recognition Interface. LIRI will be a command line node app that takes in parameters and gives you back data.
Full-stack Web application that allows gym goers to find a gym buddy with similar interests, based on the results from the survery that each user has to take.
Welcome 2 Good Burger is a simple full-stack application that demonstrates understanding of http (CRUD) methods. Create a burger, update the status of the burger and delete the burger.
Created CLI application that is an Amazon-like storefront with the MySQL. The app will take orders, add to stock and deplete stock from the store's inventory
Vehicle service app that connects responsible car owners and hardworking mechanics; making people’s lives easier. This is like Uber for vehicle maintenance.
MERN Stack application that connects Web Developers across the globe. Full stack social network application using Node.js, Express, React, Redux and MongoDB along with ES6+.


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|
SuanShu, a Java numerical and statistical library | |||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.MADecomposition
public class MADecomposition
This class decomposes a time series into the trend, seasonal and the stationary random components using the Moving Average Estimation with symmetric window.
That is,
Xt = mt + st + Yt
We have
The R equivalent function is decompose
.
| Field Summary | |
|---|---|
TimeSeries |
random
the stationary random component of the time series after the trend and seasonal components are removed |
TimeSeries |
seasonal
the estimated seasonal effect of the time series |
TimeSeries |
trend
the estimated trend of the time series |
| Constructor Summary | |
|---|---|
MADecomposition(TimeSeries Xt,
double[] MAFilter,
int period)
Decompose a time series into the trend, seasonal and the stationary random components using the Moving Average Estimation. |
|
MADecomposition(TimeSeries Xt,
int period)
Decompose a periodic time series into the seasonal and stationary random components using no MA filter. |
|
MADecomposition(TimeSeries Xt,
int MAOrder,
int period)
Decompose a time series into the trend, seasonal and the stationary random components using the default filter. |
| Method Summary |
|---|
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
public final TimeSeries trend
public final TimeSeries seasonal
public final TimeSeries random
| Constructor Detail |
|---|
public MADecomposition(TimeSeries Xt, double[] MAFilter, int period)
Xt
- a time seriesMAFilter
- the moving average filter to smooth the time seriesperiod
- the period of the time series; if aperiodic, use 1public MADecomposition(TimeSeries Xt, int period)
Xt
- a time seriesperiod
- the period of the time series; if aperiodic, use 0public MADecomposition(TimeSeries Xt, int MAOrder, int period)
Xt
- a time seriesMAOrder
- the length of the MA filter (automatically increased by 1 for even MAOrder
)period
- the period of the time series; if aperiodic, use 0
|
SuanShu, a Java numerical and statistical library | |||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||
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This is the course website for IS445(AOG) in Fall 2020
This week we will learn about ipywidgets and traitlets and apply them to visualizations in Python.


bam2wig¶
This is a java program that creates a coverage WIG file from a BAM file, filtering some of the reads based on base quality, mapping quality and duplicates.
Compile and build:
mvn compile
mvn package
Mode of use:
module load java/jdk1.8.0_45
java -jar /genomes/software/apps/gel-coverage/target/bam2wig-jar-with-dependencies.jar --bam <BAM_FILE> --output-prefix <OUTPUT_PREFIX> --config <CONFIG>
Where the config file has the following content:
[bam2wig]
base_quality : 30
mapping_quality : 10
filter_duplicates : true
Note
You will get the following files: $OUTPUT_PREFIX.wig and $OUTPUT_PREFIX.chr
Due to the size of the output it is quite convenient produce a bigWig. In our pipeline should be run in the following way:
module load java/jdk1.8.0_45
module load python
java -jar /genomes/software/apps/gel-coverage/bam2wig-jar-with-dependencies.jar --bam <BAM_FILE> --output-prefix <OUTPUT_PREFIX> --config <CONFIG> --stdout | wigToBigWig stdin <OUTPUT_PREFIX>.chr <BIGWIG_FILE>


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REST
Common API
Resources are accessible by URIs
Data in JSON format
Client uses AJAX
Status
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Server
Team A
Django-nonrel was used for server-side representation of models
Tastypie as the REST interface
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JQuery for DOM manipulation
Raphaël SVG manipulation
Backbone a Model-View-Controller pattern on client
Underscore functional programming features
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SocialAuth library was used for Facebook and Google login