Youtube daily report w Apr 24 2017

This video is about how to divide the

data into a training set and a test

set. So for our first example, we are

going to consider the packages data and

now I've read in the data. Look at the

dimensions, make sure it looks good. Okay,

there 730 observations and 16

characteristics in the dataset.

Let's just look at the first row. OK, so

we have a year, whether it's a weekend,

whether it's the holidays. It seems like

we're measuring in days. I had the days I

would know that these are indeed

measured in or the first day in the dataset

is January first. So since it's measured

in time order, I want to create two

datasets, the training and test with a test

that is comprised of the most recent

data. So should be the latest thirty

percent of the data. So I'm gonna go

ahead and create two lists of the numbers. One

is train and one is test. First

thing I need is to know how many

observations we have. So it will take just

the length of one variable and now I can

see that it's 730 which I already knew,

but now I have stored in. So the

training data is going to be the first

series of the data, it's going to go from one

to 0.7 times n and what does that mean? It's

going to count one,two,three, all the way

up to 0.7 times n. So let's run that

line of code and see what happens. To

create the list train and let's print train out and

train contains 1 2 3 4 and so on

all the way up to 5, 11 which is seventy

percent of the 730 observations we have.

Now I want to put everything else into

the test set.

So I'm gonna take a special command

called "setdiff", this is the difference

between two sets of numbers, the first

set of numbers is 1 to n and that's all the

observations that I have available

1 2 3 and so on, up to 730. But I want to

take out the second set train, because I

already used that in one place. So if I

run this line and then print out with

test is. If all the numbers from 5 to 12

to 730, so you can see that test contains all

the numbers from 1 to 511 and I'm sorry

train contains all the numbers from 1 to

511 and test contains 512 to 730.

So I've used every observation in

the dataset but the later ones, the last

ones are contained inside of test. So the

training data is going to be our

development, we're going to use that to

create this model. It's going to be this space

we use in the workshop to build a

product. Then the test dataset we're

going to use after the models being

created.

We're going to use it to see if the

model can stand up in the future. So we

have this data models never have seen before,

which is going to test its performance.

So am I done?

The answer's no. I only have a list of

numbers. Now I need to create two

datasets, I'll create the dtrain because

it's a training data created from our

data set d and I'll create dtest

because it's a testing data created from

our data set d and the way that I'll do

that is take all the elements of

d,the original data such that there

in the list train. So this is going to

pull every row that's contained within

train and put it in dtrain our new

dataset. So it's going to take the first

row the second row, the third row, the forth row and

so on, all the way to 511th row and put

it into a new dataset called dtrain

and then this

dtest is going to take every row in the

list test the 512th row to 513th row, all

the way up to the 730th row and store

them in dtest. When I run these two

lines of code, our two new datasets, the

dimensions of dtrain are 511 rows

with 16 characteristics and the

dimensions of the dtest are 219 rows, the

remaining from 512 to 730. So these two

datasets don't contain any the same

elements. It's like dividing the group of

students into some that are going to go

into one room and some that are going to

go into another. There's no overlap

between them.

Now what if I use a different datasets,

so that's when things were in order, we

put the last bit into the test set. What if I

use instead the scores data. So I've got

students, remember in this dataset, let's

look at what this dataset looks like.

I've got a student ID, hours studied, whether

they slept eight hours, their previous

grade and their grade on the exam.

Students are not in time order. I'm going

to have to randomly select that

according to the slides in the previous

video. So instead of putting the first

seventy percent and last seventy percent,

I'm going to randomly select using this

function sample, but the process is going

to be the same. I'm going to create a

train and a test. So sample, I want to

sample from 1 to n so I want to choose from

that list of numbers at random. And I

want to choose how many numbers, I want

to choose 0.7 times n numbers.

So the first argument here is from what

set should I choose.

This one colon n ,the second element

here 0.7 times n is how many

numbers do I want to choose and then this

replace=False is the third element and

what that means is after I select

something, I don't want to ever be

selected again. I'm putting it into a set.

That's it. This is the code that I would use

always if the data is organized by

subject and it's not in time order. So

what's going to happen when I do that?

Let's just see. Now train looks like this.

Oops. What's my mistake? Why do I have so many

observations in here? 727 .The scoress dataset

only have a hundred of students in it,

because n is still 730. I forgot

to reset n. So let's do that. n is the

length of the first variable, the first

variable is student ID. When I run this,

now n is 100. So train, when I rerun

this, now it's going to rerun with n

equals to a hundred instead of the old

one. Now train is a list of randomly

selected students out of 100. So it's

going to take the 57th student,the53rd

student, the 38th student,the 78th student and put them all

into the training data. Now the test that

is created using the same command

setdiff(1:n, train), because I'm still going to

take the numbers 1 to 100 and

remove everything that's already been

put into the training data. So when I see

what test looks like, it's just the remaining

students. The first student was never

randomly selected, so he's left over to

go into the test set ,the second student was

never selected, so he left over to go

into the test set.

So these are the 30 remaining students

after 70 students were chosen at random.

So now we have two sets that do not

overlap. 70 of the students are in the training

data, 30 of the students in the test

data, but I haven't created the datasets

yet. I will need to create them. So dtrain

and dtest for the new dataset,

and d[train,]

and d[test,] when I run these two

lines of code, I'll be creating two new

datasets. dtrain.

Let's test the dimensions of be dtrain,

has 70 students with five characteristics 177 00:09:15,190 --> 00:09:23,830 each. Let's look at the first row of

dtrain. It's the 57th student, student ID is 57 and

these are the characteristics about that student. Now

let's look at the dimensions of dtest.

30th student is in there and each of their

five characteristics are with them. So we

created 2 datasets. One for creating a

model in the workshop and one for testing the

model and a beta test.

For more infomation >> Lin Reg Prediction Divide Data in R - Duration: 9:46.

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Renault Captur 1.2 TCe Helly Hansen, Automaat, R-Link, Pdc, 9.000 km !! Nieuwstaat - Duration: 1:08.

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Renault Captur TCE 90pk Dynamique (Camera/R-LINK/17"LMV/Climate) - Duration: 0:44.

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MOAB - Mother of All Bombs GBU-43/B Massive Ordnance Air Blast - US Military - Duration: 3:13.

For the first time ever, the United States used the most powerful non-nuclear bomb from

its arsenal.

That's right, the US military dropped what it calls the mother of all bombs on a tunnel

network in Eastern Afghanistan.

Although the GBU-43 is officially called the Massive Ordnance Air Blast bomb, it picked

up the nickname "mother of all bombs" due to its abbreviation and its giant size.

But what is this seemingly new weapon, and is it really nearly as powerful as a nuclear

bomb?

We thought we'd take a closer look at the specs of the MOAB in this episode of The Infographics

Show, "The Massive Ordnance Air Blast Bomb."

Don't forget to subscribe and click the bell button so that you can be part of our

Notification Squad.

Developed by Albert L. Weimorts, Jr. in 2002, the MOAB was very nearly used in an attempt

to take out Saddam Hussein, the then dictator of Iraq.

But US Generals at the time were concerned that it would inadvertently hurt or kill civilians,

and they ultimately decided against its use.

Since 2003, 15 MOABS have been manufactured.

According to the the engineers who designed them, the bomb weighs approximately 22,600

lbs, is around 30 feet in length, and has a diameter of about 40 inches.

Most importantly, however, it has an explosive yield of 11 tons of TNT, or 46 billion joules.

The surviving Afghanis who were relatively close to the blast site described the effects

of the bomb as feeling "like the heavens were falling."

This should come as no surprise since the explosive energy released by a MOAB is roughly

the same as that unleashed during an M6.0 earthquake.

The detonation itself is caused by a mixture of TNT (80 percent) and aluminum powder (20

percent), which is a highly explosive mixture known as Tritonal.

The addition of aluminum helps the TNT ignite and reach an extremely high pressure far quicker

than TNT would be able to do alone.

Guided to the ground by GPS after being literally pulled out of a massive C-130 cargo aircraft

by parachute, the MOAB doesn't detonate upon impact.

Instead, it explodes in the air above its target at a height of just 6 feet (1.8 meters).

The bomb is so destructive that it has an actual bomb blast radius of 1 mile from the

epicenter (1.6 kilometers), obliterating anything and everything in its path.

These death dealers don't come cheap, however; each MOAB costs approximately $170,000, with

some experts suggesting that Research and Development for the bomb cost as much as $300

million.

A little known fact about the MOAB is that it was originally painted green because the

military was in such a rush to get the weapon into their inventory in 2003, and the only

color available in the amount they needed was John Deere green.

And finally, for those who feel assured that at least the bomb is in American hands, we

have bad news for you: Russia has its own version, called, rather predictably, the "Father

of All Bombs" and apparently it's four times as powerful as the MOAB.

No wonder Vladimir Putin horseback rides around town topless as if he doesn't have a care

in the world.

Spasiba, Mother Russia!

So, do you think the US military was justified in dropping the MOAB?

Let us know in the comments!

And if you want to see an actual MOAB exploding, follow this link to our other channel, The

Military Show, for some very exciting footage of this and other military wonders.

Thanks for watching, and, as always, don't forget to like, share, and subscribe.

Also, please consider heading over to our Patreaon; we are currently raising money to

hire more writers so that we can continue bringing you this bi-weekly show!

For more infomation >> MOAB - Mother of All Bombs GBU-43/B Massive Ordnance Air Blast - US Military - Duration: 3:13.

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Chopped firewood - Duration: 5:08.

Look! Who is it there?

what is he doing there?)

The neighbor is standing next to our barn

Frightened me =)

As many already know ... we live next to the forest

Have been sawing old trees for several days already

Trees that fell after snowfall

Here are some

Honestly it's illegal =) we are forbidden to take even dry and rotten trees in the forest

"Criminal Russia: Contemporary Chronicles"

But I do not think it's worth bringing the forest to this state

Around the fallen trees

There used to be exactly the same before, but we removed the old trees

Here the pond is not big. Water by the way it does not dry out over the summer

And this is what the forest looks like

Many trees fell from snowfall this year

This tree has eaten beetle bark beetle

Dead

Next, too, will soon die.

Dead

And here to us the forest area forbids to clean dry and fallen trees

Look! There is a windbreak. For many years there was not even a forester

And not to allow people who live here to clean this dead forest, because soon it will spread to other trees.

But they themselves do not clean the forest and others do not give .... everything is rotting

This tree will never be removed from here except us

If you have a sawmill then you can sell lumber

How she cracked

Further it is even, and thick

Yeah ..... Let's go see the second ravine

We have here one small ravine and one big

Oh look here water

This ravine is usually dry, just now the snow melts

how beautiful!

There's even more firewood

If everything is cut down here, then enough for heating throughout the winter

A deep layer of needles on the ground, springs

cool

All the trees that lie I'll cut for firewood

It is better to start now, because in summer there will be a lot of nettles growing and insects will not let us work

That's how much we did for today

it's hailing

Here I have ice drops on my knee, I hope to see the camera

This is our cool weather in Russia. It will be soon May 1, and we have hail and snow

Well done today

That's so much wood

And all for free =)

As I love =)))))

For more infomation >> Chopped firewood - Duration: 5:08.

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10 Natural Plants That Help in Relieving Anxiety and Depression - Duration: 3:51.

10 natural herbs that help in relieving anxiety and depression

With the rush of everyday life, many people He has been suffering from stress and anxiety.

The psychological health is that influence all activities and functions of our body.

To alleviate this problem many people It has made use of antidepressant medications.

But these may cause a range of effects side:

- Difficulty walking - Yellowing of eyes and skin

- Memory Problems - Hallucinations and suicidal thoughts

- Lack of coordination - Talking Difficulty

- Seizures

However, there are natural alternatives that can relieve depression.

- Lavender Lavender has neuroprotective properties

that help control mood and disorders neurological. Make a tea, take a bath

with a few drops of lavender essential oil, or put some dried flowers on the pillow

before bedtime.

- Saint John's herb This herb is a great antidepressant. however

can cause some effects like rashes skin, diarrhea, nervousness, anxiety,

irritability, dizziness, stomach pain, fatigue, tingling, dry mouth and lack of sleep.

Besides if consumed in excess may cause allergy if exposure

Sun.

- Valeriana Acts to combat headache, anxiety

and insomnia. However, there are cases where it may cause these same symptoms.

- Passion Flower The passion flower helps to relax and acts

with sedative action. Combating insomnia, anxiety and convulsions.

- Ashwagandha It can be used in cases of insomnia and treatment

anxiety for fear of open spaces and crowds. This herb reduces the levels of

cortisol which is associated with stress. It can be taken as tea or in capsules.

Can cause side effects like vomiting, diarrhea and stomach pain.

- Golden Root Fighting exhaustion and chronic fatigue. relieves

stress and promotes wellness. Prolonged use can be dangerous.

- Chamomile Chamomile brings tranquility. principled

assets such as luteolin, apigenin and abisabolol it lowers blood pressure.

You can take chamomile tea all nights.

- Rosemary The rosemary improves memory and performance

cognitive. Its overuse causes redness the skin, uterine bleeding, irritation

kidney, vomiting and sensitivity to the sun.

- Vanilla Just the smell of vanilla relax already. however

if not consumed in moderation it can cause headaches, swelling, irritation

and insomnia.

- Lemongrass This herb reduces anxiety and bring more quality

life when it comes to dementia cases serious. The lemongrass provides tranquility

and strengthens memory.

When consumed in excess can cause pain abdominal, nausea, dizziness and vomiting.

Children are only allowed to use for 7 days as adults for 30 days.

All these natural antidepressants are insurance, as well as all, should not be consumed

in an exaggerated way.

And even if they are natural, the ideal is that you consult your doctor about the use.

Enjoy this video? If you liked the video, short, join the channel and share

with your friends.

For more infomation >> 10 Natural Plants That Help in Relieving Anxiety and Depression - Duration: 3:51.

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Shadowhunters - Primeira cena de beijo de Jace e Clary - Duration: 1:08.

I got the cup I care about the cup I

came out of the tongs I didn't see you I

was worried something whenever the demon

shapeshifter head look just like you all

right yeah and the demon I set him

straight back down how'd you know wasn't

me I just never really ever arrest quiz

me well may come as a surprise but i

actually do listen to some of the things

you tell me you just have to pay

attention to the details well I for the

first time we met you have the site near

Shadowhunters cigarette

you

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Peugeot 208 1.4 E-HDI BLUE LEASE LEER NAVIGATIE PDC - Duration: 1:02.

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Reflects CrossFollowers - The SANCTIFICATION factor | #11 - Duration: 1:13.

''And Joshua said unto the people: sanctify yourselves, for to morrow the LORD will do wonders among you.'' (Josh 3:5).

The greatest work of the Holy Spirit in the life of a true Christian is the sanctification.

If we want to see the manifestation of the glory of God, it's indispensable a life of purity and holiness.

As it is written: ''without holiness, no one will see the Lord'' (Heb 12:14).

Already many millennia ago, God gave an order to his people: "Be holy because I am holy" (Lev 11:44).

But how? ''How can a young person stay on the path of purity? By living according to your word.'' (Ps 119:9).

Only through prayer and commitment to the Word of God.

Therefore, sanctify yourself, consecrate yourself, do your best for God.

Then the Lord will do wonders in our midst and all his glory and power will flood our hearts.

For this is the will of God - our sanctification (1 Th 4:3).

For more infomation >> Reflects CrossFollowers - The SANCTIFICATION factor | #11 - Duration: 1:13.

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Lin Reg Prediction Divide Data in R - Duration: 9:46.

This video is about how to divide the

data into a training set and a test

set. So for our first example, we are

going to consider the packages data and

now I've read in the data. Look at the

dimensions, make sure it looks good. Okay,

there 730 observations and 16

characteristics in the dataset.

Let's just look at the first row. OK, so

we have a year, whether it's a weekend,

whether it's the holidays. It seems like

we're measuring in days. I had the days I

would know that these are indeed

measured in or the first day in the dataset

is January first. So since it's measured

in time order, I want to create two

datasets, the training and test with a test

that is comprised of the most recent

data. So should be the latest thirty

percent of the data. So I'm gonna go

ahead and create two lists of the numbers. One

is train and one is test. First

thing I need is to know how many

observations we have. So it will take just

the length of one variable and now I can

see that it's 730 which I already knew,

but now I have stored in. So the

training data is going to be the first

series of the data, it's going to go from one

to 0.7 times n and what does that mean? It's

going to count one,two,three, all the way

up to 0.7 times n. So let's run that

line of code and see what happens. To

create the list train and let's print train out and

train contains 1 2 3 4 and so on

all the way up to 5, 11 which is seventy

percent of the 730 observations we have.

Now I want to put everything else into

the test set.

So I'm gonna take a special command

called "setdiff", this is the difference

between two sets of numbers, the first

set of numbers is 1 to n and that's all the

observations that I have available

1 2 3 and so on, up to 730. But I want to

take out the second set train, because I

already used that in one place. So if I

run this line and then print out with

test is. If all the numbers from 5 to 12

to 730, so you can see that test contains all

the numbers from 1 to 511 and I'm sorry

train contains all the numbers from 1 to

511 and test contains 512 to 730.

So I've used every observation in

the dataset but the later ones, the last

ones are contained inside of test. So the

training data is going to be our

development, we're going to use that to

create this model. It's going to be this space

we use in the workshop to build a

product. Then the test dataset we're

going to use after the models being

created.

We're going to use it to see if the

model can stand up in the future. So we

have this data models never have seen before,

which is going to test its performance.

So am I done?

The answer's no. I only have a list of

numbers. Now I need to create two

datasets, I'll create the dtrain because

it's a training data created from our

data set d and I'll create dtest

because it's a testing data created from

our data set d and the way that I'll do

that is take all the elements of

d,the original data such that there

in the list train. So this is going to

pull every row that's contained within

train and put it in dtrain our new

dataset. So it's going to take the first

row the second row, the third row, the forth row and

so on, all the way to 511th row and put

it into a new dataset called dtrain

and then this

dtest is going to take every row in the

list test the 512th row to 513th row, all

the way up to the 730th row and store

them in dtest. When I run these two

lines of code, our two new datasets, the

dimensions of dtrain are 511 rows

with 16 characteristics and the

dimensions of the dtest are 219 rows, the

remaining from 512 to 730. So these two

datasets don't contain any the same

elements. It's like dividing the group of

students into some that are going to go

into one room and some that are going to

go into another. There's no overlap

between them.

Now what if I use a different datasets,

so that's when things were in order, we

put the last bit into the test set. What if I

use instead the scores data. So I've got

students, remember in this dataset, let's

look at what this dataset looks like.

I've got a student ID, hours studied, whether

they slept eight hours, their previous

grade and their grade on the exam.

Students are not in time order. I'm going

to have to randomly select that

according to the slides in the previous

video. So instead of putting the first

seventy percent and last seventy percent,

I'm going to randomly select using this

function sample, but the process is going

to be the same. I'm going to create a

train and a test. So sample, I want to

sample from 1 to n so I want to choose from

that list of numbers at random. And I

want to choose how many numbers, I want

to choose 0.7 times n numbers.

So the first argument here is from what

set should I choose.

This one colon n ,the second element

here 0.7 times n is how many

numbers do I want to choose and then this

replace=False is the third element and

what that means is after I select

something, I don't want to ever be

selected again. I'm putting it into a set.

That's it. This is the code that I would use

always if the data is organized by

subject and it's not in time order. So

what's going to happen when I do that?

Let's just see. Now train looks like this.

Oops. What's my mistake? Why do I have so many

observations in here? 727 .The scoress dataset

only have a hundred of students in it,

because n is still 730. I forgot

to reset n. So let's do that. n is the

length of the first variable, the first

variable is student ID. When I run this,

now n is 100. So train, when I rerun

this, now it's going to rerun with n

equals to a hundred instead of the old

one. Now train is a list of randomly

selected students out of 100. So it's

going to take the 57th student,the53rd

student, the 38th student,the 78th student and put them all

into the training data. Now the test that

is created using the same command

setdiff(1:n, train), because I'm still going to

take the numbers 1 to 100 and

remove everything that's already been

put into the training data. So when I see

what test looks like, it's just the remaining

students. The first student was never

randomly selected, so he's left over to

go into the test set ,the second student was

never selected, so he left over to go

into the test set.

So these are the 30 remaining students

after 70 students were chosen at random.

So now we have two sets that do not

overlap. 70 of the students are in the training

data, 30 of the students in the test

data, but I haven't created the datasets

yet. I will need to create them. So dtrain

and dtest for the new dataset,

and d[train,]

and d[test,] when I run these two

lines of code, I'll be creating two new

datasets. dtrain.

Let's test the dimensions of be dtrain,

has 70 students with five characteristics 177 00:09:15,190 --> 00:09:23,830 each. Let's look at the first row of

dtrain. It's the 57th student, student ID is 57 and

these are the characteristics about that student. Now

let's look at the dimensions of dtest.

30th student is in there and each of their

five characteristics are with them. So we

created 2 datasets. One for creating a

model in the workshop and one for testing the

model and a beta test.

For more infomation >> Lin Reg Prediction Divide Data in R - Duration: 9:46.

-------------------------------------------

Renault Captur 1.2 TCe Helly Hansen, Automaat, R-Link, Pdc, 9.000 km !! Nieuwstaat - Duration: 1:08.

For more infomation >> Renault Captur 1.2 TCe Helly Hansen, Automaat, R-Link, Pdc, 9.000 km !! Nieuwstaat - Duration: 1:08.

-------------------------------------------

Renault Captur TCE 90pk Dynamique (Camera/R-LINK/17"LMV/Climate) - Duration: 0:44.

For more infomation >> Renault Captur TCE 90pk Dynamique (Camera/R-LINK/17"LMV/Climate) - Duration: 0:44.

-------------------------------------------

MOAB - Mother of All Bombs GBU-43/B Massive Ordnance Air Blast - US Military - Duration: 3:13.

For the first time ever, the United States used the most powerful non-nuclear bomb from

its arsenal.

That's right, the US military dropped what it calls the mother of all bombs on a tunnel

network in Eastern Afghanistan.

Although the GBU-43 is officially called the Massive Ordnance Air Blast bomb, it picked

up the nickname "mother of all bombs" due to its abbreviation and its giant size.

But what is this seemingly new weapon, and is it really nearly as powerful as a nuclear

bomb?

We thought we'd take a closer look at the specs of the MOAB in this episode of The Infographics

Show, "The Massive Ordnance Air Blast Bomb."

Don't forget to subscribe and click the bell button so that you can be part of our

Notification Squad.

Developed by Albert L. Weimorts, Jr. in 2002, the MOAB was very nearly used in an attempt

to take out Saddam Hussein, the then dictator of Iraq.

But US Generals at the time were concerned that it would inadvertently hurt or kill civilians,

and they ultimately decided against its use.

Since 2003, 15 MOABS have been manufactured.

According to the the engineers who designed them, the bomb weighs approximately 22,600

lbs, is around 30 feet in length, and has a diameter of about 40 inches.

Most importantly, however, it has an explosive yield of 11 tons of TNT, or 46 billion joules.

The surviving Afghanis who were relatively close to the blast site described the effects

of the bomb as feeling "like the heavens were falling."

This should come as no surprise since the explosive energy released by a MOAB is roughly

the same as that unleashed during an M6.0 earthquake.

The detonation itself is caused by a mixture of TNT (80 percent) and aluminum powder (20

percent), which is a highly explosive mixture known as Tritonal.

The addition of aluminum helps the TNT ignite and reach an extremely high pressure far quicker

than TNT would be able to do alone.

Guided to the ground by GPS after being literally pulled out of a massive C-130 cargo aircraft

by parachute, the MOAB doesn't detonate upon impact.

Instead, it explodes in the air above its target at a height of just 6 feet (1.8 meters).

The bomb is so destructive that it has an actual bomb blast radius of 1 mile from the

epicenter (1.6 kilometers), obliterating anything and everything in its path.

These death dealers don't come cheap, however; each MOAB costs approximately $170,000, with

some experts suggesting that Research and Development for the bomb cost as much as $300

million.

A little known fact about the MOAB is that it was originally painted green because the

military was in such a rush to get the weapon into their inventory in 2003, and the only

color available in the amount they needed was John Deere green.

And finally, for those who feel assured that at least the bomb is in American hands, we

have bad news for you: Russia has its own version, called, rather predictably, the "Father

of All Bombs" and apparently it's four times as powerful as the MOAB.

No wonder Vladimir Putin horseback rides around town topless as if he doesn't have a care

in the world.

Spasiba, Mother Russia!

So, do you think the US military was justified in dropping the MOAB?

Let us know in the comments!

And if you want to see an actual MOAB exploding, follow this link to our other channel, The

Military Show, for some very exciting footage of this and other military wonders.

Thanks for watching, and, as always, don't forget to like, share, and subscribe.

Also, please consider heading over to our Patreaon; we are currently raising money to

hire more writers so that we can continue bringing you this bi-weekly show!

For more infomation >> MOAB - Mother of All Bombs GBU-43/B Massive Ordnance Air Blast - US Military - Duration: 3:13.

-------------------------------------------

Honda Civic 2.0 TYPE R GT 310 PK Navi Achteruitrijcamera LED - Duration: 0:54.

For more infomation >> Honda Civic 2.0 TYPE R GT 310 PK Navi Achteruitrijcamera LED - Duration: 0:54.

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Chopped firewood - Duration: 5:08.

Look! Who is it there?

what is he doing there?)

The neighbor is standing next to our barn

Frightened me =)

As many already know ... we live next to the forest

Have been sawing old trees for several days already

Trees that fell after snowfall

Here are some

Honestly it's illegal =) we are forbidden to take even dry and rotten trees in the forest

"Criminal Russia: Contemporary Chronicles"

But I do not think it's worth bringing the forest to this state

Around the fallen trees

There used to be exactly the same before, but we removed the old trees

Here the pond is not big. Water by the way it does not dry out over the summer

And this is what the forest looks like

Many trees fell from snowfall this year

This tree has eaten beetle bark beetle

Dead

Next, too, will soon die.

Dead

And here to us the forest area forbids to clean dry and fallen trees

Look! There is a windbreak. For many years there was not even a forester

And not to allow people who live here to clean this dead forest, because soon it will spread to other trees.

But they themselves do not clean the forest and others do not give .... everything is rotting

This tree will never be removed from here except us

If you have a sawmill then you can sell lumber

How she cracked

Further it is even, and thick

Yeah ..... Let's go see the second ravine

We have here one small ravine and one big

Oh look here water

This ravine is usually dry, just now the snow melts

how beautiful!

There's even more firewood

If everything is cut down here, then enough for heating throughout the winter

A deep layer of needles on the ground, springs

cool

All the trees that lie I'll cut for firewood

It is better to start now, because in summer there will be a lot of nettles growing and insects will not let us work

That's how much we did for today

it's hailing

Here I have ice drops on my knee, I hope to see the camera

This is our cool weather in Russia. It will be soon May 1, and we have hail and snow

Well done today

That's so much wood

And all for free =)

As I love =)))))

For more infomation >> Chopped firewood - Duration: 5:08.

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LEARN WORDS AND COLOURS WITH COLOURFUL LETTERS - Duration: 5:17.

For more infomation >> LEARN WORDS AND COLOURS WITH COLOURFUL LETTERS - Duration: 5:17.

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WHY I DON'T SWEAR/CURSE 🚫😡💢👿 - Duration: 8:29.

For more infomation >> WHY I DON'T SWEAR/CURSE 🚫😡💢👿 - Duration: 8:29.

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Nikki Haley To North Korea: 'Don't Give Us A Reason' To Fight With You | TODAY - Duration: 4:27.

NATIONS SECURITY COUNCI SET TO VISIT.

MATT? SAVANNAH?

>> ALL RIGHT, KELLY. THANK YOU VERY MUCH.

>>> NIKKI HALEY, THE U.S. AMBASSADOR TO THE UNITED

NATIONS, JOINING US NOW. AMBASSADOR HALEY, GOOD MORNING

TO YOU. >> GOOD MORNING, MATT.

>> I WANT TO TALK ABOUT THE AMERICAN BEING DETAINED IN NORTH

KOREA IN A SECOND. BUT WHEN YOU TAKE THAT INCIDENT

AND YOU COMBINE IT WITH A THREAT TO SINK A U.S. AIRCRAFT CARRIER

AND A THREAT TO CONDUCT A NUCLEAR STRIKE AGAINST

AUSTRALIA. WHEN YOU AND YOUR COUNTERPARTS

MEET THIS MORNING, WHAT CAN YOU COME UP WITH TO REIN IN NORTH

KOREA THAT HASN'T BEEN TRIED IN THE PAST AND HAVEN'T FAILED IN

THE PAST? >> KIM JONG-UN IS STARTING TO

FLEX HIS MUSCLES BECAUSE HE FEELS THE PRESSURE.

LAST WEEK THE SECURITY COUNCIL UNANIMOUSLY CONTEMPTED WHAT

NORTH KOREA IS DOING WITH THEIR TESTING.

CHINA HAS BEEN HELPING PUTTING PRESSURE ON HIM.

AND HE'S TRYING TO SHOW STRENGTH TO HIS COUNTRY.

>> WE'VE BEEN TALKING ABOUT CONTAINING NORTH KOREA FOR

DECADES NOW AND WHAT'S NOT WORKING.

WHAT NEW CAN YOU COME UP WITH? >> WORKING WITH CHINA FOR THE

FIRST TIME, THEY'VE REALLY BEEN OUR PARTNER IN HOLDING HIM AT

BAY. IT'S A NEW DAY WHEN YOU HAVE

CHINA AND THE UNITED STATES WORKING TOGETHER ON A STATEMENT

TO CONDEMN NORTH KOREA. THEY PUT PRESSURE ON HIM.

HE FEELS IT. THAT'S WHY HE'S RESPONDING THIS

WAY. AN I THINK IT IS A DIFFERENT

DAY. WHAT WE SAID FROM THE BEGINNING

AND I WILL CONTINUE TO SAY, THE UNITED STATES IS NOT LOOKING FOR

A FIGHT. DON'T GIVE US A REASON TO HAVE

ONE. >> IT'S INTERESTING THAT YOU SAY

THAT THE YOU THINK HE'S RESPONDING TO THE PRESSURE BY

FLEXING MUSCLE, BY CONDUCTING MORE NUCLEAR TESTS.

I DON'T HAVE TO TELL YOU, YOU HAVE AN UNSTABLE ADVERSARY

THERE. DOES THE TOUGH TALK AND THE

RHETORIC, IF CHINA DOESN'T HELP US HERE, WE MAY DO IT OURSELVES.

WE MAY CONSIDER A PRE-EMPTIVE STRIKE.

DO YOU WORRY ABOUT THE POINT OF NO RETURN WITH WORDS?

>> NO. THAT'S NOT THE CASE.

AND KEEP IN MIND, HE'S TRYING TO GET THE CONFIDENCE OF HIS OWN

PEOPLE.

WHEN HE DOES THESE THINGS, HE'S NOT DOING THEM TO ALL OF US, AS

MUCH AS HE'S TRYING TO PROVE TO HIS OWN PEOPLE HE CAN HANDLE

THIS. HE'S VERY MUCH STARTING TO FEEL

THE PRESSURE. YOU'RE STARTING TO SEE HIM GET

PARANOID. AND I THINK YOU'LL SEE PRESSURE

COMING FROM ALL PARTS OF THE COMMUNITY.

AND WE HAVE TO KEEP THE PRESSURE UP.

>> I WHI THAT SAVANNAH IS GETTING AT, WHEN YOU HAVE

SOMEONE AS UNSTABLE AS KIM JONG-UN, DO YOU WORRY THAT WORDS

MIGHT FORCE HIM INTO A CATASTROPHIC MISTAKE?

>> NO. AND I THINK IF YOU LOOK AT

WHAT'S HAPPENING NOW, IF THERE'S A CATASTROPHIC MISTAKE IT'S

GOING TO BE BECAUSE HE'S CONTINUING TO INSTIGATE AN

ISSUE. WE'RE GOING TO CONTINUE TO BE

STABLE. WE'RE GOING TO CONTINUE TO HAVE

THE INTERNATIONAL COMMUNITY STABLE.

IT'S THE REASON THAT NONE OF US ARE EVEN TRYING TO PICK A FIGHT

WITH HIM. BUT WE'LL HAVE TO WAIT AND SEE.

WHAT I CAN TELL YOU IS THE INTERNATIONAL COMMUNITY IS VERY

UNITED. >> AMBASSADOR HALEY, EVERY

LEADER SAYS ALL OPTIONS ARE ON THE TABLE.

THEY ALWAYS SAY THAT. IS A PRE-EMPTIVE STRIKE AGAINST

NORTH KOREA BEING CONSIDERED? IS THE ADMINISTRATION ACTIVELY

PLANNING FOR THAT? >> WE'RE NOT GOING TO DO

ANYTHING UNLESS HE GIVES US REASON TO DO SOMETHING.

SO, OUR GOAL -- >> THAT'S WHAT REASON?

WHAT WOULD THAT REASON BE? DO YOU HAVE THAT THRESHOLD IN

YOUR MIND? >> IF YOU SEE HIM ATTACK A

MILITARY BASE. IF YOU SEE AN INTERCONTINENTAL

BALLISTIC MISSILE, OBVIOUSLY, WE'RE GOING TO DO THAT.

RIGHT NOW, WE'RE SAYING DON'T TEST.

DON'T USE NUCLEAR MISSILES. DON'T DO ANYMORE ACTIONS.

AND I THINK HE'S UNDERSTANDING THAT.

AND CHINA IS HELPING PUT THAT PRESSURE ON.

>> IF HE TESTS ANOTHER INTERCONTINENTAL BALLISTIC

MISSILE, IF HE WERE TO TEST ANOTHER NUCLEAR DEVICE, YOU SAY,

OBVIOUSLY, WE'RE GOING TO DO THAT, DO YOU MEAN MILITARY

RETALIATION? >> I THINK THEN THE PRESIDENT

STEPS IN AND DECIDES WHAT'S GOING TO HAPPEN.

>> LET ME ASK YOU REAL QUICKLY BEFORE I LEAVE YOU.

DO YOU HAVE ANY INFORMATION ON THIS AMERICAN BEING DETAINED?

HIS WHEREABOUTS OR WHY HE'S BEING DETAINED?

>> IT'S HARD TO GET INFORMATION OUT OF NORTH KOREA, OBVIOUSLY.

WE'RE DOING EVERYTHING WE CAN. THIS MAKES THREE DETAINEES THAT

THEY HAVE RIGHT NOW. AND AGAIN, THIS IS HIM TRYING TO

PICK A FIGHT WITH US. AND WHAT WE'RE GOING TO HAVE TO

DO IS WORK VERY HARD TO FIND OUT INFORMATION AND SEE WHAT WE NEED

TO DO TO GET THE THREE OUT SAFELY.

>> AMBASSADO

For more infomation >> Nikki Haley To North Korea: 'Don't Give Us A Reason' To Fight With You | TODAY - Duration: 4:27.

-------------------------------------------

Burstner Brevio 600 t - Duration: 1:21.

For more infomation >> Burstner Brevio 600 t - Duration: 1:21.

-------------------------------------------

Opel Zafira 1.4 T(140pk) BUSINESS+ 7P. NAVI/ECC/AGR STOELEN - Duration: 1:02.

For more infomation >> Opel Zafira 1.4 T(140pk) BUSINESS+ 7P. NAVI/ECC/AGR STOELEN - Duration: 1:02.

-------------------------------------------

Nissan QASHQAI 1.2 115pk DIG-T XTRONIC N-Connecta - Duration: 1:03.

For more infomation >> Nissan QASHQAI 1.2 115pk DIG-T XTRONIC N-Connecta - Duration: 1:03.

-------------------------------------------

Kia Rio 1.0 T-GDI First Edition 100PK - Duration: 0:58.

For more infomation >> Kia Rio 1.0 T-GDI First Edition 100PK - Duration: 0:58.

-------------------------------------------

Volvo S80 2.5 T AUTOMAAT LEER/NAVI/CLIMA - Duration: 1:00.

For more infomation >> Volvo S80 2.5 T AUTOMAAT LEER/NAVI/CLIMA - Duration: 1:00.

-------------------------------------------

Opel Zafira Tourer 1.4 T 140PK 7PERS COSMO CAMERA/NAVI/PDC - Duration: 0:54.

For more infomation >> Opel Zafira Tourer 1.4 T 140PK 7PERS COSMO CAMERA/NAVI/PDC - Duration: 0:54.

-------------------------------------------

Kia cee'd 1.0 T-GDI 88KW GT-LINE SW - Duration: 0:58.

For more infomation >> Kia cee'd 1.0 T-GDI 88KW GT-LINE SW - Duration: 0:58.

-------------------------------------------

Kia cee'd 1.0 T-GDI 88KW FIRST EDITION SW - Duration: 1:00.

For more infomation >> Kia cee'd 1.0 T-GDI 88KW FIRST EDITION SW - Duration: 1:00.

-------------------------------------------

Exam skills: 6 tips for getting ready for your exams - Duration: 2:46.

For more infomation >> Exam skills: 6 tips for getting ready for your exams - Duration: 2:46.

-------------------------------------------

Resident Evil 4 Wii Edition - Leon Story Final Chapter (Full Play) - Duration: 11:10.

For more infomation >> Resident Evil 4 Wii Edition - Leon Story Final Chapter (Full Play) - Duration: 11:10.

-------------------------------------------

agFlier - Saving area - Salvando área - Duration: 1:39.

Tap anywhere on the map to create each vertex of the polygon in the center of the map (crosshair).

Change the type of drawing tool by clicking on the crosshair button to start creating the vertex of the polygon at the point where you touch the screen.

Add more polygons to the project by clicking the "+" button.

To save the project (area), click the "disk" button.

Choose a prefix to identify the customer / owner and a description to identify the area, then click SAVE.

DONE!

For more infomation >> agFlier - Saving area - Salvando área - Duration: 1:39.

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agFlier - Navigating to runway / Navegando para pista - Duration: 0:40.

Select the "Open folders - Waypoints" option and choose the destination runway / waypoint for navigation.

Tap the "Go To" button to start navigation.

The navigation data will appear above, and beside you will see a list of the runway closest to you at the moment.

To navigate to one of the alternate runways, tap on it, and then tap "Navigate."

For more infomation >> agFlier - Navigating to runway / Navegando para pista - Duration: 0:40.

-------------------------------------------

agFlier - Setting Home / Definindo Base - Duration: 0:20.

Select the "Open folders - Waypoints" option and choose the desired runway.

Touch the "Hangar" button to set it as home.

For more infomation >> agFlier - Setting Home / Definindo Base - Duration: 0:20.

-------------------------------------------

agFlier - Wind direction and area selection / Direção do vento e seleção de área - Duration: 1:04.

Open Wind Direction, and choose the desired wind condition on the slider on the right.

Open a project / area in the Open Folders - Areas option.

Open a multi-polygon project, and tap on the polygons you want to work with.

Now open the "Draw Area" option so that the selected polygons are isolated on the map.

Open the "Simulate and measure" option to see the direction of application options for the selected areas and orientation towards the wind.

For more infomation >> agFlier - Wind direction and area selection / Direção do vento e seleção de área - Duration: 1:04.

-------------------------------------------

agFlier - Sharing area / Compartilhando área - Duration: 0:33.

Open a project / area in the Open Folders - Areas option.

Touch the "share" button on the right.

Write a registered e-mail account in the destination and tap the button to add.

You can add more users to receive the project / area. The destination user can open it in the Open Folders / Shared option.

For more infomation >> agFlier - Sharing area / Compartilhando área - Duration: 0:33.

-------------------------------------------

Masha and the Bear, Masha cooks gross real food /w spiders, Doc McStuffins Checkup & маша и медведь - Duration: 3:25.

Ewww, yuck.

Poor bear, shall I call the doctor?

Hello, doctor McStuffins!

Yes.

Yes, okay, on my way, bye!

Doctor will be here soon.

Ah, already!

Hello.

Okay, let me have a look.

You have a cold, I can make a soup to make you feel better.

Masha, can you get some vegetables and I will put some water on.

Okay.

Ah good, these are perfect.

Ah, smells good.

Come Masha.

Here.

What, is it not good?

Ewww, yuck.

If you enjoyed this video, please like and subscribe. BYE!!!!!!

For more infomation >> Masha and the Bear, Masha cooks gross real food /w spiders, Doc McStuffins Checkup & маша и медведь - Duration: 3:25.

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10 PESTS MOST LIKELY LIVING IN YOUR FOOD RIGHT NOW! - Duration: 8:57.

Hey!

If you don't know already I'm Clover the curiously clever cat and today I'm here

to share a top twelve list that is curiously disgusting.

See, breakfast is my favorite meal of the day.

Or at least it used to be until I realized exactly how many bugs spend their whole lives

trying to steal breakfast or even spend their lives living in breakfast.

Sitting at number 10 is the grain mite because while disgusting its too tiny to ever notice

and as long as I keep things dry easy to deter.

Grain mites like cereal, dried vegetables, cheese, corn, and dried fruits but need moisture

to truly feel at home.

Grain mites are tiny and people say an infestation is grain dust because the light brown coloring

of their legs is noticeable sort of like dust buildup.

People say these mites give off a minty odor so if you smell toothpaste and no one has

brushed lately, look for the dust.

Coming in at number nine on the list is the bean weevil.

They are usually a mottled looking brown color and only about an eighth of an inch long.

These guys are tricky weevils though because they don't have the long snout that makes

most weevils obvious.

Their larva are small, white, legless and shaped like the letter c.

As the name suggests, the only time you need to worry about the bean weevil at breakfast

is if you happen to be eating beans though they do like peas too so later in the day

you might want to do a double check.

Number eight on the list of nasty beasts that try to eat your food before you do are a group

known as granary, rice or maize weevils.

You'll know them when they see them by the big snout thy have on the front of their head.

If you are still in doubt, they are dark brown and sometimes have four orangish spots on

their wings.

Their larva are about a quarter of an inch long and are white and legless.

Sadly, the larva are only ever found inside whole kernels or seeds so you'll eat them

before you see them.

The only defense against accidental larva ingestion is to look for small round holes

in the kernels where the adults stuck the eggs inside your popcorn, nuts, or seeds though

if you have whole grins, rice, corn millet, beans, or caked meal, they are also fair game

for this nasty weevil.

7.

Coming in at number seven though certainly nasty enough to rank higher is the spider

beetle.

The spider beetle is a one third inch, reddish brown beetle with long legs that let it masquerade

as a harmless spider with no designs on our breakfast.

Larvae are shaped like tiny letter c's and you probably never see them even if they are

there.

Spider beetles prefer to eat plant products though they'll invade cereals, seeds, and

even dog food if it is moist.

The spider beetle is particularly nasty because it often like to breed in accumulations of

animal poo before setting out to have a taste of your food.

6.

Number six on the list is the flour beetle.

Flour beetles are usually about a third of an inch long and reddish brown in color.

Their larvae are white or cream colored and have pointed spines on their back end though

your likely not to notice.

Contrary to their name, flour beetles aren't happy just ruining flour.

These monsters also like all kinds of cereal, cake mixes, beans, peas, dried fruits, nuts

and even chocolate so it might be that they need to be moved up to a higher category of

things I don't like than number 6.

5.

The fifth most hated pantry invader is the Warehouse or Cabinet Beetle who looks like

a tiny oval when at rest with and comes in shades from black to mottled yellow and brown.

These nasty beetles are particularly wicked because they feed on grain products – yep

your cereal, as well as seeds and dried fruits if they can find them.

That's not the nastiest part though.

Its what they might have eaten just before jumping in your cereal box.

Cabinet beetles are also known to eat dead insects or mammals so I guarantee their feet

are not clean enough to walk my cereal bowl.

4.

Number four on the list of most disgusting things that like to ruin breakfast is actually

two things, the drugstore beetle and the cigarette beetle.

These two nefarious beetles are only about 1/8 inch long and are brownish in color.

If you look closely you'll notice that their head points downward a bit but really and

their body is covered with fine hair, whose gonna look that close.

Both the Cigarette Beettle and the Drugstore Beetle prefer dried plant materials and the

most risky place in your kitchen when it comes to them is the spice rack but they are bugs

after all and will also go after grains, raisins, peppers, spices, seeds and pastas.

Worst of all, these nasty little beetles love pet food and might be in MY food right now

which is a true tragedy.

3.

Number 3 on the list of most disgusting pests that might be in your pantry is the meal moth.

Meal moths are about three quarters to an inch long and are recognizable by the dark

reddish band across the top and bottom of their wings usually accented in a yellowish

green.

You'll likely also notice the white squiggly lines in the center of their wings.

Meal moths larvae have a black head with a whitish colored body tipped in orange.

Meal moth like to live in flour and grain products though they will also invade seeds,

especially if they are a bit damp.

Despite the fact that they have wings, You normally won't see them flying around the

house so look closely next time you sift that flour.

2.

Number 2 on the list is the saw toothed grain beetle.

Saw toothed beetles are tiny, like one tenth of an inch long and very slender.

Unfortunately they are also flattened and a brownish red to black in color making them

easy to mistake for some dropped seasoning or other common kitchen item that is okay

to have around.

Saw Toothed Beetles aren't happy with just breakfast.

While they do like to invade cereal, they are also at home in your dried fruit, nuts,

meat, and pastas.

Sometimes they will also invade flour but at least here their dark coloring comes in

handy.

Rule of thumb, if there are moving black specks in your flour, skip the cookie baking.

The most terrifying thing about this beetle and the reason it made the number two spot

is that it is flat enough to slip right into what is apparently a sealed box making nothing

truly safe once the saw toothed beetle invades your home.

1.

And finally, the number one breakfast invader is the Indianmeal moth.

They are the most common moth you will find infesting your foods.

Even though they are only about a half inch long, they are recognizable by their wings.

The front wing is pale gray or tan with the other two thirds changing to a reddish brown

color with a coppery tone.

The good news is these wing markings are pretty distinctive.

The bad news is that sometimes the scales get rubbed off the indianmeal moth making

the wings more boring in appearance.

You'll most often find them flying around your house but they or their larvae could

also be hiding out in stored food.

The larva are whitish worms with a bit of yellow, pink, green or brown mingled in and

run about one half inch long just like their parents.

Both parents and young like to eat whole grains, like cereal, and the biggest giveaway that

you have an infestation is that the surface of the food might have a silk webbing on top.

Look before you break that webbing because it is hard to see.

Another piece of bad news, Indian Meal Moths also like chocolate, dried fruits, pasta,

crackers, nuts, powdered milk, candies, and even dried peppers so you aren't even safe

after breakfast.

Pantry pests contaminate more food than they eat so even if you don't see them in your

cereal bowl, keep a watchful eye around the house.

Now with that truly happy thought, click subscribe and I'll be back tomorrow with something

curious to share – and I promise it won't be as gross.

For more infomation >> 10 PESTS MOST LIKELY LIVING IN YOUR FOOD RIGHT NOW! - Duration: 8:57.

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Sole female candidate Sim Sang-jung is voice of working class - Duration: 4:30.

A labor activist-turned politician, and a long-time critic of the corruption in Korea's

public and private sectors.

With an impressive resume, Sim Sang-jung, the presidential hopeful of the minor left-wing

Justice Party, entered the race with a vow to create a nation where everyone can work

with a sense of pride.

"Together with me, Sim Sang-jung, let's build a new nation that brings change to everyone's

lives."

Sim began her political career under the then-Democratic Labor Party in 2000, a party she ended up

leading.

But don't let her soft smile fool you,... she's a tough cookie.

Before becoming a force in the National Assembly, Sim fought for decades to improve workers'

rights.

When she was a college student she took a job as a seamstress at a factory, where teenagers

worked day and night in poor conditions.

Thus began Sim's 25 years of activism.

Leading workers' organizations, she was often isolated in tough battles.

At one point she was even wanted on charges of instigating strikes,...

but her supporters say her experiences are what made her who she is today..a respected

candidate who's not afraid to give a voice to the underprivileged.

Her first stop on the campaign trail?

To Seoul's subway system to meet with mechanics, cleaners, and irregular laborers to tell them

they are the engine that moves Korea.

As someone who believes in the value of hard work... it's only natural for her to encourage

working-class voters.

"What time do you come to work?"

"10a.m."

"What time do you get off?"

"I get home at midnight."

The self-employed merchants at this market, who can only dream of having a day off...

let alone a week,... also welcome Sim's vision.

"Seomyeon, a popular meetup place and the commercial center of Busan.

This is the spot Sim chose to discuss with local residents her ambitions, to better young

workers rights as well as the potential this city holds."

With piercing confidence, Sim assures voters that she will bring an end to the widening

gap between the rich and the poor.

"I want to build a nation where everyone can work with a sense of pride.

And that's a nation that values skill and hard work, not one's wealth."

Her pledges center around helping women who are struggling to balance work and family

life....

"I love you."

"Please make our nation a great place to live in."

...something that both men and women have long called for.

"She's the most trusted candidate, especially among workers and young people.

If she becomes president, I believe she'll establish good polices on women's issues and

women's rights."

"We need forward-thinking policies when it comes to working mothers and the rising youth

unemployment rate.

I believe Sim will also work harder than any other candidate to make the economy better

for working-class people."

"As a worker, I think the reality is we can't take pride in what we do.

That's why I'm rooting for Sim.

I want a society in which I can see my value as a person through my labor."

Making voters in Busan, a conservative stronghold, listen... and even convert to her way of thinking

is one of Sim's uncanny abilities.

She's yet to poll higher than the other four major candidates,... but the party says that's

mostly due to its scale; as it holds just 6 seats in the 300-seat National Assembly.

"She hasn't had the same exposure as the other candidates, but those who meet her in person

or hear what she stands for come to realize she's the leader our country needs.

Sim's progressive policies are what we need in order to represent those who lit their

candles, against corruption among the powerful."

The corruption among the powerful caused an early election in Korea.

But Justice Party believes the nation now cries out for more than just an administrational

change and in need of a societal reformation.

As Sim tours the length and breadth of the nation to spread her message of protecting

the weak and vulnerable...her supporters have no doubt that she will be the one to deliver

that change in everyone's lives.

Lee Unshin, Arirang News.