mapleprimes.com Report : Visit Site


  • Ranking Alexa Global: # 174,494,Alexa Ranking in United States is # 226,947

    Server:Microsoft-IIS/8.5...
    X-Powered-By:ASP.NET

    The main IP address: 199.71.183.11,Your server Canada,Waterloo ISP:Waterloo Maple Software Inc.  TLD:com CountryCode:CA

    The description :about help contact register login posts and questions questions posts users mapleprimes advanced search questions posts products users unanswered maplesoft blog badges recent more tags rss feeds submi...

    This report updates in 07-Oct-2018

Created Date:2001-08-29
Changed Date:2017-08-30

Technical data of the mapleprimes.com


Geo IP provides you such as latitude, longitude and ISP (Internet Service Provider) etc. informations. Our GeoIP service found where is host mapleprimes.com. Currently, hosted in Canada and its service provider is Waterloo Maple Software Inc. .

Latitude: 43.505603790283
Longitude: -80.545486450195
Country: Canada (CA)
City: Waterloo
Region: Ontario
ISP: Waterloo Maple Software Inc.

HTTP Header Analysis


HTTP Header information is a part of HTTP protocol that a user's browser sends to called Microsoft-IIS/8.5 containing the details of what the browser wants and will accept back from the web server.

Content-Length:38759
Content-Encoding:gzip
Set-Cookie:MTC=TC-6885; path=/, .MapleLanguage=1; domain=www.mapleprimes.com; expires=Sun, 06-Oct-2019 20:44:42 GMT; path=/, ASP.NET_SessionId=z3di3kqvb2qr0uuapejhzp3j; path=/; HttpOnly
X-AspNet-Version:4.0.30319
Vary:Accept-Encoding
X-Powered-By:ASP.NET
Server:Microsoft-IIS/8.5
Cache-Control:private
Date:Sat, 06 Oct 2018 20:44:42 GMT
Content-Type:text/html; charset=utf-8

DNS

soa:ns.sentex.ca. hostmaster.maplesoft.com. 2014111700 3600 1200 604800 3600
ns:ns2.sentex.ca.
ns2.sentex.net.
ns.sentex.ca.
ipv4:IP:199.71.183.11
ASN:11647
OWNER:SENTEX-NET - Sentex Communications Corporation, CA
Country:CA
mx:MX preference = 5, mail exchanger = mh.maplesoft.com.
MX preference = 10, mail exchanger = mh2.maplesoft.com.

HtmlToText

about help contact register login posts and questions questions posts users mapleprimes advanced search questions posts products users unanswered maplesoft blog badges recent more tags rss feeds submit software change request maplesoft.com ask a question create a post featured post edit tina 70 making math fun – the... fourteen year old lazar paroski is an exceptional student. not only is he an overachiever academically, but he has a passion to help struggling students, and to think of innovative ways to help them learn. lazar is particularly fond of math, and in his interactions with other students, he noticed how students have a hard time with math. putting on his creative cap, lazar came up with the idea of an easily accessible “math wall” that explains simple math concepts for students in a very visual way. “the music wall on pinterest was my inspiration,” says lazar. “i thought i can use the same idea for math, and why not a math wall”? "the math wall is basically all the tools you'll have on the wall in your classroom outside," said lazar. making the math wall and getting it set up, took time and effort. but he had help along the way, which, fueled by his passion and enthusiasm, helped turn his creative dream into reality. lazar received a grant of $6000 from the local government to implement the project; his teachers, principal and family helped promote it; and the community of parents provided encouragement. the math wall covers fundamental math concepts learnt in grades 1 to 6. lazar engaged with over 450 students in the community to understand what would really be helpful for students to see in this math wall, and then he carefully picked the top themes he wanted to focus on. the three meter math wall is located in the morrison community park, and was officially inaugurated by the mayor of kitchener in july 2018. many students have already found it to be useful and educative. parents who bring their children to the park stop by to give their kids a quick math lesson. at maplesoft, we love a math story like this! and that too in our backyard! we wanted to appreciate and encourage lazar and his efforts in making math fun and easy and accessible to students. so we invited lazar to our offices, gifted him a copy of maple, and heard more about his passion and future plans. “in many ways, lazar embodies the same qualities that maplesoft stands for – making it easy for students to understand and grasp complex stem concepts,” said laurent bernardin, maplesoft’s chief operating officer. “we try to impress upon students that math matters, even in everyday life, and they can now use advanced, sophisticated technology tools to make math learning fun and efficient.” we wish lazar all the very best as he thinks up new and innovative ways to spread his love for math to other kids. well done, lazar! september 14 9 0 math student community + manage tags read full post featured post edit samir khan 1009 hybrid images, visual... you might recall this image being shared on social media some time ago. source: http://cvcl.mit.edu/hybrid_gallery/monroe_einstein.html look closely and you see albert einstein. however, if you move further away (or make the image smaller), you see marilyn monroe. to create the image, the high spatial frequency data from an image of albert einstein was added to the low spatial frequency data from an image of marilyn monroe. this approach was pioneered by oliva et al . (2006) and is influenced by the multiscale processing of human vision. when we view objects near us, we see fine detail (that is, higher spatial frequencies dominate). however, when we view objects at a distance, the broad outline has greater influence (that is, lower spatial frequencies dominate). i thought i'd try to create a similar image in maple (get the complete application here ). here's an overview of the approach (as outlined in oliva et al ., 2006 ). i used different source images of einstein and monroe. let's start by loading some packages and defining a few procedures. restart: with(imagetools): with(signalprocessing): fft_shift := proc(m) local nrows, ncols, quad_1, quad_2, quad_3, quad_4, crows, ccols; nrows, ncols := linearalgebra:-dimensions(m): crows, ccols := ceil(nrows/2), ceil(ncols/2): quad_1 := m[1..crows, 1..ccols]: quad_2 := m[1..crows, ccols + 1..-1]: quad_3 := m[crows + 1..-1, ccols + 1..-1]: quad_4 := m[crows + 1..-1, 1..ccols]: return <<quad_3, quad_2 |quad_4, quad_1>>: end proc: powerspectrum2d := proc(m) return sqrt~(abs~(m)) end proc: gaussian_filter := (a, b, sigma) -> matrix(2 * a, 2 * b, (i, j) -> evalf(exp(-((i - a)^2 + (j - b)^2) / (2 * sigma^2))), datatype = float[8]): fft_shift() swaps quadrants of a 2d fourier transform around so that the zero frequency components are in the center. powerspectrum2d() returns the spectra of a 2d fourier transform gaussian_filter() will be used to apply a high or low-pass filter in the frequency domain (a and b are the number of rows and columns in the 2d fourier transform, and sigma is the cut-off frequency. now let's import and display the original einstein and monroe images (both are the same size). einstein_img := read("einstein.png")[..,..,1]: embed(einstein_img) marilyn_img := read("monroe.png")[..,..,1]: embed(monroe_img) let's convert both images to the spatial frequency domain (not many people know that signalprocessing:-fft can calculate the fourier transform of matrices). einstein_fourier := fft_shift(fft(einstein_img)): monroe_fourier := fft_shift(fft(monroe_img)): visualizing the power spectra of the unfiltered and filtered images isn't necessary, but helps illustrate what we're doing in the frequency domain. first the spectra of the einstein image. lower frequency data is near the center, while higher frequency data is further away from the center. embed(create(powerspectrum2d(einstein_fourier))) now the spectra of the monroe image. embed(create(powerspectrum2d(monroe_fourier))) now we need to filter the frequency content of both images. first, define the cutoff frequencies for the high and low pass gaussian filters. sigma_einstein := 25: sigma_monroe := 10: in the frequency domain, apply a high pass filter to the einstein image, and a low pass filter to the monroe image. nrows, ncols := linearalgebra:-dimension(einstein_img): einstein_fourier_high_pass := einstein_fourier *~ (1 -~ gaussian_filter(nrows/2, ncols/2, sigma_einstein)): monroe_fourier_low_pass := monroe_fourier *~ gaussian_filter(nrows/2, ncols/2, sigma_monroe): here's the spectra of the einstein and monroe images after the filtering (compare these to the pre-filtered spectra above). embed(create(powerspectrum2d(einstein_fourier_high_pass))) embed(create(powerspectrum2d(monroe_fourier_low_pass))) before combining both images in the fourier domain, let's look the individual filtered images. einstein_high_pass_img := re~(inversefft(fft_shift(einstein_fourier_high_pass))): monroe_low_pass_img := re~(inversefft(fft_shift(monroe_fourier_low_pass))): we're left with sharp detail in the einstein image. embed(fitintensity(create(einstein_high_pass_img))) but the monroe image is blurry, with only lower spatial frequency data. embed(fitintensity(create(monroe_low_pass_img))) for the final image, we're simply going to add the fourier transforms of both filtered images, and invert to the spatial domain. hybrid_image := create(re~(inversefft(fft_shift(monroe_fourier_low_pass + einstein_fourier_high_pass)))): embed(hybrid_image) so that's our final image, and has a similar property to the hybrid image at the top of this post. move close to the computer monitor and you see albert einstein. move to the other side of the room, and marilyn monroe swims into vision (if you're myopic, just take off your glasses and don't move back as much). to simulate this, here, i've successively reduced the size of the hybrid image and just because i can, here's a hybrid image of a cat and a dog, generated by the same worksheet. september

URL analysis for mapleprimes.com


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https://www.mapleprimes.com/users/samir%20khan
https://www.mapleprimes.com/questions/225629-why-is-maple-missing-solutions

Whois Information


Whois is a protocol that is access to registering information. You can reach when the website was registered, when it will be expire, what is contact details of the site with the following informations. In a nutshell, it includes these informations;

Domain Name: MAPLEPRIMES.COM
Registry Domain ID: 76583257_DOMAIN_COM-VRSN
Registrar WHOIS Server: whois.godaddy.com
Registrar URL: http://www.godaddy.com
Updated Date: 2017-08-30T15:52:28Z
Creation Date: 2001-08-29T18:59:47Z
Registry Expiry Date: 2018-08-29T18:59:47Z
Registrar: GoDaddy.com, LLC
Registrar IANA ID: 146
Registrar Abuse Contact Email: [email protected]
Registrar Abuse Contact Phone: 480-624-2505
Domain Status: clientDeleteProhibited https://icann.org/epp#clientDeleteProhibited
Domain Status: clientRenewProhibited https://icann.org/epp#clientRenewProhibited
Domain Status: clientTransferProhibited https://icann.org/epp#clientTransferProhibited
Domain Status: clientUpdateProhibited https://icann.org/epp#clientUpdateProhibited
Name Server: NS.SENTEX.CA
Name Server: NS2.SENTEX.CA
Name Server: NS2.SENTEX.NET
DNSSEC: unsigned
URL of the ICANN Whois Inaccuracy Complaint Form: https://www.icann.org/wicf/
>>> Last update of whois database: 2018-07-31T16:46:18Z <<<

For more information on Whois status codes, please visit https://icann.org/epp

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The Registry database contains ONLY .COM, .NET, .EDU domains and
Registrars.

  REGISTRAR GoDaddy.com, LLC

SERVERS

  SERVER com.whois-servers.net

  ARGS domain =mapleprimes.com

  PORT 43

  TYPE domain

DOMAIN

  NAME mapleprimes.com

  CHANGED 2017-08-30

  CREATED 2001-08-29

STATUS
clientDeleteProhibited https://icann.org/epp#clientDeleteProhibited
clientRenewProhibited https://icann.org/epp#clientRenewProhibited
clientTransferProhibited https://icann.org/epp#clientTransferProhibited
clientUpdateProhibited https://icann.org/epp#clientUpdateProhibited

NSERVER

  NS.SENTEX.CA 199.212.134.1

  NS2.SENTEX.CA 199.212.134.2

  NS2.SENTEX.NET 64.7.153.49

  REGISTERED yes

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