Warehouse Keeper Valkon:
Only mules and fools should be loaded with heavy and nonessential packs. Why not deposit your items in this safe and affordable branch of the Iron Gate Guild? I swear by Maphr that we will protect your valuable with our lives...
Private Warehouse
Clan Warehouse
Learn skills.
Quest


SUBCLASS CHANGER
Community Subclass Manager.
Add Subclass
Deposit Selection.
Change Subclass
Withdraw Selection.
Cancel Subclass
Deposit Selection.
Get Certified
Withdraw Selection.


First Name is required
E-mail is required
Phone is required
Password is required
Confirm Password is required
Accept Terms & Conditions


HOME
ABOUT US
FLEX-BOX
Make Your Order Here
Type
...
Taco Piza
Blueberry
classic
Size
...
Large
Medium
Small
Topping
...
Mushroom
Pepperoni
Sausage
Crust
...
Thick
Thin
Add
Your Orders
Type
Topping
Crust
Total
Delivery: $.
Total: $.
Checkout
Checkout Form
Name
Delivery Option
...
Deliver
Collect
Submit
Enter Location
Estate
House Number
Submit


15 RCEP countries likely to proceed without India, says deputy minister
KUALA LUMPUR, Oct 13 — Indications have shown the 15 Regional Comprehensive Economic Partnership (RCEP) countries are likely to proceed with the trade deal without India, said Deputy International Trade and Industry Minister Ong Kian Ming.
He said, indications at the recent ASEAN + 5 countries (excluding India) showed that India still has major reservations (about RCEP).
“At this point in time, chances for India being able to sign the deal seem to be quite low.
“But nevertheless, the fact that we can have substantive conclusion at the ASEAN + 5 countries meeting, showing that we are able to send a very possible message to international trading system, that we are still very much pushing ahead with the multilateral arrangement to include more countries into higher standard free trade agreement, such as RCEP,” he said.
Ong told reporters after delivering the keynote address at “Listing on Bursa: Unlock Your Business Potential through Listing” here, today. — Bernama
MORE TO COME


Short description about self comes here! when our power of choice is untrammelled and when nothing prevents our being able to do what we like best, every pleasure is to be welcomed and every pain avoided.
Jan 2016 Dec 2015
On the other hand, we denounce with righteous indignation and dislike men who are so beguiled and demoralized by the charms of pleasure of the moment, so blinded by desire, that they cannot foresee the pain.
Mauris at justo vitae tortor malesuada placerat in vitae arcu.
Nam aliquam est et fringilla euismod.
Mauris aliquet augue at tempor blandit.
Vestibulum dignissim libero a leo pellentesque sollicitudin.
Sed faucibus magna tempor dolor auctor finibus.
Jul 2015 Sep 2014
Yes it is possible, although I don't think anyone will want to just google it and research for you without any evidence of what you have tried so far. In a free hour, when our power of choice is untrammelled and when nothing prevents our being able to do what we like best, every pleasure is to be welcomed and every pain avoided.
Feb 2014 Feb 2013
In a free hour, when our power of choice is untrammelled and when nothing prevents our being able to do what we like best, every pleasure is to be welcomed and every pain avoided.
Mauris at justo vitae tortor malesuada placerat in vitae arcu.
Nam aliquam est et fringilla euismod.
Mauris aliquet augue at tempor blandit.
Vestibulum dignissim libero a leo pellentesque sollicitudin.
Sed faucibus magna tempor dolor auctor finibus.
May 2013 Dec 2012
In certain circumstances and owing to the claims of duty or the obligations of business it will frequently occur that pleasures have to be repudiated and annoyances accepted. The wise man therefore always holds in these matters to this principle of selection: he rejects pleasures to secure other greater pleasures, or else he endures pains to avoid worse pains.
Vestibulum dignissim libero a leo pellentesque sollicitudin.
Sed faucibus magna tempor dolor auctor finibus.
Nam aliquam est et fringilla euismod.
Mauris aliquet augue at tempor blandit.
Mar 2012 Nov 2011
Duis gravida metus massa, sed egestas magna faucibus non. Nulla semper egestas sapien, ut suscipit lectus suscipit vel. Morbi urna quam, suscipit et eros id, ultrices viverra mauris. Nulla justo est, dictum non aliquet nec, bibendum vel tortor. Morbi imperdiet neque non gravida laoreet. In a free hour, when our power of choice is untrammelled and when nothing prevents our being able to do what we like best, every pleasure is to be welcomed and every pain avoided.
Jan 2011 Oct 2010
Nulla justo est, dictum non aliquet nec, bibendum vel tortor. Morbi imperdiet neque non gravida laoreet.
Vestibulum dignissim libero a leo pellentesque sollicitudin.
Sed faucibus magna tempor dolor auctor finibus.
Nam aliquam est et fringilla euismod.
Mauris aliquet augue at tempor blandit.
Aug 2010 Apr 2009
Think anyone will want to just google it and research for you without any evidence of what you have tried so far. Yes it is possible, although I don't. In a free hour, when our power of choice is untrammelled and when nothing prevents our being able to do what we like best, every pleasure is to be welcomed and every pain avoided. In a free hour, when our power of choice is untrammelled and when nothing prevents our being able to do what we like best, every pleasure is to be welcomed and every pain avoided.
Vestibulum dignissim libero a leo pellentesque sollicitudin.
Sed faucibus magna tempor dolor auctor finibus.
Nam aliquam est et fringilla euismod.
Mauris aliquet augue at tempor blandit.
Apr 2009 Sep 2008
When our power of choice is untrammelled and when nothing prevents our being able to do what we like best, every pleasure is to be welcomed and every pain avoided. But in certain circumstances and owing to the claims of duty or the obligations of business it will frequently occur that pleasures have to be repudiated and annoyances accepted. The wise man therefore always holds in these matters to this principle of selection: he rejects pleasures to secure other greater pleasures, or else he endures pains to avoid worse pains.
Sep 2008 Sep 2007
The wise man therefore always holds in these matters to this principle of selection: he rejects pleasures to secure other greater pleasures, or else he endures pains to avoid worse pains.
Mauris at justo vitae tortor malesuada placerat in vitae arcu.
Nam aliquam est et fringilla euismod.
Jan 2007 Feb 2006
Duis gravida metus massa, sed egestas magna faucibus non. Nulla semper egestas sapien, ut suscipit lectus suscipit vel. Morbi urna quam, suscipit et eros id, ultrices viverra mauris. Nulla justo est, dictum non aliquet nec, bibendum vel tortor. Morbi imperdiet neque non gravida laoreet.
Vestibulum dignissim libero a leo pellentesque sollicitudin.


Serif
Sample text:
This is a test
Sans-Serif
Sample text:
This is a test
Display
Sample text:
This is a test
handwriting
Sample text:
This is a test
Monospace
Sample text:
This is a test


GenM3U
File
Import
Export
Settings
Edit
Add
Clear the list
Check All
#
Actions
ID
Name
Metadata
Url
Last Check
{{channel.ID}}
{{channel.last_check | date:"medium"}}
Add channel
×
Add a new channel to the list
Name
Meta
Url
Clear list
×
Do you want to clear the list?
Import list
×
Import a new list
File
Export list
×
Export the channel list
Options
All
Online Only
Offline Only
Playlist served at:
{{servingUrl}}
Settings
×
Playlist served at
Private Key
Server
Attempts


Land and Water
I am an Environmental Economist interested in water-energy-food nexus, agricultural development, water economics and policy, gender issues.
Past academic studies that have looked into cross-country data indicated that the relationship between women’s labour participation (WLPR) and economic development is linear or curvilinear. This relationship is expressed in the popular U-shaped hypothesis which presumes a kind of trade-off between economic growth and women’s labour participation in the course of a country’s development (figure below).
The objective of this project is to use machine learning (ML) techniques to predict drivers of WLPR (with Principal Component and Exploratory Factor Analysis) and its linkage with GDP per capita across countries.
The project has been divided into three stages:
Stage 1. Data processing. The dataset obtained from the World Development Indicators. It covers 183 countries for 1990-2016 (383 features). Data processing included: data tidying and handling missing data (MD). Variables with >20% MD have been deleted (81 features retained). The remaining MD have been imputed by the Multiple Imputation by Chained Equations (MICE) technique with the Classification and Regression Tree method (CART, m=5, maxit=50). However, MICE has limitations in data imputation (figure below shows before and after MICE, yellow indicates MD). Therefore, for the remaining MD, a mean value imputation has been used.
Stage 2. Data scaling and normalization.
Fertility rate, men’s labour participation and GDP per capita were identified as main drivers of WLPR. To employ ML algorithm in the next stage data must be scaled and normalized. Thus, identified drivers have been scaled by three techniques (standard, min-max and robust).
Stage 3. Machine learning algoritm application. Regression technique has been used to predict WLPR based on GDP per capita with different training and testing sample size. The most representative with 70/30 ratio yielded RMS=53.6 (orange are predicted values).
R packages (tidyverse, dplyr, ggplot2, psych, gridExtra, ggpubr, data.table, pairedData, mice, VIM) was used in the first stage and Python packages (pandas, numpy, sklearn, matplotlib, seaborn, ggplot, plotly) in the second and third stages.
The most challenging part of the project was ML itself as three days of lessons during Data School was not enough. Therefore, the first couple of weeks I spent on learning ML algorithms. Data preparation took a significant amount of time as well (roughly 70-80% of the whole project time).
Although I ran PCA/EFA, their results were not satisfactory, therefore my next plan is to run PCA/EFA to reduce dimension of the initial dataset and employ other ML algorthms for similar prediction.


StackOverflow-lite®
LOGIN
Sign Up
Please fill in this form to create an account.
Full Name
Email
Password
Already have an account?
LOGIN
.
Sign Up


|
SystemC
2.3.3
Accellera SystemC proof-of-concept library
|
Files | |
| file | sc_hash.h [code] |
| file | sc_list.h [code] |
| file | sc_machine.h [code] |
| file | sc_mempool.h [code] |
| file | sc_pq.h [code] |
| file | sc_pvector.h [code] |
| file | sc_report.h [code] |
| file | sc_report_handler.h [code] |
| file | sc_stop_here.h [code] |
| file | sc_string.h [code] |
| file | sc_string_view.h [code] |
| file | sc_temporary.h [code] |
| file | sc_typeindex.h [code] |
| file | sc_utils_ids.h [code] |
| file | sc_vector.h [code] |


US Ignite and GENI, with the help of our partners at the National Science Foundation and Mozilla Foundation, will showcase new applications running on deeply programmable cyberinfrastructure that transcends the current Internet and has the potential to completely transform how we live, work, learn, and play.
The Beyond Today's Internet: Experiencing a Smart Future summit gives developers, industry, communities, government, foundations and universities working with software defined networks (SDN), cloud computing and gigabit networks a place to gather, learn and showcase their work. As these new technologies become a cornerstone of next-generation application development there’s a lot of new information to learn and share. The best way to learn is to spend time with people who are actually working with these new technologies and inventing ways to apply them to new products and services.
During the Summit, you will experience first-hand demos of next-generation applications run on this new network. Learn from engaging keynotes, tech presentations, and workshops lead by visionaries in the field. Hear from community leaders highlighting recent case studies, success stories, and best practices to improve your group’s next-generation technology initiatives.
The Summit is for individuals and organizations who work with next-generation technologies including software defined networking, local clouds and gigabit to end-user. If you are an application developer, university researcher, US Ignite community, foundation, corporation or government agency with a focus on advanced technologies, the Smart Future Summit is for you.
The program has been carefully designed to offer value to all experience levels, from students to senior researchers, software architects, network engineers and senior management. We look forward to having you join for this exciting event.
Get ready for panels/talks, demos and action when you join us for the Smart Future Summit in Washington, DC!
We are partnering with GENI and George Washington University to host the Summit on the GWU campus in Washington, DC.
Hilton Crystal City Hotel at Washington Reagan National Airport
Reservation can be made at this link: Hilton Crystal City Hotel Room Reservation
A block of rooms has been reserved for March 22, 2015 - March 27, 2015.
Address:
2399 Jefferson Davis HighwayArlington, Virginia, 22202
Tel: +1-703-418-6800
Applications are now closed and all travel awards have been issued.
We have a very limited number of travel awards available for academics and students of US institutions who wish to attend the US Ignite Application Summit. Due to hotel availability and deadline, your travel grant applications should be submitted by February 6th, 2015. Travel grant applications may be reviewed after the deadline but acceptance will be based on funding availability. Applications received by February 6 will be reviewed by the GENI Project Office and US Ignite and will be notified by no later than February 13th, 2015. Learn more: http://www.geni.net/wp-content/uploads/2015/01/Travel-Grant-Application-Instructions-GEC-22.docx
Washington, DC is accessible from Baltimore, Dulles and Ronald Reagan National airports. Consider the cost of ground transportation when making your flight selections.
We are adding speakers on a daily bases, so be sure to check back often to learn more about the exciting speakers at the Summit.
Mark Berman is GENI Project Director. As Project Director, he has overall responsibility for GENI’s technical direction and successful implementation. Mark works with the GENI community, which spans dozens of universities, government and industry partners, to ensure that GENI is well designed, technically feasible, and satisfies its research requirements.
Glenn Ricart brings forty years of innovation in computer networking and related fields to US Ignite. Glenn is an Internet pioneer who implemented the first Internet interconnection point (the FIX in College Park, Maryland) and was recognized for this achievement by being inducted into the Internet Hall of Fame in August 2013.
Leo M. Chalupa became the George Washington University’s first vice president of research on April 1, 2009. He serves as GW’s chief research officer, charged with overseeing the strategic and operational development of GW’s rapidly growing research enterprise. An accomplished scientist and administrator, Dr. Chalupa comes to GW following a 34-year career at the University of California, Davis, most recently serving as the chair of neurobiology, physiology and behavior in the College of Biological Sciences.
Tom Kalil is the Deputy Director for Policy for the White House Office of Science and Technology Policy and Senior Advisor for Science, Technology and Innovation for the National Economic Council. From 2001 to 2008, Kalil was Special Assistant to the Chancellor for Science and Technology at the University of California at Berkeley. He was responsible for developing major new multi-disciplinary research and education initiatives at the intersection of information technology, nanotechnology, microsystems, and biology.
France Córdova is the Director of the National Science Foundation (NSF). In that role, Córdova leads the only government science agency charged with advancing all fields of scientific discovery, technological innovation, and science, technology, engineering and mathematics (STEM) education. NSF's programs and initiatives keep the United States at the forefront of science and engineering, empower future generations of scientists and engineers, and foster U.S. prosperity and global leadership. Córdova is president emerita of Purdue University, where she served as president from 2007 to 2012.
Matt S. Erskine was appointed by President Obama to serve as the Deputy Assistant Secretary of Commerce for Economic Development and Chief Operating Officer of the Economic Development Administration in September 2011. Mr. Erskine brings more than 20 years of leadership and management experience in business, public sector, and public-private partnerships. Prior to joining the Obama Administration and the Department of Commerce, he led the private-public partnership driving economic development and foreign direct investment for the 5th largest metropolitan region in the U.S. and worked in senior roles at global business consulting firms.
Richard Culatta is a leader in the field of educational innovation. He has experience in K-12, higher education, and workplace learning environments. As the Director of the Office of Educational Technology for the U.S. Department of Education, his work focuses on leveraging technology to create personalized learning experiences for all students and promoting increased connectivity to improve access to education and make college more affordable. Prior to joining the U.S. Department of Education, he served as an education policy advisor to U.S. Senator Patty Murray.
Jim Kurose serves as the head of the National Science Foundation’s Directorate for Computer and Information Science and Engineering (CISE). He received a B.A. degree in physics from Wesleyan University and a Ph.D. degree in computer science from Columbia University. He has served as Distinguished University Professor in the School of Computer Science at the University of Massachusetts Amherst. In addition, he has been a Visiting Scientist at IBM Research, INRIA, Institut EURECOM, the University of Paris, the Laboratory for Information, Network and Communication Sciences, and Technicolor Research Labs.
William Wallace is Executive Director of US Ignite and brings to US Ignite more than 35 years of experience in the telecommunications industry, most recently as co-founder of DigitalBridge Communications (DBC), a venture-backed startup dedicated to bringing 4G broadband wireless services to underserved portions of the U.S.
Niky Riga is a Network Scientist for the GENI Project Office (GPO). Niky is responsible for supporting GENI users in integrating and deploying their experiments within the GENI infrastructure, and ensuring that the deployment makes the best use of GENI resources. Before joining the GPO in 2010, Niky worked on innovative projects within the Network Research department of BBN. Niky earned a Diploma in electrical and computer engineering at the National Technical University of Athens, and M.S. and Ph.D. degrees in computer science at Boston University.
Akihiro Nakao received his B.S. (1991) in physics and M.E. (1994) in information engineering from the University of Tokyo. He was at IBM Yamato Laboratory, Tokyo Research Laboratory, and IBM Texas Austin from 1994 until 2005. He received a M.S. (2001) and Ph.D. (2005) in computer science from Princeton University. He has been teaching as an associate professor (2005-2014) and as a professor (2014-present) in Applied Computer Science at the Interfaculty Initiative in Information Studies within the Graduate School of Interdisciplinary Information Studies at the University of Tokyo.
Chip Elliott is GENI Futures Director. As Futures Director, he is responsible for planning “what comes after GENI,” with a mission to maximize the impact and adoption of GENI technology and concepts. He has been actively involved in GENI’s planning since early 2006 as a system engineer for the wireless group. As founding Project Director, Chip led the GENI community in bringing the project to fruition, building from early concept and design, through initial implementation phases, and eventually to its initial nationwide deployment.
Steve Lohr reports on technology, business and economics for the New York Times. He was a foreign correspondent for The Times for a decade and served brief stints as an editor, before covering technology, starting in the early 1990s. In 2013, he was part of the team awarded the Pulitzer Prize for Explanatory Reporting “for its penetrating look into business practices by Apple and other technology companies that illustrates the darker side of a changing global economy for workers and consumers.""
Lev Gonick is co-founder and CEO of OneCommunity, which provides Internet services to anchor institutions throughout northeast Ohio. In 2011, Government Technology named Lev one of its “Top 25 Doers, Dreamers & Drivers in Public-Sector Innovation.” In the same year, Crain’s Business Cleveland named Gonick one of its “10 Difference Makers” in Northeast Ohio, and Broadband Properties honored him with its Cornerstone Award for “using fiber to build an inclusive society and empower individuals.”
Lev Gonick is co-founder and CEO of OneCommunity, which provides Internet services to anchor institutions throughout northeast Ohio. In 2011, Government Technology named Lev one of its “Top 25 Doers, Dreamers & Drivers in Public-Sector Innovation.” In the same year, Crain’s Business Cleveland named Gonick one of its “10 Difference Makers” in Northeast Ohio, and Broadband Properties honored him with its Cornerstone Award for “using fiber to build an inclusive society and empower individuals.”
Dr. Suzi Iacono is the National Science Foundation (NSF) deputy assistant director for CISE. During her tenure at NSF, she has served in many capacities, including CISE senior science advisor, acting division director in Computer and Network Systems (CNS) and Information and Intelligent Systems (IIS), and Program Director in IIS. Dr. Iacono also currently serves as the co-chair of the interagency subcommittee on Networking Information Technology Research and Development (NITRD) under the National Science and Technology Council (NSTC).
Dr. Craig Partridge is a Chief Scientist at Raytheon BBN Technologies and works in the Internetwork Research Department. Craig has worked on internetworking problems at BBN since 1983. Notable bits of work include designing how Internet email is routed, working with Phil Karn on TCP round-trip time estimation, and designing and building the world's fastest router in the mid-1990s. Craig has been an active member of ACM SIGCOMM and the IEEE Communications Society and chaired the National Research Council committee on how the Internet functioned on September 11, 2001.
Joseph (Joe) Kochan joins US Ignite as management consultant from Widelity, Inc. specializing in business strategy, business plan development and modeling, project management, network deployment and operations, and federal grant compliance.
Prior to joining Widelity, Mr. Kochan worked as part of the Department of Commerce’s BTOP grant program. Prior to that role, he was a founder and Vice President–Operations of DigitalBridge Communications (DBC), a Virginia-based startup backed by over $40M in venture funding dedicated to bringing broadband services to small, underserved markets nationwide using broadband wireless technology. At DBC, Mr. Kochan managed the design and deployment of 4G wireless networks covering over 600,000 people in 6 states, as well as the acquisition of the company’s first 20,000 customers.


Axe .json report generator
To get started, choose a .json file generated by axe and then click on `Generate Report`.
Upload a file
Generate Report


Invite people from your WTHContacts to join WTHApps. Everyone you invite will receive a welcome email and a 30 days Free Trial. Thanks!
{{ user.name }}
{{ user.emails[0].value }}


PAST
ONE LIVES
Ever miss out on our OneLive event streams? Not to worry – we’ve got it all saved for you here to watch. Have a look around!
Load More


Home
About Our Farm
Shop
Our Animals
Our Dames
Our Sires
Our Chickens
Goats For Sale
Contact Us
Products
Shop Now
Available Goats
Shop Now
Our Herd
Meet The Parents
About Us
See What Makes Us Different
→ Follow Us On Facebook ←


tech 5
Problem Solving
When writing code having problems occur is very common. You can expect to have got something slightly wrong in each block of code when you're learning. An extremely common problem for me is incorrect syntax. I find that the best way to tackle this problem is to re-read my code each character at a time. If I still can't find the problem after looking through a few times then I usually go for a walk. I find that taking a break and going outside then coming back to my work really helps as I have a clearer mind when I get back to it and can usually spot the issue pretty quickly.
Problem soving techniques
Pseudocode is something that I can't say that I have really experimented with yet as I don't usually write things down in this way. Other techniques consist of trying somethiing, rubber ducky method, reading error messages, console.logging, googling, asking peers/coaches for help and reflection. Of these techniques I've found that the ones I've been using the most are trying something, reading error messages and googling. This is because I find them the most efficient.
Definitions
.map() - This is a method used to create a new array which returns of the old array with new changed values from a function.
.filter() - This will create a new array in which all of the elements implemented return true, 'filtering' out the false ones.
.reduce() - This will 'reduce' all elements in an array into a single element.


You have {{ installationObject.monitors.length }} energy and water flow metres set up on the {{ installationObject.name }} installation. The live readings from these metres will update every 2 minutes.


--- title: "Quick-and-dirty image segmentation" author: "Einar" date: 2018-01-15 tags: ["image_segmentation", "mixture_models", "ocr", "handwritten_digits"] description: "Splitting images of three-digit handwritten numbers into the three separate digits using R." ---
A member of our lab does handwritten digit recognition in a highly structured setting. Without going into details, we want to read images of three-digit handwritten codes and recognize which number the image depicts. To avoid having to predict one of a thousand classes, we want to to split the images into three single digits.
I’m sure there are some very fancy ways indeed of doing this, but the following structure makes me think we can start with simpler solutions: (i) There are always three digits. Knowing how many digits we’re looking for is useful information. (ii) One image is one number. There is not much else in the image, so it’s enough to just find two cut points along the x-axis.
My best guess is that the best cut points will be the ones where there is the least amount of ink if you were to somehow collapse the image to fit entirely within the x axis. We do leave gaps between digits when writing, though some digits may be connected by a line due to quirks in handwriting and so on. You can see this in some pretty great data that I made for the purposes of this treatment. I cut out the individual numbers in that photo with the crop tool in the OS X Preview app and put them in a folder.
R is my preferred statistical computing environment, but I’m sure you can find this type of functionality anywhere. I choose to focus on the number I consider the worst: 586. I can never get those 8s right.
library(magick) # for image maipulation
## Warning: package 'magick' was built under R version 3.3.2
## Linking to ImageMagick <IP_ADDRESS>
## Enabled features: cairo, fontconfig, freetype, pango, rsvg, webp
## Disabled features: fftw, ghostscript, lcms, x11
library(plyr) # vectorized operations
img <- image_read("data/digits/586.jpeg")
plot(img)
#convert to greyscale
img <- image_quantize(img, max = 256, colorspace = "gray", dither = NULL, treedepth = NULL)
# get the intensities & look at them
mat <- image_data(img)[1,,]
nrows <- dim(mat)[1]
gsm <- matrix(as.numeric(mat), nrow=nrows)
hist(gsm, main="Histogram of intensities")
As we can see, the intensities roughly form two clusters, lights and darks (higher and lower numbers). Let’s say that intensity 130 roughly separates the lights from the darks.
# thresholding
gsm_tf <- gsm < 130
image(t(apply(gsm_tf, 1, rev)))
OK! Looks decent. I will go over this row by row (ie column by column because the matrix is sideways) and output the column numbers (ie row numbers, corresponds to x-coordinates in the original image) where there is ink (ie a True value after thresholding). This will yields a distribution over ink horizontally in the image.
hst <- alply(gsm_tf, 2, which)
occ <- NULL
for (i in 1:length(hst)) {
occ <- c(occ, hst[[i]])
}
hist(occ, nclass=20, main="Where is the ink at")
This looks roughly like three clusters roughly corresponding to the locations of the three digits. I will model this as a mixture of three normal distributions. That’s exactly what it sounds like: fit three normal distributions to these data. Hopefully one for each bump, which hopefully correspons to one for each digit.
Mixture models are fit with the EM algorithm, which we can mostly gloss over.
But: One important detail is that the method accepts as an argument your best
guess as to the size, scale, and location of the three components. I reason as
follows: (i) if you split the image into thirds, it’s reasonable to believe that
the three numbers each lie in the middle of one of these thirds. These are my
guesses for for the means, mu
. (ii) Probably there goes as much ink into one
digit as the next, so the size, lambda
, of each component is probably one
third. (iii) I set the initial scale or standard deviation, sigma
, to .5
arbitrarily. These are just starting points, you understand; the algorithm
iterates toward better values to maximize the likelihood of the data.
library(mixtools) # fits mixture distributions
## Warning: package 'mixtools' was built under R version 3.3.2
## mixtools package, version 1.1.0, Released 2017-03-10
## This package is based upon work supported by the National Science Foundation under Grant No. SES-0518772.
third <- nrows/3 # nrows because the image is tipped on its side
mix <- normalmixEM(occ, lambda = 1/3, mu = c(third/2, third + third/2, 2*third + third/2), sigma = .5)
## number of iterations= 50
plot(mix, whichplots=2)
The plot above shows the mixture distribution, its three components in different colors. This is everything we need: now I can simply choose my first cut as the point where red becomes less likely than green, and the second cut as the point where green becomes less likely than blue. This is the intersection between the respective density curves. You can easily find the analytical solution for this, but I just brute force it with a numerical solver below.
# I want to be sure that the clusters are in order so that I don't suddenly
# compare the wrong components
mu <- mix$mu[order(mix$mu)]
sigma <- mix$sigma[order(mix$mu)]
sepline <- function(mu, sigma) {
f <- function(x) dnorm(x, m=mu[1], sd=sigma[1]) - dnorm(x, m=mu[2], sd=sigma[2])
uniroot(f, interval=c(mu[1], mu[2]))$root
}
# for knitr reasons I have to reload the image
img <- image_read("data/digits/586.jpeg")
plot(img)
abline(v=sepline(mu[1:2], sigma[1:2]), lwd=2, col="red")
abline(v=sepline(mu[2:3], sigma[2:3]), lwd=2, col="red")
There you have it! I’m super happy with how well that turned out. It might not be sexy methodology; mixture models date back at least to the late 1800s. But I think it’s good progress for a short afternoon’s work.
I’ll show the results for all of my numbers now. I’ve packaged the above in a function, shown at the end of this post, because that’s just good sense.
# don't believe for a second that I didn't copy-paste this from the
# terminal and format it with the vim blockwise visual mode
filenames <- c(
"097.jpeg",
"210.jpeg",
"350.jpeg",
"351.jpeg",
"460.jpeg",
"463.jpeg",
"586.jpeg",
"727.jpeg",
"768.jpeg",
"846.jpeg"
)
for (fname in filenames) {
img <- image_read(paste0("data/digits/", fname))
plot(img)
abline(v=cutpoints(img), col="red", lwd=2)
}
## number of iterations= 10
## number of iterations= 8
## number of iterations= 10
## number of iterations= 9
## number of iterations= 9
## number of iterations= 18
## number of iterations= 50
## number of iterations= 16
## number of iterations= 7
## number of iterations= 9
cutpoints <- function(img) {
img <- image_quantize(img, max = 256, colorspace = "gray", dither = NULL, treedepth = NULL)
mat <- image_data(img)[1,,]
nrows <- dim(mat)[1]
gsm <- matrix(as.numeric(mat), nrow=nrows)
gsm_tf <- gsm < 130
hst <- alply(gsm_tf, 2, which)
occ <- NULL
for (i in 1:length(hst)) {
occ <- c(occ, hst[[i]])
}
third <- nrows/3 # nrows because the image is tipped on its side
mix <- normalmixEM(occ, lambda = 1/3, mu = c(third/2, third + third/2, 2*third + third/2), sigma = .5)
mu <- mix$mu[order(mix$mu)]
sigma <- mix$sigma[order(mix$mu)]
sepline <- function(mu, sigma) {
f <- function(x) dnorm(x, m=mu[1], sd=sigma[1]) - dnorm(x, m=mu[2], sd=sigma[2])
uniroot(f, interval=c(mu[1], mu[2]))$root
}
c(sepline(mu[1:2], sigma[1:2]), sepline(mu[2:3], sigma[2:3]))
}


Bagels
Description
Homemade bagels that are fresh out of the oven are delicious! Once you get the technique down, they are relatively easy to make.
During quarantine (2020), we stopped going to our grocery store to pick up fresh bagels in the mornings. After a few months, I decided to try making bagels at home. I could not believe how much I missed bagels!
Bagels are delicious by themselves, but I especially like them with peanut butter and jelly or as a breakfast sandwich (with scrambled eggs and bacon)!
Tips
When making the hole in the bagels, use your thumb to press a hole through the center of the dough ball and then use your index fingers to stretch out the dough to make the hole about 1" in diameter.
It may seem that the dough is to wet when it comes out of the boiling water, but this is good. The moisture on the dough makes for a crunchy exterior while keeping the interior nice and soft.
The water needs to be between 100-110 degrees (Fahrenheit) to active the yeast; I use a thermometer to check the water temperature. The sugar also helps the yeast bloom.
Make sure to thoroughly combine the salt into the flour; salt can kill the yeast if applied directly to the yeast.
List of Ingredients
- 500 grams of Bread Flour
- 1.5 Tablespoons of Sugar
- 1 Packet (10g) of Instant Dry Yeast
- 320 mL Water (between 100-100 degrees (Fahrenheit))
- 1.5 Teaspoons of Salt
- 0.5 Tablespoons of Canola Oil
Recipe Steps
- Pour the yeast into the bowl of a stand mixer; Add the water and sugar to bloom the yeast.
- Measure out the flour and salt into a separate bowl and combine thoroughly.
- Knead all the ingredients in a stand mixer for 5-10 minutes. The dough should come together with almost no dough sticking to the sides of the bowl.
- Transfer the dough (using a spatchula) onto a clean surface and knead into a smooth ball of dough.
- In a new bowl, spray the Canola oil on the bottom and sides to prevent the dough from sticking during the rise time.
- Place the dough ball into the new bowl and cover tightly with sticky wrap.
- Place the bowl in a warm spot in the kitchen to let rise for 1-2 hours. The dough should double in size during this time.
- Transfer the dough onto a clean surface and divide into 8 pieces.
- Form each dough piece into a little ball and let rest on baking sheet (no parchment paper is needed).
- Bring a large pot of water to a gentle boil.
- Preheat the oven to 425 degrees (F).

- Once the water is boiling, place each bagel into the boiling water. You'll need to do this multiple batches to prevent crowding the pot.
- Boil for 1 minute on each side and then return the bagels to the baking sheet.
- When the bagels are wet, place any toppings on the bagels (like sesame seeds).
- Bake for 20 minutes at 425 degrees (F).
- Let the bagels cool for 10 minutes before eating!


CREATE TABLE AS -- define a new table from the results of a query
CREATE [ GLOBAL TEMPORARY ] TABLE table_name [ (column_name [, ...] ) ] [ ON COMMIT { PRESERVE ROWS | DELETE ROWS } ] [ TABLESPACE tablespace ] AS query
CREATE TABLE AS creates a table and fills it with data computed by a SELECT command. The table columns have the names and data types associated with the output columns of the SELECT (except that you can override the column names by giving an explicit list of new column names).
CREATE TABLE AS bears some resemblance to creating a view, but it is really quite different: it creates a new table and evaluates the query just once to fill the new table initially. The new table will not track subsequent changes to the source tables of the query. In contrast, a view re-evaluates its defining SELECT statement whenever it is queried.
GLOBAL TEMPORARY
If specified, the table is created as a temporary table. Refer to CREATE TABLE for details.
table_name
The name (optionally schema-qualified) of the table to be created.
column_name
The name of a column in the new table. If column names are not provided, they are taken from the output column names of the query.
query
A query statement (that is, a SELECT command). Refer to SELECT for a description of the allowed syntax.


Match Play. 2-2 to 5. Should Red redouble? If redoubled, should White take?
pips Red=53 White=47
(CorrectAnswer= 0/0, ErrorScore= 0)
Trice’s Formula 62 will give you the correct answer to this problem, but Reichert’s formula will not. Simply looking at the pip count is insufficient in positions like this one – you need a formula.
This is a redouble (just) and a trivial take. For money it would be a blunder to redouble here but the cube has no value to White and Red is within his doubling window so he should redouble
This is a redouble (just) and a trivial take. For money it would be a blunder to redouble here but the cube has no value to White and Red is within his doubling window so he should redouble
Cube analysis 2-ply cubeless equity +0.339 (Money: +0.339) 0.670 0.000 0.000 - 0.330 0.000 0.000 Cubeful equities: 1. Double, take +0.677 2. Double, pass +1.000 (+0.323) 3. No double +0.651 (-0.026) Proper cube action: Redouble, take


95% of our boating experience has been on mono hulls, mainly racing from J22s to a Beneteau 45. Kris’s dad owns a F27 trailer trimaran that we have sailed a few times. In 1992 Dean and Kris purchased a 36 foot Cascade mono hull and cruised the western coast of the US and into Mexico. This is a light weight boat, 12,000 lbs, and as we came down the coast the boat usually only needed its jib up to hit boat speed. In the Sea of Cortez the light winds were not an issue for our boat and we could usually sail from anchorages to anchorages. The anchorages were all fairly deep and the boat was easily handled with just one person. We sailed for two years and then went back to the world of making money and being on solid ground.
Based upon all the great people and families we met on our first cruise we talked about going again when our son was 10 to 12. The opportunity has now come up so we started to look for a boat that would fit our family. Our needs now are slightly different then when we went the first time. We thought a slightly heavier boat would be nice, we wanted to have a shallow draft for the islands and our son’s dog would be joining us as well so we wanted easy access in and out of the dingy.
We started with many mono hulls on our mind but eventually went and looked at a catamaran which fit our needs very nicely. After deciding two hulls vs. one the real work began because we did not know much about the multihull designs or performance. The price of a multihull compared to a mono hull is higher and so that limited our choices as well. Our list narrowed down to a Gemini 105, for two it would have been nice but 3 and a dog just made it too small. A PDQ 36 looked good but we thought with a dog it would be nice to have a larger dinning/entry area. We looked at a Victory 35, and a Prout 37 as well. Since we have cruised before, we had an idea of what we wanted, and non of these met our criteria. We saw many boats we liked online, but unfortunately our budget did not like them. Dean finally spotted a boat on Craiglist that we had ruled out as too expensive, but this one we could afford. After looking at it, we knew it was the boat for us. So far, we are very happy with the Manta 38 Catamaran.
Selection of the Boat


Local area network
问题描述 :
A local area network (LAN) supplies networking capability to a group of computers in close proximity to each other such as in an office building, a school, or a home. A LAN is useful for sharing resources like files, printers, games or other applications. A LAN in turn often connects to other LANs, and to the Internet or other WAN.
In this contest, everybody is connecting with each others like the following figure.
In this contest, everybody is connecting with each others like the following figure.
The contest’s network was built as N rows and M columns, your computer locate at (0, 0) and the judger’s computer locate at (m-1, n-1) The code you submit would only transfer to up or right smoothly. It doesn’t matter if some accidents happened. Could you tell me how many ways from your computer to judger when a data wire was broken?
输入:
There are multiple cases. Every case contains two integers in the first line, N, M (3<=N+M<=40). Second line contains four integers X1, Y1, X2, Y2 (0<=X1, X2<M, 0<=Y1, Y2<N, |X1+Y1-X2-Y2|=1), meaning the broken wire position.
输出:
There are multiple cases. Every case contains two integers in the first line, N, M (3<=N+M<=40). Second line contains four integers X1, Y1, X2, Y2 (0<=X1, X2<M, 0<=Y1, Y2<N, |X1+Y1-X2-Y2|=1), meaning the broken wire position.
样例输入:
3 3 0 0 1 0
样例输出:
3
#include<iostream> #include<cstdio> #include<cstdlib> #include<cstring> #include<string> #include<queue> #include<algorithm> #include<map> #include<iomanip> #define INF 99999999 using namespace std; const int MAX=40+10; int dp[MAX][MAX]; bool mark[MAX][MAX]; int main(){ int n,m,x1,y1,x2,y2; while(cin>>n>>m){ memset(mark,false,sizeof mark); cin>>x1>>y1>>x2>>y2; dp[0][1]=1; mark[y1+1][x1+1]=mark[y2+1][x2+1]=true; for(int i=1;i<=n;++i){ for(int j=1;j<=m;++j){ dp[i][j]=dp[i-1][j]+dp[i][j-1]; if(mark[i][j] && mark[i-1][j])dp[i][j]-=dp[i-1][j]; if(mark[i][j] && mark[i][j-1])dp[i][j]-=dp[i][j-1]; } } cout<<dp[n][m]<<endl; } return 0; }
解题转自：http://blog.csdn.net/xingyeyongheng/article/details/9672933
(adsbygoogle = window.adsbygoogle || []).push({});
柒公公看见你真是太太高兴了 ！姐就一言迷啊！每天都头也不抬的盯着手机！晚上也抱着手机睡！像偶这种银缺文看比饿肚子还难受呀！偶喜欢看温馨感人细水长流女主强男主也不弱的感情故事最不喜欢那些虐死人的感情故事
这种题解就相当于直接贴代码了，，想看的是思路
这个差别应该不会太大，或许编辑器就自动优化成内联函数了
整理的很好，学习了
&这是C语言？
题本身没错，但是HDOJ放题目的时候，前面有个题目解释了什么是XXX定律。
这里直接放了这个题目，肯定没几个人明白是干啥
对于第一题，我的直觉告诉我换不换都一样，求指教
有些说不通吧，只有1个孩子肯定是男孩了
有点意思
老实说，这种方法就是穷举，复杂度是2^n，之所以能够AC是应为题目的测试数据有问题，要么数据量很小，要么能够得到k == t，否则即使n = 30，也要很久才能得出结果，本人亲测
第一段代码中：
next = next ;
明显不对吧，应该是 next =j;才对
这个分析相当全面，经典！
Thanks for using the time to examine this, I truly feel strongly about it and enjoy finding out far more on this subject matter. If achievable, as you achieve knowledge
great!
为什么暴力求解方法循环到sqrt(n) 就可以了呢


Toggle navigation
Coral Web Client
Dashboard
Login
Logout
Overview
Reservations
Enables
Equipment Info
Report a Problem
People
Supplies
Login
Username:
Password:
Dashboard
Upcoming Reservations
Start Time
End Time
Project
Instrument
9/24 5:00pm
9/24 9:00pm
Example Project
TMV Super
9/24 5:00pm
9/24 9:00pm
Example Project
Cambridge Fiji F200
Reservations
TBD


| {{match.startedAgo}}m ago | {{match.mode}} |
{{player.actor|vgLookup}} ({{player.player}}){{$last ? '' : ', '}} |
VS |
{{player.actor|vgLookup}} ({{player.player}}){{$last ? '' : ', '}} |
Lookup a Match by ID |
|
|
Enter a match id number to gather view prediction results and match insights! |
|
| {{input.match}} |
Lookup a Player by ID |
|
|
Enter a player id number to gather view prediction results and match insights! |
|