--- title: "Week 5 Lab" author: "Drew Tyre" date: "2017-08-01" output: html_document weight: 803051 ---
In this exercise we’ll practice fitting glms and making predictions. The data is hanson_birds
in package NRES803
. This data set was collected by Andrea Hanson during her MSc. project in the School of Natural Resources. She sampled 14 transects in CRP fields scattered across SE Nebraska 4 times throughout the summer. She measured Visual Obstruction Readings (VOR) at 12 spots along each transect; these were averaged to obtain a single number representing vegetation structure within the CRP field. She also recorded the amount of 4 types of land use in the surrounding 2 km radius circle. These landscape metrics were highly correlated, so she used a Principle Components analysis to derive two combined metrics that were uncorrelated with each other. PC1 represents a gradient of increasing row crops, while PC2 represents decreasing woodland.
Begin your analysis of Dickcissels (column “DICK” in the data.frame) by plotting the response variable against all three covariates individually. Check for any signs of non-linearities.
library(NRES803)
data(hanson_birds)
library(tidyverse) # load all the things
library(gridExtra) # to put multiple plots on one page
# make up a theme object that does what I want
my_theme <- theme_classic() + theme(text = element_text(size = rel(4)))
# some points overlap so use geom_count()
ggvor <- ggplot(hanson_birds, aes(x = vor, y = DICK)) + geom_count() +
geom_smooth() + scale_size_area(max_size = 4) + guides(size = FALSE) +
my_theme
## OMG I just figured out how to make these plots with
## different x axis variables!!!
ggpc1 <- ggvor + aes(x = pc1)
ggpc2 <- ggvor + aes(x = pc2)
# geom_bar with stat='count' nice for discrete data
ggdick <- ggplot(hanson_birds, aes(x = DICK)) + geom_bar(stat = "count") +
my_theme
grid.arrange(ggvor, ggpc1, ggpc2, ggdick)
Our response is discrete; only integer values occur. Moreover it is a count of events (seeing a bird), so no negative values occur. Both of these suggest that a Poisson distribution is a good choice.
So, we start by fitting a glm with a poisson error distribution using all three covariates and their pairwise interactions. Get the summary, and calculate the overall goodness of fit test to look for lack of fit. There aren’t many more models more complex than this for these data, so this will be our global model. We assess our assumptions with this model.
library(broom)
dick.1 <- glm(DICK ~ (vor + pc1 + pc2)^2, data = hanson_birds,
family = poisson)
sum.dick.1 <- glance(dick.1)
gof.p.dick.1 <- with(sum.dick.1, pchisq(deviance, df.residual,
lower = FALSE))
So our model is significantly over-dispersed (\(\chi^2=\) 88.06, df = 49, p = 0.0005217). That means that the estimated standard errors of our model are too small. For the moment we will ignore this issue, but keep in mind that tests of significance with this model are biased towards rejecting null hypotheses.
We can check the linearity assumption by plotting the deviance residuals against each covariate.
dick.1.test <- augment(dick.1)
lin.vor <- ggplot(dick.1.test, aes(x = vor, y = .std.resid)) +
geom_count() + scale_size_area(max_size = 4) + geom_hline(yintercept = 0,
linetype = 2) + geom_smooth() + guides(size = FALSE) + my_theme
lin.pc1 <- lin.vor + aes(x = pc1)
lin.pc2 <- lin.vor + aes(x = pc2)
grid.arrange(lin.vor, lin.pc1, lin.pc2)
That’s a bit squashed, but the horizontal line is inside the confidence polygon of the smooth fit throughout, so there is no indication that the linearity assumption is violated.
Finally, examine the residual plots.
resd1 <- ggplot(dick.1.test, aes(x = .fitted, y = .resid)) +
geom_point() + geom_smooth() + geom_hline(yintercept = 0,
linetype = 2) + my_theme
resd2 <- resd1 + aes(y = sqrt(abs(.std.resid))) + geom_hline(yintercept = 1,
linetype = 2)
resd3 <- ggplot(dick.1.test, aes(.hat, .std.resid)) + geom_vline(size = 2,
colour = "white", xintercept = 0) + geom_hline(size = 2,
colour = "white", yintercept = 0) + geom_point(aes(size = .cooksd)) +
geom_smooth(se = FALSE) + my_theme
# get int and slope for qqline
probs <- c(0.25, 0.75)
y <- quantile(dick.1.test$.std.resid, probs, names = FALSE, na.rm = TRUE)
x <- qnorm(probs)
slope <- diff(y)/diff(x)
int <- y[1L] - slope * x[1L]
qq.dick <- ggplot(dick.1.test, aes(sample = .std.resid)) + geom_qq(size = rel(4)) +
geom_abline(intercept = int, slope = slope, linetype = 2,
size = 2) + my_theme
grid.arrange(resd1, resd2, resd3, qq.dick)
Nothing particularly worrisome there.
Although this model is overdispersed, we’ll work with it for now. We can use the ratio of the summed Pearson residuals to residual degrees of freedom to correct the AICc values. First we want to create a list of possible models. With 3 main effects and their 3 interactions, we have 48 possible models to consider. That is far too many for such a limited dataset. Background knowledge suggests that we know vor will be important, so all models we consider should include that effect.  AICc model selection table for Dickcissel relative abundance in CRP fields.",
split.tables = Inf)
The top model includes pc2 and it’s interaction with vor. In fact, the four top models all include those terms. The second through fourth ranked models are all within 2 quasi-likelihood units of the top model, suggesting that nesting is playing a role here. Thus it seems justifiable to simply use the top model as our model for prediction. However, model averaging the predictions is quite easy given the AICcmodavg package, so lets try both ways and see how much it matters. As before, create some new data assuming pc1 and pc2 are at the median values:
nd <- data.frame(vor = seq(2, 9, 0.1), pc1 = median(hanson_birds$pc1),
pc2 = median(hanson_birds$pc2))
pred.dick <- augment(fits[[6]], newdata = nd, type.predict = "response")
pred.mavg <- modavgPred(fits, newdata = nd, type = "response",
c.hat = c_hat(fits[[11]]), modnames = modnames)
pred.dick$mod.avg.pred <- pred.mavg$mod.avg.pred
pred.dick$uncond.se <- pred.mavg$uncond.se
ggplot(hanson_birds, aes(x = vor, y = DICK)) + geom_count() +
scale_size_area(max_size = 4) + geom_line(aes(y = .fitted),
data = pred.dick, size = 2) + geom_line(aes(y = mod.avg.pred),
data = pred.dick, size = 2, linetype = 2) + my_theme + guides(size = FALSE)
So the model averaged prediction is right on top of the top model prediction in this case. Let’s look at the model coefficients for those top four models
# poo. easy way with stargazer doesn't play with tidyverse
# make a dataframe
tidy_w_name <- function(.x, .y) {
df <- tidy(.x) #get the coefficient table
df$modname <- .y #add a column with the modname
df # return df
}
# just the top 4 models to save grief later
etc <- map2_df(fits[c(6, 9, 10, 11)], modnames[c(6, 9, 10, 11)],
tidy_w_name)
etc <- mutate(etc, Estimate = paste(formatC(estimate, digits = 3,
format = "f"), " (", formatC(std.error, digits = 3, format = "f"),
")", sep = ""))
tab <- spread(etc[, c(1, 6, 7)], key = modname, value = Estimate)
# arrange the models in order ...
pander(tab[, c(1, 5:2)], split.tables = Inf, caption = "Table 2. Estimates (SE) for each of the top four models.")
The row ordering of that table isn’t the best, but it’ll work for now. What I want to do is check to see if any of the coefficients from the second through fourth ranked models have estimates more than 2 SE from zero. For example, pc1
is at most 2 times the SE in those models. The value of the other two coefficients pc1:pc2
and vor:pc1
also have small magnitudes relative to their SE. This increases our confidence that nesting effects are responsible for the model selection uncertainty. Ignoring the model selection uncertainty might make our predictions a bit too precise, but the parameters vor
, pc2
and vor:pc2
are very similar across the four models.
Finally, I want to make a plot showing the prediction from the top model that demonstrates the interaction with pc2
. To do this, I’ll make predictions from the lower quartile, median and upper quartile of pc2
for a range of vor.
nd <- crossing(vor = seq(2, 9, 0.1), pc2 = quantile(hanson_birds$pc2))
nd$pc2Labels <- factor(rep_len(c("Min", "25%", "50%", "75%",
"Max"), nrow(nd)))
pred.dick <- augment(fits[[6]], newdata = nd, type.predict = "response")
ggplot(hanson_birds, aes(x = vor, y = DICK)) + geom_count() +
scale_size_area(max_size = 4) + geom_line(aes(y = .fitted,
colour = pc2Labels), data = pred.dick, size = 2) + my_theme +
guides(size = FALSE) + theme(legend.text = element_text(size = 16)) +
scale_color_discrete(breaks = c("Min", "25%", "50%", "75%",
"Max"), name = "PC2") + scale_y_continuous(limits = c(0,
25)) + xlab("Visual Obstruction Reading") + ylab("Dickcissel Abundance")
I spent a long time fussing around to make that graph look like I wanted. The defaults are often nice but sometimes you want something specific. To see the “quick and dirty” starting point for that graph run the first 4 lines leaving out the final ‘+’.
Working with binary data is similar, but back-transforming the link function is a bit more involved. Also the global goodness of fit test doesn’t work when the data are zero/one. The data are isolation
, which has three variables, incidence (presence/absence of a species), area of island (km^2), and isolation (distance to mainland in km). This exercise is modified from pg. 595 of Michael Crawley’s “The R Book”.
data(isolation)
names(isolation)
geom_boxplot()
).Ecological Thought provoker - Do you expect there to be effects of area and isolation, and in which direction should they go?
Next we’ll fit a binomial GLM, and then simplify using backwards selection.
isolation.1 <- glm(incidence ~ area * isolation, data = isolation,
family = binomial)
isolation.2 <- glm(incidence ~ area + isolation, data = isolation,
family = binomial)
anova(isolation.2, isolation.1, test = "Chisq")
So the simpler model is not worse than the more complex model. Check the summary to find the weakest single term, and continue with the backwards selection.
summary(isolation.2)
# area has the smallest z score
isolation.3 <- update(isolation.2, . ~ . - area)
anova(isolation.3, isolation.2, test = "Chisq")
So removing area
does make a significant difference, so we stop with isolation.2
.
Ecological thought provoker - Does the sign of the coefficients for area and isolation match your expectations from the boxplots?
Next we want to plot the effects.
nd <- data.frame(area = seq(0, 9, 0.01), isolation = median(isolation$isolation))
pred.p <- augment(isolation.2, newdata = nd, type.predict = "response")
ggplot(data = pred.p, mapping = aes(x = area)) + geom_line(mapping = aes(y = .fitted)) +
geom_rug(data = isolation[isolation$incidence > 0, ], sides = "t") +
geom_rug(data = isolation[isolation$incidence == 0, ], sides = "b") +
xlab("Island Area [km^2]") + ylab("Probability of Presence")
The “rug plots” are a way to show where the data points are located along the x-axis without cluttering up the graph too much.
Make a plot of the effect of isolation on incidence when island area is held at the median value.
Adding confidence limits to this sort of plot requires making the prediction on the linear predictor scale, constructing the confidence limits, and then back-transforming the predictions to the response scale using the inverse link function. There are several ways to write the inverse link function for a logit link model, but the easiest to use in my opinion is \[ \hat{p} = \frac{1}{1+e^{-\beta X}} \] where \(\beta X\) is the prediction on the link scale.
nd <- data.frame(area = seq(0, 9, 0.01), isolation = median(isolation$isolation))
pred.p <- augment(isolation.2, newdata = nd, type.predict = "link",
se.fit = TRUE) %>% mutate(p = 1/(1 + exp(-.fitted)), lowerci = 1/(1 +
exp(-(.fitted - 2 * .se.fit))), upperci = 1/(1 + exp(-(.fitted +
2 * .se.fit))))
ggplot(data = pred.p, mapping = aes(x = area)) + geom_line(mapping = aes(y = p)) +
geom_ribbon(mapping = aes(ymin = lowerci, ymax = upperci),
alpha = 0.5) + geom_rug(data = isolation[isolation$incidence >
0, ], sides = "t") + geom_rug(data = isolation[isolation$incidence ==
0, ], sides = "b") + xlab("Island Area [km^2]") + ylab("Probability of Presence")
What would happen if we used AIC model selection on this dataset?
models <- list(incidence ~ 1, incidence ~ area, incidence ~ isolation,
incidence ~ area + isolation, incidence ~ area + isolation +
area:isolation)
fits <- lapply(models, glm, family = binomial, data = isolation)
aictab(fits, as.character(models))


Hello
* * *
## Table of Contents
- [Introduction](#Introduction)
- [Add a map to a web page](#Add_a_map_to_a_web_page)
- [Plotting circles and donuts](#Plotting_circles_and_donuts)
- [Intersecting shapes to find the common area](#Intersecting_shapes_to_find_the_common_area)
- [Gumtree Seller Triangulation Example](#Gumtree_Seller_Triangulation_Example)
- [The solution - Binning](#The_solution_Binning)
- [Summary](#Summary)
- [See also](#See_also)
- [Other Languages](#See_also)
# Introduction
You can do some powerful things with Bing Maps and the Geospatial modules that come with the API and supporting services.
**This exercise is a warning to anyone who uses services similar to eBay, Craigslist, Gumtree, or even dating/hookup sites.**
**Some websites still do not take enough care to hide your actual home/account address.**
There are many legitimate reasons a person may want to offer a service. A cleaner for example, or a mobile hairdresser. They may not want to give their personal home address to anyone on the Internet. Many sites just show a seller's stated location. However,
they still have to register with the website using their full personal address - for billing and accounts.
Even if you hide address specifics, as shown below, some sites still calculated distance based on your exact postcode!
So, you may still be found through that old radar technique of triangulation!
Some sites think it's enough to round your distance up to a wider margin, like "within 5 miles" or "20-30" miles.
Sounds like a big enough area to get lost in right? Wrong!!
On some sites I tested, multiple searches from gradually moving locations, found the exact point at which "20-30" changes down to "10-20", or up to "30-40".
If the search feature is badly written, that is the point you can say the user is exactly 20 or 30 miles away (depending which way you were moving) - within a mile. In fact down to a quarter mile, in the example below!
Of course, that is still somewhere on the circumference path of a 30-mile radius circle. That's C = 2\*π\*R of course. In other words a path 188.5 square miles long!
That is when you need further search hits from other angles.
With multiple search rings, these searches combine to reveal an intersection area of all searches.
This intersection pinpoints the individual or item down to a very small area.
I tested quite a few times and this is often scarily accurate.
**I was looking for examples where moving my account address to an adjacent postcode made the triangulation point also move.**
Sometimes I was able to pinpoint remote locations, or a postcode area representing half of one side of a short street.
Try for yourself.
No web server is needed.
Just a file editor, a browser, and a some JavaScript basics.
# Add a map to a web page
This can be any HTML file, even one on your desktop.
Depending on how you serve the data, Bing Maps API doesn't need a server, just a browser to execute the web page in.
Links at the end of this article will get you started.
I'll skip the basics as this isn't just a 101 on using Bing Maps.
**This is more of a vulnerability analysis - using shapes and triangulation made so easy by the Bing Maps API, the map, and its awesome modules.**
# Plotting circles and donuts
Generating circles on maps used to be quite painful, as system.drawing was not really geared for longitude and latitudes.
You'd need to create a big enough drawing object and you'd need to multiply your location into an integer, then divide back down after.
But with **Microsoft.Maps.SpatialMath** Javascript library, everything gets simple again.
Below is the code to add a simple regular polygon with 36 sides, which nicely presents a circular-looking polygon:
Microsoft.Maps.loadModule("Microsoft.Maps.SpatialMath", function () {
var path = Microsoft.Maps.SpatialMath.getRegularPolygon(_loc, RadiusMeters, 36, Microsoft.Maps.SpatialMath.Meters);
var outerPoly = new Microsoft.Maps.Polygon(path,
{
fillColor: 'rgba(0, 0, 0, 0.5)',
strokeColor: 'black',
strokeThickness: 0.5
});
map.entities.push(outerPoly);
}
If your search result has a minumum/maximum figure, for example, "20-30", then you need to carve out a hole in your polygon.
This is achieved by calling the Microsoft.Maps.SpatialMath.Geometry.difference function, which returns the bit from the first shape which is NOT in the second shape.
if(_search.MinDistance == 0 || (_search.MinDistance - margin <= 0)) {
// Push as solid circle
sysCirclesLayer.add(outerPoly);
triCanvasArray.push(outerPoly);
}
else{
// Push as donut
varholeRad = _search.MinDistance - margin;
path = Microsoft.Maps.SpatialMath.getRegularPolygon(_loc, ((holeRad) * 1609.34), 36, Microsoft.Maps.SpatialMath.Meters);
varinnerPoly =newMicrosoft.Maps.Polygon(path);
vardonut = Microsoft.Maps.SpatialMath.Geometry.difference(outerPoly, innerPoly);
sysCirclesLayer.add(donut);
triCanvasArray.push(donut);
}
# Intersecting shapes to find the common area
Once you've built up a collection of circles or donuts, you can push them each, through a base green rectangle, leaving just the shared areas:
Microsoft.Maps.loadModule("Microsoft.Maps.SpatialMath",function () {
varbnds = Microsoft.Maps.SpatialMath.Geometry.bounds(triCanvasArray);
varcent = Microsoft.Maps.SpatialMath.Geometry.centroid(triCanvasArray);
varhalfWidth = bnds.width / 2;
varhalfHeight = bnds.height / 2;
varbndAry = [
newMicrosoft.Maps.Location(cent.latitude - halfHeight, cent.longitude - halfWidth),
newMicrosoft.Maps.Location(cent.latitude - halfHeight, cent.longitude + halfWidth),
newMicrosoft.Maps.Location(cent.latitude + halfHeight, cent.longitude + halfWidth),
newMicrosoft.Maps.Location(cent.latitude + halfHeight, cent.longitude - halfWidth),
newMicrosoft.Maps.Location(cent.latitude - halfHeight, cent.longitude - halfWidth),
];
varrect =newMicrosoft.Maps.Polygon(bndAry,
{
fillColor:'rgba(0, 255, 0, 0.5)'
});
for(vara = 0; a < triCanvasArray.length; a++) {
varnewRect = Microsoft.Maps.SpatialMath.Geometry.intersection(rect, triCanvasArray[a]);
rect = newRect;
}
spatMathTriLayer.add(rect);
vartLoc =newMicrosoft.Maps.Location(cent.latitude, cent.longitude)
vartPin =newMicrosoft.Maps.Pushpin(tLoc, {'draggable':false,'color':'green','text':'O' });
spatMathTriLayer.add(tPin);
});
# Gumtree Seller Triangulation Example
There are also many positive uses for this...
Tracking down stolen items on auction sites, for example.
I wouldn't recommend visiting the home or workplace of a seller to reclaim your items, who themselves may have just bought it from someone at a car boot sale!
However, it is often enough evidence for local police to pay the seller a visit and potentially recover matching forensics, a concrete lead, or indeed your stolen property!
I've chosen an example advert from Gumtree (free classifieds ads website) to show you. I picked this one simply because it advertises its postcode location - so we can confirm the triangulation results.
[![ ](https://social.technet.microsoft.com/wiki/resized-image.ashx/__size/550x0/__key/communityserver-wikis-components-files/00-00-00-00-05/2538.CaptureCar1b.PNG)](http://social.technet.microsoft.com/wiki/cfs-file.ashx/__key/communityserver-wikis-components-files/00-00-00-00-05/2538.CaptureCar1b.PNG)
Above showing at 2 miles from the searched postcode.
This [now old] advert is by a company called "Ford Wimbledon", whose address is this map location shown.
[![ ](https://social.technet.microsoft.com/wiki/resized-image.ashx/__size/550x0/__key/communityserver-wikis-components-files/00-00-00-00-05/7183.CaptureCar.PNG)](http://social.technet.microsoft.com/wiki/cfs-file.ashx/__key/communityserver-wikis-components-files/00-00-00-00-05/7183.CaptureCar.PNG)
[![ ](https://social.technet.microsoft.com/wiki/resized-image.ashx/__size/550x0/__key/communityserver-wikis-components-files/00-00-00-00-05/2620.CaptureCar2.PNG)](http://social.technet.microsoft.com/wiki/cfs-file.ashx/__key/communityserver-wikis-components-files/00-00-00-00-05/2620.CaptureCar2.PNG)
The search tool allows you to specify a full postcode to query from.
[![ ](https://social.technet.microsoft.com/wiki/resized-image.ashx/__size/550x0/__key/communityserver-wikis-components-files/00-00-00-00-05/2061.CaptureCar1a.PNG)](http://social.technet.microsoft.com/wiki/cfs-file.ashx/__key/communityserver-wikis-components-files/00-00-00-00-05/2061.CaptureCar1a.PNG)
Results are down to a quarter mile.
[![ ](https://social.technet.microsoft.com/wiki/resized-image.ashx/__size/550x0/__key/communityserver-wikis-components-files/00-00-00-00-05/4705.CaptureCar1.PNG)](http://social.technet.microsoft.com/wiki/cfs-file.ashx/__key/communityserver-wikis-components-files/00-00-00-00-05/4705.CaptureCar1.PNG)
[![ ](https://social.technet.microsoft.com/wiki/resized-image.ashx/__size/550x0/__key/communityserver-wikis-components-files/00-00-00-00-05/2548.CaptureCar1c.PNG)](http://social.technet.microsoft.com/wiki/cfs-file.ashx/__key/communityserver-wikis-components-files/00-00-00-00-05/2548.CaptureCar1c.PNG)
Further searches narrow the location down to a small area, which you can even visit in street view.
[![ ](https://social.technet.microsoft.com/wiki/resized-image.ashx/__size/550x0/__key/communityserver-wikis-components-files/00-00-00-00-05/1300.CaptureCar5b.PNG)](http://social.technet.microsoft.com/wiki/cfs-file.ashx/__key/communityserver-wikis-components-files/00-00-00-00-05/1300.CaptureCar5b.PNG)
Zooming in close, you see how small an area it carves out, down to quarter-mile accuracy:
[![ ](https://social.technet.microsoft.com/wiki/resized-image.ashx/__size/550x0/__key/communityserver-wikis-components-files/00-00-00-00-05/6433.CaptureCar6.PNG)](http://social.technet.microsoft.com/wiki/cfs-file.ashx/__key/communityserver-wikis-components-files/00-00-00-00-05/6433.CaptureCar6.PNG)
Switching to aerial view confirms the same rooftop/postcode as the advertising company.
[![ ](https://social.technet.microsoft.com/wiki/resized-image.ashx/__size/550x0/__key/communityserver-wikis-components-files/00-00-00-00-05/3443.CaptureCar5.PNG)](http://social.technet.microsoft.com/wiki/cfs-file.ashx/__key/communityserver-wikis-components-files/00-00-00-00-05/3443.CaptureCar5.PNG)
I then tested this on quite a few popular sites that have distance search features.
In this example below, I set the profile address as East London.
However, search results still used the 'supposedly private' account postcode for search queries.
[![ ](https://social.technet.microsoft.com/wiki/resized-image.ashx/__size/550x0/__key/communityserver-wikis-components-files/00-00-00-00-05/3365.CaptureTriangulated.PNG)](http://social.technet.microsoft.com/wiki/cfs-file.ashx/__key/communityserver-wikis-components-files/00-00-00-00-05/3365.CaptureTriangulated.PNG)
*I set the profile location as East London (blue box) but search results pinpointed the account location at "TN2X 1SL", which was the privately registered address.*
**I tried shifting the account postcode to the next address one mile away, and the triangulation also shifted.**
**This showed that it was querying on the exact postcode location, rather than the stated minimum five-mile accuracy.**
The green area is the intersection of all three searches, using Bing Maps API Spatial.Math modules.
The green dot is just the 'centroid' of the shape if all three searches were combined into one shape.
The red circle is the accuracy circle round a point calculated using the "age-old" method of intersecting shapes - using the system.drawing namespace and a graphics object.
So it's nice to see both green area and red circle match.
# The solution - Binning
The solution to triangulation (as old as the mathematical technique itself) is termed binning, which is a form of statistical quantization.
Locations are grouped into one shared "box" and are queried on as a whole, by the middle of that box. This is a technique we can also employ with the visual tools on our Bing map, with
**[Bing Map API Data Binning](https://www.bing.com/api/maps/sdk/mapcontrol/isdk/bivariatedatabins)**.
Binning allows you to group all the postcodes from an area and report back a common and consistent center (centroid) for them all. As shown in the last image, the green dot represents the centroid of the boundary of the shape, which represents all the other
shapes combined together.
This was clearly being done by about half the sites I tested and since by most that I contacted.
**Please test your own favorite services and let them know if you find this "vulnerability".**
# Summary
In conclusion, some services I tested did not properly protect its users from this most basic form of location pinpointing.
Long before posting this, I contacted the worst offenders.
To be fair, *most*were quick to act.
In the worst case I found, the "who's online now" widget of a "mental health support" website allowed me to triangulate the "closest support worker in your area" to the address of a farm. When I called the helpline to tell them, they confirmed they were
indeed registered as a user on the site at that address - which of course should have been private to their account.
There are no doubt a great many smaller sites, which fall foul of this and I hope you'll join me, keeping an eye out for this.
This highlights how even these days, a naïve implementation of a common website feature can put potentially vulnerable users at risk.
# See also
- [Data Binning Module](https://msdn.microsoft.com/en-us/library/mt743067.aspx)
- [Bing Spatial Data Services](https://msdn.microsoft.com/en-us/library/ff701734.aspx)
- [Bing Maps - Official Site](https://www.bing.com/maps)
- [Bing Maps API Documentation](https://msdn.microsoft.com/en-us/library/dd877180.aspx)
- [Bing Maps V8 Web Control](https://msdn.microsoft.com/en-us/library/mt712542.aspx)
- [Developer code samples](https://code.msdn.microsoft.com/site/search?f[0].Type=SearchText&f[0].Value=bing%20maps)
- [Extra Map API Modules](https://msdn.microsoft.com/en-us/library/mt712663.aspx)
# Other Languages
- [Advertencia
para usuarios de redes sociales y vendedores de servicios: su ubicación real potencialmente expuesta. Vulnerabilidades de triangulación, con ejemplos, usando la API de Bing Maps(es-MX)](https://social.technet.microsoft.com/wiki/contents/articles/51633.advertencia-para-usuarios-de-redes-sociales-y-vendedores-de-servicios-su-ubicacion-real-potencialmente-expuesta-vulnerabilidades-de-triangulacion-con-ejemplos-usando-la-api-de-bing-maps-es-mx.aspx)
* * *


#assign jsonindb = "true">
Postgres and Oracle have extensive support with JSON stored in the database. Both provide a lot of support for writing queries using document path expressions.
Ebean provides mapping support via @DbJson
and @DbJsonB
to map JSON documents to
various database types including Postgres JSON, JSONB types as well as standard Varchar, Clob and Blob types.
The mapping can be used with all supported databases and Postgres and Oracle provide support for including
JSON expressions in query where clauses.
Both Postgres and Oracle support writing queries with JSON expressions and Ebean exposes the most common query expressions.:
For all databases JSON documents can be mapped on entity beans and saved and loaded from the database.
In your entity bean you can annotate a property with @DbJsonB
and that indicates that the property
maps to a JSONB database type. For non-Postgres databases this maps to a database Clob.
In your entity bean you can annotate a property with @DbJson
and that indicates that the property
maps to a JSON database type. For non-Postgres databases this maps to a database Clob.
You put JSON content into the content property and save it and fetch is as normal.
```java String rawJson = "{\"docName\":\"My document\", \"docScore\":234, \"title\":\"Some title\"}"; // get the JSON into a map using Jackson or similar tool. // Ebean has EJson which using Jackson core which can be used // to parse JSON content Map
Postgres
and Oracle
provide expressions such that you can use a path
expression to test is a given path EXISTS
or test the value at a path.
Ebean ExpressionList
has expressions for:
Ebean uses Postgres ->>
and #>>
operators to support the JSON expressions.
For Postgres Ebean's jsonExists()
jsonNotExists()
expression result in the
path value using ->>
or #>>
and IS NULL
and IS NOT NULL
.
The function can then be used in an Ebean query like:
```sql select t0.id c0, ... where (t0.content #>> '{path,other}') is not null ```
For Postgres Ebean's value expressions such as jsonEqualTo()
, jsonGreaterThan()
etc use
the ->>
or #>>
operator depending on the path and then cast the result depending on the
value testing against. That is, if the value tested is a Integer or Long the DB path expression is cast to
::INTEGER
and there is similar casting for ::DECIMAL
and ::BOOLEAN
.
Ebean uses Oracles json_exists
and json_value
functions to support Ebean's JSON
expressions.
For Oracle Ebean's jsonExists() expression uses the Oracle json_exists
function.
The function can then be used in an Ebean query like:
```sql select t0.id c0, ... where json_exists(t0.content, '$.path.other') ```
For Oracle Ebean's value's jsonEqualTo() jsonGreaterThan() etc use the Oracle json_value
function.
If the provided expressions do not match what is required you can use raw()
expressions.


Toggle navigation
Validation With KnockOut JS
Employee Form
First Name
Last Name
Email
Country
Phone Number
Address
Password
Confirm Password
20 + 30
Save
Reset
Form has submitted with successful
Please check your submission


MicroProfile
Hello JAX-RS endpoint
Fault tolerance
Fallback after timeout
Health
Health (Live) status (with custom status)
Health (Ready) status (with custom status)
Metrics
Timed endpoint
Metrics page
Rest Client
Call REST endpoint using generated client based on interface


Toggle navigation
Nutrition Facts Calculator
Home
Nutrition Facts Calculator
Use the interactive tool below to easily calculate nutrition information
Net Weight
Grams
Serving Size
Grams
Total Fat
Grams
Total Carbohydrate
Grams
Protein
Grams
Calculate
Nutrition Fact Calculated per Grams
#
Nutrition Name
Fact Size Per Serving
Fact Size Per Net Weight
1
Total Fat
2
Total Carbohydrate
3
Protein


Module: Truth::Hookable
Instance Method Summary (collapse)
- - (Object) emit(name, *args)
- - (Object) get_hooks(name)
- - (Object) hook(name, &blk) (also: #on)
- - (Object) hook_wrap(name, *args, &blk)
- - (Object) hooks
Instance Method Details
- (Object) emit(name, *args)
16 17 18 19 20 21 22 23 24 |
# File 'lib/truth/hookable.rb', line 16 def emit(name, *args) # first ask the object itself send(:"on_#{name}", *args) if respond_to? :"on_#{name}" # then look for external hooks get_hooks(name).each do |blk| blk.call(*args) end end |
- (Object) get_hooks(name)
7 8 9 |
# File 'lib/truth/hookable.rb', line 7 def get_hooks(name) hooks[name.to_sym] ||= [] end |
- (Object) hook(name, &blk) Also known as: on
11 12 13 |
# File 'lib/truth/hookable.rb', line 11 def hook(name, &blk) get_hooks(name) << blk end |
- (Object) hook_wrap(name, *args, &blk)
26 27 28 29 30 31 32 |
# File 'lib/truth/hookable.rb', line 26 def hook_wrap(name, *args, &blk) emit "before_#{name}", *args r = yield emit "#{name}", *args emit "after_#{name}", *args r end |
- (Object) hooks
3 4 5 |
# File 'lib/truth/hookable.rb', line 3 def hooks @hooks ||= {} end |


_______ _______ ______ _______ | | | ___| __ \ | | | ___| < - | |___|___|_______|___|__|_______| web PLAYER
....so take Your time and if You still want to visit us consider to disable the adblocked or to add out domain to the white list!


Mobile formats available (PDF, Mobi, ePub) DRM-free
Streaming Dataset API for aggregates
groupBy Operator — Untyped Streaming Aggregation
Demo: groupBy Streaming Aggregation with Append Output Mode
groupByKey Operator — Streaming Aggregation
window Function — Stream Time Windows
withWatermark Operator — Event Time Watermark
mapGroupsWithState Operator — Stateful Streaming Aggregation (with Explicit State Logic)
...and 40 mins of our time went awayRead Spark Structured Streaming gitbook
Read Mastering Apache Spark 2 gitbook
Follow @jaceklaskowski on twitter
Upvote my questions and answers on StackOverflow


type: Component
selector: nb-breadcrumb
exportAs: nbBreadcrumb
nb-breadcrumb
used to show the current site level, and navigate quickly.
Two modes are supported, one is href
navigation(set the href
property in datasource),
the other is router
navigation(set the path
property in datasource).


| Package | Description |
|---|---|
| com.here.android.mpa.common |
This
package includes classes, interfaces, and enumerations that are generally used by other
packages in the Android SDK.
|
| com.here.android.mpa.mapping |
The mapping
package provides classes, interfaces, and enumerations that display an
interactive map, and related functionality that allows your application
to create and add map content.
|
| com.here.android.mpa.routing |
This
package provides classes, interfaces, and enumerations for route calculation and
route description (directions).
|
| com.here.android.mpa.search |
The search package provides classes for performing places and geocoder searches.
|
| Class and Description |
|---|
| CopyrightLogoPosition
Represents values that describe on-display view positions for the HERE copyright logo.
|
| GeoBoundingBox
Represents a rectangular area in a geographic coordinate system.
|
| GeoCoordinate
Represents a WGS84 coordinate with double precision.
|
| GeoPolyline
Interface representing a
GeoPolyline . |
| GeoPosition
Represents position, speed, and heading information as provided by a positioning device.
|
| Image.Type
This helps the application know the base type of the
Image . |
MapEngine
MapEngine manages all mapping resources and services provided in this SDK. |
| OnEngineInitListener
Represents a listener to provide notification of the engine status upon completion of
initialization.
|
| OnEngineInitListener.Error
Represents values describing initialization errors.
|
| PositioningManager
Represents a manager for information received from positioning devices, such as updates to the
current position and the average speed.
|
| PositioningManager.LocationMethod
Represents values describing the location method.
|
| PositioningManager.LocationStatus
Represents values describing the location status of a particular location method.
|
| PositioningManager.OnPositionChangedListener
Represents an interface for position update listeners.
|
| RoadElement.Attribute
Defined values for different road attributes
|
| RoadElement.FormOfWay
Form of Way Types
|
| RoadElement.PluralType
Plural type identifies when a Junction is made up of multiple Road Elements.
|
| ViewObject.Type
Represents values describing various types of selectable view objects.
|
| Class and Description |
|---|
| CopyrightLogoPosition
Represents values that describe on-display view positions for the HERE copyright logo.
|
| GeoBoundingBox
Represents a rectangular area in a geographic coordinate system.
|
| GeoCoordinate
Represents a WGS84 coordinate with double precision.
|
| GeoPolygon
Represents a
GeoPolygon a polygon object defined in terms of the geographic coordinates of its vertices. |
| GeoPolyline
Interface representing a
GeoPolyline . |
| Image
Encapsulates an image file.
|
| OnEngineInitListener
Represents a listener to provide notification of the engine status upon completion of
initialization.
|
| ViewObject
Represents the base class implementation for all objects that are selectable from a view.
|
| ViewObject.Type
Represents values describing various types of selectable view objects.
|
| ViewRect
Represents a rectangle defined by the top-left corner's coordinate and the width and height of
the rectangle.
|
| Class and Description |
|---|
| GeoBoundingBox
Represents a rectangular area in a geographic coordinate system.
|
| GeoCoordinate
Represents a WGS84 coordinate with double precision.
|
| GeoPolyline
Interface representing a
GeoPolyline . |
| RoadElement |
| Class and Description |
|---|
| GeoBoundingBox
Represents a rectangular area in a geographic coordinate system.
|
| GeoCoordinate
Represents a WGS84 coordinate with double precision.
|


Helping our juniors to perfectly fit in their passion is exactly what we do here. We do two Career Counselling phases, for 10th students and for 12th students. On this day, the students will be given guidance about what their next step going to be, by the Joshians who are proficient in various fields. So the entire event will be full of career info, motivational talks and fun riddles. La’ Orientation Professionelle happens twice a year that is one for 10th students and another for 12th students. We encourage queries from the students after each session so that we get to know what they actually want to know. Information regarding competitive exams, course details, college details, board exam tips, entrance exam details will be provided to the students on this day. So thus this event takes our student’s perception of education to a complete different level.
JAMFEST embraces twenty five plus events, titled under different categories like arts, literary and cultural. Each and every event is designed for senior and junior category separately. Participants from distinctive schools, around 400 students compete to win the overall final trophy. A judge panel of one internal judge (Joshian who is skilled at that particular event), one external judge, and a staff member of James will be judging the entire event and the winners will be decided by the total points awarded by the judge panel. Food stalls, fun games and many other lively factors will be going on simultaneously. We shaped JAMFEST to create wings to young talents.
JOSH Talent League is a real treat for the students of St James. Students
from kinder garden to higher secondary, participates in JTL. JTL has twenty plus events
categorised as arts, literary and cultural. With the best set of contestants, audiences, judges
and staffs we take this event forward to create opportunity and space to showcase the
ability of Jameians and to award them for what they are really enthusiastic about.
JOSH-The Phoenix is an alumni crew with nearly 1300 members from various parts of the world. We take pleasure in organising events like Career Counselling, JTL , Jamfest. So to make this happen without any shades of flaws, to strengthen communication among all joshians, to enhance the bond between each of us, to give detailed description on what we are carrying on to each and every alumnus, we put ourselves together on a complacent day to sit and have casual discussions to take JOSH to the next level of improvement. We validate feedbacks after each event and try to put it in a right shape. It gives us satisfaction that we give back something worth and useful to the place which carved us so finely to be in the position we are right now. So we are planning out alumni get-together every year to strengthen JOSH.


I am a multi-skilled professional with strong focus on SaaS Product Development in startups. With strong technical background and experience in management and customer service, I'm able to identify problems and develop quality solutions while always focusing on the end-user.
Built a successful software services startup from scratch. Leveraging my technical knowledge to constantly raise the bar of quality across our software portfolio. Successfully providing services of software development to various national and international clients.
BE: Nodejs, Express, AWS, Serverless, RESTAPIs,
FE: ReactJs, Redux, ReactQuery, TypeScript, MUI, Flexbox,
DB: MySQL, MSSQL, MariaDB, Sequilize, MongoDB, Mongoose
Server: AWS, Azure, Lambda, Apachi
DevOps: AWS Continuous Deployment Pipeline, Docker, JIRA, Git
Successfully completed various projects for various national and international clients. Always striving to deliver more than promised.
Founded and developed successful tech blog with the peak traffic exceeding 100,000 UMV. Built using React, PHP, MYSQL. Monitized using various income streams, like Google Adsense, affiliate marketing, direct promotions, shout outs, social media marketing channels.
Successfully lead a team of developers on various projects. Achieved key performance indicators KPI to maximise output. Keeping an eye on the ball while performing a deep dive on the start-up mentality to derive convergence on cross-platform integration.
Design, build and maintain quality software applications.
Apart from being a IT Consultant and Full Stack Developer, I am an accomplished Orator, Community Servant and a family man.
I believe the first and most important change anyone can bring about is to change oneself. The one who cannot positively change himself can never change anything else except ruin it.


Everyone knows that the journey of becoming a software developer is challenging, but a rewarding one. On my journey, it was apparent to me that the need for clarity and assurance was the main focus when beginning. When people enter the world of programming, it is like traveling into outer space. The stars and planets are all the technologies and concepts that we have to learn and our space suit is the resources we can make use of.
Usually, people who go into programming even people who are in school do not have a mentor. I think that having a mentor that is in the field and is passionate about his/her craft is the single biggest advantage one can have when learning programming. After a lot of struggling one may be just starting to grasp their first programming language. After becoming somewhat proficient in that language they may just decide that they would need to learn a new language to move on with a project.
This is especially the case when a front end developer realizes he needs to learn a backend language like PHP, Python, Ruby, C#, or even Java. Some may say that it isn't necessary to get into a completely different language since javascript can be used in the back end now because of node.js, but I beg to differ.
This is where the title of this post really shines. I am a Computer Science sophomore and in my school and I was taught C++. I was well informed that C++ was a very relevant language when it came to memory optimization and speed, but I knew I needed to learn how to build things. My goal from the start was becoming a web developer; I learned HTML and CSS which gave me the ability to create static websites.
I was a little intimidated by the fact I had to learn javascript sooner or later. This was because in the past I had heard many people complain and say that javascript was hard and very weird to learn. The thing is when it comes to learning new things, my approach is very unorthodox. I always look for ways to optimize the learning process in whatever I do, so that I can carry over that process in different situations.
My crazy idea was that I should learn algorithms and data structures using javascript so that I could learn it. The idea behind this was that it would get me to really dig deep into the language and learn the real nitty and gritty things. The reason I thought this was possible is that each language has different nuances and cases and so by focusing on learning the different data structures and algorithms you have to dig deep to understand what you are doing. A perfect example of this is how built-in sort methods have different time complexities depending on what language they are used in. Specifically, in the case of javascript, the time complexity and algorithm used in its built-in sort method will change from browser to browser because different browsers use different sort methods.
The ability to contrast the differences in languages also gives you enough context to really learn the concept in another language. An example would be comparing a struct in C++ to an object in javascript or remembering the logic you used to create a linked list in C++ and converting into javascript by only taking into consideration the fact that javascript uses garbage collection to clear its memory and learning what the 'this.' the keyword means.
Ultimately learning algorithms and data structures while also doing programming questions will accelerate the process of learning the new language. The facts about javascript that I described above were all discovered while learning data structures and algorithms.
After learning data structures and algorithms, you could also try teaching them to your friends or people who are generally looking to learn them. I have been recently doing videos on solving programming problems on youtube using javascript. Explaining hard concepts to people reinforces your knowledge and challenges you to really understand the material.
Contact Me


Currently my long term career goal / reason for doing Dev Academy is because it’s my dream to build a career in which I’m continuously learning and working collaboratively on forward thinking, meaningful projects and I believe I can achieve these things (and more) with a career in web development. I’m also excited by the huge number of possibilities a career in dev can offer and as someone engaged in local DIY arts communities I’d love to be able to contribute dev skills within this area. I’m also excited by how I could apply dev skills and different ways of problem solving to my own creative projects.
I’d like to develop my self-motivation and discipline while at EDA and increase my self-belief that I’m able to approach any kind of problem with the right mindset and tools. In the past I’ve been guilty of shying away from projects or challenges that I think I “won’t be good at” but I’d like to challenge this kind of fixed mindset while at EDA and instead focus not on being ‘good’ or ‘bad’ but on process and building good habits rather than just relying on motivation to apply effort.
In terms of strengths I’d say I have strong communications skills, am good at adapting to different kinds of situations and I’m really perseverant. I also think I’m good at approaching problems creatively and not taking myself or life too seriously!
In terms of weaknesses I’d definitely say my perfectionism - which means I have a tendency to be a bit too thorough, detailed etc and can get a bit tunnel vision when working on a particular project / problem. Another weakness would be my tendency for self-doubt and to overthink things.
Based on what I’ve outlined above I’m committed to actively challenging my perfectionism and keeping the ‘big picture’ in mind when completing tasks and challenges to ensure I’m moving through the curriculum and covering topics in a sustainable amount of depth and length of time. I’m also therefore committed to doing my best to stick to the time box suggestions as a way of managing my time and am committed to working everyday on content. I’m also committed to staying open minded in my approach and listening and learning from my peers, facilitators and industry/community representative. I also acknowledge that it is my responsibility to manage my time and workload and ask for help if I need it in a timely way.
My expectation from the DEV facilitation team is that I’m able to check in regularly and receive feedback on my work to date. I’d also like to be provided with feedback on areas of improvement and areas I’m doing well in.


HSBC warned by British regulator over weak fraud and staff controls
HSBC has been told by the Bank of England to tighten up compliance controls for fraud, staff conduct and other non-financial risks, a source close to the bank said on Thursday.
LONDON: HSBC has been told by the Bank of England to tighten up compliance controls for fraud, staff conduct and other non-financial risks, a source close to the bank said on Thursday.
Prudential Regulation Authority regulators had highlighted the weaknesses and HSBC executives will discuss ways to address them at a forthcoming meeting, the source told Reuters, confirming an earlier report by Bloomberg.
Samir Assaf, HSBC's global banking and markets division head, told senior bankers on a conference call on Tuesday of the issue, said the source, adding the weaknesses had been identified during routine regulatory work.
HSBC has been dogged by compliance problems, with the most high profile scandal involving helping Mexican drug cartels launder money, leading to a US$1.9 billion U.S. settlement in 2012.
A Department of Justice deferred prosecution agreement ended five years later, after HSBC invested hundreds of millions of dollars in compliance measures.
The PRA compliance issue adds to HSBC interim chief executive Noel Quinn's workload as he begins a costly overhaul to address sluggish European and U.S. performances.
(Reporting by Iain Withers; Editing by Alexander Smith)


|
| def | colvec (args) |
| | Create a numpy array representing a column vector. More...
|
| |
| def | photometric_distortions (image, labels) |
| | Performs the photometric distortions defined by the train_transform_param instructions of the original Caffe implementation of SSD. More...
|
| |
| def | transform_aabb (transform, aabb) |
| | Apply a transformation to an axis aligned bounding box. More...
|
| |
| def | deformable_transform_aabb (shape, transform, aabb) |
| | Apply a deformable transformation to the bounding boxes. More...
|
| |
| def | deformable_transform_aabb_bkp (shape, transform, aabb) |
| | Apply a deformable transformation to the bounding boxes. More...
|
| |
| def | motion_distortion_aabb (shape, kernel, aabb) |
| | Adjust the bounding box points according to the blur applied. More...
|
| |
| def | rotation (angle) |
| | Construct a homogeneous 2D rotation matrix. More...
|
| |
| def | random_rotation (min, max, prng=DEFAULT_PRNG) |
| | Construct a random rotation between -max and max. More...
|
| |
| def | translation (translation) |
| | Construct a homogeneous 2D translation matrix. More...
|
| |
| def | random_translation (min, max, prng=DEFAULT_PRNG) |
| | Construct a random 2D translation between min and max. More...
|
| |
| def | shear (angle) |
| | Construct a homogeneous 2D shear matrix. More...
|
| |
| def | random_shear (min, max, prng=DEFAULT_PRNG) |
| | Construct a random 2D shear matrix with shear angle between -max and max. More...
|
| |
| def | scaling (factor) |
| |
| def | random_scaling (min, max, prng=DEFAULT_PRNG) |
| | Construct a random 2D scale matrix between -max and max. More...
|
| |
| def | random_flip (flip_x_chance, flip_y_chance, prng=DEFAULT_PRNG) |
| | Construct a transformation randomly containing X/Y flips (or not). More...
|
| |
| def | change_transform_origin (transform, center) |
| | Create a new transform representing the same transformation, only with the origin of the linear part changed. More...
|
| |
| def | random_transform (min_rotation=0, max_rotation=0, min_translation=(0, 0), max_translation=(0, 0), min_shear=0, max_shear=0, min_scaling=(1, 1), max_scaling=(1, 1), flip_x_chance=0, flip_y_chance=0, prng=DEFAULT_PRNG) |
| | Create a random transformation. More...
|
| |
| def | random_transform_generator (prng=None, kwargs) |
| | Create a random transform generator. More...
|
| |
Copyright 2017-2018 Fizyr (https://fizyr.com)
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
Modifications copyright (C) 2019 Bruno Gregorio - BIPG
https://brunoggregorio.github.io
https://www.bipgroup.dc.ufscar.br
| def mynet.utils.transform.random_transform |
( |
|
min_rotation = 0 , |
|
|
|
max_rotation = 0 , |
|
|
|
min_translation = (0, 0) , |
|
|
|
max_translation = (0, 0) , |
|
|
|
min_shear = 0 , |
|
|
|
max_shear = 0 , |
|
|
|
min_scaling = (1, 1) , |
|
|
|
max_scaling = (1, 1) , |
|
|
|
flip_x_chance = 0 , |
|
|
|
flip_y_chance = 0 , |
|
|
|
prng = DEFAULT_PRNG |
|
) |
| |
Create a random transformation.
The transformation consists of the following operations in this order (from left to right):
- rotation
- translation
- shear
- scaling
- flip x (if applied)
- flip y (if applied)
Note that by default, the data generators in keras_retinanet.preprocessing.generators
interpret the translation as factor of the image size. So an X translation of 0.1 would translate the image by 10% of it's width. Set relative_translation
to False
in the TransformParameters
of a data generator to have it interpret the translation directly as pixel distances instead.
- Parameters
-
| min_rotation | : The minimum rotation in radians for the transform as scalar. |
| max_rotation | : The maximum rotation in radians for the transform as scalar. |
| min_translation | : The minimum translation for the transform as 2D column vector. |
| max_translation | : The maximum translation for the transform as 2D column vector. |
| min_shear | : The minimum shear angle for the transform in radians. |
| max_shear | : The maximum shear angle for the transform in radians. |
| min_scaling | : The minimum scaling for the transform as 2D column vector. |
| max_scaling | : The maximum scaling for the transform as 2D column vector. |
| flip_x_chance | : The chance (0 to 1) that a transform will contain a flip along X direction. |
| flip_y_chance | : The chance (0 to 1) that a transform will contain a flip along Y direction. |
| prng | : The pseudo-random number generator to use. |
| def mynet.utils.transform.random_transform_generator |
( |
|
prng = None , |
|
|
|
kwargs |
|
) |
| |
Create a random transform generator.
Uses a dedicated, newly created, properly seeded PRNG by default instead of the global DEFAULT_PRNG.
The transformation consists of the following operations in this order (from left to right):
- rotation
- translation
- shear
- scaling
- flip x (if applied)
- flip y (if applied)
Note that by default, the data generators in keras_retinanet.preprocessing.generators
interpret the translation as factor of the image size. So an X translation of 0.1 would translate the image by 10% of it's width. Set relative_translation
to False
in the TransformParameters
of a data generator to have it interpret the translation directly as pixel distances instead.
- Parameters
-
| min_rotation | : The minimum rotation in radians for the transform as scalar. |
| max_rotation | : The maximum rotation in radians for the transform as scalar. |
| min_translation | : The minimum translation for the transform as 2D column vector. |
| max_translation | : The maximum translation for the transform as 2D column vector. |
| min_shear | : The minimum shear angle for the transform in radians. |
| max_shear | : The maximum shear angle for the transform in radians. |
| min_scaling | : The minimum scaling for the transform as 2D column vector. |
| max_scaling | : The maximum scaling for the transform as 2D column vector. |
| flip_x_chance | : The chance (0 to 1) that a transform will contain a flip along X direction. |
| flip_y_chance | : The chance (0 to 1) that a transform will contain a flip along Y direction. |
| prng | : The pseudo-random number generator to use. |


$37.9
12%
The GDP in EM and developing countries has been rising
However, EM represents only about
Trillion
of the global equity market capitalization
So, EM is
under-represented in investors' portfolios
$29.5
The've increased by more than
2026
1990
2020
$53.5
81% within 10 years
Open your eyes to a world of investment opportunity
EM Now
How much do you know?
The world’s three biggest Internet users:
313m
of the population in emerging markets are now connected to the internet
1st
China
60%
2nd
854m
India
3rd
US
Who’s most connected?
560m
$2.3trn
Who’s biggest in eCommerce, US or China?
More than 150m people are typically entering the middle class every year in EM, boosting consumption and growing a partly well-educated workforce
A growing middle class
$795m
EM as an economic force
6-7% p.a. or more
86%
2
of the world's population lives
in Emerging Markets
x
the growth rate of developed countries
More than
Many of the largest emerging countries are growing at an annual rate of about
4
EM countries were among the ten largest R&D spenders in 2018
1
8th
China
5th
9th
3
6th
Brazil
Korea
5
India
Russia
12
Number of analysts per company in the Dow Jones Industrial (US) or Stoxx 50 (EU)
This lower level of coverage provides skilled active stock pickers with the potential to add meaningful alpha
Compared to the average analysts cover for Chinese and Brazilian companies
30
EM equities are much less efficient compared to developed markets


Adaboost
Classifiers are chosen as decision tree stumps at random, so it's possible the desired result is unattainable
1D
2D - Plus sign
2D - Plus sign with axis aligned classifiers
2D - Random split
2D - Random split with axis aligned classifiers
2D - Circle
Iterations
Per iteration the following is listed: best classifier, current adaboost output, sample weights


Seattle
Monday - Saturday | 6AM - 8PM
12345 Sea St
Seattle, WA
555-460-8475
<EMAIL_ADDRESS>Tokyo
Monday - Saturday | 6AM - 8PM
12345 Whale St
Tokyo, Japan
555-460-8475
<EMAIL_ADDRESS>Dubai
Monday - Saturday | 6AM - 8PM
12345 Shark St
Dubai, United Arab Emirates
555-460-8475
<EMAIL_ADDRESS>Paris
Monday - Saturday | 6AM - 8PM
12345 Wave St
Paris, France
555-460-8475
<EMAIL_ADDRESS>Lima
Monday - Saturday | 6AM - 8PM
12345 Ocean St
Lima, Peru
555-460-8475
lima@salmon-cookies.com


WHO ARE WE?
Team Shakti is a group of budding young female minds who have joined together for the cause of bringing about a change in the field of cyber-security. Established as a Capture The Flag team, the team works tirelessly to spread knowledge and make a contribution to balance the prevalent gender gap in the field.
Team Shakti works on the principle of team peer mentoring where the senior members mentor the juniors. Members support and help each other ultimately making the entire team stronger.
Since its foundation in 2019 by Shri Vipin Pavithran, Team Shakti has been recognised to be the only CTF team in India which exclusively comprises female students.


This account hasn’t been verified yet, so it’s hidden to reduce spam. $if can_vouch: If you know its owner, please vouch for their non-spamminess!
$def with (request, targetid, target_username, can_vouch) $:{RENDER("common/stage_title.html", ["Unverified Account"])}
This account hasn’t been verified yet, so it’s hidden to reduce spam. $if can_vouch: If you know its owner, please vouch for their non-spamminess!


Certain icons make more sense to appear after the button's text label rather than before. This can be accomplished by putting the icon markup after the mdcButtonLabel element.
NOTE: The mdc-button-label element is required in order for the trailing icon to be styled appropriately.
Material Design spec advises that touch targets should be at least 48 x 48 px. To meet this requirement, add the `touch` property.
Note that the outer mdc-touch-target-wrapper element is only necessary if you want to avoid potentially overlapping touch targets on adjacent elements (due to collapsing margins).


Materials
Ranging from lecture notes, past questions and tutorial questions. Get all the materials you need here. Exclusive to members only
Any queries? Reach out to us!
Ranging from lecture notes, past questions and tutorial questions. Get all the materials you need here. Exclusive to members only
Any queries? Reach out to us!


Histories of Little Mix
- Formation and The X-Factor 2011-2012
- DNA and International Breakthough 2012-2013
- Salute and "WORD UP!" 2013-2014
- Get Weird 2015-2016
- Glory Days and LM5 2016-2019
- Confetti and other projects 2020
A Supporting Appearance
- The X Factor Live Tour (2012)
- Neon Lights Tour (2014)
- The Dangerous Woman Tour (2017)


Jeff Goldblum teases 'nice part' in Jurassic World 3 and we're too excited
Jeff Goldblum will reprise his iconic role of Dr Ian Malcolm from the Jurassic Park films in the newest franchise release, Jurassic World 3.
The 67-year-old said he has a ‘nice part’ in the upcoming film, which is due to be released in 2021.
Jeff revealed: ‘Yes, I have a nice part in it.’
The Thor actor then praised Jurassic World’s director, Colin Trevorrow as ‘so wonderful’.
‘He’s going to write in and direct it,’ he told Collider.
Advertisement Advertisement
Jeff then explained: ‘I’ve been reading it every day, working on it.
‘I am eager to do it and get reunited with Sam Neill, Laura Dern, Chris [Pratt] and Bryce [Dallas Howard] and I can’t wait.’
Jeff originally played the role of Dr Ian Malcolm in Jurassic Park (1993), then The Lost World: Jurassic Park (1997) and Jurassic World: Fallen Kingdom (2018).
This will make the fourth film he’s played the brainy Ian Malcolm, out of six films in the franchise.
It was revealed last year Jeff’s iconic Jurassic Park role almost never came about.
Jeff confessed that Steven revealed that his character and that of Sam Neill’s, Dr Alan Grant, were set to get merged into one during a cast roundtable.
‘When I first met Steven Spielberg at Amblin, he came in and said, “You know, there’s a movement afoot, a new rewrite is happening, and your character, Ian Malcolm, is being written out,’ he said.
‘We probably wanna give these funny lines and kinda incorporate your character into the Sam Neil character.”’
Thank god that didn’t happen.
Jurassic World 3 is set for release in 2021.
Got a showbiz story?
If you've got a celebrity story, video or pictures get in touch with the Metro.co.uk entertainment team by emailing us<EMAIL_ADDRESS>calling 020 3615 2145 or by visiting our Submit Stuff page - we'd love to hear from you.


GNOME-SESSION(1) GNOME-SESSION(1) NAME gnome-session - Start the GNOME desktop environment SYNOPSIS gnome-session [--autostart=DIR] [--session=SESSION] [--failsafe|-f] [--debug] DESCRIPTION The gnome-session program starts up the GNOME desktop environment. This command is typically executed by your login manager (either gdm, xdm, or from your X startup scripts). It will load either your saved session, or it will provide a default session for the user as defined by the system administrator (or the default GNOME installation on your system). The default session is defined in gnome.session, a .desktop-like file that is looked for in $XDG_CONFIG_HOME/gnome-session/sessions, $XDG_CON‐ FIG_DIRS/gnome-session/sessions and $XDG_DATA_DIRS/gnome-session/ses‐ sions. When saving a session, gnome-session saves the currently running applica‐ tions in the $XDG_CONFIG_HOME/gnome-session/saved-session directory. gnome-session is an X11R6 session manager. It can manage GNOME applica‐ tions as well as any X11R6 SM compliant application. OPTIONS The following options are supported: --autostart=DIR Start all applications defined in DIR, instead of starting the applications defined in gnome.session, or via the --session option. Multiple --autostart options can be passed. --session=SESSION Use the applications defined in SESSION.session. If not specified, gnome.session will be used. --failsafe Run in fail-safe mode. User-specified applications will not be started. --debug Enable debugging code. --whale Show the fail whale in a dialog for debugging it. SESSION DEFINITION Sessions are defined in .session files, that are using a .desktop-like format, with the following keys in the GNOME Session group: Name Name of the session. This can be localized. RequiredComponents List of component identifiers (desktop files) that are required by the session. The required components will always run in the ses‐ sion. RequiredProviders List of task providers that are required by the session. A default provider for each task has to be defined with a DefaultProvider- TASK key; the provider can be overridden by required components, the saved session or autostart applications. The task providers will always run in the session. DefaultProvider-TASK Identifier (desktop file) of the default provider for TASK. If no provider for TASK is found in the required components, the saved session and in the autostart applications, the default provider will be started. Here is an example of a session definition: [GNOME Session] Name=GNOME fallback RequiredComponents=gnome-panel;metacity;gnome-settings-daemon; RequiredProviders=notifications; DefaultProvider-notifications=notification-daemon The .session files are looked for in $XDG_CONFIG_HOME/gnome-session/ses‐ sions, $XDG_CONFIG_DIRS/gnome-session/sessions and $XDG_DATA_DIRS/gnome- session/sessions. ENVIRONMENT gnome-session sets several environment variables for the use of its child processes: SESSION_MANAGER This variable is used by session-manager aware clients to contact gnome-session. DISPLAY This variable is set to the X display being used by gnome-session. Note that if the --display option is used this might be different from the setting of the environment variable when gnome-session is invoked. FILES $XDG_CONFIG_HOME/config/autostart $XDG_CONFIG_DIRS/config/autostart /usr/share/gnome/autostart The applications defined in those directories will be started on login. gnome-session-properties(1) can be used to easily config‐ ure them. $XDG_CONFIG_HOME/gnome-session/sessions $XDG_CONFIG_DIRS/gnome-ses‐ sion/sessions $XDG_DATA_DIRS/gnome-session/sessions These directories contain the .session files that can be used with the --session option. $XDG_CONFIG_HOME/gnome-session/saved-session This directory contains the list of applications of the saved ses‐ sion. BUGS If you find bugs in the gnome-session program, please report these on https://bugzilla.gnome.org. SEE ALSO gnome-session-properties(1) gnome-session-save(1) GNOME GNOME-SESSION(1)


--- layout: post title: Lecture notes on Bayesian Data Assimilation in submission ---
My lecture notes on data assimilation methodology for the geosciences have been released in a condensed form in the ArXiv pre-print A Tutorial on Bayesian Data Assimilation. This tutorial provides a broad introduction to Bayesian data assimilation that will be useful to practitioners, in interpreting algorithms and results, and for theoretical studies developing novel schemes with an understanding the rich history of geophysical data assimilation and its current directions. This work is currently in submission to a Cambridge University Press collection on Applications of Data Assimilation and Inverse Problems in the Earth Sciences, to appear in 2022.


100
Charizard
86
100
Blastoise
86
What should Blastoise do?
Water Cannon
Water Pulse
Surf
Tackle
Continue


₹2.53-lakh cr loans disbursed by PSBs in October: Finance Ministry
by Our BureauAt the end of the second and last phase of the customer outreach initiative, which was announced by Finance Minister Nirmala Sitharaman in September, public sector banks (PSBs) had, in aggregate, disbursed loans worth ₹2.53-lakh crore, the Finance Ministry said on Thursday.
While the first phase (from October 1 to 9) saw loan disbursals of ₹81,695 crore, the second phase (from October 9 to October 31) saw disbursals of ₹1,70,893 crore. While 226 districts were covered under the first phase, as many as 148 districts were covered under the second phase.
Of the total disbursement of ₹2,52,589 crore (including camps and branches), ₹1,05,599 crore was disbursed towards new term loan and ₹46,800 crore towards new working capital loans, an official release said. Total credit of ₹19,627.26 crore was given by PSBs to NBFCs in October.
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Supported targets:
Note that supported targets are only those that have been tested and confirmed
working. It is quite possible that libco will work on more processors, compilers
and operating systems than those listed below.
libco.x86
Overhead: ~5x
Supported processor(s): 32-bit x86
Supported compiler(s): any
Supported operating system(s):
- Windows
- Mac OS X
- Linux
- BSD
libco.amd64
Overhead: ~10x (Windows), ~6x (all other platforms)
Supported processor(s): 64-bit amd64
Supported compiler(s): any
Supported operating system(s):
- Windows
- Mac OS X
- Linux
- BSD
libco.ppc
Overhead: ~20x
Supported processor(s): 32-bit PowerPC, 64-bit PowerPC
Supported compiler(s): GNU GCC
Supported operating system(s):
Mac OS X
Linux
BSD
Playstation 3
Note: this module contains compiler flags to enable/disable FPU and Altivec
support.
libco.fiber
Overhead: ~15x
Supported processor(s): Processor independent
Supported compiler(s): any
Supported operating system(s):
libco.sjlj
Overhead: ~30x
Supported processor(s): Processor independent
Supported compiler(s): any
Supported operating system(s):
- Mac OS X
- Linux
- BSD
- Solaris
libco.ucontext
Overhead: ~300x
Supported processor(s): Processor independent
Supported compiler(s): any
Supported operating system(s):


API Basejump: File MetaData Microservice
User stories:
I can submit a FormData object that includes a file upload.
When I submit something, I will receive the file size in bytes within the JSON response
Upload Your File
File Metadata:
Upload a file to see JSON response
{ filename: "<IP_ADDRESS> ", filesize(mb): "en-US ", filetype: "X11; Linux x86_64", url:"" }


Register
1 / 3
Hone your coding skills with us
2 / 3
Love coding? You're at the right spot.
3 / 3
Develop your skills, make yourself an offer companies can't turn down.


That's right, YOU! Verus is a free and open source project. We hope to foster a healthy community of contributors. Check out our GitHub and visit the Verus Discord channel to chat and find ways to get involved! We also have a community on QQ.
We are also specifically looking for independant developers working on their own PBaaS autochain.
You can also donate Verus to the project in VRSC or KMD at RVjvbZuqSGLGDm1B9BFkbHWySPKEx4tfjQ or with ETH at 0x06E2F78E650C88c6D89440E778004037FEAbefC5.
Former Vice President and Technical Fellow at Microsoft, recognized founder and architect of Microsoft's .Net platform, ex-Technical Fellow of Microsoft's advertising platform, ex-CTO, Parallels Corporation, experienced distributed computing and machine learning architect.
With a focus on design and GUI programming, Michael is responsible for the Verus Logo, significant white paper content, and mining and usability improvements in the Verus enhanced Agama. Michael is a University Student of CS with a passion for competitive swimming.
Alex's background is varied, including software development, system administration, embedded development, and technical editing. He became a cryptocurrency user in 2012 and has followed the technology since. He has grown to love shell scripts while managing Verus infrastructure.
Decades of experience delivering successful products including real time financial engines moving billions of dollars in international remittances. Dave taught Mike assembly language over 30 years ago and has ensured that Verus enhanced Agama can be used on all platforms.
Automation wizard extraordinaire, Asher keeps the Verus builds and backend test systems on track - Windows, Mac, Linux, and Android soon - Asher works tirelessly to automate builds and testing using github, gitlab, TravisCI, scripting and more as needed.
jl777 is the lead developer of Komodo, Supernet, Marketmaker behind Barterdex, and a lot more. He's one of, if not the most productive devs in crypto. He's also one of our trusted advisers, and has added an invaluable technical and crypto-veteran perspective to our decision making.
Oliver Westbrook, Ben O'Hanlon, 0x03, DeckerSu, Mammothine, Crupti, Paia, SadykovT, ok88, nmnm, Chris - Loud Mining, Godballz, Meyes, aelder, Hellcatz, Blackjok3r, SHossain, Oink, zpajk, LOUD Mining, Thoskk, Draeth, Fishyguts, Stretcher83, Wattpool


Three lexicons for sentiment analysis are combined here in a tidy data frame. The lexicons are the NRC Emotion Lexicon from Saif Mohammad and Peter Turney, the sentiment lexicon from Bing Liu and collaborators, of Finn Arup Nielsen, and of Tim Loughran and Bill Loughran. Words with non-ASCII characters were removed from the lexicons.
sentiments
A data frame with 27,314 rows and 4 variables:
An English word
A sentiment whose possible values depend on the lexicon. The "afinn" lexicon has no sentiment category (all are NA), and each of the others can be "positive" or "negative". The NRC lexicon can also be "anger", "anticipation", "disgust", "fear", "joy", "sadness", "surprise", or "trust", and the Loughran lexicon can also be "litigious", "uncertainty", "constraining", and "superfluous".
The source of the sentiment for the word. One of either "nrc", "bing", or "AFINN".
A numerical score for the sentiment. This value is NA
for the Bing and NRC lexicons, and runs between -5 and 5 for the AFINN
lexicon.
Note that the loughran lexicon is best suited for financial text, (e.g. where words like "share" is not necessarily positive, and "liability" not necessarily negative).


|
| | __init__ () |
| |
| | __init__ (const FilterProperties) |
| |
| | addChorus (float drymix, float wet1, float wet2, float wet3, float delay, float rate, float depth) |
| | Add a chorus filter to the end of the DSP chain. More...
|
| |
| | addCompress (float threshold, float attack, float release, float gainmakeup) |
| | Add a compress filter to the end of the DSP chain. More...
|
| |
| | addDistort (float level) |
| | Add a distort filter to the end of the DSP chain. More...
|
| |
| | addEcho (float drymix, float wetmix, float delay, float decayratio) |
| | Add a echo filter to the end of the DSP chain. More...
|
| |
| | addFlange (float drymix, float wetmix, float depth, float rate) |
| | Add a flange filter to the end of the DSP chain. More...
|
| |
| | addHighpass (float cutoff_freq, float resonance_q) |
| | Add a highpass filter to the end of the DSP chain. More...
|
| |
| | addLowpass (float cutoff_freq, float resonance_q) |
| | Add a lowpass filter to the end of the DSP chain. More...
|
| |
| | addNormalize (float fadetime, float threshold, float maxamp) |
| | Add a normalize filter to the end of the DSP chain. More...
|
| |
| | addParameq (float center_freq, float bandwidth, float gain) |
| | Add a parameq filter to the end of the DSP chain. More...
|
| |
| | addPitchshift (float pitch, float fftsize, float overlap) |
| | Add a pitchshift filter to the end of the DSP chain. More...
|
| |
| | addSfxreverb (float drylevel, float room, float roomhf, float decaytime, float decayhfratio, float reflectionslevel, float reflectionsdelay, float reverblevel, float reverbdelay, float diffusion, float density, float hfreference, float roomlf, float lfreference) |
| | Add a reverb filter to the end of the DSP chain. More...
|
| |
| | clear () |
| | Removes all DSP postprocessing. More...
|
| |
| Public Member Functions inherited from TypedObject |
| TypeHandle | getType () |
| |
| int | getTypeIndex () |
| | Returns the internal index number associated with this object's TypeHandle, a unique number for each different type. More...
|
| |
| bool | isExactType (TypeHandle handle) |
| | Returns true if the current object is the indicated type exactly. More...
|
| |
| bool | isOfType (TypeHandle handle) |
| | Returns true if the current object is or derives from the indicated type. More...
|
| |
| Public Member Functions inherited from ReferenceCount |
| int | getRefCount () |
| | Returns the current reference count. More...
|
| |
| | ref () |
| | Explicitly increments the reference count. More...
|
| |
| bool | testRefCountIntegrity () |
| | Does some easy checks to make sure that the reference count isn't completely bogus. More...
|
| |
| bool | testRefCountNonzero () |
| | Does some easy checks to make sure that the reference count isn't zero, or completely bogus. More...
|
| |
| bool | unref () |
| | Explicitly decrements the reference count. More...
|
| |


Guards who were with Juice Wrld when he died arrested on gun charges
They are both due in court later this month.
Two security guards who were with US rapper Juice Wrld when he died after suffering a medical emergency at Chicago’s Midway International Airport have been arrested on gun charges.
According to the Chicago Tribune, Harry Dean, 27, of Chicago, and Christopher Long, 36, who is from California, were charged with misdemeanour gun counts after police found three guns, a high-capacity magazine and metal-piercing bullets.
They are both due in court later this month.
The rapper, whose legal name is Jarad A Higgins, was with a group of about a dozen people on Sunday when he was transported from Midway to an area hospital after suffering what Chicago Fire Department spokesman Larry Langford said was cardiac arrest. He was pronounced dead a short time later.
Police said there were no signs of foul play in the death of the 21-year-old rapper and a post-mortem examination was scheduled for Monday at the Cook County Medical Examiner’s office.
The rapper, who was named top new artist at the 2019 Billboard Music Awards in May, lived in the Chicago suburb of Homewood.


Use this form to send bulk voice messages.
The messages will be sent using your Twilio account.
You will also need a SimpleWorker account so that the messages can be sent in a background job.
The QuickBase Application must have these application variables:
The QuickBase Table must have a 'Pending Voice Messages' report. The report must contain these fields:
Except for 'QuickBase Realm' and 'QuickBase Application Token', the fields below are all required.


Work Smarter
Will you not like to go home early
to watch that one extra GOT episode ?
to spent time with your family ?
Where do we spend most of our time ?
Key Areas
-
Hours spent on noisy internet for solutions
-
Browsing code
-
Retrieving lost code
-
Dealing with syntactic dragons
-
Formatting code
Skilling Up
-
Git - Github - Gist
-
Jekyll - Markdown - Documentation
-
Node / NPM
-
Modular Code Design
- Template
- Snippet
- Component
- Module
-
Component Release Process
Community Building
-
Identify Leaders / Project owners
-
Frequent Releases
-
Blog / Tweet
-
Stickers / Contributor Thank You Cards
-
Participate In Existing Open Source Projects
- Social Networks
- Issues
- Events
Need Analysis
-
Components frequently required by the community
-
Frequently searched key words
-
If no search results, ability to request for a component
-
Feedback form
Sustained Participation
-
Weekly Challenge
-
Post Training Issues Challenge
-
Hiring Issues Challenge
-
Bench project assignment
Metrics
-
Components Released Per Week
-
Downloads Per Week
-
Issues Fixed / Pull Request Per Week
-
Dashboard
Metrics
Action Items
-
Upgrade plugits portal to support tags and categories
-
Daily Release
-
Weekly Issue Challenge
-
Metrics : Install OSSTracker Dashboard
-
Metrics : Plugit Portal Google Analytics
-
POC: VSCode Plugits Plugin


win-back
win-star
win-semanticzoom-button
win-pivot-navbutton-prev
win-pivot-navbutton-next
win-navbar-ellipsis
win-toggleicon
win-flyouticon-left
win-flyouticon-right
win-commandingsurface-ellipsis
win-searchbox-button
win-splitviewpanetoggle


You've found the Underwater Hockey Tourist, the largest list of underwater hockey clubs around
the world. Pick a country below, browse the map or load
everything in one page. Please let us know if you notice stale or
missing information.
{% for country in world.child_places|sort(attribute='name') %}
{{country.name}} navigate_next
{% endfor %}
{% if world.recently_updated %}