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Meet Aditi, 23-Yr-Old With Down Syndrome...
Meet Aditi, 23-Yr-Old With Down Syndrome Who Runs Her Own Café| Detcare
Aditi is the owner of Aditi's corner, a cafe she runs in Bhoomi Mall, Belapur, Mumbai. The cafe serves light snacks, homemade meals.
Aditi has Down syndrome, a rare genetic disorder which affects one in every 800-1,000 live births.
Down syndrome is caused because of a Chromosomal defect since birth. It is typically associated with physical growth delays, characteristic facial features and mild to moderate intellectual disability.
There is no cure for Down syndrome. Education and proper care have been shown to improve quality of life. Most important is the constant support and motivation from the family and parents and their equal acceptance by the society.
And she is really doing well with her determination. She takes orders, wipes the table, manages accounts, handle phone calls and if the place is running short on inventory, she will make a note.
"I used to get bored at home," says a proud Aditi when asked about why she enjoys coming here. "Here I can do whatever I want."
The cafe was gifted by her parents who wanted to keep her busy and happy. They wanted to ensure that she becomes self-reliant. The cafe is now in good shape and achieved its break even within the first three months.
"I love working in the cafe and always wanted one of my own. With my parents' support, I have learned to manage the work myself," said Aditi
"Accept your child for who they are," said Aditi's father, Amit Verma. "Kids who suffer from Down's syndrome are lovely children and I feel blessed to have Aditi. The key is to give them space. They are thorough with their work and are dedicated individuals. Once you teach them something, they will retain it for life. There is no need to overprotect them. The children need to live their lives on their terms," he added.
The Detcare community of Doctors feels motivated to see her doing so well and gives us an example to tell parents, and everyone who is born with such a challenge that if given proper opportunities, they have enough strength to do well in their life.
How to bring down Assaults ? - Suggest


I had a question regarding the guest wireless capabilities with Ruckus. Do I have the ability to "turn off" the wireless password requirement for guest wireless for certain times and have it require a password again after that time window, following a schedule?
I didn't find any configuration option that allows for something like that. It might be easier to have two different SSID's on mutually exclusive schedules, such that the no-password one appears during certain hours, and during the other hours the password-based one appears.
The only troublesome part is you have to teach your users two SSIDs, but once their devices learn them, they should automatically join the right one.
Without a ZoneDirector, there's no formal notion of a guest network or scheduling. Of course, if you use something behind the Ruckus (e.g. some sort of firewall / UTM / gateway) to provide the captive portal functionality, it could also potentially have this feature.
This feature is available in Ruckus Cloud Wi-Fi under Advanced Network Settings -> User Connection settings.
You have the option to set the total duration of connection and a grace period after disconnection, so that user is not required to login again during that period.


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Q: Logistic regression with multi-class features in R I'm working with a data set like the following:
X =
c1 c2 c3 c4 c5 y
a  c  f  h  j  0
a  d  f  i  k  0
a  c  g  h  j  1
a  c  f  h  k  0
b  d  g  h  k  0
b  e  f  h  j  0

I'm trying to create a logistic regression model that is able to predict y (0 or 1) based on the features of X.
Info on X:
The values of c1–c5 are all factors.
The features have a varying number of levels (e.g. c1: 2 levels, c2: 4 levels, c3: 3 levels, etc.)
Approx 10% of y is 1.
I've tried using SVM and GLM without any good result.
model <- svm(y ~ ., data = X)
pred <- predict(model, X)
table(pred,X$y)

        y
pred    FALSE TRUE
FALSE   1332   113
TRUE       0     0

and
model <- glm(y ~ ., family=binomial("logit"), data=X)
pred <- predict(model, X, type="response")
table(pred,X$y)

pred                   FALSE TRUE
4.2260288377431e-08        2    0
4.24333100181876e-08       1    0
...
0.706714407238236          1    1
0.736650629322038          0    1

I'm used to working with features with continuous values when creating a predictive model, but I don't really know how to tackle a problem with factors.
What would you guys recommend for this type of problem? Changing from logistic regression to something else or using other functions besides GLM & SVM?

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