Enabling/Disabling Entry of Markup Code Scripts
How to enable filtering of data that contains markup code or scripts that is entered into a form or list on the Forms and Lists module. Note: Filtering is always enabled for Anonymous users.
-
- Select the Form and List Settings tab.
- At Filter entry for markup code or script input. Note: filtering is always enabled for Anonymous users., to enable filtering - OR - to remove filtering. This field is unchecked by default.
-
Click the Update button.
Enabling data filtering for lists and forms


Economy is the method by which we prepare today to afford improvements of tomorrow.
The relationship between GDP per capita and life expectancy for different countries is shown. Click on Play Button to Start Animation.
The working age population is defined as those aged 15 to 64.
Merchandise imports and exports from year 1961 to 2014.


I like apples and oranges.
I also like bananas, mangoes, cherries, apricots, plums, peaches and grapes.
You can see other fruits I like here.
Warning: Eating too many oranges can give you heart burn.
My favorite kind of orange is the mandarin, properly known
as citrus reticulata.
Oranges at my local store cost $1 each $2 for 3.
The FDOC regulates the Florida
citrus industry.
I still remember the best apple I ever tasted.
I bought it at
on .


| 284 | (A) | thare were flewande in the flete Fercostes fułł many |
| 279 | (C) | Ther were floygenes on flote . & farstes manye |
| 280 | (D) | þer were shippes on flote and farecostis many |
| 281 | (E) | ¶ There were schippes aflote . & farecostys manye . |
| (Ex) | ---- no text ---- | |
| 285 | (L) | þer were floynes a-flot farcostes many |
| 277 | (P) | þar was floynes in þe flode farcostes many |
| 276 | (U) | ¶ There were floignes on fote / and farecostes many |
| (V) | ---- no text ---- |


Binary gcd (Greatest common divisor) algorithm
Binary gcd algorithm makes use of computations like testing parity of binary integer, subtraction and halving instead of calculating remainders
a. If a and b are even numbers, then :
Consider a, b both as even numbers. Then the common divisor property can be written as:
Now using property (if and this implies , the equation given above can also be written as:
Now, taking divisor 2 as common from R.H.S. and take it to L.H.S., the modified equation can be written as:
… … (1)
Now take,
Again using property (if and this implies, the equation given above can also be written as:
As per equation (1), it is clear that:
Thus, from both the equations, there comes a conclusion that
Therefore
When both a and b are even numbers
b. If a is odd and b is even number, then:
Consider a as odd and b as even number. Then the common divisor property can be written as:
Now using property (if and this implies, the equation given above can also be written as:
// as we can always choose an even y
// where z= y/2
Now take,
Again using property (if and this implies, the equation given above can also be written as:
It is described above that
So
This conclude that
When a is an odd number and b is even number
c. If a and b is odd numbers, then:
Consider a, b both are odd numbers. The common divisor property can be written as:
Now using property (if and this implies , the equation given above can also be written as:
Thus we can rewrite the equation as:
// where w = x/2 and z= y–x/2
Now take,
Then,
Again using property (if and this implies, the equation given above can also be written as:
This conclude that
When both a and b are odd numbers
d. Algorithm:
Input: two positive integers say a and b
Output: gcd(a,b)
//if condition to check whether first number is zero
if (a==0)
// greatest common divisor gcd(0, b)=b
return b ;
else
//if condition to check whether second number is zero
if (b==0)
// greatest common divisor gcd (a, 0)=a
return a;
else
//if condition to check whether both numbers are even
if (when both a and b are even)
return gcd (a/2, b/2)
else
//if condition to check whether first number is odd and second number is even
if (when a is odd and b is even )
return gcd (a, b/2)
else
//if condition to check whether first number is even and second number is odd
if (when a is even and b is odd)
return gcd( a/2, b)
//This will be executed when both numbers are odd
else
return gcd ( |a–b|/2, b)
This algorithm uses a complexity of. In above algorithm a and b are two inputs and in which a is greater than b. It is clear from the algorithm given above that the maximum capability of extension is a, which is greater than b. So, the complexity can be measured by.
Bit operations in Euclidean Algorithm:
Paper and pencil algorithm:
• Paper and pencil division algorithm is used to perform the division operation using decimal notations.
• At each stage, there is the shifting of dividend and subtraction of largest divisor from left to right.
• To perform a simple long division operation and to calculate the total bit operations performed, consider divisor as b and the dividend as a.
• Here, a is divided by b as a result of which quotient q and the remainder r are obtained.
There are mainly three operations that are performed in the paper and pencil algorithm. They are as follows:
1. Division operation
2. Calculating quotient operation
3. Calculating remainder operation
Order of operations:
The first operation is division operation where the dividend (a) is divided by the divisor (b).
The total number of bit operations required for each division operation is.
The number of bit operations required to calculate the quotient is equal to .
The number of bit operations required to calculate the remainder is equal to .
Hence, the total number of bit operations required to perform long division operations using “paper and pencil” algorithm is equal to .
The greatest common divisor of any two integer a and b is such that the divisor divides both the integers without leaving any remainder.
The name itself describes that the number should be the greatest and there should be no other greater number which divides both integers without leaving a remainder.
For example:
The gcd of 20 and 130 is 10. The factors of 20 are: (1, 20), (2, 10) and (4, 5). Similarly, the factors for 130 are: (1, 130), (2, 65), (5, 26) and (10, 13). Among both the sets of factors, the common factor is 10. Thus, the gcf of 20 and 130 is 10.
The greatest common divisor is denoted by gcd (a, b) for the two integers a and b.
Here, the Euclidean algorithm is used to calculate the gcd of (a, b), that is, the larger of the two numbers is divided by the smaller one.
In each step, the long division and sliding is followed. The term sliding means that the remainder and divisor move to the left so that they become the divisor and dividend respectively. This process is continued till the remainder becomes 0.
Define the following equation:
In the equation given above, integers a and b are the inputs and and are their running times respectively.
Reduce equation (3) by equation (2). In the reduction process, the basic long divisions and the sliding operation as discussed above are performed.
The running time can be calculated as follows:
Add and subtract 1 in the second parentheses.
Equation (1) can be written as follows:
To calculate the total number of bit-operations, a constant should be multiplied with the equation given above. Suppose that the constant is c, the equation after multiplications is given below:
Hence the number of bit operations to be performed will be for the value of c greater than 0 which is sufficiently large.
Euclid operation with inputs:
Consider r and q as the remainder and the quotient in the long division performed in part a.
The Euclidean algorithm where the division is of the form where the value of i is from and the value of has been set and the value of.
Calculate the total r time as follows:
Apply Backward approach to the Euclidean algorithm, then .
Substitute the above value in equation (4).
From part (b) of the question, .
Using the above equation and the Euclidean expression, the number of bit operations required by is equal to.
From second part of the question, the input for theexpression is twobits size numbers.
Hence, the total time taken to calculate the expression is equal to,
(up to time).
Therefore, the total time is equal to for the input size of bits.
Three algorithms for Fibonacci numbers are as follows:
• Fibonacci numbers represent a sequence of numbers in which each subsequent number is the sum of previous two numbers.
• The value of number at nth position will be the sum of numbers at n–1 and n–2 positions respectively.
• In Fibonacci numbers, the value of numbers at first and second position is fixed. First number is always 0 and the second number is always 1.
• Fibonacci series: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34… and so on.
a.
Straightforward recursive method for computing Fibonacci numbers:
The straightforward recursive method is used to compute the value of number at a certain position in the Fibonacci series.
The values at positions 1 and 2 are fixed and represented by F0 and F1. The values can be calculated by the equation given below:
This is called recurrence equation because the function F calls itself to calculate the value at a position.
// defining Fibonacci number as long
1. long int f (int n)
2. {
// to check if n is zero
3. if
4. return 0;
//to check if n is 1
5. else if
6. return 1;
7. else
// return the sum the two previous numbers
8. return;
9. }
It is clear from the algorithm given above that the condition for the values at first and second positions are checked, because the values at both positions are fixed.
The sum of two previous numbers is returned. This has been calculated by using recursion (called as recursive method).
In FIB-procedure, a tree for f(n) has been maintained in such a manner that its left child always shows f(n–2) and right child shows value of f(n–1).
This procedure has been followed until the left child becomes f(1) and right child becomes f(0). It is because the values of both of them are fixed. A tree representation of f(4) is given below:
Assume that calls were made to calculate .
, each term is in form .
Recursion:
In the equation given above, 2 is added because the node also calls to left child and right child.
This takes up time and it is seen that the time complexity is polynomial. Thus, the running time has the value of n in the exponential form.
b.
Memoization for Fibonacci numbers:
Memoization is an efficient implementation of hash tables.
The values calculated earlier are stored in the table and used later. Memoization is an effective technique to create algorithms.
Let fib memoized = n
Let memo: int option array=Array. Create (n+1) Node in
Let recursive f _memoized n = match memo (n) with
Some
Let result= if then 1
else f memoized +f memoized in
Memo (n) some result;
Result
In f_ memoized n
The term f_memoized describes the original recursive algorithm. It also checks whether the result has been already calculated and stored in the table.
The total time taken in a particular call of f_memoized is.
There is a method to bind the recursive calls by observing the ways of the work that has already been done.
The best method to measure progress is counting the number of nonempty entries in the table for each case of memoization.
Every time the f_memoization is called for the two recursive calls, it succeeds and the number of nonempty entries increase by one.
As the table above has only entries, only calls are required for f _memoization, and the total running time is .
c.
Computing Fibonacci value at a certain position:
The Fibonacci value at a certain position can be calculated by considering a matrix and its power. This approach is given below:
If , then , n1
Here,is the nth Fibonacci number anddefined to be 0.
F n representation can be given as,
, when n is even
, when n is odd
This dynamic algorithm in form of a mathematical expression is given below:
Let two variables be x and y.
Using matrix multiplication,
It is clear from the above math expression that the right hand side expression is a sub-part to find an nth Fibonacci number. Using the above concept, the expression below gives the exact expression of nth Fibonacci number.
Right hand side expression is expression for a Fibonacci sequence.
This dynamic approach is better than the earlier one because in computing nth Fibonacci number, this algorithm takes only integer arithmetic expression.
Therefore, computing n th power of any value requires only multiplication and te remaining multiplication and addition takes constant time.
d.
Running time of methods:
Assume that the time taken in addition of two -bit numbers takes time and multiplication of two -bit numbers takes time.
The running time of all the above methods can be calculated as shown below:
For straight forward recursive method:
Let calls are made to calculate .
, each term is in the form .
As it is assumed that adding two numbers take time, hence, the running time of this method will be a polynomial term,.
For memoization:
In case of memoization, the data that has been obtained is used for further calculations. Here, the total time will be the sum of time taken to calculate operations and. This is given below:
For matrix multiplication: The running time for this method would be as it involves matrix multiplication.
Quadratic Residues
It is a concept related to a number theory. An integer r is called as quadratic residue modulo n if congruent relationship exists for a perfect modulo n. For any integer y there exists a relation given as:
Otherwise r will be termed as a quadratic non-residue modulo n. It has a wide range of application as-engineering related to acoustics, factoring of a large numbers.
According to the question there is variable p which is an odd prime (that is the prime number except 2). It is because prime numbers are the numbers that are divisible by them and by 1. Examples of prime numbers include 2, 3, 17, 31 etc.
A number is termed as a quadratic residue if the equation:
Has a solution for the unknown variable x. This means that a number will be called as the quadratic residue only when the condition given above will be satisfied.a.
As a number to be a quadratic modulo, it should satisfy the condition of. Now, considering the values of x as 1 to prime number p, the quadratic residues are the non-zero numbers which are squares modulo p, so the numbers are as:
After moving further along the residue, the square of the remaining number will start repeating in the reverse order as:
So, there is only requirement to move along the half of the squares. So to show that there is only quadratic residue. For showing all the numbers are different modulo p. Consider two number and which lies between 1 and. Now, suppose that and we have to show that.b.
In the given question p and a is a prime and quadratic residue modulo. Defined Legendre symbol as function of a and p which is defined as,
It is clear from the equation given above that if the value of is obtained to be equal to 1, then the a is quadratic residue modulo p. Also, (mod p). If the value of is obtained to be equal to -1, then it is quadratic non-residue modulo of prime p. If the value of is obtained to be equal to 0, then . The definition of the Legendre’s symbol as:
Also consider that the value of can have value 0, 1 or -1. It is shown below:
Consider integer a as quadratic residue for modulo p. If its square is non-zero, it means variable x will be there such that. Otherwise it is said to be non-residue. This is characterised with the Euler’s algorithm. It is very efficient in determining the quadratic residue.
c.
To compute the square root modulo of the prime of the form. Consider that be a quadratic residue of modulo p. Also it belongs from the value of integers. It can be given as.Now considers the following equation:
Which is the square root of: Such that
d.
When we perform the repeated squaring we have the condition that mod p. Now, let us assume that A=a and b=1 then at each step we have and at the end we have A=1.
So, a is the square root a mod p. At each step the power of 2 is decreasing by dividing the order of A. so to initiate we have:
if we have
If it is not so then. So power of 2 dividing the order of a is exactly which is same as the power of 2 dividing .So, consider set, and we found that:
So, power of 2 which divides the order has decreased by 1. So in the next step, we have:
,
If yes do nothing.
Claim that is a square root of A mod p.
So the algorithm just returns:
as.
So, a random number is a quadratic non-residue having probability so if k trial is run then probability of not getting a quadratic non-residue is which is equal to log p. So, this randomized algorithm is the most efficient, having the number of operation less than.


LOAD ALL STUDENTS
ID Number
First Name
Last Name
Faculty Number
Grade
Create
Close
ID
First Name
Last Name
Faculty Number
Grade
Create Student


{% extends "_base.html" %} {% block head %} {% endblock%} {% block body %}
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| dep_auto {knitr} | R Documentation |
When the chunk option autodep = TRUE
, all names of objects created in
a chunk will be saved in a file named ‘__objects’ and all global objects
used in a chunk will be saved to ‘__globals’. This function can analyze
object names in these files to automatically build cache dependencies, which
is similar to the effect of the dependson
option. It is supposed to be
used in the first chunk of a document and this chunk must not be cached.
dep_auto(path = opts_chunk$get("cache.path"))
path |
Path to the dependency file. |
NULL
. The dependencies are built as a side effect.
Be cautious about path
: because this function is used in a
chunk, the working directory when the chunk is evaluated is the directory
of the input document in knit
, and if that directory differs
from the working directory before calling knit()
, you need to adjust
the path
argument here to make sure this function can find the cache
files ‘__objects’ and ‘__globals’.
https://yihui.org/knitr/demo/cache/


{% extends "base.html" %} {% load i18n %} {% block head_title %}{% trans "tlsscout" %}{% endblock head_title %} {% block content %}
With tlsscout you can configure automatic periodic checks of your websites using the API of the excellent SSL Labs scanner, with notifications when something changes.
All use of the SSL Labs API is subject to the terms and conditions listed on their website.
{% if ENABLE_SIGNUP %} {% else %}Signups are currently disabled. Log In
{% endif %}


{% load static %}
Futiweb helps you being up to date with the latest football standings via the football-data.org API in the league of your desire.
Just pick your country
made by yabbes using the Football-Data.org API, Django and Bootstrap


- x 1 Rolex Classic Watch $1230
- x 1 Rolex Classic Watch $1230
- x 1 Rolex Classic Watch $1230
- x 1 Rolex Classic Watch $1230
- x 1 Rolex Classic Watch $1230
- x 1 Rolex Classic Watch $1230
- x 1 Rolex Classic Watch $1230
- x 1 Rolex Classic Watch $1230
Buttons
Buttons
Default Bootstrap Buttons(Customized to Match Theme Style)
Metronic Style Buttons
Button Sizes
Button Tags
LinkBlock Buttons
LinkIcon Buttons
Font Awesome Styled Buttons
Users
2
Products
4
Reports
Categories
Calendar
4
Inbox
12
Notification
3
Locations
Finance
Projects
21
Feedback
2
Servers
2
Regions
Popularity
221
Social Icons
Social Icons (Colored)
Button Groups
Basic Example
Button Toolbar
Button Group Sizing
Vertical variation
Button Dropdowns
Default Bootstrap Style
Metronic Style
Sizing
Dropup
Hoveralbe Dropdowns
NOTE:
By adding
hold-on-click
class you can avoid closing the dropdown on click


ALTER TABLE APPEND
Appends rows to a target table by moving data from an existing source table. Data in the source table is moved to matching columns in the target table. Column order doesn't matter. After data is successfully appended to the target table, the source table is empty. ALTER TABLE APPEND is usually much faster than a similar CREATE TABLE AS or INSERT INTO operation because data is moved, not duplicated.
Note
ALTER TABLE APPEND moves data blocks between the source table and the target table. To improve performance, ALTER TABLE APPEND doesn't compact storage as part of the append operation. As a result, storage usage increases temporarily. To reclaim the space, run a VACUUM operation.
Columns with the same names must also have identical column attributes. If either the source table or the target table contains columns that don't exist in the other table, use the IGNOREEXTRA or FILLTARGET parameters to specify how extra columns should be managed.
You can't append an identity column. If both tables include an identity column, the command fails. If only one table has an identity column, include the FILLTARGET or IGNOREEXTRA parameter. For more information, see ALTER TABLE APPEND Usage Notes.
Both the source table and the target table must be permanent tables. Both tables must use the same distribution style and distribution key, if one was defined. If the tables are sorted, both tables must use the same sort style and define the same columns as sort keys.
An ALTER TABLE APPEND command automatically commits immediately upon completion of the operation. It can't be rolled back. You can't run ALTER TABLE APPEND within a transaction block (BEGIN ... END).
Syntax
ALTER TABLE target_table_name APPEND FROM source_table_name [ IGNOREEXTRA | FILLTARGET ]
Parameters
- target_table_name
-
The name of the table to which rows are appended. Either specify just the name of the table or use the format schema_name.table_name to use a specific schema. The target table must be an existing permanent table.
- FROM source_table_name
-
The name of the table that provides the rows to be appended. Either specify just the name of the table or use the format schema_name.table_name to use a specific schema. The source table must be an existing permanent table.
- IGNOREEXTRA
-
A keyword that specifies that if the source table includes columns that are not present in the target table, data in the extra columns should be discarded. You can't use IGNOREEXTRA with FILLTARGET.
- FILLTARGET
-
A keyword that specifies that if the target table includes columns that are not present in the source table, the columns should be filled with the DEFAULT column value, if one was defined, or NULL. You can't use IGNOREEXTRA with FILLTARGET.
ALTER TABLE APPEND Usage Notes
ALTER TABLE APPEND moves only identical columns from the source table to the target table. Column order doesn't matter.
If either the source table or the target tables contains extra columns, use either FILLTARGET or IGNOREEXTRA according to the following rules:
-
If the source table contains columns that don't exist in the target table, include IGNOREEXTRA. The command ignores the extra columns in the source table.
-
If the target table contains columns that don't exist in the source table, include FILLTARGET. The command fills the extra columns in the target table with either the default column value or IDENTITY value, if one was defined, or NULL.
-
If both the source table and the target table contain extra columns, the command fails. You can't use both FILLTARGET and IGNOREEXTRA.
If a column with the same name but different attributes exists in both tables, the command fails. Like-named columns must have the following attributes in common:
-
Data type
-
Column size
-
Compression encoding
-
Not null
-
Sort style
-
Sort key columns
-
Distribution style
-
Distribution key columns
You can't append an identity column. If both the source table and the target table have identity columns, the command fails. If only the source table has an identity column, include the IGNOREEXTRA parameter so that the identity column is ignored. If only the target table has an identity column, include the FILLTARGET parameter so that the identity column is populated according to the IDENTITY clause defined for the table. For more information, see DEFAULT.
ALTER TABLE APPEND Examples
Suppose your organization maintains a table, SALES_MONTHLY, to capture current sales transactions. You want to move data from the transaction table to the SALES table, every month.
You can use the following INSERT INTO and TRUNCATE commands to accomplish the task.
insert into sales (select * from sales_monthly); truncate sales_monthly;
However, you can perform the same operation much more efficiently by using an ALTER TABLE APPEND command.
First, query the PG_TABLE_DEF system catalog table to verify that both tables have the same columns with identical column attributes.
select trim(tablename) as table, "column", trim(type) as type, encoding, distkey, sortkey, "notnull" from pg_table_def where tablename like 'sales%'; table | column | type | encoding | distkey | sortkey | notnull -----------+------------+-----------------------------+----------+---------+---------+-------- sales | salesid | integer | lzo | false | 0 | true sales | listid | integer | none | true | 1 | true sales | sellerid | integer | none | false | 2 | true sales | buyerid | integer | lzo | false | 0 | true sales | eventid | integer | mostly16 | false | 0 | true sales | dateid | smallint | lzo | false | 0 | true sales | qtysold | smallint | mostly8 | false | 0 | true sales | pricepaid | numeric(8,2) | delta32k | false | 0 | false sales | commission | numeric(8,2) | delta32k | false | 0 | false sales | saletime | timestamp without time zone | lzo | false | 0 | false salesmonth | salesid | integer | lzo | false | 0 | true salesmonth | listid | integer | none | true | 1 | true salesmonth | sellerid | integer | none | false | 2 | true salesmonth | buyerid | integer | lzo | false | 0 | true salesmonth | eventid | integer | mostly16 | false | 0 | true salesmonth | dateid | smallint | lzo | false | 0 | true salesmonth | qtysold | smallint | mostly8 | false | 0 | true salesmonth | pricepaid | numeric(8,2) | delta32k | false | 0 | false salesmonth | commission | numeric(8,2) | delta32k | false | 0 | false salesmonth | saletime | timestamp without time zone | lzo | false | 0 | false
Next, look at the size of each table.
select count(*) from sales_monthly; count ------- 2000 (1 row) select count(*) from sales; count ------- 412,214 (1 row)
Now execute the following ALTER TABLE APPEND command.
alter table sales append from sales_monthly;
Look at the size of each table again. The SALES_MONTHLY table now has 0 rows, and the SALES table has grown by 2000 rows.
select count(*) from sales_monthly; count ------- 0 (1 row) select count(*) from sales; count ------- 414214 (1 row)
If the source table has more columns than the target table, specify the IGNOREEXTRA parameter. The following example uses the IGNOREEXTRA parameter to ignore extra columns in the SALES_LISTING table when appending to the SALES table.
alter table sales append from sales_listing ignoreextra;
If the target table has more columns than the source table, specify the FILLTARGET parameter. The following example uses the FILLTARGET parameter to populate columns in the SALES_REPORT table that don't exist in the SALES_MONTH table.
alter table sales_report append from sales_month filltarget;


public class Attribute
extends java.lang.Object
| Modifier and Type | Field and Description |
|---|---|
(package private) Attribute |
next
The next attribute in this attribute list.
|
java.lang.String |
type
The type of this attribute.
|
(package private) byte[] |
value
The raw value of this attribute, used only for unknown attributes.
|
| Modifier | Constructor and Description |
|---|---|
protected |
Attribute(java.lang.String type)
Constructs a new empty attribute.
|
| Modifier and Type | Method and Description |
|---|---|
(package private) int |
getCount()
Returns the length of the attribute list that begins with this attribute.
|
protected Label[] |
getLabels()
Returns the labels corresponding to this attribute.
|
(package private) int |
getSize(ClassWriter cw,
byte[] code,
int len,
int maxStack,
int maxLocals)
Returns the size of all the attributes in this attribute list.
|
boolean |
isCodeAttribute()
Returns true if this type of attribute is a code attribute.
|
boolean |
isUnknown()
Returns true if this type of attribute is unknown.
|
(package private) void |
put(ClassWriter cw,
byte[] code,
int len,
int maxStack,
int maxLocals,
ByteVector out)
Writes all the attributes of this attribute list in the given byte
vector.
|
protected Attribute |
read(ClassReader cr,
int off,
int len,
char[] buf,
int codeOff,
Label[] labels)
Reads a
type attribute. |
protected ByteVector |
write(ClassWriter cw,
byte[] code,
int len,
int maxStack,
int maxLocals)
Returns the byte array form of this attribute.
|
public final java.lang.String type
byte[] value
Attribute next
protected Attribute(java.lang.String type)
type
- the type of the attribute.public boolean isUnknown()
public boolean isCodeAttribute()
protected Label[] getLabels()
protected Attribute read(ClassReader cr, int off, int len, char[] buf, int codeOff, Label[] labels)
type
attribute. This method must return a
new Attribute
object, of type type
,
corresponding to the len bytes starting at the given offset, in
the given class reader.cr
- the class that contains the attribute to be read.off
- index of the first byte of the attribute's content in
cr.b
. The 6 attribute header bytes,
containing the type and the length of the attribute, are not
taken into account here.len
- the length of the attribute's content.buf
- buffer to be used to call readUTF8
, readClass
or readConst
.codeOff
- index of the first byte of code's attribute content in
cr.b
, or -1 if the attribute to be read
is not a code attribute. The 6 attribute header bytes,
containing the type and the length of the attribute, are not
taken into account here.labels
- the labels of the method's code, or null if the
attribute to be read is not a code attribute.Attribute
object corresponding to the given
bytes.protected ByteVector write(ClassWriter cw, byte[] code, int len, int maxStack, int maxLocals)
cw
- the class to which this attribute must be added. This
parameter can be used to add to the constant pool of this
class the items that corresponds to this attribute.code
- the bytecode of the method corresponding to this code
attribute, or null if this attribute is not a code
attributes.len
- the length of the bytecode of the method corresponding to this
code attribute, or null if this attribute is not a
code attribute.maxStack
- the maximum stack size of the method corresponding to this
code attribute, or -1 if this attribute is not a code
attribute.maxLocals
- the maximum number of local variables of the method
corresponding to this code attribute, or -1 if this attribute
is not a code attribute.final int getCount()
final int getSize(ClassWriter cw, byte[] code, int len, int maxStack, int maxLocals)
cw
- the class writer to be used to convert the attributes into
byte arrays, with the write
method.code
- the bytecode of the method corresponding to these code
attributes, or null if these attributes are not code
attributes.len
- the length of the bytecode of the method corresponding to
these code attributes, or null if these attributes
are not code attributes.maxStack
- the maximum stack size of the method corresponding to these
code attributes, or -1 if these attributes are not code
attributes.maxLocals
- the maximum number of local variables of the method
corresponding to these code attributes, or -1 if these
attributes are not code attributes.final void put(ClassWriter cw, byte[] code, int len, int maxStack, int maxLocals, ByteVector out)
cw
- the class writer to be used to convert the attributes into
byte arrays, with the write
method.code
- the bytecode of the method corresponding to these code
attributes, or null if these attributes are not code
attributes.len
- the length of the bytecode of the method corresponding to
these code attributes, or null if these attributes
are not code attributes.maxStack
- the maximum stack size of the method corresponding to these
code attributes, or -1 if these attributes are not code
attributes.maxLocals
- the maximum number of local variables of the method
corresponding to these code attributes, or -1 if these
attributes are not code attributes.out
- where the attributes must be written.


Contains the character codes for the available control characters on the keyboard, such as space and return.
This object contains the keyboard layouts that are available for the keyboard widget. Each keyboard layout is a list with one entry for each keyboard row. Each row is a string that contains the characters available on that row.
Parses a custom template layout that was specified by the user. Rows are separated by commas, keys on a row may be separated by dashes.
A custom layout template specified by the user.
The parsed keyboard layout template. Contains one item for each row, each item contains the characters on that keyboard row.
Finds and returns the keycode for the given control character. You can use this keycode in a custom keyboard layout.
string Name of the control keycode to get.
The keycode with the given name, if it exists.
Finds and returns a built-in layout with the given name. Currently available layout are qwerty
, qwertyBasic
,
and alphabetic
.
Name of a layout to get.
The layout with the given name, if it exists.
Checks whether a built-in control with the given name exists. If it does, you can retrieve it via
getPresetControl
.
string Name of the control keycode to check.
true
if a control for the given key is defined, false
otherwise.
Generated using TypeDoc
Contains a few utilities for parsing and working with different keyboard layout. Used by the Keyboard widget.


MCMC¶
This page gives the details about the code in biasd.mcmc.
Markov chain Monte Carlo¶
To sample the posterior probability distribution in BIASD, we’ll use an affine invariant Markov chain Monte Carlo (MCMC) sampler. The implementation here uses emcee, which allow very efficient MCMC sampling. It is described in
| Title: | emcee: The MCMC Hammer |
|---|---|
| Authors: | Daniel Foreman-Mackey, David W. Hogg, Dustin Lang, and Jonathan Goodman |
| arXiv: | http://arxiv.org/abs/1202.3665 |
| DOI: | 10.1086/670067 |
Which extends upon the paper
| Title: | Ensemble samplers with affine invariance |
|---|---|
| Authors: | Jonathan Goodman, and Jonathan Weare |
| Citation: | Comm. Appl. Math. Comp. Sci. 2010, 5(1), 65-80. |
| DOI: | 10.2140/camcos.2010.5.65> |
Setup and Run MCMC¶
-
mcmc.
setup
(data, priors, tau, nwalkers, initialize='rvs', threads=1)¶ Prepare the MCMC sampler
- Input:
data is a np.ndarray of the time series
priors is a biasd.distributions.parameter_collection of the priors
tau is the measurement period each data point
nwalkers is the number of walkers in the MCMC ensemble. The more the better
- initialze =
- ‘rvs’ will initialize the walkers at a random spot chosen from the priors
- ‘mean’ will initialize the walkers tightly clustered around the mean of the priors.
- an (nwalkers,5) np.ndarray of whatever spots you want to initialize the walkers at.
threads is the number of threads to use for evaluating the log-posterior of the walkers. Be careful when using the CUDA log-likelihood function, because you’ll probably be bottle-necked there.
- Results:
- An emcee sampler object. Please see the emcee documentation for more information.
-
mcmc.
burn_in
(sampler, positions, nsteps=100, timer=True)¶ Burn-in will run some MCMC, getting new positions, and then reset the sampler so that nothing has been sampled.
- Input:
- sampler is an emcee sampler
- positions is the starting walker positions (maybe provided by biasd.mcmc.setup?)
- nsteps is the integer number of MCMC steps to take
- timer is a boolean for displaying the timing statistics
- Results:
- sampler is now a cleared emcee sampler where no steps have been made
- positions is an array of the final walkers positions for use when starting a more randomized sampling
-
mcmc.
run
(sampler, positions, nsteps, timer=True)¶ Acquire some MCMC samples, and keep them in the sampler
- Input:
- sampler is an emcee sampler
- positions is the starting walker positions (maybe provided by biasd.mcmc.setup?)
- nsteps is the integer number of MCMC steps to take
- timer is a boolean for displaying the timing statistics
- Results:
- sampler is the updated emcee sampler
-
mcmc.
continue_run
(sampler, nsteps, timer=True)¶ Similar to biasd.mcmc.run, but you do not need to specify the initial positions, because they will be the last sampled positions in sampler
Example use:
import biasd as b
# Load data
data = b.smd.load('data.smd')
tau = 0.1
# Get a molecule and priors
d = data.data[0].values.FRET
priors = b.distributions.guess_priors(d,tau)
# Setup the sampler for this molecule
# Use 100 walkers, and 4 CPUs
sampler, initial_positions = b.mcmc.setup(dy, priors, tau, 100, initialize='rvs', threads=4)
# Burn-in 100 steps and then remove them, but keep the final positions
sampler,burned_positions = b.mcmc.burn_in(sampler,initial_positions,nsteps=100)
# Run 100 steps starting at the burned-in positions.
sampler = b.mcmc.run(sampler,burned_positions,nsteps=100)
# Continue on from step 100 for another 900 steps. Don't display timing
sampler = b.mcmc.continue_run(sampler,900,timer=False)
# Save the sampler data
result = b.mcmc.mcmc_result(sampler)
data = b.smd.add.mcmc(result)
b.smd.save('data.smd',data)
Analyze MCMC samples¶
-
mcmc.
chain_statistics
(sampler, verbose=True)¶ Calculate the acceptance fraction and autocorrelation times of the samples in sampler
-
mcmc.
get_samples
(sampler, uncorrelated=True, culled=False)¶ Get the samples from sampler
- Input:
- sampler is an emcee sampler with samples in it
- uncorrelated is a boolean for whether to provide all the samples, or every n’th sample, where n is the larges autocorrelation time of the dimensions.
- culled is a boolean, where any sample with a log-probability less than 0 is removed. This is necessary because sometimes a few chains get very stuck, and their samples (not being representative of the posterior) mess up subsequent plots.
- Returns:
- An (N,5) np.ndarray of samples from the sampler
-
mcmc.
plot_corner
(samples)¶ Use the python package called corner <https://github.com/dfm/corner.py> to make some very nice corner plots (joints and marginalized) of posterior in the 5-dimensions used by the two-state BIASD posterior.
- Input:
- samples is a (N,5) np.ndarray
- Returns:
- fig which is the handle to the figure containing the corner plot
-
mcmc.
create_posterior_collection
(samples, priors)¶ Take the MCMC samples, marginalize them, and then calculate the first and second moments. Use these to moment-match to the types of distributions specified for each dimension in the priors. For instance, if the prior for \(\epsilon_1\) was beta distributed, this will moment-match the posterior to as a beta distribution.
- Input:
- samples is a (N,5) np.ndarray
- priors is a biasd.distributions.parameter_collection that provides the distribution-forms to moment-match to
- Returns:
- A biasd.distributions.parameter_collection containing the marginalized, moment-matched posteriors
Note, for the corner plot, you must have corner. Anyway, continuing on from the previous example...
Example:
# ...
# Calculate auto-correlation times for each variable
largest_autocorrelation_time = b.mcmc.chain_statistics(sampler)
# Collect uncorrelated samples from the sampler
samples = b.mcmc.get_samples(sampler)
# Plot the joint and marginalized distributions from the samples using corner, and then save the figure
f = b.mcmc.plot_corner(samples)
plt.savefig('mcmc_test.pdf')
# Create a collection of the marginalized posterior distributions
posterior = b.mcmc.create_posterior_collection(samples,priors)
# View that collection
b.distributions.viewer(posterior)


ICRA
Monitoring
Identity
Include Path
Connection
Broker Address
Broker Port
Use SSL
Username
Password
Save and Connect
Disconnect


How to watch tonight’s 2020 Democratic debate
The fifth and certainly not the final debate
by Makena KellyThere is yet another 2020 Democratic presidential debate tonight, and the pool of candidates that will be onstage has shrunk down to just 10 participants. This fifth debate will be hosted by MSNBC and The Washington Post at Tyler Perry Studios in Atlanta, Georgia.
How do I watch?
There are a number of ways you’ll be able to watch the debate tonight.
You’ll be able to stream it for free on MSNBC.com and WashingtonPost.com; it will be featured on both homepages. You’ll also be able to find it on the NBC News and Washington Post apps. It will air exclusively on MSNBC, too, if you’re hoping to watch it on cable.
When does it start?
The debate will take place on November 20th starting at 9 p.m. ET and last for two hours.
The candidates
Only 10 candidates qualified for tonight’s event, which is two fewer than October’s debate in Ohio at Otterbein University:
- Former Vice President Joe Biden
- Sen. Bernie Sanders
- Sen. Elizabeth Warren
- Mayor Pete Buttigieg
- Sen. Cory Booker
- Sen. Kamala Harris
- Tom Steyer
- Sen. Amy Klobuchar
- Rep. Tulsi Gabbard
- Andrew Yang
The moderators
- MSNBC anchor Rachel Maddow
- MSNBC anchor Andrea Mitchell
- NBC News White House correspondent Kristen Welker
- Washington Post White House reporter Ashley Parker
The next debate will take place at UCLA on December 19th, and so far, only six candidates have qualified: Biden, Sanders, Warren, Buttigieg, Harris, and Klobuchar.


Citing
If you use Adifa in a scientific publication, we would appreciate citations to the following Zenodo reference.
Dave Horsfall, Jim McGrath, Issac Goh. (2022). Adifa software for Single Cell Insights. Zenodo. https://doi.org/10.5281/zenodo.5824896
The importance of citing software
Motivation.
Citing a specific version
If you would like to cite a specific version of the software for reasons of reproducibility, please search for correct version on Zenodo and use the version specific DOI.
Bibtex
@software{dave_horsfall_2022_5824896,
author = {Dave Horsfall and Jim McGrath},
title = {Adifa software for Single Cell Insights},
year = 2022,
publisher = {Zenodo},
version = {v0.1.0},
doi = {10.5281/zenodo.5824896},
url = {https://doi.org/10.5281/zenodo.5824896}
}


A MySQL-Driver for Go’s database/sql package
sql.RawBytes
support.LONG DATA
handling in prepared statementsLOAD DATA LOCAL INFILE
support with file Whitelisting and io.Reader
supporttime.Time
parsingSimple install the package to your $GOPATH with the go tool from shell:
$ go get github.com/go-sql-driver/mysql
Make sure Git is installed on your machine and in your system’s PATH
.
Go MySQL Driver is an implementation of Go’s database/sql/driver
interface. You only need to import the driver and can use the full database/sql
API then.
Use mysql
as driverName
and a valid DSN as dataSourceName
:
import "database/sql"
import _ "github.com/go-sql-driver/mysql"
db, err := sql.Open("mysql", "user:password@/dbname")
Examples are available in our Wiki.
MPL 2.0 Copyright Julien Schmidt et al


Class used to compute the gradient for a loss function, given a single data point.
Class used to solve an optimization problem using Gradient Descent.
Compute gradient and loss for a Hinge loss function.
Updater that adjusts learning rate and performs L1 regularization.
Compute gradient and loss for a logistic loss function.
A simple updater that adaptively adjusts the learning rate the square root of the number of iterations.
Compute gradient and loss for a Least-squared loss function.
Updater that adjusts the learning rate and performs L2 regularization
Class used to update weights used in Gradient Descent.


I want to preface this post by giving some background to my university situation. As of the post date, I'm a first year software engineering student at the University of Waterloo. When school began on September 7th 2020, I wasn't sure what to expect. With the brand new online learning system being implemented, my first year was looking to be filled with surprises and anomalies. And boy were there surprises and anomalies. Since I'm in the engineering faculty, I take a 6 course workload, unlike most other programs which would take 5 courses. The 6 courses in my first term are ECE 105 (physics), Math 117 (calculus), Math 115 (linear algebra), Math 135 (discrete math), CS 137 (Intro to Programming) and SE 101 (a program specific design course). Overall, the courseload has been pretty heavy. While most courses are relatively fair in workload, ECE 105 specifically has taken a big toll on me. The course has been significantly harder compared to the other courses. The material for the course has been comprehensible but the assesments have been extremely difficult and buggy. The website that holds the assesments (mobius) constantly has errors, and the questions on the assesments have been much harder than those I practice on. Students in the program have notified the professors about the issues that pop up, so I will have to see how the course changes as time goes on. There have been signs of improvement so I am still hopeful. As of now, ECE 105 is by far my lowest mark but that doesn't mean my other courses have been easy or that I've been slacking on physics more than other courses. Math 135 has quickly been ramping up in difficulty since highschool does not teach you how to prove statements mathematically or the mathematical language in doing so. Math 115 has also been difficult since linear algebra is another portion of math not taught in secondary education. However unlike phyiscs, when I put time and effort into these courses I see it pay off. Math 117 and CS 137 have been relatively easy compared to the rest of the courses since programming and calculus were both focal points in my highschool education. SE 101 has mainly been a course to meet others, and not so much as an academic priority. I've been creating a budget braille printer as part of the design project in the course alongside an amazing team and so far everything has been smooth sailing. As of now, I have a 90+ average in my courses not including ECE 105, although I have 2 midterms next week so things may change.
Because of my school workload, I haven't been able to pursue many hobbies. However there are a few that I have been able to practice and enjoy. One of which has been picking up the electric guitar and playing with my friends on a weekly/bi-weekly basis. As you can see in the first picture of the post, my friends and I have been practicing and playing together in my friend Jordan's (hairy guy looking at the camera) newly rennovated room, which also happens to have studio like qualities (which is pretty amazing). Hanging out with my friends and playing in our own band setting has been a huge stress reliever for me, and has quickly risen to become one of my favourite past times. Over the reading week, I have frequently visited some of my favourite people to talk, take a break from school and play guitar and it's been inspiring every time.
Other than playing guitar, I have still kept up with some of my old hobbies. Before university started I hit diamond 4 in league of legends, but since then I have not been able to muster enough time and reasoning to play league other than for a few small games with my friends. I have been watching worlds 2020, and once again I am disappointed to see North America take a group stage exit. I'm pretty sure Damwon Gaming is going to take an easy championship but I've been wrong before. As an avid anime watcher, I have been keeping up with the current anime season and I have not been let down. Haikyuu to the Top season 2 has been great so far, I'm really vibing with Hinata's growth as a character and volleyball player. Irregular at Magic High has been very good as well, the plot keeps expanding on a world that has realistic modern day problems for a society engrained in the use of magical technology. Danmachi has been my guilty pleasure this season, if you watch it then you know what I mean. It's a bummer that Toronto has gone back to stage 2 because of the rising covid cases. I was planning on going to the gym at least 3-4 times a week but now that they've closed all I can rely on is doing some pushups, jogging/walking and using the free weights I have at home. But I can tell that my motivation is waning with every single week.
Outside of my entertainment hobbies, I was able to finish up the groundwork of my website during reading week. At the moment I'm planning on keeping it simple and leaving it as a blog website. As time goes by, I will start linking projects that I have completed to the website, along with better contacts and about me pages when I get better pictures of myself! I currently do not have many ideas as to what I will do for programming projects but I have a few interests. Other than the braille printer I'm currently working on for SE 101, my friend Lukas has gotten me interested in making a discord bot. I also wanted to make some sort of webscraper but I haven't decided what web application to scrape after learning that amazon removed their web scraping potential. Hopefully I will muster enough intiative to participate in a hackathon before first term ends.
All in all, university hasn't been too bad. I have a few goals to keep in mind, such as not failing physics, but otherwise online learning has actually been pretty comfortable. I haven't been lonely since I talk to my friends every day, although I have lost the opportunity to meet my program peers in person. Being at home means I get to spend every day with my family, which by itself relieves tons of stress. So far my approach to university has been working well, as long as I continue to work hard in school and have fun with my hobbies/friends the future is looking great.


Module: ActionText::SystemTestHelper
| Relationships & Source Files | |
| Defined in: | actiontext/lib/action_text/system_test_helper.rb |
Instance Method Summary
-
#fill_in_rich_text_area(locator = nil, with:)
Locates a Trix editor and fills it in with the given HTML.
Instance Method Details
#fill_in_rich_text_area(locator = nil, with:)
Locates a Trix editor and fills it in with the given HTML.
The editor can be found by:
-
its
id
-
its
placeholder
-
the text from its
label
element -
its
aria-label
-
the
name
of its input
Examples:
# <trix-editor id="message_content" ...></trix-editor>
fill_in_rich_text_area "message_content", with: "Hello world!"
# <trix-editor placeholder="Your message here" ...></trix-editor>
fill_in_rich_text_area "Your message here", with: "Hello world!"
# Message content
# <trix-editor id="message_content" ...></trix-editor>
fill_in_rich_text_area "Message content", with: "Hello world!"
# <trix-editor aria-label="Message content" ...></trix-editor>
fill_in_rich_text_area "Message content", with: "Hello world!"
# <input id="trix_input_1" name="message[content]" type="hidden">
# <trix-editor input="trix_input_1"></trix-editor>
fill_in_rich_text_area "message[content]", with: "Hello world!"
# File 'actiontext/lib/action_text/system_test_helper.rb', line 32
def fill_in_rich_text_area(locator = nil, with:) find(:rich_text_area, locator).execute_script("this.editor.loadHTML(arguments[0])", with.to_s) end


Hello {{username}}, this message is to inform you that your password has been changed as requested.
Best Regards,EbookMarket


(You can
search any file or page on this web site by following the steps found by
clicking on Search.)
OSCAR FRANK FAMILY BACKGROUND
The Frank Family
has used several variants on the spelling of Frank. These include Frank, Franks,
Franke, Franch, Franche, Franck, and probably more.
The relationship
between Louisa Young (December 22, 1863 - June
17, 1913) and August Herman Frank (September 3, 1854 - October 7, 1916)
introduced the Frank family into the Young family tree. At the time of this
writing, however, I have been unsuccessful in tracing the Frank family to
Europe. For the moment, therefore, the story of the Frank family begins with
the immigrant ancestor, Oscar Frank (September 27, 1825 - June 4, 1890)
Oscar Frank
(September 27, 1825 - June 4, 1890) immigrated to America in the 1840s. He
first appears in the Federal Census data in 1850 where he is listed as a single
22 year old laborer from Saxony, Germany. He was living with a German family,
Michael and Elizabeth Bertram who were 48 and 45 years old, respectively.
[Michael Bertram was a farmer from Rumbach, Germany. He and his wife,
Elisabetha Feldner immigrated to America, landing June 1832. They had one child
named Heinrich Jacob Bertram born in Rumbach, Germany and also landed June
1832.] At that time and at the time of the 1870 Census, Oscar spelled his name,
Oskar. Oscar Frank married Carolina Brubach (May 4, 1830 - February 27, 1912)
and the couple had 9 children, one of whom was August Herman Frank (September
3, 1854 - October 7, 1916), the author's great grandfather.
According to the
German Church
Records translated by Dr. Shirley Harmon, Oscar Franke was a witness at the
May 11, 1851 baptism of Johannes Schenk, the second son of David Schenk and
Margaretha Freitag Schenk. David Schenk was born in Rumbach, RB on Dec 30, 1822
and landed in America in 1840.
The following is
the "Last will and testament of Oscar Frank of Wayne Township in the
county of Monroe, Ohio:
The last will
and testament of Oscar Frank of Wayne Township in the County of Monroe
"and state of Ohio," In the name of the Benevolent father of
all,"
I the said Oscar
Frank being of sound and disposing mind and memory, "Considering the uncertainty
of Continuance in life," and desiring to make such disposition of my
Worldly Estate as I deem best, "do make publish and declare," This to
be my last will and testament." hereby revoking and annulling any and all
former will or wills. Whatsoever by me made,"
ITEM 1st I desire all my just debts and funeral
expenses to be paid as soon as possible after my deceased
ITEM 2nd I give and bequeath to my beloved wife
Caroline Frank, all my real and personal property of every description that I
may own at my decease, which she is to take possession of at my decease without
inventory or appraisement hereby given her power to sell any and all of said
property, and apply the proceeds as follows,
ITEM 3rd Pay to Henry Frank (Deceased) his heirs, one
hundred dollars each," to be paid in two years after, the sale of the
above real estate and personal property and without intrest.
ITEM 4th I have this day executed a quit claim deed to
Matilda A. Frank wife of August Frank, in full of his share of said estate.
ITEM 5th Pay to my son Oscar J. Frank One thousand
dollars, said amt to be paid in two years after the sale of the above real
estate and personal property of said estate without interest.
ITEM 6th Pay to my Daughters Flora Frank wife of John
Pohlmann Two Hundred Dollars," Mollie Frank, wife of Michael Young, Two
Hundred Dollars, Caroline Frank wife of George Feiock Jr. Two Hundred Dollars,
Rosa Ann, Frank wife of Elmer Cronin Two Hundred Dollars, Hattie Frank two
Hundred Dollars, the above amounts to be paid in two years after the sale of
the real estate and personal property of said estate, and without interest.
In testimony
whereof I, Oscar Frank Testator aforesaid, have hereunto set my hand and seal
at his residence in Wayne Township, Monroe County Ohio, this 28th day of May
A.D. 1890
Appears to have
been signed with a mark and his name spelled Oscar Franke signed for him.
Signed, sealed
and acknowledged as his last will and testament in our presence "and we
have, at his request signed the same, as witnesses in his presence, and in the
presence of each other,"
The death record
of Oscar Frank lists his date of death as Jan. 4, 1890. His age on this date
was 64 years, 4 months and 6 days. His date of birth that appears on his tomb
stone does not agree with these data. If his date of death and age at the time
of death are taken as correct, he should have been born August 29, 1825.
In the
application of Probate of Will executed 30 June, 1890 is the following:
"Your
petitioner respectfully represents that Oscar Franke late a resident of the
Township of Wayne in said County, died on or about the 4 day of June A.D. 1890,
leaving an instrument in writing, hereto attached, purporting to be his last
will and Testament: That the Said Oscar Franke died leaving Caroline Franke,
his widow and the following name persons his only next of kin resident of the
State of Ohio:
|
August H.
Franke |
son |
Lewisville,
Ohio |
|
Charles F.
Franke |
son |
Griffith, OH |
|
Flora Pohlman |
daughter |
Woodsfield, OH |
|
Mollie Young |
daughter |
Lewisville, OH |
|
Hattie Franke |
daughter |
Lewisville, OH |
|
Caroline
Feiock |
daughter |
Lewisville, OH |
|
Rosa Cronin |
daughter |
Edwina, OH |
|
Oscar J. Frank |
son |
Lewisville, OH |
|
Oscar Franke |
grandson |
Harrietsville,
OH |
|
Katie Franke |
granddaughter |
Harrietsville,
OH |
|
Henry Franke |
grandson |
Harrietsville,
Oh |
|
Jacob Franke |
grandson |
Harrietsville,
OH |
|
Christ Franke |
grandson |
Harrietsville,
OH |
|
Clara Franke |
granddaughter |
Harrietsville,
OH |
Click here for the Short-Cut Table of Contents


TRCTR-PLLR
{% include 'head.html' %}
I needed a way to randomly sample location data that mirrored population distribution in the United States. My particular need was to study visual changes in my maps as they collected 100, 1,000, 10,000, or 100,000 points and to alter their style accordingly. The underlying idea could also be used in factories for unit tests, or for creating simulation models based on United States locations.
Is it necessary to point out that this is a simple visual design tool? Census tracts are chosen randomly based on population data, points are generated simply with the requirement that they fit within the boundaries of the tract. TRCTR-PLLR has no awareness of cultural or physical features within a tract that would determine or explain where people genuinely live.
This hosted instance may disappear in the not-too-distant future so once instructions are available, you should set up your own copy. The source code is available at the project's GitHub repository and there's a blog post in the works that explains the motivation and setting up your own instance. And the name.
I hope you find it useful in the work you do.


{% extends "layout.html" %} {% block title %} Login {% endblock %} {% block body %}
Hey,
you're here!
New around here?
Note, the charicter on the this page is from Icons8's vector creator


About
The Beginning
A single action can impact lives across centuries. One decision can change the course of history. In the same way, one design can influence change in unexpected ways, causing a ripple affect of inspiration. Our name, Cloud Atlas, is derived from an influential stumbling upon of the 2012 movie, which was adapted from the 2004 David Mitchell novel, which in turn was inspired by the musical composition of the same name by the Japanese composer Toshi Ichiyanagi. Though sources of inspiration vary, the reception and acceptance of design relies solely on others. The human need for connection is one of many inherent behaviors we all possess, and without it, revolution wouldn’t be possible.
What We Do
You work hard to create your product. We work hard to make sure others know about it. Our aim is to spread your message through a creative outlet specific to you and your customers.
Our services include:
- Business Cards
- Logos
- Newsletters
- Invitations
- Thank You Cards
- Web Design
- Book Covers
- Amatuer Videography
*No request is off the table. Contact us about specific needs.


Schedule Overview
→ Google Calendar | Full Schedule | Talk Abstracts ←
SUN 4/28
Workshops
Bossanova Ballroom
Doors @ 9:00am
9:30am-11:30am
Workshop: TensorFlow Docs Sprint
9:30am-11:30am
Workshop: How to Have Curious Conversations
12:30pm-4:30pm
Workshop: Getting Started w/ Keras/OpenCV
Bike Ride
2:00pm @ Bossanova Ballroom
Join your fellow attendees for a leisurely ride around Portland.
 Open bar, special guest speakers, live entertainment, and more!
MON 4/29
Conf Day 1
Bossanova Ballroom
Doors @ 8:00am
Talks from 9:00am-5:00pm
Model Building: Refreshing Yoga Session @ 10:15am
Lunch @ Noon
Lightning Talks @ 1:00pm
Hiring Speed Networking @ 3:00pm
Family Photo @ 5:00pm
Official Party
7:00pm-11:00pm @ Pips & Bounce
NOTE: Minors are welcome, but only until 9pm!
TUE 4/30
Conf Day 2
Bossanova Ballroom
Doors @ 8:00am
Talks from 9:00am-5:00pm
Model Building: Refreshing Yoga Session @ 10:15am
Lunch @ Noon
Lightning Talks @ 1:00pm
Hiring Speed Networking @ 3:00pm
Dinner and Mingle
The conference has ended, but we're all still here. Find some friendly faces and invite them to dinner or #relaxml brunch before you leave the venue!
Find your tribe on Slack, or on Twitter using the hashtag #ml4all.


--- layout: directory title: Tutorial Directory permalink: /tutorials/ ---
There's so much more to learn about Jekyll. Explore the tutorials on CloudCannon Academy and become a Jekyll master!


We don't store your search history.We therefore have nothing to sell to advertisers that track you across the Internet


This is a ECE Senior project on IoT and data analytics. The experiment intends to give an analytical synthesis of human behaviour in a given space and time. 3 motion sensors were installed in 3 spaces - Rooms ( Hall, Master, Guest )
The Sensor component - ( JAVA ) sits on an Application Server and listens to the Raspberry pi GPIO pins using the pi4j API. The sensor data is saved in to MongoDB. This data collectively provides an analytical representation of the data collected over a considerable period of time.
Map Reduce is an algorithm to process huge volumes of data. The entire data process in basically broken into 2 steps.
MAP Step - In this stage the data is grouped per day.
Reduce Step - In this stage the value is summed for each day.
The Map Reduce process is repeated for each of the sensors for the entire data base.
| # | Sensor Id | Day | Time |
|---|---|---|---|
| 1 | HALL_SENSOR | Sunday | 12:20:000 |
| 2 | HALL_SENSOR | Sunday | 17:50:000 |
| 3 | HALL_SENSOR | Monday | 22:32:000 |
| 4 | HALL_SENSOR | Tuesday | 11:10:000 |
| 5 | HALL_SENSOR | Tuesday | 12:22:000 |
| Day | Value Array |
|---|---|
| Sunday | [1, 1] |
| Monday | [1] |
| Tuesday | [1, 1] |
| Day | Value - Sum |
|---|---|
| Sunday | 2 |
| Monday | 1 |
| Tuesday | 2 |
The UI is built on Bootstrap Framework, ANgular JS running on Node.JS. The Application has MongoDB based security management. The Processed data is presented in the form of 2 charts
Occupancy volume per day in a week. This is displayed for each of Sensors.
Over all Occupancy volume across all the sensors.
View Charts
The Project is managed and maintained in GitHub publicly. The repository handles are as follows.


#include <candidate_sampling_ops.h>
Computes the ids of the positions in sampled_candidates that match true_labels.
When doing log-odds NCE, the result of this op should be passed through a SparseToDense op, then added to the logits of the sampled candidates. This has the effect of 'removing' the sampled labels that match the true labels by making the classifier sure that they are sampled labels.
Arguments:
Optional attributes (see Attrs
):
Returns:
Output
indices: A vector of indices corresponding to rows of true_candidates.Output
ids: A vector of IDs of positions in sampled_candidates that match a true_label for the row with the corresponding index in indices.Output
weights: A vector of the same length as indices and ids, in which each element is -FLOAT_MAX.
Constructors and Destructors |
|
|---|---|
ComputeAccidentalHits(const ::tensorflow::Scope & scope, ::tensorflow::Input true_classes, ::tensorflow::Input sampled_candidates, int64 num_true)
|
|
ComputeAccidentalHits(const ::tensorflow::Scope & scope, ::tensorflow::Input true_classes, ::tensorflow::Input sampled_candidates, int64 num_true, const ComputeAccidentalHits::Attrs & attrs)
|
Public attributes |
|
|---|---|
ids
|
|
indices
|
|
operation
|
|
weights
|
Public static functions |
|
|---|---|
Seed(int64 x)
|
|
Seed2(int64 x)
|
Structs |
|
|---|---|
|
tensorflow:: |
Optional attribute setters for ComputeAccidentalHits. |
::tensorflow::Output ids
::tensorflow::Output indices
Operation operation
::tensorflow::Output weights
ComputeAccidentalHits( const ::tensorflow::Scope & scope, ::tensorflow::Input true_classes, ::tensorflow::Input sampled_candidates, int64 num_true )
ComputeAccidentalHits( const ::tensorflow::Scope & scope, ::tensorflow::Input true_classes, ::tensorflow::Input sampled_candidates, int64 num_true, const ComputeAccidentalHits::Attrs & attrs )
Attrs Seed( int64 x )
Attrs Seed2( int64 x )


| Top |
WebKitWebsiteData represents data stored in the client by a particular website.
A website is normally a set of URLs grouped by domain name. You can get the website name,
which is usually the domain, with webkit_website_data_get_name()
.
Documents loaded from the file system, like file:// URIs, are all grouped in the same WebKitWebsiteData
with the name "Local files".
A website can store different types of data in the client side. WebKitWebsiteDataTypes is an enum containing
all the possible data types; use webkit_website_data_get_types()
to get the bitmask of data types.
It's also possible to know the size of the data stored for some of the WebKitWebsiteDataTypes by using
webkit_website_data_get_size()
.
A list of WebKitWebsiteData can be retrieved with webkit_website_data_manager_fetch()
. See WebKitWebsiteDataManager
for more information.
WebKitWebsiteData *
webkit_website_data_ref (WebKitWebsiteData *website_data
);
Atomically increments the reference count of website_data
by one.
This function is MT-safe and may be called from any thread.
Since: 2.16
void
webkit_website_data_unref (WebKitWebsiteData *website_data
);
Atomically decrements the reference count of website_data
by one.
If the reference count drops to 0, all memory allocated by
WebKitWebsiteData is released. This function is MT-safe and may be
called from any thread.
Since: 2.16
const char *
webkit_website_data_get_name (WebKitWebsiteData *website_data
);
Gets the name of WebKitWebsiteData. This is the website name, normally represented by a domain or host name. All local documents are grouped in the same WebKitWebsiteData using the name "Local files".
Since: 2.16
WebKitWebsiteDataTypes
webkit_website_data_get_types (WebKitWebsiteData *website_data
);
Gets the types of data stored in the client for a WebKitWebsiteData. These are the
types actually present, not the types queried with webkit_website_data_manager_fetch()
.
Since: 2.16
guint64 webkit_website_data_get_size (WebKitWebsiteData *website_data
,WebKitWebsiteDataTypes types
);
Gets the size of the data of types types
in a WebKitWebsiteData.
Note that currently the data size is only known for WEBKIT_WEBSITE_DATA_DISK_CACHE
data type
so for all other types 0 will be returned.
Since: 2.16
Enum values with flags representing types of Website data.
|
Memory cache. |
||
|
HTTP disk cache. |
||
|
Offline web application cache. |
||
|
Session storage data. |
||
|
Local storage data. |
||
|
WebSQL databases. |
||
|
IndexedDB databases. |
||
|
Plugins data. |
||
|
Cookies. |
||
|
All types. |
Since: 2.16


Nominees
selected out of
records |
Reset All
Nominees
Nominators
Prize Category of Nominees
reset
Nominees by Male/Female
reset
Nomination Year
Year Of Birth
Nominees by Nomination Year
reset
Nominees by Year of Birth
reset
reset


{% extends "_base.html" %} {% block content %}
Some Notes Here
This is the dashboard. I hope you find what you need.
Official Python Documentation
30 Python Features You May Not Know
Simple Python Programs


You can help shape Waterloo Region's future
Open houses will be held and input can be submitted online
by KitchenerToday StaffThe Region of Waterloo is looking to the future - far into the future!
It wants to know what the game plan should be in the years to come.
By the year 2041, the Region's population is set to reach 835,000, with over 400,000 jobs.
Officials are currently reviewing the Regional Official Plan, which will guide long-term growth and development.
If you have any ideas or feedback, you can have your say.
A number of open houses will be held in the weeks to come and input can be submitted online.
You can see more details by clicking here.


public class SleepData
extends java.lang.Object
implements java.lang.Comparable<java.lang.Object>
| Constructors and instructions |
|---|
SleepData() |
SleepData(int cali_flag,
int sleepQulity,
int wakeCount,
int deepSleepTime,
int lowSleepTime,
int allSleepTime,
java.lang.String sleepLine,
TimeData sleepDown,
TimeData sleepUp)
Sleep data
|
| qualifiers and types | Methods and instructions |
|---|---|
int |
compareTo(java.lang.Object another) |
int |
getAllSleepTime()
Get the total sleep time, unit: minute
|
int |
getCali_flag()
Get calibration value
|
java.lang.String |
getDate()
Get the date of sleep,date format isyyyy-mm-dd
|
int |
getDeepSleepTime()
Get the duration of deep sleep, unit: minute
|
int |
getLowSleepTime()
Get light sleep duration in minutes
|
static java.lang.String |
getSleepDate(TimeData time)
2015-10-02 8points-2015-10-03 8points- both10months2days of sleep
|
TimeData |
getSleepDown()
Get Sleep Time
|
java.lang.String |
getSleepLine()
Get sleep curve, mainly used for more iconicUIto display sleep status (refer to our companyAPP,360Application Market SearchHband) if you sleep the interface toUINo special requirements, ignore,Sleep curve is divided into ordinary sleep and precision sleep, ordinary sleep is a group of0,1,2A string of characters, each character representing the duration is5minutes of which0means light sleep,1means deep sleep,2means wake,such as "201112"with length6, indicating a total of sleep stages30minutes, head and tail awake5minutes with light sleep5minutes, deep sleep15minutes;For precise sleep, the sleep curve is a set of0,1,2,3,4A string of characters, each character representing the duration is1minutes of which0means deep sleep,1means light sleep,2for rapid eye movement,3indicates insomnia,4means wake up.
|
int |
getSleepQulity()
Get Sleep Quality[1-5], the higher the level, the better the sleep quality
|
TimeData |
getSleepUp()
Get Wake Up Time
|
int |
getWakeCount()
Get the number of waking up during sleep
|
void |
setAllSleepTime(int allSleepTime)
Set total sleep time, unit: minute
|
void |
setCali_flag(int cali_flag)
Set calibration value
|
void |
setDate(java.lang.String date)
Setting the date of sleep,date format isyyyy-mm-dd
|
void |
setDeepSleepTime(int deepSleepTime)
Set the duration of deep sleep, unit: minute
|
void |
setLowSleepTime(int lowSleepTime)
Set light sleep time, unit: minute
|
void |
setSleepDown(TimeData sleepDown)
Set sleep time
|
void |
setSleepLine(java.lang.String sleepLine)
Get sleep curve, mainly used for more iconicUIto display sleep status (refer to our companyAPP,360Application Market SearchHband) if you sleep the interface toUINo special requirements, ignore,Sleep curve is divided into ordinary sleep and precision sleep, ordinary sleep is a group of0,1,2A string of characters, each character representing the duration is5minutes of which0means light sleep,1means deep sleep,2means wake,such as "201112"with length6, indicating a total of sleep stages30minutes, head and tail awake5minutes with light sleep5minutes, deep sleep15minutes;For precise sleep, the sleep curve is a set of0,1,2,3,4A string of characters, each character representing the duration is1minutes of which0means deep sleep,1means light sleep,2for rapid eye movement,3indicates insomnia,4means wake up.
|
void |
setSleepQulity(int sleepQulity)
Setting Sleep Quality[1-5], the higher the level, the better the sleep quality
|
void |
setSleepUp(TimeData sleepUp)
Set wake up time
|
void |
setWakeCount(int wakeCount)
Setting the number of wake-ups during sleep
|
java.lang.String |
toString() |
public SleepData()
public SleepData(int cali_flag, int sleepQulity, int wakeCount, int deepSleepTime, int lowSleepTime, int allSleepTime, java.lang.String sleepLine, TimeData sleepDown, TimeData sleepUp)
cali_flag
- Sleep calibration value, this value is currently uselesssleepQulity
- Sleep QualitywakeCount
- Number of waking ups during sleepdeepSleepTime
- Duration of Deep SleeplowSleepTime
- Light Sleep DurationallSleepTime
- Total Sleep TimesleepLine
- Get sleep curve, mainly used for more iconicUIto display sleep status (refer to our companyAPP,360Application Market SearchHband) if you sleep the interface toUINo special requirements, ignore,Sleep curve is divided into ordinary sleep and precision sleep, ordinary sleep is a group of0,1,2A string of characters, each character representing the duration is5minutes of which0means light sleep,1means deep sleep,2means wake,such as "201112"with length6, indicating a total of sleep stages30minutes, head and tail awake5minutes with light sleep5minutes, deep sleep15minutes;For precise sleep, the sleep curve is a set of0,1,2,3,4A string of characters, each character representing the duration is1minutes of which0means deep sleep,1means light sleep,2for rapid eye movement,3indicates insomnia,4means wake up.sleepDown
- Sleep timesleepUp
- Wake Up Timepublic static java.lang.String getSleepDate(TimeData time)
time
- public int getAllSleepTime()
public void setAllSleepTime(int allSleepTime)
public java.lang.String getDate()
public void setDate(java.lang.String date)
public int getCali_flag()
public void setCali_flag(int cali_flag)
public int getSleepQulity()
public void setSleepQulity(int sleepQulity)
public int getWakeCount()
public void setWakeCount(int wakeCount)
public int getDeepSleepTime()
public void setDeepSleepTime(int deepSleepTime)
public int getLowSleepTime()
public void setLowSleepTime(int lowSleepTime)
public java.lang.String getSleepLine()
public void setSleepLine(java.lang.String sleepLine)
public TimeData getSleepDown()
public void setSleepDown(TimeData sleepDown)
public TimeData getSleepUp()
public void setSleepUp(TimeData sleepUp)
public java.lang.String toString()
toString
in class java.lang.Object
public int compareTo(java.lang.Object another)
compareTo
in interface java.lang.Comparable<java.lang.Object>


WITNESS LIST Appropriations Committee March 13, 2001-7:00A Budget On: Avant, Bob (Texas Food and Fibers Commission) Bowen, Ray (Texas A&M University) Brown, Don (Texas Higher Education Coordinating Board) Elliott, Roger (Texas Higher Education Coordinating Board) Eugster, Konrad (Texas A&M University Veterinary Medical Diagnostic Laboratory) Faulkner, Larry (University of Texas at Austin) Fehlis, Chester (Texas Agricultural Extension Service) Franklin, Charles (University of Texas at Austin) Gaston, Jerry (Texas A&M University System) Hiler, Edward (Texas A&M University System) Hines, Charles (Prairie View A&M University) Holmes, Harry (University of Texas M.D. Anderson Cancer Center) Hull, Charles (Texas Forest Service) Monroe, Bill (Texas Education Agency) Moore, Richard (University of Texas Medical Branch) Nelson, Jim (Texas Education Agency) Porretto, John (University of Texas Health Science Center at Houston) Pritchett, Melanie (Texas Education Agency) Segura, Bill (Texas State Technical College) Slade, Priscilla (Texas Southern University) Smisko, Ann (Texas Education Agency) Wisnoski, Joe (Texas Education Agency)


THE SIXTH SENSE (director/writer: M. Night Shyamalan; cinematographer:Tak Fujimoto; cast: Bruce Willis (Malcolm Crowe), Haley Joel Osment (Cole Sear), Toni Collette (Lynn Sear), Olivia Williams (Anna Crowe), Trevor Morgan (Tommy Tammisimo), Donnie Wahlberg (Vincent Gray), M. Night Shyamalan (Dr. Hill ), 1999)
Reviewed by Dennis Schwartz
It's kitsch all right; but, nevertheless, fine storytelling by the former NYU film school graduate M. Night Shyamalan (Wide Awake), makes this moody ghost piece palpable. It offers a superb performance from the 8 year old elementary school aged boy lead, Cole Sear, played by the eleven year old Haley Joel Osment. This well-crafted mystery, is a first-rate summer entertainment vehicle, flaws and all--one large (the story if examined carefully, especially leading up to its surprise discovery, would not hold up to careful scrutiny, it's all really Hollywood hokum), one medium (ghosts can't move physical objects around, this is pure Hollywood invention), and one minor (ghosts don't leave marks on one's body, though that was a ploy that added questions about parental abuse to the story, making it fit into a modern problem in society). This last point also gave the director a chance to make a cameo in the film, as the doctor is shown having the mother sent to a social worker because of the nail scratching marks on the boy's arm.
Dr. Malcolm Crowe (Bruce Willis), a gifted child psychologist in Philadelphia, who helps Cole get it off his chest, the dark secret that makes him think he is a freak of nature, different than the other children, just because he has the ability to see dead people, in other words, ghosts. Crowe is gentle with him, listens well, has a nice professional smile, and devotes his whole sense of being to helping the child out, something that gets the child's trust.
This secret is something he can't even tell his divorced mom, Lynn (Toni Collette), who works at two jobs to keep things going for them and loves him dearly, but who, even as she accepts him for what he is still fears that he is a bit strange. Though, this rare psychic gift, having a sixth sense, enables him to see things clearly about the dead, as they regularly visit him, it also frightens him, as he does not understand what the ghosts want from him, as he tries to resist them and they sometimes leave bruises on his body.  This, afterall, is quite a burden for the lad to have on his small shoulders.
Dr. Malcolm Crowe's life is seemingly blissful- doing a job he loves, making a beneficial contribution to society and to boot, receiving an award by the city of Philadelphia in recognition for his work in helping children; he also has a wife, Anna (Olivia), whom he loves dearly, while she in return also loves him very much and supports his work. But, there is a problem, and that comes when he is tipsy one evening and there is a break-in to his upscale house, as his failing effort with a child patient, Vincent Gray (Donnie Wahlberg), is standing in the bathroom, now an adult, in his underwear, as the doctor is slowly remembering his case. The deranged former patient is telling him that he couldn't listen to him when he treated him, he didn't understand what it meant to be alone, and abruptly shoots him in the stomach, angrily saying, "You failed me," and then turns the gun on himself.
Next fall, we see a crestfallen Dr. Crowe, seemingly recovered from the gunshot, follow Cole into a church and in a concerned way offers to help him, slowly gaining the child's trust through free association games and showing a genuine liking for the child, in a non-judgmental sort of way. This is seen by him, as a chance to help this deeply troubled boy and also gain professional redemption for his past failure.
Willis is both likable and credible as the vulnerable doctor, who develops a warm relationship with Haley, both sharing a sadness about the events in their lives. The mother, Toni Collette, adds to the good rapport felt throughout the film by the three leads but has a minor role in getting through to Haley, mainly because she only wants to hear about good things and Haley's visions are often violent ones.
Haley's fright is convincing because he does not over emote the role but plays it as a child would who knows that adults don't like to hear things that are not understood by them. So he speaks in a low, almost hushed voice of haunting terror, adding punch and gravity to his hallucinations and ghost stories, making his frightful experience seem real.
What helps this story out enormously, is that almost everyone you speak to has some strange tale themselves to tell about their contacts with a dead person. If you don't believe that, take note of the popular psychics, such as a James Van Praagh, and see how many calls they get about relatives communicating with those who are departed. Most psychics would say that the dead choose to communicate with those who are most receptive to them, and that they might just be asking for some help from someone not realizing that they are dead or they are trying to help someone they care about see something that only they can see. I don't think this film added much to our knowledge of the paranormal, but it was an entertaining film, plus it showed how a murder can be solved by having a sixth sense (something that police sometimes find valuable in solving a crime). The story was mildly chilling, showing the boy's visions of the dead people as real, but without the gore that follows many of this genre's usual commercial horror stories... This escapist film allows you to take pleasure in this supernatural hokum; perhaps, even making you feel satisfied by the film's surprise ending, as you will probably not give this film another passing scary thought: accepting it for the Hollywood hokum it is, thinking more about the cleverness of the plot than about whether or not ghosts exists. I didn't find anything deeper than a good story told here, and for that, the filmmaker did an admirable job.
REVIEWED ON 8/20/99 GRADE: B-
Dennis Schwartz: "Ozus' World Movie Reviews"
http://www.sover.net/~ozus
<EMAIL_ADDRESS>© ALL RIGHTS RESERVED DENNIS SCHWARTZ
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Buttons
Anything tag be styled to look like a button by adding class="button"
, the buttons should
all line up in a horizontal line.
States
Many form elements support disabled and readonly states.
|
Normal
Required
|
Valid
Invalid
|
Disabled
Readonly
|
|---|---|---|
|
|
|
|


As most of you lot know, I do not engage with Twitter. (The Hooting Yard Twitfeed is an automated bit of gubbins that updates whenever I post something here.). It has been brought to my attention, however, that last week I was all over Twitter like a rash—if being retwitted over fifty times is, as I am assured, a rash. The cause of the hoo-hah was the attention given to a letter I had published in The Spectator which is, I hope, self-explanatory.


PAULMON2
Using Built-In Functions
PAULMON2 has built-in functions which you can call from your
programs. Most of these functions provide I/O with the serial
port. To use these, you must copy lines from the
PAULMON2.EQU file, or call directly to
the address for the desired function.
- phex1
- Print a single digit in HEX. Acc should contain a value from
0 to 15.
- cout
- Print the byte in Acc to the serial port.
- cin
- Get a character from the serial port. This routine will wait
until a character arrives, if one is not already in the buffer. The
received character is returned in Acc.
- phex
- Print the value of Acc as a 2-digit Hex number
- phex16
- Print the value of DPTR as a 4-digit Hex number
- pstr
- Print a string, which is located in CODE memory. DPTR should be
loaded with the address of the first byte of the string. The string
should be terminated with a zero (which is not sent), or a byte with
the most significant bit set (which is send, with the msb cleared).
DPTR is returned with it's value pointing to the next byte in memory
after the end of the string.
- ghex
- Get a 2-digit HEX number from the serial port, which is returned in
Acc. If the user presses ESC, C is set (clear otherwise) and Acc is
unknown. If the user presses Enter with no input, PSW.5 is set (clear
otherwise), and Acc is unknown. R2 and R3 are changed.
- ghex16
- Get a 4-digit HEX number from the serial port, which is returned in
DPTR. If the user presses ESC, C is set (clear otherwise) and DPTR is
unknown. If the user presses Enter with no input, PSW.5 is set (clear
otherwise), and DPTR is unknown. Acc, R2, R3, R4, and R5 are changed.
- esc
- Checks to see if is waiting on serial port
C=clear if no , C=set if pressed buffer is flushed
- upper
- Convert the character in Acc to uppercase, if it is a lowercase letter.
If a non-alpha character is in Acc, it is not changed.
- autobaud
- Do an automatic baud rate detection (wait for user to press Enter)
- pcstr
- Print a string in compressed format. The format of the on-the-fly
string compression used in PAULMON2 is not documented, unfortunately.
- newline
- Print a carriage return and a newline to the serial port.
- lenstr
- Measure the length of a string, which is located in CODE memory.
DPTR should be
loaded with the address of the first byte of the string. The string
should be terminated as described above in pstr.
DPTR is returned with it's value pointing to the next byte in memory
after the end of the string. The length of the string is returned in
R0. Obviously strings longer than 255 characters can't be measured,
but pstr should handle long strings without trouble.
- pint8u
- Print the value in Acc as an unsigned (ordinary base 10) integer.
In other words, a number between 0 to 255 will be printed. Flag F0 is
changed.
- pint8
- Print the value in Acc as a signed (ordinary base 10) integer.
In other words, a number between -128 to 127 will be printed. Flag F0 is
changed.
- pint16u
- Print the value in DPTR as an unsigned (ordinary base 10) integer.
In other words, a number between 0 to 65535 will be printed. Registers
R2, R3, R4, R5, and flag PSW.5 are changed.
- smart_wr
- Attempt to write a byte in Acc to memory at location specified
by DPTR. If PAULMON2 is configured for a Flash ROM, and the specified
memory location is in the Flash ROM, then smart_wr will call
prgm so that the byte is written with the flash programming
algorithm. Carry is cleared if the byte was written sucessfully,
or set if the byte could not be verified.
- prgm
- Write a byte in Acc to Flash ROM at DPTR.
Carry is cleared if the byte was written sucessfully,
or set if the byte could not be verified. Interrupts are disabled for
brief periods of time.
- erall
- Erase the Flash ROM. This can time quite some time.
- find
- Find a program header in memory. This function is unfortunately
not well documented.
PAULMON2 Documentation, Paul Stoffregen
http://www.ece.orst.edu/~paul/8051-goodies/pm2_docs/functions.html
Last updated:
Status: This page could use a bit more work
Suggestions, comments, bug reports???
<EMAIL_ADDRESS>Return to PAULMON2 Documentation, Table of Contents


--- layout: post title: English Nuttiness date: '2013-05-01 09:12:52 -0700' mt_id: 1515 blog_id: 1 post_id: 1515 basename: english_nuttiness categories: - grammar ---
One of the many things that having children has taught me is that English is a very difficult language. If they weren't totally immersed in it from birth, I don't know how you'd learn it. (As an aside, I have a lot of respect for anyone that picks English up as a second language.)
A favorite quirk of mine is how pronunciations change wildly and seemingly for no reason. For example:
| Life | the thing we only have one of (hard "i") |
| Live | what we do with that (short "i") |
| Live | from New York, it's Saturday Night (long "i") |
| Lives | the present participle (short "i") |
| Lives | two or more (long "i") |
For more English fun, you can't go wrong with contronyms.


--- title: OCO-2 CO2 peak detector keywords: fastai sidebar: home_sidebar nb_path: "notebooks/index.ipynb" ---
The goal of our project is to localize CO2 emissions on Earth based on the the carbon concentration data measured by the OCO-2 Satellite from the NASA.
We are working with:- Matthieu Porte, from IGN who submit the projet- Marie Heckmann, from the French Ministry of Ecology
1/ OCO-2 Satellite data
The OCO-2 Satellite (Orbiting Carbon Observatory) from the NASA orbits around Earth and measures the CO2 concentration in the atmosphere.
Here is a visualisation of the CO2 concentration mesured by the OCO-2 satellite in December 2019.
The satellite uses spectrometers to detect CO2 in the atmosphere, as shown in the image bellow.
More info here : https://oco.jpl.nasa.gov/instrument/
There are some limitations to the satellite measurement of the CO2 concentration:
!!
More info on the mission on https://earth.esa.int/web/eoportal/satellite-missions/o/oco-2.
The NASA made a global CO2 image (see bellow), however this is an extrapolation of the data, and not what the satellite really see.
2/ Data on known CO2 emissions
First approach: peak detection from O-CO2 & inference from inventory data
Detect peak in O-CO2 data, 2 step methodology
Aggregate known sources of CO2 from inventory data: Using EDGAR & World Resource Institute
Find nearest inventory from peak position, using the wind vector.
Compare peak to known sources emissions and confirm them
Second approach: supervised model to learn to detect peaks from inventory data [not started]
On top: dynamic visualization of data
Here is a sample of a peak witth the gaussian found :
And the result on the website :
Warning : The project use NBDev so the doc (including this README !) and the modules ar generated from Notebooks. So you have only to edit the Notebooks.
We do not store the original OCO-2 files from NASA.
If you are interested to use only our modules for your own project :
pip install oco2peak
docker-compose up
Front on http://localhost:7901
docker-compose -f docker-compose-dev.yml up
You need a config.json with token to your OpenStack:
{
"swift_storage": {
"user":"B..r",
"key":"ep..ca",
"auth_url":"https://auth.cloud.ovh.net/v3/",
"tenant_name":"8..8",
"auth_version":"3",
"options" : {
"region_name": "GRA"
},
"base_url" : "https://storage.gra.cloud.ovh.net/v1/AUTH_2...d/oco2/"
}
}
config = '../configs/config.json'
datasets = Datasets(config)
datasets.get_files_urls(prefix="/datasets/oco-2/peaks-and-invent/", pattern='1908')
datasets.get_files_urls(prefix="/map/peaks_map/", pattern='1908')
datasets.upload(mask='../*.md', prefix="/Trash/",content_type='text/text')
In docker-compose-dev.yml
change source: /media/NAS-Divers/dev/datasets/
to the path to you NC4 files.
Then run :
docker-compose -f docker-compose-dev.yml up
In another terminal, run:
docker exec -it batch7_satellite_ges_oco2-dev_1 /bin/bash
python pipeline/01_extract_nc4_to_csv.py
python pipeline/02_find_peak_in_all_files.py
python pipeline/03_upload_json_to_the_cloud.py


The IEEE Micromouse DeCal is aimed at students with a strong interest in robotics, who want to pursue a hardware project but may not have the resources to do so on their own. The course will be taught in the context of IEEE’s Micromouse competition, in which students form teams of 2-3 to navigate a 16x16 maze. By the end of the semester, students will be able to build an autonomous, maze-solving robot with minimal assistance, using skills that are extendable to real-world robotics problems. Special focus is given to topics including electrical and firmware engineering, brushed motors, sensing, pathfinding, and control theory. This course fits in with other courses in the department like EE16B.
No notices yet!
<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>| Week | Title | Content | Links |
|---|---|---|---|
|
1 (Date) |
What is Micromouse? |
• Tournament video, rules • Course logistics, questions |
Slides Reading Recording |
|
2 (Date) |
Lab 1: Arduino Basics |
• Team matching/signups • High-level overview of schematic |
Slides Lab Page Recording |
|
3 (Date) |
Lab 2: Encoders |
• Finally we interact with the real world! • Hall Effect Sensors • Polling, Interrupts |
Slides Lab Page Recording |
|
4 (Date) |
Lab 3: ToF Sensors |
• More Sensor Communication! • ToF (Time of Flight) Distance Sensors • I2C |
Slides Lab Page Recording |


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