Please feel free to explore beyond the problems given, and ask questions at any time.
Description: In this exercise, you will practice implementing a simple expression in Cython, and applying it to a numpy array.
Assignment: Implement a function in Cython that computes x**3 - 4x + 2 on each element of a large floating point array. Is this function faster than NumPy by default? If so, can you explain why?
You will need to create two files: setup.py and fast_poly.pyx.
Use the following for setup.py:
from distutils.core import setup from distutils.extension import Extension from Cython.Distutils import build_ext setup( cmdclass = {'build_ext': build_ext}, ext_modules = [ Extension("fast_poly", ["fast_poly.pyx"]), ] )
And for fast_poly.pyx:
import numpy as np def my_poly(...): ... return np.asarray(out)
You need to call np.asarray on your output, otherwise a Cython MemoryView object is returned instead of a NumPy array.
Benchmarking the NumPy version in IPython or Jupyter:
import numpy as np x = np.linspace(0, 1, 10000) %timeit x**3 - 4*x + 2
For your Cython version, do the same, after importing:
from fast_poly import my_poly
Description: In this exercise, you will wrap an existing C library (provided) in Cython, so that it may be accessed from Python. (You may also use Numba, if you prefer.)
Assignment: In the wrapping directory is a simple C library that performs some operation on a Numpy array. The header src/stuff.h defines the function with signature:
void compute(int n, double *input, double *output)
which takes two C arrays of doubles, each of length n. This is a pretty typical C function signature, like one you may run into in the real world.
Now, write a Cython wrapper:
def do_compute(double[:] input_array): ... return np.asarray(output_array)
for this function, to expose it to Python.
The C function compute requires pointers to the array data, which can be found using &input_array[0] (or &input_array[0, 0] in the case of a 2D array). The & means "address of", and gives a double *, ready for use in C.
The behaviour of the function can be verified by running run.py (open it up to see what it does).
Description: In this exercise, you will practice manipulating two-dimensional arrays in-place.
Assignment: The Game of Life is a well-known cellular automaton that exhibits interesting behavior. It is defined on a grid of cells, where each cell has 8 neighbors:
......... ......... ...ooo... ...oxo... ...ooo... ......... .........
Each cell is either alive or dead, and at any point in time this is know as the "state" of the game. The update rule used to evolve to the next state is:
Write a Cython function life_update(old_state, new_state) in life.pyx that takes an N x N Numpy array old_state of type int, and writes the new state to new_state. Use four nested for-loops, and remember to add type declarations for the counters.
We've provided a script run_life.py that will execute the game based on your update definition.
Notes: You can modify the starting state of the game by reading in other initial states:
These examples come from the Game of Life simulator Golly.
Description: In this exercise, you will practice accelerating operations on Python structures, such as lists and dictionaries.
Assignment: Implement an L-system in Cython. Try, for example, to build a Sierpinski Triangle or the Dragon Curve. If you want, you can first implement it in pure Python, and then add the type information later.
Use your Cython program to generate coordinates, then simply "connect the dots" using matplotlib (import matplotlib.pyplot as plt; plt.plot(...)).
Cython can accelerate operations on non-numerical types too. For example, if you store your coordinates in a list, you can use:
cdef list L = []For dictionaries, the type is dict.


{% extends "global/Page.html" %} {% load otree staticfiles %} {% block title %} Change of partner {% endblock %} {% block content %}
You have now been paired with a new partner, with whom you will play {{ Constants.number_rounds_per_partner }} rounds of the Task Game.
{% next_button %} {% endblock %}


Background¶
The chain rule, gradient (Jacobian), computational graph, elementary functions and several numerical methods serve as the mathematical cornerstone for this software. The mathematical concepts here come from CS 207 Lectures 9 and 10 on Autodifferentiation.
The Chain Rule¶
\[\frac{\partial h}{\partial x} =\frac{\partial h}{\partial u} \cdot \frac{\partial u}{\partial x}\]
\[\frac{\partial h}{\partial x} =\frac{\partial h}{\partial u} \cdot \frac{\partial u}{\partial x} + \frac{\partial h}{\partial v} \cdot \frac{\partial v}{\partial x}\]
Gradient and Jacobian¶
If we have \(x\in\mathbb{R}^{m}\) and function \(h\left(u\left(x\right),v\left(x\right)\right)\), we want to calculate the gradient of \(h\) with respect to \(x\):
In the case where we have a function \(h(x): \mathbb{R}^m \rightarrow \mathbb{R}^n\), we write the Jacobian matrix as follows, allowing us to store the gradient of each output with respect to each input.
In general, if we have a function \(g\left(y\left(x\right)\right)\) where \(y\in\mathbb{R}^{n}\) and \(x\in\mathbb{R}^{m}\). Then \(g\) is a function of possibly \(n\) other functions, each of which can be a function of \(m\) variables. The gradient of \(g\) is now given by
The Computational Graph¶
Let us visualize what happens during the evaluation trace. The following example is based on Lectures 9 and 10. Consider the function:
If we want to evaluate \(f\) at the point \(x\), we construct a graph where the input value is \(x\) and the output is \(y\). Each input variable is a node, and each subsequent operation of the execution trace applies an operation to one or more previous nodes (and creates a node for constants when applicable).
As we execute \(f(x)\) in the “forward mode”, we can propagate not only the sequential evaluations of operations in the graph given previous nodes, but also the derivatives using the chain rule.
Elementary functions¶
An elementary function is built up of a finite combination of constant functions, field operations \((+, -, \times, \div)\), algebraic, exponential, trigonometric, hyperbolic and logarithmic functions and their inverses under repeated compositions. Below is a table of some elementary functions and examples that we will include in our implementation.
| Elementary Functions | Example |
|---|---|
| powers | \(x^2\) |
| roots | \(\sqrt{x}\) |
| exponentials | \(e^{x}\) |
| logarithms | \(\log(x)\) |
| trigonometrics | \(\sin(x)\) |
| inverse trigonometrics | \(\arcsin(x)\) |
| hyperbolics | \(\sinh(x)\) |
Note
Background for additional features, Newton’s root finding, Gradient Descent, BFGS and quadratic splines can be found in Additional Features.


fastboot.js
fastboot.js is an implementation of the Android fastboot protocol in JavaScript. It runs in web browsers by using the WebUSB API, which is currently supported by Chrome.
Why?
Many users, particularly those with less technical experience, have trouble flashing custom operating systems on Android devices. This is not necessarily their fault; there are many steps in the process that can go wrong. Broken or outdated Android platform tools, missed commands or steps, and many other factors can cause problems during flashing.
WebUSB makes it possible to move most of the complexity into the browser, where the environment is much more controlled and most of the steps can be automated. This makes it easier for users to flash ROMs onto their devices and is more likely to result in success.
Google's Android Flash Tool for AOSP CI images and Pixel factory images is already taking advantage of this, but unfortunately, it is proprietary and closed-source. Furthermore, it only supports flashing the aforementioned images from Google, so flashing custom ROMs with it is not possible. This is where fastboot.js comes in: it is an open-source library that can be used to create web installers for flashing anything.
Features
The following fastboot features are supported:
- Running commands (erase, lock, unlock, getvar, reboot, etc.)
- Flashing raw, bootloader, sparse, and custom AVB key images
- Flashing AOSP factory image zips (update.zip), including firmware, logical partitions, and verified boot keys
- Flashing images larger than the bootloader's maximum download size (by splitting sparse images)
- Flashing logical partitions
Detailed progress callbacks are also provided for many flashing steps.
Installation
This library is available as a package on npm, so you can easily add it to your project:
# Using npm
npm install --save android-fastboot
# Using yarn
yarn add android-fastboot
Examples
A basic demo of fastboot.js can be found here. The source code is included in this repository.
There is also a user-friendly ROM installer available, with a live ProtonAOSP instance that can be used to flash devices officially supported by ProtonAOSP.
Documentation
Documentation generated from JSDoc comments can be found here.


All Folders
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Thanks
Codebase -
https://github.com/tsquillario/MiniSub
Icons -
http://somerandomdude.com/work/iconic
Audio Library -
http://www.schillmania.com/projects/soundmanager2
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- HiringManager - Class in server.model
-
Represents the Hiring Manager object
- HiringManager(String, String, String) - Constructor for class server.model.HiringManager
-
Creates a userID object
- hiringManagerFailure(String) - Static method in class server.rest.responses.HiringManagerResponse
-
Creates an error response object
- HiringManagerResponse - Class in server.rest.responses
-
Response object for Hiring Manager Add and Edit REST API links
- HiringManagerResponse(HiringManager) - Constructor for class server.rest.responses.HiringManagerResponse
-
Creates a Hiring manager Response
- hiringmanagers(String) - Method in class server.rest.controllers.HiringManagersController
-
- HiringManagersController - Class in server.rest.controllers
-
- HiringManagersController() - Constructor for class server.rest.controllers.HiringManagersController
-
- HiringManagersControllerTest - Class in server.rest.controllers
-
- HiringManagersControllerTest() - Constructor for class server.rest.controllers.HiringManagersControllerTest
-
- hiringManagersFailure(String) - Static method in class server.rest.responses.HiringManagersResponse
-
Creates an error response object
- HiringManagersResponse - Class in server.rest.responses
-
Response object for HiringManagers REST API view link
- HiringManagersResponse(ArrayList<HiringManager>) - Constructor for class server.rest.responses.HiringManagersResponse
-
Creates a Hiring Managers Response object
- HRAddEditPayGradeResponse - Class in server.rest.responses
-
Response object for PayGrades' Add and Edit REST API links
- HRAddEditPayGradeResponse(HRPayGrade) - Constructor for class server.rest.responses.HRAddEditPayGradeResponse
-
Creates a HRAddEditPayGradeResponse object
- HRPayGrade - Class in server.model
-
Represents the pay grade of the object
- HRPayGrade(String, int, int, String) - Constructor for class server.model.HRPayGrade
-
Creates a user object
- HRPayGradeController - Class in server.rest.controllers
-
Controller for HR PayGrade table
Provides all the REST endpoints related to HR Pay Grades and stored SQL procedures
- HRPayGradeController() - Constructor for class server.rest.controllers.HRPayGradeController
-
- hrPayGradeFailure(String) - Static method in class server.rest.responses.HRPayGradeResponse
-
Creates an error response object
- HRPayGradeResponse - Class in server.rest.responses
-
Response object for PayGrades' view link
- HRPayGradeResponse(ArrayList<HRPayGrade>) - Constructor for class server.rest.responses.HRPayGradeResponse
-
Creates a HRPayGrade Response object
- HRPositionRole - Class in server.model
-
Represents the HR Position Role of the object
- HRPositionRole(String, String, String) - Constructor for class server.model.HRPositionRole
-
Creates a HRPositionRole object
- HRPositionRoleController - Class in server.rest.controllers
-
Controller for Position Role table in the database
Provides all the REST endpoints related to HR Position Roles and stored SQL procedures
- HRPositionRoleController() - Constructor for class server.rest.controllers.HRPositionRoleController
-
- HRPositionRoleResponse - Class in server.rest.responses
-
Response Object for HR Position Role REST API view link
- HRPositionRoleResponse(ArrayList<HRPositionRole>) - Constructor for class server.rest.responses.HRPositionRoleResponse
-
Creates a HRPositionRole object
- hrroles(String) - Method in class server.rest.controllers.HRPositionRoleController
-
REST API link for viewing all HR Roles
- HRRolesResponse - Class in server.rest.responses
-
Response object for REST API add and edit links of HRRoles
- HRRolesResponse(HRPositionRole) - Constructor for class server.rest.responses.HRRolesResponse
-
Creates a HRRolesResponse object


79; 12022 H.E.
Horimiya is one of the most realistic depictions of the first love I have ever watched. It captured the beauty, awkwardness, embarrassment, and vivid colors of what it means to fall in love for the first time. I would even dare to say the privilege of almost feeling like being a part of it. It’s good to be young.
This will be a short review, as most of what I have to say is encapsulated above. It is usually a rare feat for films and media set in high school settings to portray real emotions and feelings. Most are slapstick comedies (think of any Disney/CN/Nick show), super cringey (anything coming out now), and way over the top on the life part.
I love Dostoyevsky; many would claim that he goes over the top; however, his stories are more nuanced, as he explores every soul as if it were a whole Universe. However, I must note that this “over the top” simply talks about a story that lacks genuine emotions, which makes them desperate to over-compensate that with writing that has no restraints. It reads dull and disconnected from reality. We will have another time for him.
Horimiya was nothing like it. The relationship built between Hori and Miyamura felt natural and genuine. How first love blooms, develops, and how it must go through thick and thin to last have meaning that goes beyond the initial inexperience of lovers, so it can grow into stability and mutual understanding. What does it mean to give colors of life to your loved one? To be close to someone.
Every human is their whole Universe, which is yet to be found and loved by their special someone. They explored different relationships, lives, and people around them, like their classmates and friends (or yet-to-be friends). The successes in love, failures, misunderstandings, and selfishness were a part of the story, which made it so much more relatable. ◼


[gecode-users] Generating constraints
Christian Schulte
cschulte at kth.se
Tue Oct 28 14:42:15 CET 2008
Yes, you have to flip (or just normalize your tree before).
Remember, Gecode is a library with a minimal interface: only variants that
matter for efficiency are there. That explains that some variants are just
not there. Maybe we should change that...
On a different take. Did you consider translating your representation to
MiniZinc and use the MiniZinc to FlatZinc converter and Gecode's flatzinc
interface?
Christian
--
Christian Schulte, www.ict.kth.se/~cschulte/
-----Original Message-----
From: users-bounces at gecode.org [mailto:users-bounces at gecode.org] On Behalf
Of Max
Sent: Tuesday, October 28, 2008 2:36 PM
To: Christian Schulte
Cc: 'Mikael Zayenz Lagerkvist'; users at gecode.org
Subject: Re: [gecode-users] Generating constraints
I have written the code for the analyzer now, but i just wanted to avoid
this code-bloating.
46 void GecodeSolver::SearchSpace::generateConstraint(CSPConstraint c,
unsigned int boolvar)
47 {
48
49 if (c.getType() == CSPConstraint::RELATION)
50 {
51 CSPConstraint* x;
52 CSPConstraint* y;
53 CSPConstraint::Relation r = c.getRelation(x,y);
54
55 IntVar r1;
56 IntVar r2;
57 int i1;
58 int i2;
59 bool b1 = false;
60 bool b2 = false;
61 if (x->getType() == CSPConstraint::VARIABLE | x->getType() ==
CSPConstraint::OPERATOR)
62 {
63 r1 = generateVariable(*x);
64 b1 = true;
65 }
66 else
67 if (x->getType() == CSPConstraint::INTEGER)
68 {
69 i1 = x->getInteger();
70 }
71
72 if (y->getType() == CSPConstraint::VARIABLE | y->getType() ==
CSPConstraint::OPERATOR)
73 {
74 r2 = generateVariable(*y);
75 b1 = true;
76 }
77 else
78 if (y->getType() == CSPConstraint::INTEGER)
79 {
80 i2 = y->getInteger();
81 }
82
83 Gecode::IntRelType ir;
84 switch(r)
85 {
86 case CSPConstraint::EQ:
87 ir = IRT_EQ;
88 break;
89 case CSPConstraint::NE:
90 ir = IRT_NQ;
91 break;
92 case CSPConstraint::LT:
93 ir = IRT_LE;
94 break;
95 case CSPConstraint::LE:
96 ir = IRT_LQ;
97 break;
98 case CSPConstraint::GE:
99 ir = IRT_GQ;
100 break;
101 case CSPConstraint::GT:
102 ir = IRT_GR;
103 break;
104 }
105
106 if (b1)
107 {
108 if (b2)
109 Gecode::rel(this, r1, ir, r2, b_[boolvar]);
110 else
111 Gecode::rel(this, r1, ir, i2, b_[boolvar]);
112 }
113 else
114 {
115 if (b2)
116 Gecode::rel(this, i1, ir, r2, b_[boolvar]);
117 else
118 Gecode::rel(this, i1, ir, i2, b_[boolvar]);
119
120 }
121 }
This is not very nice, but maybe i have to change my tree structure for
better code.
(as you can see i wanted to avoid all the different kind of variables of
type IntVar and integer and all the if else constructs)
But, with this code written i do get some errors, because the rel method
is not defined for constants
as:
- both arguments
- first argument
so i can not write
rel(this, 5, IRT_GR, x, b);
Why?
Do i have manually to flip the operands ?
Christian Schulte wrote:
> Yes, it is even worse: it sacrifices propagation!
>
> If you need to get started look to the code that posts propagators based
on
> LinExpr and LinRel values. That is actually nothing but a tree analyzer
> posting the minimal number of required propagators for linear relations.
>
> Cheers
> Christian
>
> --
> Christian Schulte, www.ict.kth.se/~cschulte/
>
>
> -----Original Message-----
> From: users-bounces at gecode.org [mailto:users-bounces at gecode.org] On Behalf
> Of Max
> Sent: Tuesday, October 28, 2008 1:56 PM
> To: Mikael Zayenz Lagerkvist
> Cc: users at gecode.org
> Subject: Re: [gecode-users] Generating constraints
>
> I have no problem in writing a tree analyzer but i looked for a uniform
> representation of the variables, operators, relations and constants, so
> i do not have to write an extra function for all of them.
> I want to write
>
> recursive_function_call rfc(X):
> IntVar temp;
> //switch for operator
> add(rfc(x1), ADD, rfc(x2), temp);
> return temp;
>
> I don't want to distinguish the leafs of the node at this step. So i
> need a uniform return value.
> PS: Does it influence the performance if i use temporary variables for
> my constants.
>
> IntVar x(this, 5,5);
>
>
>
>
> Mikael Zayenz Lagerkvist wrote:
>
>> Hi,
>>
>> If you have a tree representing an expression, then you should write a
>> tree-analyzer (a tree-walker for example) that posts constraints that
>> correspond to the tree. This is how the linear expressions in Gecodes
>> MiniModel works. For more information on writing tree analyzers, see a
>> compiler text as it corresponds to instruction selection.
>>
>> There is no way to undo a tell - you have to copy the space.
>>
>> Cheers,
>> Mikael
>>
>>
>> On Tue, Oct 28, 2008 at 12:58 PM, Max <chaosangel at gmx.de> wrote:
>>
>>
>>> Hello all,
>>>
>>> i currently try to post constraints and need your help.
>>> I have my constraints not in a textual format, but in a self made tree
>>> structure of the form
>>>
>>>
>>> rel">="
>>> / \
>>> op+ const=5
>>> / \
>>> var=x const=7
>>>
>>>
>>> (i hope this is readable)
>>>
>>> Now i want to generate and post a gecode constraint of it.
>>> Is there an easy way to recursivly define a constraint, because it seems
>>> to me that there is no baseclass or something that can be used.
>>>
>>> I wanted to to something of the form
>>>
>>> GeCodeConstraint recursive_converter(MyConstraint)
>>> {
>>> if "variable" return x;
>>> if "constant" return 5;
>>> if "op+" return recursive_converter(left_node) +
>>> recursive_converter(right_node);
>>> if "rel>=" return recursive_converter(left_node) >=
>>> recursive_converter(right_node);
>>> }
>>>
>>>
>>> I i found for GeCodeConstraint was MiniModel::LinRel<>, is there
>>> something more uniform, because i want to use boolean and integer
>>> variables (reified constraints) and stuff.
>>> (the arithmetic functions seem very generic returning a variable, but
>>> then a lot of extra variables would have to be generated)
>>>
>>>
>>> Any ideas ?
>>>
>>> 2nd question:
>>>
>>> Is there a way to post the value of a variable not in form of a
>>> constraint, so "branch" on a boolean variable but being able to undo it
>>>
> so
>
>>> so
>>> b[0].set(0);
>>> //after some time
>>> b[0].set(1);
>>>
>>> without copying the whole space?
>>>
>>> Thank you a lot.
>>>
>>> Max
>>>
>>> _______________________________________________
>>> Gecode users mailing list
>>> users at gecode.org
>>> https://www.gecode.org/mailman/listinfo/gecode-users
>>>
>>>
>>>
>>
>>
>>
>
>
> _______________________________________________
> Gecode users mailing list
> users at gecode.org
> https://www.gecode.org/mailman/listinfo/gecode-users
>
>
> _______________________________________________
> Gecode users mailing list
> users at gecode.org
> https://www.gecode.org/mailman/listinfo/gecode-users
>
>
_______________________________________________
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{% extends "hello/base.html" %}
{% block content %}
{% for post in posts %}
{% if post.productType == "pork" %}
|
Decription: {{post.description}} Recipe: {{post.Recipe}}: {{post.recipe_name}} Recommended price: 14.99€ |
Temperature: Stored at 1 degrees on its way to Helsinki
Standards: This product has been produced in accordance with EU standards
Ingredients: Pork, salt, pepper
Calories: 220 kcal
This product was produced on our own farm in Mikkeli. The current temperature there is 3 degrees. The product takes an average of 18 hours to arrive at your local supermarket.
The farm this product was produced on spends an average of 0.2 liters of water per product which is sourced from local lakes. This is 32% less than the industry average.
The farm this product was produced on has contributed 16.8% of the total CO2 produced by the production, which is 15% less than average.
Finnsih HK scan farms produce 12% less CO2 on average than other Finnish farms.
{% endblock content %}


Benefits of mindfulness for staff include improved wellbeing and ability to manage stress. These benefits lead to less absenteeism and greater productivity.
Other benefits include heightened emotional intelligence and greater self-management, which in turn improves relationships with colleagues and decreases conflict in the workplace. When mindfulness is embedded within an organisation, it is likely there will be increased creativity, better decision making and a more productive and compassionate workplace culture. Evidence shows an increase in collaboration and greater awareness of fostering good relationships in the workplace. Read the Mindful Nation UK report.
In 2021, the Wellcome evidence-based report on workplace mental health recommended that all staff should be given access to mindfulness courses. And perhaps more significantly, the most recent NICE guidance on mental wellbeing at work that came out in March 2022: Recommendations | Mental wellbeing at work | Guidance | NICE recommends that mindfulness should be offered to "all employees…on an ongoing basis". Paragraph 1.6.4 and 1.7.4 states that, "The committee agreed that mindfulness, meditation and yoga were most effective overall in reducing job stress and mental health symptoms and having a positive effect on employee mental wellbeing."
Our own research shows:


|
e-puck
1.0
|
#include "ComModule.h"
#include <stdlib.h>
#include "./motor_led/e_epuck_ports.h"
#include "./I2C/e_I2C_protocol.h"
#include "./I2C/e_I2C_master_module.h"
Macros | |
| #define | COM_MODULE_I2C_ADDR (0x3F<<1) |
| #define | BUFFER_DATA_LENGTH (COM_MODULE_MAXSIZE + 14) |
| #define | STATUS_REG_ADDR 0x00 |
| #define | CONFIG_REG_ADDR 0x01 |
| #define | SEND_REG_ADDR 0x02 |
| #define | SOFTATT_REG_ADDR 0x03 |
| #define | OWNGROUP_REG_ADDR 0x04 |
| #define | OWNADDRL_REG_ADDR 0x05 |
| #define | OWNADDRH_REG_ADDR 0x06 |
| #define | SEND_BUFFER_START 0x07 |
| #define | SEND_BUFFER_END (SEND_BUFFER_START + BUFFER_DATA_LENGTH) |
| #define | REC_BUFFER_START (SEND_BUFFER_END + 1) |
| #define | REC_BUFFER_END (REC_BUFFER_START + BUFFER_DATA_LENGTH) |
| #define | AM_MSGTYPE 0x0A |
| #define | AM_MSGTYPE_IN_PACKET_OFFSET 0x08 |
| #define | ADDRLDATA_IN_PACKET_OFFSET 0x06 |
| #define | ADDRHDATA_IN_PACKET_OFFSET 0x07 |
| #define | TYPEDATA_IN_PACKET_OFFSET 0x08 |
| #define | GROUPDATA_IN_PACKET_OFFSET 0x09 |
| #define | FIRSTDATA_IN_PACKET_OFFSET 0x0A |
| #define | PACKET_READY_FLAG 0x01 |
| #define | TX_IDLE_FLAG 0x02 |
| #define | PACKET_LOST_FLAG 0x04 |
| #define | TX_SEND_ERROR 0x08 |
| #define | HARDWAREATT_SET_FLAG 0x01 |
| #define | RADIO_ENABLED_FLAG 0x80 |
| #define | REQUEST_TO_SEND_FLAG 0x01 |
Functions | |
| unsigned char | ReadRegister (unsigned char registeraddr) |
| void | WriteRegister (unsigned char registeraddr, unsigned char value) |
| void | InitComModule (unsigned char owngroup, unsigned int ownaddress, unsigned char hardwareattenuatormode, unsigned char softwareattenuatorvalue) |
| int | IsModulePlugged () |
| void | SetRadioEnabledState (unsigned char mode) |
| void | SetHardwareAttenuator (unsigned char attenuatormode) |
| void | SetSoftwareAttenuator (unsigned char attenuatorvalue) |
| void | SetOwnGroup (unsigned char owngroup) |
| void | SetOwnAddress (unsigned int ownaddress) |
| unsigned char | GetHardwareAttenuator () |
| unsigned char | GetRadioEnabledState () |
| unsigned char | GetSoftwareAttenuator () |
| unsigned char | GetOwnGroup () |
| unsigned int | GetOwnAddress () |
| unsigned char | GetStatus () |
| int | SendPacket (unsigned char destinationgroup, unsigned int destinationaddress, unsigned char *packet, int packetsize) |
| int | IsPacketReady (unsigned char *packet, int *packetsize) |
| #define ADDRHDATA_IN_PACKET_OFFSET 0x07 |
| #define ADDRLDATA_IN_PACKET_OFFSET 0x06 |
| #define AM_MSGTYPE 0x0A |
| #define AM_MSGTYPE_IN_PACKET_OFFSET 0x08 |
| #define BUFFER_DATA_LENGTH (COM_MODULE_MAXSIZE + 14) |
| #define COM_MODULE_I2C_ADDR (0x3F<<1) |
| #define CONFIG_REG_ADDR 0x01 |
| #define FIRSTDATA_IN_PACKET_OFFSET 0x0A |
| #define GROUPDATA_IN_PACKET_OFFSET 0x09 |
| #define HARDWAREATT_SET_FLAG 0x01 |
| #define OWNADDRH_REG_ADDR 0x06 |
| #define OWNADDRL_REG_ADDR 0x05 |
| #define OWNGROUP_REG_ADDR 0x04 |
| #define PACKET_LOST_FLAG 0x04 |
| #define PACKET_READY_FLAG 0x01 |
| #define RADIO_ENABLED_FLAG 0x80 |
| #define REC_BUFFER_END (REC_BUFFER_START + BUFFER_DATA_LENGTH) |
| #define REC_BUFFER_START (SEND_BUFFER_END + 1) |
| #define REQUEST_TO_SEND_FLAG 0x01 |
| #define SEND_BUFFER_END (SEND_BUFFER_START + BUFFER_DATA_LENGTH) |
| #define SEND_BUFFER_START 0x07 |
| #define SEND_REG_ADDR 0x02 |
| #define SOFTATT_REG_ADDR 0x03 |
| #define STATUS_REG_ADDR 0x00 |
| #define TX_IDLE_FLAG 0x02 |
| #define TX_SEND_ERROR 0x08 |
| #define TYPEDATA_IN_PACKET_OFFSET 0x08 |
| unsigned char GetHardwareAttenuator | ( | ) |
| unsigned int GetOwnAddress | ( | ) |
| unsigned char GetOwnGroup | ( | ) |
| unsigned char GetRadioEnabledState | ( | ) |
| unsigned char GetSoftwareAttenuator | ( | ) |
| unsigned char GetStatus | ( | ) |
| void InitComModule | ( | unsigned char | owngroup, |
| unsigned int | ownaddress, | ||
| unsigned char | hardwareattenuatormode, | ||
| unsigned char | softwareattenuatorvalue | ||
| ) |
| int IsModulePlugged | ( | ) |
| int IsPacketReady | ( | unsigned char * | packet, |
| int * | packetsize | ||
| ) |
| unsigned char ReadRegister | ( | unsigned char | registeraddr | ) |
| int SendPacket | ( | unsigned char | destinationgroup, |
| unsigned int | destinationaddress, | ||
| unsigned char * | packet, | ||
| int | packetsize | ||
| ) |
| void SetHardwareAttenuator | ( | unsigned char | attenuatormode | ) |
| void SetOwnAddress | ( | unsigned int | ownaddress | ) |
| void SetOwnGroup | ( | unsigned char | owngroup | ) |
| void SetRadioEnabledState | ( | unsigned char | mode | ) |
| void SetSoftwareAttenuator | ( | unsigned char | attenuatorvalue | ) |
| void WriteRegister | ( | unsigned char | registeraddr, |
| unsigned char | value | ||
| ) |


After reviewing both the Navigation and Resource timing specifications, we’ve finally arrived at the User timing spec. This is the last of the performance timing specifications I’ll review, and thankfully, one of the most straightforward.
The User Timing api allows you to measure the performance of your javascript. Quite simply, it allows you to specify a start time at any point in your code, an end point at any point in your code, and then measure the difference between the two.
Yes you can. So why do we need an api for something we can already do? The spec tells us: “…the precision of this timestamp varies between user agents.” To put it another way, the browsers are too inconsistent in how they report Date.now().
Before getting into the details, it’s important to understand that all time measurements created with the User Timing api are relative to the navigation start time of the page. In other words, when you navigate to the page, the timer starts at 0 and works it way up.
To record a start or end time, you use the mark method;
performance.mark("startTime1");
yourCode();
performance.mark("endTime1");
The only things you need to know when creating a mark are 1) You can’t use a reserved word and 2) You can reuse the same name; the value will just be overwritten each time.
In order to access the values of a mark you created, request the marks from the performance object:
var perfEntries = performance.getEntriesByType("mark");
for (var i = 0; i < perfEntries.length; i++) {
if (window.console) console.log("Name: " + perfEntries[i].name +
" Entry Type: " + perfEntries[i].entryType +
" Start Time: " + perfEntries[i].startTime +
" Duration: " + perfEntries[i].duration + "\n");
}
name - This is the name you gave the mark.
entryType - This will be “mark”.
startTime - This is the time value that was recorded when your mark function ran.
duration - For a mark, this will return a 0.
The measure function is a convenience method that finds the difference between two marks and stores it in a named measure.
performance.measure('myNewMeasure', 'markOneStart', 'markOneEnd');
Retrieving measure values is done exactly the same way as marks except you specify “measure” as the type to retrieve:
var perfEntries = performance.getEntriesByType("measure");
name - This is the name you have assigned to the measure.
entryType - This will be “measure”.
startTime - This is the time the measure was taken.
duration - This is the calculated duration of the measure.
The measure function also has two other modes of operation you need to be aware. First, if you only specify a measure name, then the reported duration will be the difference between the navigation start and the current time.
Second, if you only specify a measure name and a start mark name, then the reported duration will be the difference between the start mark and the current time.
clearMarks - If you call this method with no name, you’ll clear all the marks on the page. If you specify a mark name, it will clear all the marks with that name. If you specify a mark name that doesn’t exist, then this function does nothing.
clearMeasures - This behaves in all the same ways as the clearMarks function except it applies to your measures.
Here’s an example of how you might use this code in an external javascript file. Once again, I’m relying heavily on a repo from Alois Reitbauer.
var scriptSource = 'myScriptName';
performance.mark(scriptSource + 'Start');
var delay= 5 * 1000 // 10 seconds
var quitAt = Date.now() + delay;
while (Date.now() <= quitAt){
; // good old busy waiting - doing nothing
}
performance.measure(scriptSource, scriptSource + 'Start');
With this in your javascript file, you query the measure types to find the duration of your scripts.


--- layout: archive title: Zulip Chat Archive permalink: /stream/144837-PR-reviews/topic/.231080.20props.20of.20elements.20in.20rings.html ---
@Neil Strickland This is a monster PR... experience has told us that it is really quite hard to review such large PR's.
pnat
-PR. Maybe also on the other one? Please indicate this in the PR message.Then, about content... I guess it would be very useful to generalise parts of this to non-commutative rings. After all, idempotent and nilpotent endomorphisms/matrices are quite useful.
It is already too bad that lots of linear algebra in mathlib makes unnecessary commutativity assumptions. We should stop doing that.
@Neil Strickland The big benefit of small PRs is that it is a lot easier to decide that everything in that 1 PR is ready for merging. I like to read through a PR top-to-bottom just before merging. If it is < ~300 lines, I can do that on the train while commuting... with PRs this size, I really need to schedule a block of time to review... ask for changes, schedule another block of time, etc...
This PR is not dependent on either of the other ones.
I think that I will leave this PR as it is for the next few days, and discuss general strategy with @Kevin Buzzard and whoever else is in Edinburgh next week.
This https://github.com/leanprover-community/mathlib/pull/1080/files#diff-b6a928a2a31b1974bf06431c20999550 suggest that the PR does depend on your pnat
PR.
This PR #1080 contains all your pnat stuff. Is that intentional?
No, that's not intentional. I thought that I had kept the branches completely separate, but I am not very skilled with git yet. I will cancel the current PR and do it again once I have understood why that did not work.
You might be interested in git cherry-picking. But if there are too many commits in your history, that might be tedious and faster to do by hand.
I just downloaded the git book and will bite the bullet and read it systematically.
You can "cherry pick" a range of commits using git rebase
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


Author Info
Profile: themeforest.net/user/bitpub
Website: www.bitpublimedia.ro
Twitter: twitter.com/bitpub
Thank you for purchasing my template. If you have any questions that are beyond the scope of this help file feel free to contact me using the form on my profile page. If you want to stay up to date with file updates and new releases, follow me on twitter or send me an email with your info and I will add you to my mailing list. Thanks so much!
Email readers have little support for CSS so if you want to design an html email that renders constantly across different email clients then an XHTML & CSS aproach to the design is wrong. You need to go back to TABLE based layouts, using minimum CSS and only for presentation purposes.
I though it would be a good idea to start the documentation with a refresher on the topic that will make it easier to understand what is going on in the newsletters provided. Below you will find general guidlines, links to external references and example source code.

 ...

 // newsletter content here

The package contains:
As I mentioned before in the documentation it is always prefered to stack more tables one under the other then nesting them or creating very complicated table structures as it reduces the risk of the layout breaking in the email clients.
Starting from this principle I created a modular newsletter system, composed of:
So, creating a layout is as simple as staking different modules in the main content section of a base file template, customizing the css to your liking and then transforming the embedded css to inline css. This last step can be automated using html Premailer, a free service found at http://premailer.dialect.ca/
To make things even easier I created some helper pages from where you can copy paste the source code for modules and base files, get dummy text, placeholder images of various sizes and examples of the tags and classes you have available to put the content in the newsletter. This greatly reduces the time needed to create a layout and also allows you to build a whole layout, that you can be sure work fine in most email clients, without having to write a single of code.
I call it the Step by Step Newsletter Creator System and you can acces it here: ../layout-creation/00-start.html
It has 4 simple steps:
We will go over every step in detail, below.
How to customize a base file:

 Mobile version here.
 To view hosted version click here.
and css
.view-mobile-browser{ line-height:14px; font-size:11px; } .view-mobile-browser a{ color:#3a3a3a; }

 Visit our website
www.YourWebsite.com
and css
.ourwebsite{ line-height:14px; font-size:11px; } .ourwebsite a{ font-weight:bold; }

 Lementu | Donecos | Sagittis | Lorem & Pellentes
and css
.menu-or-slogan{} .menu-or-slogan a{ color:#3a3a3a; text-decoration:underline; }

...

and css
.main-content-wrap{ border-width: 1px 1px 1px 1px; border-spacing: 0px; border-style: solid solid solid solid;
border-color: #d6d6d6 #d6d6d6 #d6d6d6 #d6d6d6; border-collapse: collapse; background-color: #ffffff; }
5.2 Change background color

...

and css
.main-content-wrap{ border-width: 1px 1px 1px 1px; border-spacing: 0px; border-style: solid solid solid solid;
border-color: #d6d6d6 #d6d6d6 #d6d6d6 #d6d6d6; border-collapse: collapse; background-color: #ffffff; }
Note: If you change the background color from white you will have to edit the module dividers and content spacers to make them match the new color.

  	 Connect with us:	   	  Our Blog 	   	  Facebook 	   	  LinkedIn 	   	  Twitter

and css
.social{ border-top:1px solid #D0D0D0; border-bottom:1px solid #D0D0D0; } .social a{ color:#3a3a3a; text-decoration:none; }
You will find more social media icons in layout-creation/images/social

 YourCompany, Some Adress
 Some City, XY 305, Some Country
T: +1<PHONE_NUMBER>
E: <a href="mailto:office<EMAIL_ADDRESS>
and css
.companyinfo{} .companyinfo a{}

 This newsletter was sent to<EMAIL_ADDRESS>
from YourCompany because you subscribed
Unsubscribe instantly | Forward to a friend
and css
.subscription{} .subscription a{}

© 2010 Your Company. All rights reserved.
and css
.copyright{} .copyright a{ color:#565656; text-decoration:none; }
Transform the embedded Css to inline Css
This will ensure the css is used by the majority of client email readers.
The way to do this is:
1. Change in the code each class="" with style="... the rules in the class definition int the header ..."
ex.  becomes

2. If you have general rules in the css you must add them to every tag:
ex. in the css
table{ color:#666666; font-family:Arial, sans-serif; font-size:12px; line-height:20px; }
in the html

becomes

Once finish you should delete the  section completly. Make sure the page still works.
Needless to say this is a painstaking process. Luckily there is an free online service that does all of this automatically; it is called premailer and is found as http://premailer.dialect.ca/
Visit the page, select "Use HTML as the source" and copy paste your code that has the CSS embedded in the  section. It will create a version with the css inlined.


AUD/JPY: Flashing marginal gains, 100-day MA is key support
by Omkar Godbole- AUD/JPY is attempting gains amid the uptick in the S&P 500 futures.
- Big gains may remain elusive on trade optimism and pessimism seesaw.
AUD/JPY is reporting marginal gains at press time, having defended key support for a third straight day on Thursday.
The currency pair is currently trading at 73.83, representing a 0.15% gain on the day.
The bid tone around the anti-risk Japanese Yen has likely weakened, possibly due to the uptick in the US index futures. Currently, the S&P 500 futures are adding 0.15% on the day.
China's commerce ministry on Thursday dismissed reports stating that the trade talks between the US and China are in trouble and reiterated that the world's second-largest economy will work with the US side on the basis of equality and mutual respect in addressing the core concerns.
Even so, the US equity markets dipped Thursday. For instance, the Dow Jones Industrial Average fell 0.20%. The risk sentiment, however, is looking to stabilize in Asia. The AUD/JPY pair may extend gains if the risk reset gathers pace.
That said, investors may be wary of initiating bullish bets on stocks, courtesy of optimism and pessimism seesaw. Both sides have a history of mentioning the change of interim deal only to backtrack in the same sentence.
Therefore, big gains in AUD/JPY look unlikely - more so, due to the downbeat Aussie PMI released earlier today. The headline Manufacturing PMI came in above 49.8 forecasts to 49.9 but slipped beneath 50.1 prior while Services PMI declined to 49.5 versus 53.5 expected and 50.1 earlier.
Technical levels
The 100-day MA, currently at 73.59, has been restricting downside since Nov. 19. Therefore, a break below that level, if confirmed, could embolden sellers, leading to a quick drop to 73.00.
AUD/JPY
| Overview | |
|---|---|
| Today last price | 73.84 |
| Today Daily Change | 0.14 |
| Today Daily Change % | 0.19 |
| Today daily open | 73.7 |
| Trends | |
|---|---|
| Daily SMA20 | 74.5 |
| Daily SMA50 | 73.77 |
| Daily SMA100 | 73.62 |
| Daily SMA200 | 75.57 |
| Levels | |
|---|---|
| Previous Daily High | 74.05 |
| Previous Daily Low | 73.49 |
| Previous Weekly High | 74.96 |
| Previous Weekly Low | 73.35 |
| Previous Monthly High | 75.3 |
| Previous Monthly Low | 71.73 |
| Daily Fibonacci 38.2% | 73.7 |
| Daily Fibonacci 61.8% | 73.84 |
| Daily Pivot Point S1 | 73.44 |
| Daily Pivot Point S2 | 73.18 |
| Daily Pivot Point S3 | 72.87 |
| Daily Pivot Point R1 | 74 |
| Daily Pivot Point R2 | 74.31 |
| Daily Pivot Point R3 | 74.57 |


Load your data, run our script and you are ready to go!
Ask predefined questions or create your own queries with SPARQL.
To learn more, access our GitHub repository:


--- layout: default officecolor: "#EBAF00" office: Defense Sciences Office (DSO) ---
GRAPHS разрабатывает масштабируемые алгоритмы и статистические методы для анализа и моделирования очень больших и динамически эволюционирующих сетей, с целью разработки прогнозирующих методов для аномальных и исключительных событий в сетях. Основной фокус программ количественный и структурные аспекты больших сетей и моделей присутсвия. Программа разделена на несколько выпадов, с исполнителями работающими с технологиями сбора проб для графов, геометрически вложений(geometric embeddings) в гиперболических пространствах, Гауссовы Условные Случайные Поля(Gaussian Conditional Random Fields), среднеуровневое сетевое поведение, и прогнозирование связей.
Program Manager: Dr. Reza Ghanadan
Contact<EMAIL_ADDRESS>Содержимое, приводимое ниже, было подготовлено организациями, которые частично финансируются ДАРПА; мнения и выводы, содержащиеся в нем, являются авторскими и не должны толковаться как представляющие официальную политику или одобрения, выраженные явно или подразумеваемые, ДАРПА или правительства США.
Сообщить о проблеме<EMAIL_ADDRESS>Last updated: November 28, 2016
| Команда | Проект | Описание | Instructional Material | Категория | Код | Лицензия |
|---|---|---|---|---|---|---|
| MINER | SnapVX | SnapVX is a Python-based convex optimization solver for problems defined on graphs. It provides a fast and scalable solution with guaranteed global convergence. SnapVX combines the graph capabilities of Snap.py with the convex solver from CVXPY. | Analytics | https://github.com/snap-stanford/snapvx | BSD |
| Команда | Название | Ссылка |
|---|---|---|
| Sandia National Laboratories | An In-Depth Analysis of Stochastic Kronecker Graphs | http://arxiv.org/pdf/1102.5046v3.pdf |
| Sandia National Laboratories | Wedge Sampling for Computing Clustering Coefficients and Triangle Counts on Large Graphs | http://arxiv.org/pdf/1309.3321.pdf |
| Sandia National Laboratories | A Scalable Generative Graph Model with Community Structure | http://arxiv.org/pdf/1302.6636v3.pdf |
| Sandia National Laboratories | Counting Triangles in Massive Graphs with MapReduce | http://arxiv.org/pdf/1301.5887v3.pdf |
| Sandia National Laboratories | Degree Relations of Triangles in Real-world Networks and Models | http://arxiv.org/pdf/1207.7125.pdf |
| Sandia National Laboratories | A Scalable Null Model for Directed Graphs Matching All Degree Distributions: In, Out, and Reciprocal | http://arxiv.org/pdf/1210.5288.pdf |
| Sandia National Laboratories | Triadic Measures on Graphs: The Power of Wedge Sampling | http://arxiv.org/pdf/1202.5230v2.pdf |
| Sandia National Laboratories | A Space Efficient Streaming Algorithm for Estimating Transitivity and Triangle Counts Using the Birthday Paradox | http://arxiv.org/pdf/1212.2264v3.pdf |
| University of Minnesota, Sandia National Laboratories | Dynamics of Trust Reciprocation in Multi-relational Networks | http://www.sandia.gov/~tgkolda/pubs/pubfiles/SiSuSrKo13-ASONAM13.pdf |
| Sandia National Laboratories | Why do Simple Algorithms for Triangle Enumeration Work in the Real World? | http://www.cs.princeton.edu/~csesha/pubs/conf-triangle-enum.pdf |
| Sandia National Laboratories | Decompositions of Triangle-dense Graphs | http://arxiv.org/pdf/1309.7440v3.pdf |
| Sandia National Laboratories | Using Triangles to Improve Community Detection in Directed Networks | http://arxiv.org/pdf/1404.5874v1.pdf |
| Stanford University, Sandia National Laboratories | FAST-PPR: Scaling Personalized PageRank Estimation for Large Graphs | http://arxiv.org/pdf/1404.3181v1.pdf |
| Pennsylvania State University, Carnegie Mellon University | Maximum Likelihood Estimation in the Beta Model | http://projecteuclid.org/euclid.aos/1371150894 |
| Университет Карнеги Меллон | Estimation for Dyadic-Dependent Exponential Random Graph Models | http://jalgstat.com/download/55/86/jas-2014_5_39-63.pdf |
| Университет Карнеги Меллон | Consistency under Sampling of Exponential Random Graph Models | http://projecteuclid.org/euclid.aos/1366980556 |
| Pennsylvania State University | Graphical Models | http://msp.org/jsag/2013/5-1/jsag-v5-n1-p01-s.pdf |
| Университет Карнеги Меллон | A Brief History of Statistical Models for Network Analysis and Open Challenges | http://dx.doi.org/10.1080/10618600.2012.738106 |
| Университет Карнеги Меллон | The Strength of Arcs and Edges in Interaction Networks: Elements of a Model-Based Approach | http://arxiv.org/pdf/1211.0312v2.pdf |
| Pennsylvania State University/ Illinois Institute of Technology | Combinatorial Degree Bound for Toric Ideals of Hypergraphs | http://www.worldscientific.com/doi/abs/10.1142/S0218196713500331 |
| Университет Карнеги Меллон | Is the Privacy of Network Data an Oxymoron? | http://repository.cmu.edu/cgi/viewcontent.cgi?article=1097&context=jpc |
| Illinois Institute of Technology | Toric Algebra of Hypergraphs | http://link.springer.com/article/10.1007%2Fs10801-013-0444-y |
| Университет Карнеги Меллон | Consistency of Spectral Clustering in Sparse Stochastic Block Models | http://arxiv.org/pdf/1312.2050v1.pdf |
| Университет Карнеги Меллон | Stable Mixed Graphs | http://projecteuclid.org/euclid.bj/1386078605 |
| Университет Карнеги Меллон | Markov Properties for Mixed Graphs | http://projecteuclid.org/euclid.bj/1393594002 |
| Университет Карнеги Меллон | Asymptotic Quantization of Exponential Random Graphs | http://arxiv.org/pdf/1311.1738v2.pdf |
| Illinois Institute of Technology | Goodness-of-fit for Log-linear Network Models: Dynamic Markov Bases Using Hypergraphs | http://arxiv.org/pdf/1401.4896v1.pdf |
| ORNL-Stanford-Berkeley (Tree-like structure) | On the Hyperbolicity of Small-World and Treelike Random Graphs | http://www.tandfonline.com/doi/full/10.1080/15427951.2013.828336#.VAQIz0igSqQ |
| ORNL-Stanford-Berkeley (Tree-like structure) | Evaluating OpenMP Tasking at Scale for the Computation of Graph Hyperbolicity | http://link.springer.com/chapter/10.1007%2F978-3-642-40698-0_6 |
| ORNL-Stanford-Berkeley (Tree-like structure) | Tree-like Structure in Large Social and Information Networks | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6729484 |
| ORNL-Stanford-Berkeley (Tree-like structure) | Think Locally, Act Locally: The Detection of Small, Medium-Sized, and Large Communities in Large Networks | http://arxiv.org/abs/1403.3795 |
| ORNL-Stanford-Berkeley (Tree-like structure) | Anti-differentiating Approximation Algorithms: A Case Study with Min-cuts, Spectral, and Flow | http://jmlr.org/proceedings/papers/v32/gleich14.html |
| ORNL-Stanford-Berkeley (Tree-like structure) | Tree Decompositions and Social Graphs | Еще не опубликовано |
| University of California, Santa Barbara | Metric Embedding, Hyperbolic Space, and Social Networks | http://dl.acm.org/citation.cfm?id=2582139 |
| Hewlett-Packard Labs | Mining Information from Heterogeneous Sources: A Topic Modeling Approach | http://www.hpl.hp.com/research/scl/papers/socialmedia/IntegrateSources.pdf |
| University of California, Santa Barbara | On the Most Likely Voronoi Diagram and Nearest Neighbor Searching | to be published in ISAAC 2014 |
| Boston University | Sublinear But Never Superlinear Preferential Attachment by Local Network Growth | http://iopscience.iop.org/1742-5468/2013/02/P02043 |
| Boston University | Distinct Degrees and Their Distribution in Complex Networks | http://iopscience.iop.org/1742-5468/2013/06/P06002 |
| Boston University | Highly Dispersed Networks by Enhanced Redirection | http://journals.aps.org/pre/abstract/10.1103/PhysRevE.88.050802 |
| Boston University | Choice-Driven Phase Transition in Complex Networks | http://iopscience.iop.org/1742-5468/2014/4/P04021 |
| Boston University | Highly Dispersed Networks Generated by Enhanced Redirection | http://iopscience.iop.org/1742-5468/2014/4/P04009/ |
| Boston University | Emergence of Clustering in an Acquaintance Model Without Homophily | http://arxiv.org/abs/1408.6596 |
| University of Colorado | Change-Point Detection in Temporal Networks Using Hierarchical Random Graphs | http://outlier-analytics.org/odd14kdd/odd-2014-proceedings.pdf#section*.12 |
| University of Colorado | Detecting Change Points in the Large-Scale Structure of Evolving Networks | http://arxiv.org/pdf/1403.0989v1.pdf |
| University of Colorado | Learning Latent Block Structure in Weighted Networks | http://comnet.oxfordjournals.org/content/early/2014/06/26/comnet.cnu026.full.pdf+html |
| University of Colorado | Efficiently Inferring Community Structure in Bipartite Networks | http://arxiv.org/pdf/1403.2933v2.pdf |
| University of Colorado | Adapting the Stochastic Block Model to Edge-Weighted Networks | http://arxiv.org/pdf/1305.5782v1.pdf |
| University of Colorado | Detecting Friendship within Dynamic Online Interaction Networks | http://arxiv.org/pdf/1303.6372v1.pdf |
| University of Colorado | Friends FTW! Friendship, Collaboration, and Competition in Halo: Reach | http://arxiv.org/pdf/1203.2268v2.pdf |
| University of Colorado | Complex Life Cycles in a Pond Food Web: Effects of Life Stage Structure and Parasites on Network Properties, Trophic Positions and the Fit of a Probabilistic Niche Model | http://link.springer.com/article/10.1007/s00442-013-2806-5#page-1 |
| Temple University | Continuous Conditional Random Fields for Efficient Regression in Large Fully Connected Graphs | http://www.dabi.temple.edu/~zoran/papers/KostaAAAI13.pdf |
| Temple University | Imputation of Missing Links and Attributes in Longitudinal Social Surveys | http://www.dabi.temple.edu/~zoran/papers/MachLearn2013.pdf |
| Temple University | Which Links Should I Use? A Variogram Based Selection of Relationship Measures for Prediction of Node Attributes in Temporal Multigraphs | http://www.dabi.temple.edu/~zoran/papers/alexeyASONAM13.pdf |
| Temple University | Distributed Gaussian Conditional Random Fields Based Regression for Large Evolving Graphs | http://www.dabi.temple.edu/~zoran/papers/sdm14_networksgraphs.pdf |
| Temple University | Dynamic Distributed Predictive Learning Models that Preserve Privacy for Hospitals with Insufficient Labeled Data | http://www.dabi.temple.edu/~zoran/papers/NetwModelAnalHealthInformBioinforma2013.pdf |
| Temple University | Panning for Gold: Using Variograms to Select Useful Connections in a Temporal Multigraph Setting | http://link.springer.com/article/10.1007%2Fs13278-014-0211-7#page-1 |
| Temple University | Hospital Pricing Estimation by Gaussian Conditions Random Fields Based Regression on Graphs | Еще не опубликовано |
| Temple University | Readmission Classification Using Stacked Regularized Logistic Regression Models | Еще не опубликовано |
| Temple University | Neural Gaussian Conditional Random Fields | http://www.dabi.temple.edu/~zoran/papers/ngcrf_ecml14.pdf |
| LeHigh University | Convergence of Trust-Region Methods Based on Probabilistic Models | http://arxiv.org/pdf/1304.2808v1.pdf |
| LeHigh University | Efficient Quasi-Newton Proximal Method for Large Scale Sparse Optimization | http://opt.kyb.tuebingen.mpg.de/papers/opt2013_submission_10.pdf |
| LeHigh University | Practical Inexact Proximal Quasi-Newton Method with Global Complexity Analysis | http://arxiv.org/pdf/1311.6547v3.pdf |
| University of Washington | Approximate Inference in Continuous Determinantal Point Processes | http://papers.nips.cc/paper/4916-approximate-inference-in-continuous-determinantal-processes.pdf |
| University of Washington | Nystrom Approximation for Large-Scale Determinantal Processes | https://www.stat.washington.edu/~ebfox/publications/AISTATS2013.pdf |
| University of Washington | Spatio-Temporal Low Count Processes with Application to Violent Crime Events | http://arxiv.org/pdf/1304.5642v1.pdf |
| University of Washington | Bayesian Nonparametric Covariance Regression | http://arxiv.org/pdf/1101.2017v2.pdf |
| University of Washington | Autoregressive Models for Variance Matrices: Stationary Inverse Wishart Processes | http://arxiv.org/pdf/1107.5239v1.pdf |
| University of Washington | Joint Modeling of Multiple Time Series via the Beta Process with Application to Motion Capture Segmentation | http://arxiv.org/pdf/1308.4747v2.pdf |
| University of Washington | Parsing Epileptic Events Using a Markov Switching Process for Correlated Time Series | https://www.stat.washington.edu/~ebfox/publications/icml2013.pdf |
| University of Washington | Modeling the Complex Dynamics and Changing Correlations of Epileptic Events | http://arxiv.org/pdf/1402.6951v2.pdf |
| University of Washington | Representing Documents Through Their Readers | https://www.stat.washington.edu/~ebfox/publications/badgepaper-kdd2013.pdf |
| University of Washington | A Bayesian Approach for Predicting the Popularity of Tweets | http://arxiv.org/pdf/1304.6777.pdf |
| University of Washington | Stochastic Gradient Hamiltonian Monte Carlo | http://arxiv.org/pdf/1402.4102v2.pdf |
| University of Washington | Bayesian Nonparametric Models of Sparse and Exchangeable Random Graphs | http://arxiv.org/pdf/1401.1137v2.pdf |
| MEGA Stanford University | Exploiting Social Network Structure for Person-to-Person Sentiment Analysis | http://cs.stanford.edu/people/jure/pubs/sentiment-tacl14.pdf |
| MEGA Stanford University | Uncovering the Structure and Temporal Dynamics of Information Propagation | http://cs.stanford.edu/people/jure/pubs/netrate-netsci14.pdf |
| MEGA Stanford University | Discovering Social Circles in Ego Networks | http://cs.stanford.edu/people/jure/pubs/circles-tkdd14.pdf |
| MEGA Stanford University | Detecting Cohesive and 2-mode Communities in Directed and Undirected Networks | http://cs.stanford.edu/people/jure/pubs/coda-wsdm14.pdf |
| MEGA Stanford University | Community Detection in Networks with Node Attributes | http://cs.stanford.edu/people/jure/pubs/cesna-icdm13.pdf |
| MEGA Stanford University | Information Cartography: Creating Zoomable, Large-Scale Maps of Information | http://cs.stanford.edu/people/jure/pubs/metro-kdd13.pdf |
| MEGA Stanford University | Overlapping Community Detection at Scale: A Nonnegative Matrix Factorization Approach | http://cs.stanford.edu/people/jure/pubs/bigclam-wsdm13.pdf |
| MEGA Stanford University | Community-Affiliation Graph Model for Overlapping Network Community Detection | http://cs.stanford.edu/people/jure/pubs/agmfit-icdm12.pdf |
| MEGA Stanford University | Defining and Evaluating Network Communities based on Ground-truth | http://cs.stanford.edu/people/jure/pubs/comscore-icdm12.pdf |
| MEGA Stanford University | Learning to Discover Social Circles in Ego Networks | http://cs.stanford.edu/people/jure/pubs/circles-nips12.pdf |
| Stanford University, Sandia National Labs | FAST-PPR: Scaling Personalized PageRank Estimation for Large Graphs | http://arxiv.org/abs/1404.3181 |
| Stanford Graphs Team | Gossip: Identifying Central Individuals in a Social Network | http://ssrn.com/abstract=2425379 |
| Stanford Graphs Team | Networks of Military Alliances, Wars, and International Trade | http://ssrn.com/abstract=2389300 |
| Stanford Graphs Team | Networks in the Understanding of Economic Behaviors | http://ssrn.com/abstract=2404632 |
| Stanford Graphs Team | Culture-Dependent Strategies in Coordination Games | http://web.stanford.edu/~jacksonm/Jackson-Xing-CultureAndCoordination-PNAS-2014.pdf |
| Stanford Graphs Team | Financial Networks and Contagion | http://ssrn.com/abstract=2175056 |
| Stanford Graphs Team | Tractable and Consistent Random Graph Models | http://ssrn.com/abstract=2150428 |
| Stanford Graphs Team | Games on Networks | http://papers.ssrn.com/abstract=2136179 |
| MEGA | A Dynamic Network Game for the Adoption of New Technologies | http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2425490 |
| Stanford University, Duke University | Efficient Primal-Dual Algorithms for MapReduce | http://web.stanford.edu/~ashishg/papers/distribute/densest-AHK.pdf |
| Стэнфордский университет | Personalized PageRank to a Target Node | http://arxiv.org/abs/1304.4658 |
| ICME Stanford University | Dimension Independent Similarity Computation | http://dl.acm.org/citation.cfm?id=2567715 |
| Стэнфордский университет | Re-Incentivizing Discovery: Mechanisms for Partial-Progress Sharing in Research | http://dl.acm.org/citation.cfm?id=2602888 |
| MIT | Single Pass Spectral Sparsification in Dynamic Streams | http://arxiv.org/abs/1407.1289 |
| MIT, IBM Almaden | Spanners and Sparsifiers in Dynamic Streams | http://researcher.watson.ibm.com/researcher/files/us-dpwoodru/kw.pdf |
| Stanford University, Microsoft Research Silicon Valley | On Differentially Private Low Rank Approximation | http://dl.acm.org/citation.cfm?id=2627918 |
| Стэнфордский университет | Better Bounds for Matchings in the Streaming Model | http://dl.acm.org/citation.cfm?id=2627938 |
| MIT | (Nearly) Sample-Optimal Sparse Fourier Transform | http://dl.acm.org/citation.cfm?id=2634110 |
| MIT, University of Pennsylvania, Microsoft Research New England | Streaming Lower Bounds for Approximating MAX-CUT / Approximating Matching Size from Random Streams | http://arxiv.org/abs/1409.2138 |
| Стэнфордский университет | Improved ARV Rounding in Small-set Expanders and Graphs of Bounded Threshold Rank | http://arxiv.org/abs/1304.2060 |
| Stanford University, IBM Almaden Research Center | Online Submodular Welfare Maximization: Greedy is Optimal | http://dl.acm.org/citation.cfm?id=2627905 |
| University of Notre Dame | Reducing Degeneracy in Maximum Entropy Models of Networks | http://arxiv.org/abs/1407.0991 |
| University of Notre Dame | The Brain in Space | http://obelix.phys.nd.edu/~toro/archive/IPSENChapterV2.pdf |
| University of Notre Dame | Cortical High-Density Counterstream Architectures | http://www.sciencemag.org/content/342/6158/1238406.abstract |
| University of Notre Dame | Predicting Commuter Flows in Spatial Networks Using a Radiation Model Based on Temporal Ranges | http://obelix.phys.nd.edu/~toro/archive/SpatialNetFlows_Combined.pdf |
| University of Notre Dame | On the Swap-Distances of Different Realizations of a Graphical Degree Sequence | http://www.renyi.hu/~miklosi/EKM-CPC-resubmit2.pdf |
| University of Notre Dame | A Decomposition Based Proof for Fast Mixing of a Markov Chain Over Balanced Realizations of a Joint Degree Matrix | http://arxiv.org/pdf/1307.5295v1.pdf |
| University of Notre Dame | Constructing, Sampling and Counting Graphical Realizations of Restricted Degree Sequences | http://arxiv.org/pdf/1301.7523v3.pdf |
| University of Notre Dame | Towards Random Uniform Sampling of Bipartite Graphs with Given Degree Sequence | http://www.renyi.hu/~miklosi/MES-EJC13.pdf |
| University of Notre Dame | Symmetry in Critical Random Boolean Network Dynamics | http://dx.doi.org/10.1103/PhysRevE.89.042808 |
| University of Notre Dame | Fast and Accurate Determination of Modularity and its Effect Size | Еще не опубликовано |
| University of Notre Dame | Modeling Interacting Dynamic Networks: III. Extraordinary Properties in a Population of Extreme Introverts and Extroverts | http://arxiv.org/abs/1408.5421 |
| University of Notre Dame | Extreme Thouless Effect in a Minimal Model of Dynamic Social Networks | Еще не опубликовано |
| University of Notre Dame | Dominating Scale-Free Networks Using Generalized Probabilistic Methods | http://www.nature.com/srep/2014/140909/srep06308/full/srep06308.html |
| University of Notre Dame | Minimum Dominating Sets in Scale-Free Network Ensembles | http://www.nature.com/srep/2013/130426/srep01736/full/srep01736.html |
| University of Notre Dame | Threshold-Limited Spreading in Social Networks with Multiple Initiators | http://www.nature.com/srep/2013/130731/srep02330/full/srep02330.html |
| University of Notre Dame | A Local Lemma Algorithm for Dominating Sets | http://people.math.sc.edu/czabarka/MT_Report-6.pdf |
| University of Notre Dame | On Realizations of a Joint Degree Matrix | http://arxiv.org/abs/1302.3548 |
| University of Notre Dame | Connected Balanced Subgraphs in Random Regular Multigraphs Under the Configuration Model | http://www.combinatorialmath.ca/jcmcc/jcmcc86.html |
| University of Notre Dame | Eccentricity in Trees | http://arxiv.org/abs/1408.5865 |
| University of Notre Dame | Extremal Values of Ratios: Distance Problems vs. Subtree Problems in Trees II | http://www.sciencedirect.com/science/article/pii/S0012365X14000041 |
| University of Notre Dame | A New Asymptotic Enumeration Technique: The Lovasz Local Lemma | http://arxiv.org/abs/0905.3983 |
| University of Notre Dame | Mixed Orthogonal Arrays, k-dimensional M-part Sperner Multi-Families and Full Multi-Transversals | http://arxiv.org/abs/1207.2646 |
| University of Notre Dame | Threshold Functions for Distinct Parts: Revisiting Erdos--Lehner | http://arxiv.org/abs/1209.5764 |
| University of Notre Dame | Quest for Negative Dependency Graphs | http://people.math.sc.edu/lu/papers/kostyabook.pdf |
| University of Notre Dame | Predicting Node Degree Centrality with the Node Prominence Profile | Еще не опубликовано |
| University of Notre Dame | Predicting Links in Multi-relational and Heterogeneous Networks | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6413854 |
| University of Notre Dame | Influence Activation Model: A New Perspective in Social Influence Analysis and Social Network Evolution | Еще не опубликовано |
| University of Notre Dame | Evaluating Link Prediction Methods | http://www3.nd.edu/~yyang1/papers/kais13.pdf |
| University of Notre Dame | Vertex Collocation Profiles: Theory, Computation, and Results | http://www.springerplus.com/content/3/1/116 |
| University of Notre Dame | Scaling Personalized Healthcare with Big Data | http://www.nd.edu/~nchawla/papers/bdah_1.pdf |
| University of Notre Dame | Improving Management of Aquatic Invasions by Integrating Shipping Network, Ecological, and Environmental Data: Data Mining for Social Good | https://www3.nd.edu/~nchawla/papers/kdd14a.pdf |
| University of Notre Dame | Recurrent Subgraph Prediction | http://www3.nd.edu/~snagrech/presub.pdf |
| University of Notre Dame | How Long Will She Call Me? Distribution, Social Theory and Duration Prediction | https://www3.nd.edu/~dial/papers/duration.pdf |
| University of Notre Dame | Link Prediction in Coupled Networks | Еще не опубликовано |
| University of Notre Dame | Inferring User Demographics and Social Strategies in Mobile Social Networks | http://www3.nd.edu/~ydong1/papers/KDD14-Dong-et-al-WhoAmI-demographic-prediction.pdf |
| University of Notre Dame | Inferring Social Status and Rich Club Effects in Enterprise Communication Networks | http://arxiv.org/pdf/1404.3708v3.pdf |
| University of Notre Dame | Disease and Medication Networks: An Insight into Disease-Drug Interactions | http://www.nd.edu/~nchawla/papers/bdah_2.pdf |
| MIT | Scheduling a Cascade with Opposing Influences | http://arxiv.org/abs/1311.5925 |
| MIT | Bidimensional Structures: Algorithms, Combinatorics and Logic | http://drops.dagstuhl.de/opus/volltexte/2013/4013/ |
| MIT | Brief Announcement: A Game-Theoretic Model Motivated by the DARPA Network Challenge | http://dl.acm.org/citation.cfm?id=2486160 |
| MIT | Tight Bounds for Planar Strongly Connected Steiner Subgraph with Fixed Number of Terminals (and Extensions) | http://epubs.siam.org/doi/pdf/10.1137/1.9781611973402.129 |
| MIT | Fixed-Parameter and Approximation Algorithms: A New Look | http://link.springer.com/chapter/10.1007%2F978-3-319-03898-8_11#page-1 |
| MIT | How to Influence People with Partial Incentives | http://dl.acm.org/citation.cfm?doid=2566486.2568039 |
| MIT | PREVE: A Policy Recommendation Engine based on Vector Equilibria in Multiplayer Games | Еще не опубликовано |
| MIT | PREVE: A Policy Recommendation Engine Based on Vector Equilibria Applied to Reducing LeT's Attacks | Еще не опубликовано |
| MIT | A Polynomial-Time Approximation Scheme for Planar Multiway Cut | http://mhbateni.com/academic/pubs/multiwaycut-10.pdf |
| MIT | How Effectively Can We Form Opinions | Еще не опубликовано |
| MIT | The Polarizing Effect of Network Influences | Еще не опубликовано |
| MIT | The Prize-Collecting Steiner Network Problems | http://link.springer.com/chapter/10.1007%2F978-3-642-13036-6_6#page-1 |
| MIT | Approximation Algorithms for Movement Repairmen | http://arxiv.org/abs/1306.3739 |
| MIT | LP Rounding for k-Centers with Non-uniform Hard Capacities | http://arxiv.org/abs/1208.3054 |
| MIT | Online Node-Weighted Steiner Forest and Extensions via Disk Paintings | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6686192 |
| MIT | Basic Network Creation Games | http://www.tau.ac.il/~nogaa/PDFS/adhl4.pdf |
| MIT | Minimizing Movement: Fixed-Parameter Tractability | http://link.springer.com/chapter/10.1007/978-3-642-04128-0_64#page-1 |
| MIT | Scheduling to Minimize Gaps and Power Consumption | http://link.springer.com/article/10.1007%2Fs10951-012-0309-6#page-1 |
| MIT | Improved Approximation Algorithms for (Budgeted) Node-weighted Steiner Problems | http://link.springer.com/chapter/10.1007%2F978-3-642-39206-1_8 |
| MIT | Designing FPT Algorithms for Cut Problems Using Randomized Contractions | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6375324&tag=1 |
| MIT | Directed Subset Feedback Vertex Set Is Fixed-Parameter Tractable | http://link.springer.com/chapter/10.1007%2F978-3-642-31594-7_20 |
| MIT | Approximability of the Subset Sum Reconfiguration Problem | http://link.springer.com/article/10.1007%2Fs10878-012-9562-z#page-1 |
| MIT | O(1)-Approximations for Maximum Movement Problems | http://link.springer.com/chapter/10.1007%2F978-3-642-22935-0_6#page-1 |
| MIT | Polynomial-Time Approximation Schemes for Subset-Connectivity Problems in Bounded-Genus Graphs | http://link.springer.com/article/10.1007%2Fs00453-012-9662-2#page-1 |
| MIT | Fixed-Parameter Tractability of Directed Multiway Cut Parameterized by the Size of the Cutset | http://siam.omnibooksonline.com/2012SODA/data/papers/010.pdf |
| MIT | Assignment Problem in Content Distribution Networks: Unsplittable Hard-Capacitated Facility Location | http://epubs.siam.org/doi/pdf/10.1137/1.9781611973068.88 |
| MIT | Euclidean Prize-Collecting Steiner Forest | http://link.springer.com/article/10.1007%2Fs00453-011-9491-8#page-1 |
| MIT | Local Search Algorithms for the Red-Blue Median Problem | http://link.springer.com/article/10.1007%2Fs00453-011-9547-9#page-1 |
| MIT | Swapping Labeled Tokens on Graphs | http://link.springer.com/chapter/10.1007%2F978-3-319-07890-8_31#page-1 |
| MIT | On Streaming and Communication Complexity of the Set Cover Problem | http://link.springer.com/chapter/10.1007%2F978-3-662-45174-8_33 |
| MIT | On a Local Protocol for Concurrent File Transfers | http://link.springer.com/article/10.1007%2Fs00224-013-9500-1 |
| MIT | Efficient and Practical Resource Block Allocation for LTE-Based D2D Network via Graph Coloring | http://link.springer.com/article/10.1007%2Fs11276-013-0626-5#page-1 |
| MIT | Streaming Algorithms for Estimating the Matching Size in Planar Graphs and Beyond | Еще не опубликовано |
| MIT | Parameterized Streaming: Maximal Matching and Vertex Cover | Еще не опубликовано |
| MIT | Network Cournot Competition | Еще не опубликовано |
| MIT | Randomized Revenue Monotone Mechanisms for Online Advertising | Еще не опубликовано |
| MIT | A Tight Algorithm for Strongly Connected Steiner Subgraph on Two Terminals with Demands | Еще не опубликовано |
| UCSD, NEU | Popularity Versus Similarity in Growing Networks | http://arxiv.org/pdf/1106.0286.pdf |
| UCSD, NEU | Network Cosmology | http://dx.doi.org/10.1038/srep00793 |
| UCSD, NEU | Duality Between Equilibrium and Growing Networks | http://dx.doi.org/10.1103/PhysRevE.88.022808 |
| UCSD, NEU | Entropy Distribution and Condensation in Random Networks with a Given Degree Distribution | http://dx.doi.org/10.1103/PhysRevE.89.062807 |
| UCSD, NEU | Network Mapping by Replaying Hyperbolic Growth | http://dx.doi.org/10.1109/TNET.2013.2294052 |
| UCSD, NEU | Cosmological Networks | http://arxiv.org/abs/1310.6272 |
| UCSD, NEU | Hyperbolic Graph Generator | http://named-data.github.io/Hyperbolic-Graph-Generator/ |
| UCSD, NEU | Analyzing Social Divisions Using Cell Phone Data | Еще не опубликовано |
| UC - Santa Barbara | On the Bursty Evolution of Online Social Networks | http://dl.acm.org/citation.cfm?id=2392623 |
| UC - Santa Barbara | Beyond Social Graphs: User Interactions in Online Social Networks and their Implications | http://dl.acm.org/citation.cfm?id=2382620 |
| Hewlett-Packard Labs | Using R for Iterative and Incremental Processing | https://www.usenix.org/conference/hotcloud12/workshop-program/presentation/venkataraman |
| UC - Santa Barbara | Multi-scale Dynamics in a Massive Online Social Network | http://dl.acm.org/citation.cfm?id=2398795 |
| UC - Santa Barbara | Social Turing Tests: Crowdsourcing Sybil Detection | http://arxiv.org/pdf/1205.3856v2 |
| UC - Santa Barbara | Understanding Latent Interactions in Online Social Networks | http://dl.acm.org/citation.cfm?id=2517040 |
| Hewlett-Packard Labs | Presto: Distributed Machine Learning and Graph Processing with Sparse Matrices | http://dl.acm.org/citation.cfm?id=2465371 |
| UC - Santa Barbara | Wisdom in the Social Crowd: an Analysis of Quora | http://dl.acm.org/citation.cfm?id=2488506 |
| UC - Santa Barbara | Practical Conflict Graphs for Dynamic Spectrum Distribution | http://dl.acm.org/citation.cfm?id=2465545 |
| UC - Santa Barbara | You are How You Click: Clickstream Analysis for Sybil Detection | https://www.usenix.org/conference/usenixsecurity13/technical-sessions/presentation/wang |
| UC - Santa Barbara | Follow the Green: Growth and Dynamics in Twitter Follower Markets | http://conferences.sigcomm.org/imc/2013/papers/imc018-stringhiniA.pdf |
| UC - Santa Barbara | Inferring User Interests from Tweet Times | http://dl.acm.org/citation.cfm?id=2512960 |
| UC - Santa Barbara | On the Validity of Geosocial Mobility Traces | http://dl.acm.org/citation.cfm?id=2535786 |


RUSH HOUR
*** (out of 4) - a good movie
Release Date: September 18, 1998 Starring: Jackie Chan, Chris Tucker, Tom Wilkinson, Elizabeth Pena, Tzi Ma, Julia Hsu Directed by: Brett Ratner Distributed by: New Line Cinema MPAA Rating: PG-13 (sequences of action/violence and shootings, language) URL: http://www.execpc.com/~kinnopio/reviews/1998/rushhour.htm
It's no secret in the motion picture industry that the relationship between a script and the actors involved often makes or breaks a movie at the box office. A poorly-written script can be bested by a superb acting corps, and a well-written piece can be mangled by a group of amateurs. In directing his latest action-comedy, Director Brett Ratner (MONEY TALKS) takes a relatively mediocre piece of standup comedy and turns it into a funny as all get-out buddy cop movie. In addition, RUSH HOUR serves as a first-class example of directing a movie with conservative attitude - a feature that is sure to draw in crowds of all types.
The two lead names share equal screen time here, mostly because they spend it together. Jackie Chan, in his first completely American production, makes an impressive debut by mixing dialogue with martial arts. The other martial arts flick from a few weeks ago, KNOCK OFF, stands no chance against the content of this one. Chan manages to make every fight scene exude grace and poise, and there's no doubt that a large percentage of video sales for this movie will come from viewers who couldn't believe their eyes the first time. Chris Tucker, on the opposite side, relates a hilarious comedic approach which smoothes out the rough edges to Chan's performance. He works perfectly with the script, and it's quite likely he lent scribe Jim Kouf a hand with some of his lines.
Almost essential to the action genre, the plot is nonexistent. We're quickly introduced to Detective James Carter (Tucker) is a maverick officer for the LAPD. Cut forward to another scene where the daughter (Julia Hsu) of the American Chinese Consul (Tzi Ma) is kidnapped by a gang of swarthy characters. The FBI is quick to the rescue, but the consul insists that one of his men, Detective Inspector Lee (Chan), be brought on the case to help. The FBI resists, but then requests that LAPD send a man over to babysit the Chinese detective. It's here that Carter and Lee hook up, and the two unwittingly solve the case while the FBI rushes in to back them up.
Rattner does a fine job of going the extra mile to get his movie to move a step up, but it doesn't quite reach the top tier of action-comedies like last year's GROSSE POINTE BLANK. There are moments where the plot strays too far off the straight line it sticks almost exclusively to, and if not for the comedic interactions between Tucker and Chan, this might be a major drawback. Also, some supporting characters are almost entirely along for the ride, and others are there simply to look menacing. However, none gives a standoffish performance and they mostly mesh into the background. Almost every member of the cast displays some reservation at one point or another - whether it's Tucker's toned-down routine or Chan's tight rein on his action sequences - and that contributes greatly to this being a watchable movie for all types. A recommendable visit to the theater, indeed.
-- Craig Roush<EMAIL_ADDRESS>-- Kinnopio's Movie Reviews http://www.execpc.com/~kinnopio
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Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 4
Dietary
Follow this step-by-step recipe for how to make one of the French classics, béarnaise sauce.
Clarify the butter by melting it in a small, heavy-based saucepan over a low heat. When the butter is foaming, remove the pan from the heat and leave it to stand for a few minutes so that the white solids sink to the bottom of the pan. Sieve the butter through a fine sieve and discard the solids.
Pour the vinegar into a non-reactive saucepan. Add the shallots, chopped tarragon and salt, to taste. Heat gently over a medium heat until the volume of liquid has reduced by more than half. Strain and set aside until completely cooled.
Lightly beat egg yolks with one teaspoon of water. Stir the egg yolk mixture into the cooled vinegar, then add the lemon juice.
Pour the mixture into a bowl suspended over a pan of simmering water (do not allow base of the bowl to touch the water). Whisk constantly until the sauce has thickened enough to coat the back of a spoon and has increased in volume.
Remove the bowl from the heat and slowly pour in the clarified butter in a steady stream, whisking continuously, until the mixture is thick and smooth. Fold in the tarragon leaves and season, to taste, with salt and freshly ground black pepper.


CSS is awesome because it allows you to build nice looking websites.
If you don't know how to use it, your website will look bad.


Sample Results
DataHunter_Result Run #370
In a Jenkins CI environment this would be a Jenkins Job Result page ....
Using the Jenkins HTML Plugin, you would be able to generate links to the generated JMeter reports from the Jenkins Job Results Page


Your theme.info file should look like this:
name = THEMENAME
description = ...
core = 7.x
engine = phptemplate
regions[...] = ...
; stylesheets[all][] = css/style.css ; IMPORTANT: DO NOT add your theme's CSS file here!
stylesheets[all][] = libs/font-awesome/css/font-awesome.css
scripts[] = libs/blue/js/blue.js
features[] = ...
Then, add this to your template.php:
<?php
function THEMENAME_preprocess_html(&$variables) {
drupal_add_css(path_to_theme().'/css/style.css', array('preprocess' => false));
$element = array(
'#tag' => 'meta',
'#attributes' => array(
'name' => 'viewport',
'content' => 'width=device-width, minimum-scale=1.0, maximum-scale=1.0'
)
);
drupal_add_html_head($element, 'template_viewport');
}
?>
This makes sure that the CSS file can be found by blue.frontend’s CSS and enables correct rendering on mobile devices.
For now, it is important to enable CSS compression in Drupal’s cache settings. Otherwise, the JavaScript-Bridge would not work!
Since Drupal 8 is not finished yet, this instruction may not work in the future.
Add this to your theme’s THEMENAME.libraries.yml:
blue:
version: 1.x
js:
libs/blue/js/blue.js: {}
dependencies:
- core/jquery
Your theme’s THEMENAME.info.yml should look like tihs:
name: THEMENAME
type: theme
description: '...'
core: 8.x
stylesheets:
all:
- css/style.css
- libs/font-awesome/css/font-awesome.css
libraries:
- THEMENAME/blue
regions:
#...
stylesheets-remove:
- system.theme.css # optional
For now, it is important to disable CSS compression in Drupal’s cache settings. Otherwise, the JavaScript-Bridge would not work!


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The Internet at 50: ‘We Didn’t See the Dark Side Emerging’
by Jill CowanGood morning.
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On Oct. 29, 1969, in a windowless room at U.C.L.A. a message was sent to the Stanford Research Center from a very large machine.
It was supposed to be “login,” but only the first two letters transmitted. So, the message was, simply, “lo.”
“We had no idea — we had nothing ready, because all we wanted to do was to log in,” Leonard Kleinrock, one of the men who sent that message, told me last week. “But we couldn’t have asked for a more succinct, more prophetic, more powerful message than, ‘lo.’”
As in, “Lo and behold.”
The message was the first ever sent between two computers. It was transmitted on a network called Arpanet. And from it, the internet was eventually grown. Of course, that’s a vast oversimplification of the momentous technological feat that this was.
[From The Times’s archives, here’s an interview with Mr. Kleinrock in 1999 .]
On the day that I met Mr. Kleinrock in that same windowless room — which has been largely preserved as a kind of mini-museum documenting the birth of the internet — lawmakers in Washington were grilling Mark Zuckerberg about Facebook allowing hate speech and disinformation to flourish on its platform, which reaches billions of people. Mr. Zuckerberg, Facebook’s chief executive, was there to defend his company’s project developing a kind of digital money.
Mr. Kleinrock, 85, said he first got interested in electrical engineering when, as a child in New York City, he made himself a crystal radio.
When U.C.L.A. offered him a job teaching engineering, he left his position as a researcher at the Massachusetts Institute of Technology to move out west.
Moving around the room and gesturing to decades-old equipment or diagrams hung on the walls, Mr. Kleinrock was clearly practiced at explaining packet switching and queuing theory. After more than five decades, he’s a comfortable, genial lecturer, even in one-on-one conversation.
But the story of how that message ended up being sent has been told by people who understand computers better than I do. What I wanted to know was how he now sees the world he helped create.
What, if anything, would he change about the way the internet has evolved? Did he have any regrets?
Mr. Kleinrock said his feelings were complicated.
He noted that in a news release issued by U.C.L.A. announcing Arpanet’s deployment, he is quoted as accurately predicting that “we will probably see the spread of ‘computer utilities,’ which, like present electric and telephone utilities, will service individual homes and offices.”
He said he thinks the network will become even more invisible than it is now, which seems likely.
But what he and his researcher colleagues missed, Mr. Kleinrock said, was the social side of the network. And he missed the ways in which that capability would, he wrote in an email later, “impact every aspect of our society.”
A few years ago, as hacking and spam and other undesirable uses of the internet proliferated, he said he often told people that the internet was in its disobedient teenage years, that it would grow out of its immature period.
That hasn’t happened.
“What’s happened is, it’s now more mature and what’s going on?” he said. “We have nation states putting boundaries around their national networks. We have organized crime, pilfering, money laundering and we have extremists shouting things on a network.”
And if everyone’s talking at an equal level, he said, it’s natural that extreme ideas would command the most audience.
Mr. Kleinrock said he blames two things. One, he said he and the internet’s early builders could have headed off if they’d anticipated the need for it: Strong user authentication, as well as strong file verification.
That wasn’t something researchers built in because at the time, he said, they were trying to encourage wider adoption of the network so they could continue their research — not build barriers.
The second, in retrospect, may have been more inevitable: the commercialization of the internet.
He said that in 1994, the first piece of spam reached the network: A pair of lawyers sent a message offering their services in winning a green card lottery.
“They were advertising their services on our research network — how dare they?” Mr. Kleinrock recalled. “So we sent the email back to them and said, ‘Stop, shame on you.’”
But it was too late. Mr. Kleinrock likened it to a kind of fall from grace.
[From 2005: An early look at a research project to re-engineer the internet.]
“We didn’t see the dark side emerging because of our culture, which was a bunch of good people working together,” he said. “We didn’t imagine we would reach a point where there would be a profit motive — we didn’t take out any patents, we didn’t try to own the I.P.
“This was an engineering challenge.”
Still, he said, not everything is bad.
He still marvels at the fact that, at one point, his 99-year-old grandmother and his granddaughter could be on the internet at the same time. And they’d be able to use it to talk to each other.
And he said that, at least in terms of privacy and security, it’s possible to make the internet better.
“The citizenry has to get involved, the government has a role,” Mr. Kleinrock said. “And the scientists have a role.”
Here’s what else we’re following
We often link to sites that limit access for nonsubscribers. We appreciate your reading Times coverage, but we also encourage you to support local news if you can.
- Extreme wildfires, which increasingly burn man-made material, are creating new health risks for firefighters. [The New York Times]
- To mitigate the risk of wildfires, why don’t we do these things? Here’s why. [CalMatters]
- Attorney General Xavier Becerra, unlike nearly all other state attorneys general, won’t say whether he’s investigating Google and Facebook. What is he up to? [The New York Times]
Also: Here’s more about the power of California’s attorney general. [ The New York Times ]
- Representative Katie Hill gave a farewell speech to Congress. She denounced “gutter politics.” [The New York Times]
In case you missed it on the internet
- A haunted schoolhouse in Modesto, ghosts in Merced, a supernatural being called the “Fresno Nightcrawler” that looks like a walking pair of white pants — if you missed it, here’s a Twitter thread of some creepy stories from around California for Halloween. [The Sacramento Bee]
- Gov. Gavin Newsom dressed up with his family as a portion of the Democratic presidential field for Halloween. He was Joe Biden and Jennifer Siebel Newsom was Elizabeth Warren. (Sound on.) [Gavin Newsom]
- What’s this “OK boomer” thing you’ve been hearing so much about? Read the story that started it all. [The New York Times]
California Today goes live at 6:30 a.m. Pacific time weekdays. Tell us what you want to see<EMAIL_ADDRESS>. Were you forwarded this email? Sign up for California Today here.
Jill Cowan grew up in Orange County, graduated from U.C. Berkeley and has reported all over the state, including the Bay Area, Bakersfield and Los Angeles — but she always wants to see more. Follow along here or on Twitter, @jillcowan .
California Today is edited by Julie Bloom, who grew up in Los Angeles and graduated from U.C. Berkeley.


A straight-forward demo of a Pie chart with tooltips. Remember that by
default the SVG highlights for tooltips are set with the
pointer-events
CSS property set to none
.
   Put this where you want the chart to show up:

This is the code that generates the chart - it should be placed AFTER the

tag:


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Abstraction -- a process of exposing essential features of a class/object. It hides details or functions that should be kept private. Encapsulation -- the process of putting properties and methods into a single container called class. It insulates data and hides implementation. Inheritance-- creating new class from the existing one. The new class may have some additional properties and functionality.Polymorphism -- refers to the ability to take multiple forms. Can invoke derived class methods through a base class


Identity Binding Service[[ ${ title != null } ? ' - ' + ${ title } : '' ]]
Accounts
Log In
Log In
Log In
Account


§59. Method of voting for representatives. That each voter for representative may cast a vote for as many representatives as are to be elected from the representative district in which he is entitled to vote.
The required number of candidates receiving the highest number of votes in the respective representative districts shall be the representatives for such districts.


public interface SmartCache<K,V>
To iterate over the contents of a cache, you must pass a
execute(SmartCacheTask)
instance. The code using the iterator
can be assured that it will be thread safe.
Implementations are responsible of enforcing thread safety.
| Modifier and Type | Interface and Description |
|---|---|
static interface |
SmartCache.SmartCacheTask<K,V>
Defines a task to be run over the entries of the cache.
|
| Modifier and Type | Method and Description |
|---|---|
void |
clear()
Clears the contents of this cache.
|
void |
execute(SmartCache.SmartCacheTask<K,V> task)
Executes a task over the contents of the cache and guarantees
exclusive write access while processing.
|
V |
get(K key)
Looks up and returns a cache value according to a given key.
|
V |
put(K key,
V value)
Places a key/value pair into the cache.
|
V |
remove(K key)
Removes a key from the cache.
|
int |
size()
Returns the number of elements in cache.
|
V put(K key, V value)
key
- Keyvalue
- Valuekey
or nullV get(K key)
null
is returned.V remove(K key)
key
- Keyvoid clear()
int size()
void execute(SmartCache.SmartCacheTask<K,V> task)
task
- The task to execute.