SCUTTLE Mobile Robot
SCUTTLE was designed to support teaching within Multidisciplinary Engineering Technology (MXET) at Texas A&M. The bot is a payload-capable mobile platform that is made of readily-available off-the-shelf parts and 3D printed designs. SCUTTLE is the main platform currently used for in-lab lessons and semester project for MXET 300, Mobile Robotics undergraduate course.
Figure 1. SCUTTLE Mobile Robot Rendering
A few highlights of this open-source mobile platform
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Figure 2. Github Repository |
Figure 3. Beaglebone Embedded Linux |
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Figure 4. Full Open-Source CAD Assembly |
Figure 5. Machine Vision Software |
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Figure 6. Gamepad Driving Integration |
Figure 7. 3D Printable Design |
SCUTTLE is designed to create access for students, researchers, and tinkerers to an affordable mobile robot that can carry a payload. This platform supports the load of additonal actuators, materials handling, extra battery packs, displays, or other gadgets to suit new projects. We searched high and low and found no robot under one thousand USD that can carry over 20 pounds. So, we created SCUTTLE within the Mechatronics Engineering Technology major at Texas A&M. The acronym tells what we aim to accomplish.
Affordability is an important target and this bot can be built from under $350 in parts. After exploring the designs availble (from DIY all the way to turnkey solutions) we found there was a need for this kind of robot.
The Bill of Materials (BOM) for this project is offered with suppliers and price so new teams can reproduce the project .
Kinematic parameters are predefined for classroom instruction and to give students a frame of reference for sampling sensors, calculating motion and creating autonomous navigation software. This guide explains the kinematics for SCUTTLE.
Our choices of coordinate frames, system variables, and driving strategy closely follow a research article published in Advances in Robotics & Automation on the subject of Dynamic Modeling of Differential-Drive Mobile Robots.
The two main frames for defining the robot position are the body fixed frame and the global coordinate frame. For most applications, SCUTTLE boots up with all coordinates at zero, and the body-fixed coordinates move while the global frame remains fixed.
Figure 8. Kinematic Frames
Phi Left and Phi right are configured such that positive increment on these will generate a positive movement in the body-fixed x-direction. The x vector on the body fixed frame is separated from the global frame by angle theta.
The geometry shown here defines the kinematic functions in the SCUTTLE software. Since the robot is modular, the chassis may be modified and the speed controller will be updated just by changing a few key parameters in the Kinematics program.
Figure 9. Robot Geometry
R and L are the main variables that need to be defined in order to calculate motion, indicating the wheel radius and half of the wheelbase. The default values are shown here.
The twin driven-wheeled platform was chosen for economy and robustness, but because we control three system variables (x, y, and theta) with only two actuators, the user must strategically move the actuators to achieve a given state. A holonomic robot has the same number (or more) of controllable degrees of freedom as the number of degrees of freedom, which is not our case.
SCUTTLE DOF: (x, y, theta)
SCUTTLE Controllable DOF: (left motor, right motor)
Mecanum Robot DOF: (x, y, theta)
Therefore, the configuration of the robot depends on the path taken to achieve the movement.
Figure 10. Comparison of Holonomic & Non-Holonomic Designs
Figure 9 Compares some qualities of holonomic and non-holonomic designs. In the case of a mecanum robot, there are four motors required and the user can directly make a command for a movement in x, y, or theta (provided that the software was written for it). The SCUTTLE robot has only two controlled degrees of freedom (phi dot left and right). Only two motors are required and the user cannot directly request a movement in the y-direction, for example.
Figure 11. Example of Non-Holonomic Movement
Figure 12. Controller Driving Configuration
In the provided demo program, the EasySMX USB wireless controller sends commands to the robot. The left-hand joystick outputs the motor-controlling axes, which correspond to an x_dot request and a theta_dot request as shown in Figure 11. With this configuration, each axis actually effects both wheels. When an autonomous driving program is implemented, the navigation software replaces the human driver to generate x_dot and theta_dot requests.
How-To Videos:
The videos support fabrication, electronics setup, robot assembly, programming, and robot operation. They are designed to help students build and operate the mobile robot within one semester.
View the SCUTTLE youtube playlist to see all SCUTTLE videos.
The SCUTTLE robot software has been programmed in Python3 on an embedded Linux platform. Both Beaglebone Blue and Raspberry Pi have been tested successfully. The software has been architected to make a robust starting point for students to create their own autonomous missions. These slides detail the software architecture.
Figure 13. Software Architecture
The blocks in yellow are sensors, and the items in orange are actuators or other outputs. The level-2 blocks in teal are specific to the hardware platform (beagle, pi, etc) and perform communication with the low level devices. The blocks above level 2 are non-hardware specific.
Each block aside from sensors and actuators represent an individual python program. The purple text indicates what important information is passed between programs and the black arrows indicate (for the most part) what direction the data is flowing. If a level 3 program needs information from another, it must receive the information from the top-level program, in order to maintain the structure of independence in program functions.
This software structure is preferred in order to perform subsystem testing. The data flowing through the top level is minimal and can be replaced with artificial data in the even that a sensor is unavailable.
Python importing guidelines:
1. Each file should import the files below it in hierarchy, and not the files above it.
2. Each file should not import files more than 1 level below itself.
3. Each file may import non-scuttle libraries as needed (import numpy, import time, etc)
BeagleBone Blue Integration:
· RCPY for communicating with MPU9250 & commanding motor drivers
· Adafruit GPIO for I2C Communication
· BMP280 for communicating with the onboard bmp280 sensor.
Raspberry Pi integration:
· pysicktim for accessing LIDAR data
· gpiozero for controlling GPIO pins.
Common Libraries
· os for making shell commands via python code.
· time for keeping track of time
· threading for peforming multithreading
· numpy for performing math operations
· pygame for accessing gamepad controller data
· cayenne.client for sending MQTT messages
· smbus for accessing i2c bus through python commands
This section gives background on standard hardware components, their configuration, and links to datasheets.
The latest Wiring Diagram PDF is hosted on the SCUTTLE github. This document shows how each sensor/actuator is connected on the robot.
The beaglebone Blue has been fully integrated in the SCUTTLE robot. Figure 13 shows the ports on the board.
Figure 14. Beaglebone Bubble Diagram
More information on the Beaglebone Blue exists in the following resources:
· Beaglebone Blue Wiki
· Beaglebone Blue Specification Sheet
· Beaglebone Blue Schematic
A number of motor driver options are available. The standard choice is HW-231 motor driver which uses the NXP MC3386 H-Bridge. The ground is connected directly to the battery pack and it accepts two input pin pairs as PWM channels.
Figure 15. Motor Driver
Resources for the motor driver are here:
· MC3386 Datasheet
The ultrasonic sensor is an optional item to support autonomous driving and obstacle avoidance. There are versions of this board which require 5v (more common) or only 3.3v (less common). If your board requires 5.0v then power will need to be drawn directly from the power port on the beaglebone.
Figure 16. Ultrasonic Sensor HC-SR04
Resources for the HC-SR04 are here:
· HC-SR04 Datasheet
Two AMS AS5048B encoders are required for the robot, with one at each motor pulley. Some details about the encoders:
· They are actually angular position sensors. They return a degrees value from 0 to 360.
· This sensor communicates over I2C. The left-hand encoder is addressed as 0x40 and the Right-hand encoder is addressed as 0x41, with the pullup wire connected to the A1 contact.
· They measure the rotation of the motor pulley, and the software must adjust for 1:2 wheel:motor turn ratio
There is one standardized encoder bracket used for right and left, but different mounting holes are used as shown in Figure 20. The proper mounting holes make the sensor centered over the magnet which mounts to the end of the motor output shaft.
Figure 17. Left and Right Encoder Brackets
Resources for the encoder are here:
· AMS AS5048B Datasheet
The battery pack is a 3-cell lithium ion pack with a nominal voltage of 11.1v (3.7v per cell) combined with a few off-the-shelf parts and a 3D printed case. The capacity is 3400 mAh (we verified!) And they have enough capacity to drive SCUTTLE for several hours. With additional actuators, a significant payload, or demanding sensors such as the SICK LIDAR, it is advised to add more capacity to the robot. The cells must not be drained below 2.8 volts each to prevent damage.
Figure 18. Battery Pack with Cover Removed
Resources for the battery pack are here:
· Panasonic NCR18650B datasheet
· Battery Cell handling and protection youtube video
· Battery Cell supplemental info sheet shows more on assembly.
The integrated USB camera is a Microsoft LifeCam HD-3000. On the robot, we remove the cameras mounting bracket and insert the camer into a 3D printed bracket.
Resources for the HD-3000 Camera are found here:
· LifeCam HD-3000 datasheet
· Camera Supplemental Info sheet shows how to remove the flexible grip and infrared filter
Scuttle has two motors for driving the rear wheels. Each is a DC 12v motor (shown in Figure 31) with a gearbox that reduces the output speed to 200 RPM. The shaft is offset by 7mm from the centerline of the motor, which helps raise the clearance of the motor housing from the ground in the robot chassis. Three M3x10 screws fasten the motor to the motor plate.
Figure 19. Driving Motors, 12v DC with gearbox
The motor leads must be soldered to wires of 18 AWG or larger. The other ends of those wires connect to an Anderson Powerpole connector with a 15 amp crimp connector, or heavier. The powerpole connectors shown in Figure 32 are used throughout the robot to isolate the battery pack, beaglebone, motors, and motor driver.
SCUTTLE has been enhanced with a lidar manufactured by SICK sensor company. This lidar performs laser-based ranging in 270 degree plane at 0.33 degree resolution, 15 times per second! The USB interface is used to communicate to the microprocessor and the power is directly provided by the 11.1v battery pack.
Figure 20. Sick TiM561 LIDAR unit.
Resources for the LIDAR unit are here:
· Pysicktim python library on github
· Operating instructions from SICK
· Technical information from SICK
Thank you to these groups for their support
The Mobile Integrated Solutions Laboratory at Texas A&M is an applied research team within the Engineering Technology department, and has collaborated in development and testing of the robot.
SICK USA has become a partner of the ETID department and has provided LIDAR units for the MXET Lab which are being integrated into the mobile robots.
Beagle has offered design feedback and support on integrating their education-oriented robotics hardware, the beaglebone Blue.
TI has held a longstanding partnership with the ETID at Texas A&M and supplied electronics hardware equipped with TI microcontrollers.
SCUTTLE, Robot, mechatronics, Beaglebone, beaglebone blue, raspberry pi, arduino, Texas A&M, ETID, Engineering Technology, Computer Vision, Automation, Multidisciplinary Engineering, Anderson Powerpole, powerwerx, vision tracking, autonomous navigation, OpenCV, Ultrasonic, Payload, low cost robot, DIY, IOT, TAMU, sensing connected utility transport taxi for lab environments, Industrial IOT, Python, hackster.io, thingiverse, grabCAD, open source, github, industrial robotics, educational robot, research, mechanical engineering, electronics, electrical engineering, roomba, mobile robotics, autonomous vehicle, dynamics


--- layout: beer title: De Rode Katje style: Belgian Dubbel beer: true ---
| Amt | Name | Type | # | %/IBU |
|---|---|---|---|---|
| 4 lbs | Pale Malt | Grain | 1 | |
| 4 lbs | Vienna | Grain | 2 | |
| 4 lbs | Dark Munich (10L) | Grain | 3 | |
| 1 lb | Crystal 40 | Grain | 4 | |
| 8.0 oz | Special B Malt (180.0 SRM) | Grain | 5 | |
| 8.0 oz | Aromatic | Grain | 6 | |
| 8.0 oz | Cara Munich | Grain | 7 | |
| 1.0 oz | Aged Hops (homemade) | Hops | 8 | |
| 1.0 pkg | US-05 Ale | Yeast | 9 | - |
Simple one-stage mash targetting 68.9°C for 60 minutes, sparging with 78°C to get to the desired boil volume.
Created with BeerSmith
This is the recipe cycling in and out of my 5-gallon barrel on a Solera program. This is the September, 2016 recipe, to be exact.
The recipe has "evolved" a little. It originally had a lot of pilsner malt in it, but that malt leads to a big load of diacetyl in the final, aged product, so I've switched to pale. The original was also fairly light in color, and the dark munich has brought it around to the dark, reddish brown I expect from the style.
The barrel initially got a Roselare pitch, and the second batch came with a Brett pitch (records are hazy as to which strain). That has been evolving ever since. Each new batch gets about a week in the primary with US-05, then mixed into the barrel for its secondary.


The page you requested doesn't exist yet. Since it's a wiki, what about writing yourself an introductory article? :)
Edit this page and tell us a little about $slug


{% import "_includes/forms" as forms %}
{% set config = {
id: name,
name: name,
value: value
} %}
{% set colorConfig = {
id: name ~ '-color',
name: name ~ '-color',
value: value
} %}
{{ forms.color(colorConfig) }}
{{ forms.hidden(config) }}
{% includeJsResource 'defaultcolor/js/DefaultColorInput.js' %}
{#
Here is where it all happens. We have a color picker in the usual way, and a button.
When the button is clicked, we use js to find the input field holding the value, and
change it to the default color value. The dom that we are modifying is different
depending on whether we are using a native color picker (chrome e.g.), or the javascript
one (firefox e.g.). In either case, there is an outer color field, containing an
elem with our data. In the case of the js color picker, there is also a .colorpreview
element.
You might think it would be simpler to use a prepValueFromPost() function to set the
value to the default on the backend. I thought so too, but I couldn't get values other
than the color value (I wanted a checkbox value) in that function. So doing it on the front
end.
#}


"""
This module Extracts features (player, enemy, bombs) from the main game loop
and stores the data as a two-demensional list
Project : Bomberman Bot with Machine Learning
Olin College Software Design Final Orject, Spring 2017
By : TEAM AFK
"""
import config as c
[docs]class grid:
"""
Tile Code:
0 = VALID SPACE, 1 = WALL, 2 = BRICK, 3 = SECRET BRICK, 4 = SECRET BRICK
7 = ENIMIES, 8 = PLAYERS, 9 = BOMBS
"""
def __init__(self, game):
"""
Initlizes the attributes that represent the grid status
from the current game instance
"""
self.g = game
self.field = game.field
self.players = game.players
self.bombs = game.bombs
self.enemies = game.enemies
@property
def matrix(self):
"""
A 2-d list(matrix) of players, enemies, and bombs on the grid
"""
mat = []
for row in self.field.board:
mat_row = []
for tile in row:
mat_row.append(tile.type)
mat.append(mat_row)
self.add_players(mat)
self.add_enemies(mat)
self.add_bombs(mat)
return mat
[docs] def add_bombs(self, target_matrix):
"""
Adds bombs(represented as 9) to the target_matrix
"""
# bomb.position (x,y) / config.TILE_SIZE
# update (x,y) with 9
for bomb in self.bombs:
x = int(bomb.position[0] / c.Config.TILE_SIZE)
y = int(bomb.position[1] / c.Config.TILE_SIZE)
target_matrix[y][x] = 9
[docs] def add_players(self, target_matrix):
"""
Adds players(represented as 8) to the target_matrix
"""
for player in self.players:
x = int(player.position[0] / c.Config.TILE_SIZE)
y = int(player.position[1] / c.Config.TILE_SIZE)
target_matrix[y][x] = 8
[docs] def add_enemies(self, target_matrix):
"""
Adds enimies(represented as 7) to the target_matrix
"""
for enemy in self.enemies:
x = int(enemy.position[0] / c.Config.TILE_SIZE)
y = int(enemy.position[1] / c.Config.TILE_SIZE)
target_matrix[y][x] = 7


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The following contains a gallery view of the bestseller books from the site of Book Depository in late October. You can pick the one with an attractive cover!


{% extends 'catalog/catalog.html' %} {% block breadcrumbs %} Home {% endblock breadcrumbs %} {% block content %}
Give: Share you favorite DVD or Book with someone on the internet.
Receive: When you buy a gift for someone we will send you a gift right away.
Connect: If you like the gift you recive we can connect you with the sender.
Welcome to Gift for Gift, a new platform for sharing the Movies, Music and Books you enjoy most with the world. In return we send you a Movie, Book or CD that someone else is excited to share.
Our Missions is to provide new ways to connect with people and contribute to the growing gift economy.
We have not launched yet. However, feel free to browse our site and email us any scathing critiques, angry tirades or exciting business opportunities from Nigerian Princes. If you want to learn about our launch before all your friends and get major hipster cred for knowing about us "before we where popular" then be sure to sign up for our mailing list on the right. We promise not to spam you and only send out emails when we have exiting new features to announce.


State Exchange
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"""
.. module:: base
:synopsis: Base classes and functions.
"""
from six.moves import map
[docs]class Nut(object):
"""
Base class for all Nuts. Iterables or functions wrapped in Nuts can be
chained using the '>>' operator. The aim is code with an explicit
data flow. See the following example using Python iterators versus Nuts:
>>> from six.moves import filter, range
>>> from itertools import islice
>>> list(islice(filter(lambda x: x > 5, range(10)), 3))
[6, 7, 8]
>>> from nutsflow import Range, Filter, Take, Collect, _
>>> Range(10) >> Filter(_ > 5) >> Take(3) >> Collect()
[6, 7, 8]
"""
[docs] def __init__(self, *args, **kwargs):
"""
Constructor. Nuts (and derived classes) can have arbitrary arguments.
:param args args: Positional arguments.
:param kwargs kwargs: Keyword arguments.
"""
self.args = args
self.kwargs = kwargs
[docs] def __call__(self, iterable):
"""
Nut (processor) can be called as a function and mapped on
iterable elements within an iterable.
:param iterable iterable: Iterable to process.
:return: Iterable
:rtype: iterable
"""
return self.__rrshift__(iterable)
[docs] def __rrshift__(self, iterable):
"""
Chaining operator for Nuts. Needs to be overridden!
Takes an input iterable and produces some output iterable.
If the number of elements in the input and the output iterable
does not change consider NutFunction instead.
:param iterable iterable: Iterable to process.
:return: Iterable
:rtype: iterable
:raise: NotImplementedError if not implemented.
"""
raise NotImplementedError(
'Needs to implement __rrshift__ : ' + str(self.__class__.__name__))
[docs]class NutFunction(Nut):
"""
Nut functions are are mapped onto each element of the input iterable.
Example: Square is a Nut function
>>> from nutsflow import Square, Collect, _
>>> [1,2,3] >> Square() >> Collect()
[1, 4, 9]
"""
[docs] def __call__(self, element):
"""
Override this method to transform the elements of an iterable.
:param element: Element the function is applied to.
:return: A transformed element
:rtype: any
:raise: NotImplementedError if not implemented.
"""
raise NotImplementedError(
'Needs to implement __call__() : ' + str(self.__class__.__name__))
[docs] def __rrshift__(self, iterable):
"""
Map function onto iterable and return transformed iterable.
Do not override!
:param iterable: function is applied to the elements of the iterable.
:return: transformed iterable.
:rtype: iterable
"""
return map(self, iterable)
[docs]class NutSource(Nut):
"""
Sources are nuts that have no input iterable but produce an output
iterable.
"""
[docs] def __rrshift__(self, iterable):
"""
Raises an exception when called. Sources have not input!
Do not override! Override __iter__() instead.
:param iterable iterable: Iterable
:raise: SyntaxError if called.
"""
raise SyntaxError(
"Sources don't have inputs: " + str(self.__class__.__name__))
def __iter__(self):
"""
Return iterator over some data. Needs to be overridden!
:return: Iterator for source data.
:rtype: iterator
:raise: NotImplementedError if not implemented.
"""
raise NotImplementedError(
'Needs to implement __iter__() :' + str(self.__class__.__name__))
[docs]class NutSink(Nut):
"""
Sinks are nuts that typically consume the entire input stream.
Sinks are typically at the end of a flow and aggregate the flow
to a single output, e.g. the sum of its elements.
Need to override __rrshift__()!
"""
def __iter__(self):
"""
Raises an exception when called. Sinks should not serve as sources.
:raise: SyntaxError if called.
"""
raise SyntaxError(
'Sinks cannot be inputs: ' + str(self.__class__.__name__))
[docs] def __call__(self, iterable):
"""
Sinks can serve as functions applied to iterables within a flow.
:param iterable: Sink takes iterable as input
:return: Output of sink
:rtype: any
"""
return iter(iterable) >> self


---
layout: post
title: Groovy Google Maps
date: '2009-02-17T18:36:00.003-05:00'
author: Pat Hyatt
description: Google Maps error takes me to the 70s
tags:
- google maps error
modified_time: '2010-01-12T09:31:51.675-05:00'
blogger_id: tag:blogger.com,1999:blog-1130780247100205939.post-2687160575370133641
blogger_orig_url: http://patpack.blogspot.com/2009/02/groovy-google-maps.html
---
I was attempting to use Google's Street View today to see if a local gas station had a standard beater brush Car wash, cheesy I know but who wants to drive around only to be disappointed. "Driving" around with the product I enter the groovy zone. Take a peak...
Groovy


IN LOVE AND WAR A film review by Scott Renshaw Copyright 1997 Scott Renshaw
(New Line) Starring: Sandra Bullock, Chris O'Donnell, Mackenzie Astin, Emilio Bonucci. Screenplay: Allan Scott & Clancy Sigal and Anna Hamilton Phelan, based on "Hemingway in Love and War" by Henry S. Villard and James Nagel. Producers: Dmitri Villard, Richard Attenborough. Director: Richard Attenborough. MPAA Rating: PG-13 (violence, adult situations) Running Time: 110 minutes. Reviewed by Scott Renshaw.
IN LOVE AND WAR, a thoroughly mediocre attempt at an intimate epic, suffers the added disadvantage of extraordinarily bad timing. There has already been a better film in the last couple of months about a tragic war-time romance involving a wounded man and his care-taker (THE ENGLISH PATIENT); there has already been a better film in the last couple of weeks about the ill-fated real-life true love of a suicidal author (THE WHOLE WIDE WORLD). That is not to say that IN LOVE AND WAR would have been a better film if it had been released a year ago. It does mean, however, that the points of comparison between this film and its two predecessors make its weaknesses all the more evident.
The setting is 1918 Italy, where morale is low in the wake of a German/Austrian onslaught in the final months of World War I but American troops are unable to assist due to commitment in France. Instead, the U.S. sends assistance to hospitals in the form of Red Cross nurses, among them 26-year-old Agnes von Kurowsky (Sandra Bullock). One of Agnes' patients is a gung-ho teenager from Kansas City named Ernest Hemingway (Chris O'Donnell), eager to see action despite a vision impairment which has rendered him unfit for front line duty. His journalistic trip to the Italian trenches earns Ernie a severe leg wound, but he heals under Agnes' care. The cocky young Ernie falls for his nurse, and is convinced that she loves him too in spite of competition from an Italian doctor (Emilio Bonucci) and Ernie's own friend Harry Villard (Mackenzie Astin). Even when they seem to be coming together, Agnes and Ernie find the war separating them, leading to a difficult choice for Agnes.
The first image in IN LOVE AND WAR is a weathered hand-drawn map, but it might as well be a big neon sign announcing that director Richard Attenborough (GANDHI, CHAPLIN) is now about to bring you an Epic with a capital "E." And he never lets you forget it for a moment, either, trotting out spectacular locations, battlefield footage and a grandiose score by George Fenton. Unfortunately, the locations are shot flatly by Roger Pratt, a couple of the battlefield scenes are dropped in like sympathy-seeking mortars without a moment of set-up, and Fenton's score is as loud and relentless as any theater's sub-woofers could withstand. Attenborough seems so concerned with making IN LOVE AND WAR sweeping that he ends up sweeping his characters into the background.
Sweeping characters like this aside doesn't take a particular strong broom, as it turns out. After failing to provide the grandeur of THE ENGLISH PATIENT, IN LOVE AND WAR then can't muster the kind of convincing characterizations which at least made THE WHOLE WIDE WORLD watchable. Sandra Bullock is capable of making Agnes somewhat appealing, and of lending a modicum of plausibility to the script's portrayal of her as the most fought-over female creature since Helen of Troy. Bullock pulls out every All-American girl stop, and her kindly nurse could easily win over frightened patient and stoic doctor alike. As for Chris O'Donnell...well, don't you just want to pat him on the head and send him to bed with a glass of milk?  The age difference between Agnes and Ernie becomes the focus of the rift between them, but it plays out even ickier than writers Allan Scott, Clancy Sigal and Anna Hamilton Phelan intend. You half expect "Mrs. Robinson" to start playing on the soundtrack.
O'Donnell is even worse trying to play the disillusioned sot Hemingway becomes, when his raging outbursts seem more like petulant hissy fits, but by that point no one in the audience will care much about him anyway. As an indication of how inconsequential the central romance between Agnes and Ernie is, IN LOVE AND WAR actually gains momentum during the half an hour of screen time when the focus turns to Agnes' relationship with Dr. Caraciolo. The Venice locations create a glowing romantic setting, and Bonucci turns in a nice performance as the stiffly chivalric suitor. Agnes and Caraciolo seem perfect for each other, and Agnes' decision to turn him down makes sense only if we buy that the lusty Ernie, whose mere touch of her stocking reduces her to incoherence, is the passionate man of her dreams. O'Donnell's Ernie is about as lusty as cub reporter Jimmy Olsen, and IN LOVE AND WAR is reduced to its familiarity -- an epic drama with no drama, and a personal story with no personality.
On the Renshaw scale of 0 to 10 bores to end all bores: 4.
Visit Scott Renshaw's MoviePage http://www-leland.stanford.edu/~srenshaw Subscribe to receive reviews directly via email See details on the MoviePage
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


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PORT
ROYAL.
Altitude:
o*
5
ft#
Date:
January
2,
1961
Habitat:
Dry
open
gravel.
Notes:
Plants
tufted.
collector:
George
R*
Prootor
No.
21865
AN
I
A
ff
D
1659650
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


Class Imbalance Problem
**
What is the Class Imbalance Problem?
It is the problem in machine learning where the total number of a class of data (positive) is far less than the total number of another class of data (negative). This problem is extremely common in practice and can be observed in various disciplines including fraud detection, anomaly detection, medical diagnosis, oil spillage detection, facial recognition, etc.
Why is it a problem?
Most machine learning algorithms and works best when the number of instances of each classes are roughly equal. When the number of instances of one class far exceeds the other, problems arise. This is best illustrated below with an example.
Given a dataset of transaction data, we would like to find out which are fraudulent and which are genuine ones. Now, it is highly cost to the e-commerce company if a fraudulent transaction goes through as this impacts our customers trust in us, and costs us money. So we want to catch as many fraudulent transactions as possible.
If there is a dataset consisting of 10000 genuine and 10 fraudulent transactions, the classifier will tend to classify fraudulent transactions as genuine transactions. The reason can be easily explained by the numbers. Suppose the machine learning algorithm has two possibly outputs as follows:
- Model 1 classified 7 out of 10 fraudulent transactions as genuine transactions and 10 out of 10000 genuine transactions as fraudulent transactions.
- Model 2 classified 2 out of 10 fraudulent transactions as genuine transactions and 100 out of 10000 genuine transactions as fraudulent transactions.
If the classifier’s performance is determined by the number of mistakes, then clearly Model 1 is better as it makes only a total of 17 mistakes while Model 2 made 102 mistakes. However, as we want to minimize the number of fraudulent transactions happening, we should pick Model 2 instead which only made 2 mistakes classifying the fraudulent transactions. Of course, this could come at the expense of more genuine transactions being classified as fraudulent transactions, but will be a cost we can bear for now. Anyhow, a general machine learning algorithm will just pick Model 1 than Model 2, which is a problem. In practice, this means we will let a lot of fraudulent transactions go through although we could have stopped them by using Model 2. This translates to unhappy customers and money lost for the company.
How to tell the machine learning algorithm which is the better solution?
To tell the machine learning algorithm (or the researcher) that Model 2 is better than Model 1, we need to show that Model 2 above is better than Model 1 above. For that, we will need better metrics than just counting the number of mistakes made.
We introduce the concept of True Positive, True Negative, False Positive and False Negative:
- True Positive (TP) – An example that is positive and is classified correctly as positive
- True Negative (TN) – An example that is negative and is classified correctly as negative
- False Positive (FP) – An example that is negative but is classified wrongly as positive
- False Negative (FN) – An example that is positive but is classified wrongly as negative
Based on this above. We will have also the following of True Positive Rate, True Negative Rate, False Positive Rate, False Negative Rate:
With these new metrics, let’s compare it with the conventional metrics of counting the number of mistakes made with the example above. First, we will use the old metrics to calculate the number of mistakes made (error):
As illustrated above, Model 1 looks like it has lower error (0.1% error) than Model 2 (1.0% error) but we know that Model 2 is the better one, as it makes less false negatives (FN) (maximize true positive (TP)). Now let’s see what the performance of Model 1 and Model 2 are like with the new metrics:
Now, we can see that the false negative rate of Model 1 is at 70% while the false negative rate of Model 2 is just at 20%, which is clearly a better classifier. This is what we should educate the machine learning algorithm (or us) to use in order to allow it to pick a better algorithm.
How to mitigate this problem?
Now knowing what the Class Imbalance Problem is and why is it a problem, we need to know how to deal with this problem.
We can roughly classify the approaches into two major categories: sampling based approaches and cost function based approaches.
Cost function based approaches
The intuition behind cost function based approaches is that if we think one false negative is worse than one false positive, we will count that one false negative as, e.g., 100 false negatives instead. For example, if 1 false negative is as costly as 100 false positives, then the machine learning algorithm will try to make fewer false negatives compared to false positives (since it is cheaper). For example, in the case of SVM, the generic formula is:
where w is the normal vector to the hyperplane. and E[i] is the error of each data instance, C is a cost constant and n is the number of data instances. To assign a different cost function to false negative and false positive, we can modify the formula to as follows:
Where C+ is a cost constant for positive cases and C- is a cost constant for negative cases, n+ is the total number of positive cases and n- is the total number of negative cases. Without diving too deep into the formula above, this is just an example how one may assign different to cost to positive and negative classes.
Sampling based approaches
This can be roughly classified into three categories:
- Oversampling, by adding more of the minority class so it has more effect on the machine learning algorithm
- Undersampling, by removing some of the majority class so it has less effect on the machine learning algorithm
- Hybrid, a mix of oversampling and undersampling
However, these approaches have clear drawbacks, as explained below.
Undersampling
By undersampling, we could risk removing some of the majority class instances which is more representative, thus discarding useful information. This can be illustrated as follows:
Here the green line is the ideal decision boundary we would like to have, and blue is the actual result. On the left side is the result of just applying a general machine learning algorithm without using undersampling. On the right, we undersampled the negative class but removed some informative negative class, and caused the blue decision boundary to be slanted, causing some negative class to be classified as positive class wrongly.
Oversampling
By oversampling, just duplicating the minority classes could lead the classifier to overfitting to a few examples, which can be illustrated below:
On the left hand side is before oversampling, where as on the right hand side is oversampling has been applied. On the right side, The thick positive signs indicate there are multiple repeated copies of that data instance. The machine learning algorithm then sees these cases many times and thus designs to overfit to these examples specifically, resulting in a blue line boundary as above.
Hybrid approach
By combining undersampling and oversampling approaches, we get the advantages but also drawbacks of both approaches as illustrated above, which is still a tradeoff.
More recent approaches to the problem
In 2002, an sampling based algorithm called SMOTE (Synthetic Minority Over-Sampling Technique) was introduced that try to address the class imbalance problem. It is one of the most adopted approaches due to its simplicity and effectiveness. It is a combination of oversampling and undersampling, but the oversampling approach is not by replicating minority class but constructing new minority class data instance via an algorithm.
In traditional oversampling, minority class is replicated exactly. In SMOTE, new minority instances are constructed in this way:
The intuition behind the construction algorithm is that oversampling causes overfit because of repeated instances causes the decision boundary to tighten. Instead, we will create “similar” examples instead. To the machine learning algorithm, these new constructed instances are not exact copies and thus softens the decision boundary as a result. This be can illustrated as follows:
As a result, the classifier is more general and does not overfit.
Even more recent approaches
Interested readers may look into more recent literature regarding RUSBoost, SMOTEBagging and Underbagging, which are all regarded as more promising approaches since SMOTE.
However, SMOTE is still very popular due to its simplicity.
Summary
The Class Imbalance Problem is a common problem affecting machine learning due to having disproportionate number of class instances in practice. To compare solutions, we will use alternative metrics (True Positive, True Negative, False Positive, False Negative) instead of general accuracy of counting number of mistakes.
Due to its prevalence, there are many approaches out there to deal with this problem. They can be generally classified into two major categories of 1) sampling based, and 2) cost function based. Sampling based can be broken into three major categories: a) over sampling b) under sampling c) hybrid of oversampling and undersampling.
Now armed with what, why and how, you can start dealing with real world scenarios of handling datasets with this problem.


Synchronise calendars
Synchronisation period
Synchronise from the last days
Synchronise up to the coming days
Synchronise from the last days
Synchronise up to the coming days
Update the calendar items
The calendar title will be overwritten with the values in title column of the sheet
The calendar title will be overwritten with the values in title column of the sheet
The calendar description will be overwritten with the
values in description column of the sheet


Operating Systems
Operating Systems -
An Operating System (OS) is an interface between a computer user and computer hardware. An operating system is a software which performs all the basic tasks like file management, memory management, process management, handling input and output, and controlling peripheral devices such as disk drives and printers. Some popular Operating Systems include Linux Operating System, Windows Operating System, VMS, OS/400, AIX, z/OS, etc.
Following are some of important functions of an operating System.
1. Memory Management
2. Processor Management
3. Device Management
4. File Management
5. Security
6. Control over system performance
7. Job accounting
8. Error detecting aids
9. Coordination between other software and users
View Content


this is the body! idiot!
Here is a div with some content.
Here is a div with some content.
Here is a div with some content.
Here is a div with some content.
Here is a div with some content.


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Holiday, Sabonis lead Pacers to easy win over Nets
NEW YORK (AP) - The Pacers relied on the Holiday brothers to overcome some injuries in their backcourt.
Aaron Holiday finished with career highs of 24 points and 13 assists, Justin Holiday scored 20 points and the Pacers cruised to a 115-86 victory over the Brooklyn Nets on Monday night.
“It’s a blessing he’s on the team with us and we’re two brothers in the NBA, let alone in the same team. It’s crazy,” Aaron Holiday said.
Indiana was playing without Malcolm Brogdon and Jeremy Lamb, but the backcourt tandem of the Holiday brothers was effective, especially after coach Nate McMillan was successful on a replay challenge late in the third quarter.
Aaron Holiday and Justin Holiday combined to hit three consecutive baskets to put the Pacers ahead 82-65 with 1:09 remaining in the period.
“They’re playing great. They’re playing with a lot of confidence,” Domantas Sabonis said. “Teams are doubling us, so we’re just kicking it out to open shooters and they’re knocking shots with confidence.”
Sabonis had 16 points and a career-high 18 rebounds, while T.J. Warren added 19 for the Pacers, who were coming off consecutive losses to Houston and Milwaukee.
Brooklyn was on a 7-0 run and within 75-62 with 3:10 left in the third quarter when Justin Holiday signaled to McMillan to challenge a call that the Pacers had lost the ball out of bounds.
The call was overturned and the Pacers soon after pushed their lead back to 18.
“There is a style that we want to play and we want to make sure that we are connected out there and playing together,” McMillan said. “We talked about our three Ts and being together and showing some real toughness and trusting each other, regardless of who’s in uniform. They’ve been able to do that and win some games.”
Spencer Dinwiddie had 28 points and Jarrett Allen finished with 10 points and 12 rebounds for the Nets, who played without Kyrie Irving for a second straight game and were held to their lowest point total of the season.
Irving injured his shoulder while the Nets went 2-3 on their road trip.
“Below-average teams are inconsistent and that’s what we are right now,” Nets coach Kenny Atkinson said.
The Nets didn’t get a boost from being home, scoring a season-low 18 points in the first quarter and then following it up with just 17 in the second period to trail 59-35 at halftime.
Indiana was sluggish early before tying it at 18-all. The Pacers then blitzed the Nets with a 11-0 run to start the second quarter, getting seven straight points from Warren while opening up a 29-18 advantage.
Indiana later outscored Brooklyn by 30-15 and led by as many as 28 points with 28 seconds remaining in the half when Naz Mitrou-Long sealed a 13-0 spurt with an uncontested layup.
Nets guard Joe Harris questioned the team’s effort in the second quarter.
“There’s a lot of it that’s out of our your control when you’re playing, but the things that are in your control are competing every possession, playing hard every possession, having that sense of energy,” Harris said. “The ownership, the pride, a lot of that stuff isn’t there for us right now.”
The Pacers improved to 2-0 this season against the Nets. Both of the wins have come at the Barclays Center.
TIP-INS
Pacers: Besides Brogdon (back) and Lamb (ankle), the Pacers were also without T.J. McConnell (groin). … Mitrou-Long had a career-high 12 points off the bench.
Nets: Garrett Temple started in place of Irving and finished with 10 points and six rebounds.
LETS JUST WAIT SOME MORE
Atkinson said Irving is not at the point yet where he can go out on the court and play due to his shoulder injury. The team chose to be cautious with Irving as it is already without the services of G Caris LeVert, who underwent right thumb surgery last Thursday.
“That’s the conclusion we came to for tonight’s game,” Atkinson said. “Best that he didn’t play.”
Irving leads the Nets with 28.5 points and 7.2 assists per game.
UP NEXT
Pacers: Will be off until Saturday when they open a four-game homestand against the Orlando Magic.
Nets: Continue their three-game homestand Wednesday when they host the Charlotte Hornets.
More AP NBA: https://apnews.com/NBA and https://twitter.com/AP_Sports
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A class (inheriting from Builder) that takes parsed documents and performs an action on them. Normally, builders translate the documents to an output format, but it is also possible to use the builder builders that e.g. check for broken links in the documentation, or build coverage information.
See Available builders for an overview over Sphinx’ built-in builders.
A reStructuredText markup element that allows marking a block of content with special meaning. Directives are supplied not only by docutils, but Sphinx and custom extensions can add their own. The basic directive syntax looks like this:
.. directivename:: argument ...
:option: value
Content of the directive.
See Directives for more information.
Since reST source files can have different extensions (some people like .txt, some like .rst – the extension can be configured with :confval:`source_suffix`) and different OSes have different path separators, Sphinx abstracts them: document names are always relative to the source directory, the extension is stripped, and path separators are converted to slashes. All values, parameters and such referring to “documents” expect such document names.
Examples for document names are index, library/zipfile, or reference/datamodel/types. Note that there is no leading or trailing slash.
A domain is a collection of markup (reStructuredText directives and roles) to describe and link to objects belonging together, e.g. elements of a programming language. Directive and role names in a domain have names like domain:name, e.g. py:function.
Having domains means that there are no naming problems when one set of documentation wants to refer to e.g. C++ and Python classes. It also means that extensions that support the documentation of whole new languages are much easier to write. For more information about domains, see the chapter Sphinx Domains.


{% extends 'base.html' %} {% load i18n %} {% block title %}{{ website.acro }} | {% translate "Profile deleted" %}{%endblock title %} {% block content %}
{% translate "Your profile was deleted. Thanks anyway for subscribing to" %} {{ website.name }}!


grahamcracker-py¶
grahamcracker goes great with marshmallow! Use grahamcracker
to automatically make
marshmallow schemas from dataclasses.
>>> import uuid
>>> from grahamcracker import DataSchema, schema_for
>>> from dataclasses import dataclass
>>>
>>> @dataclass
... class Name:
... id: uuid.UUID
... first: str
... last: str
...
>>> @schema_for(Name)
... class NameSchema(DataSchema[Name]):
... pass
...
>>> name_id = "fbd6283c-1963-4493-bf1e-b69ae28ee8f6"
>>> name_data = {"first": "Harry", "last": "Potter", "id": name_id}
>>>
>>> name = NameSchema().load(name_data)
>>> name
Name(id=UUID('fbd6283c-1963-4493-bf1e-b69ae28ee8f6'), first='Harry', last='Potter')
>>>
>>> dumped = NameSchema().dump(name)
>>> dumped
{'first': 'Harry', 'last': 'Potter', 'id': 'fbd6283c-1963-4493-bf1e-b69ae28ee8f6'}
The uuid is automatically serialized / deserialized and the dataclass is handled seamlessly.


Page with few buttons, different inputs (text, radio, checkbox, color, number and etc). – here we will test statistics. Client should send statistics to the server, server should save it to the database.


stoner metal band names that might be a bit on the nose
you can help
belzebong
bong
bongripper
bongzilla
dopelord
Mammoth Weed Wizard Bastard
salem's pot
stoned jesus
toke
☑
weedeater
weedpecker
chubby thunderous bad kush masters
honorable mentions despite not being the band name
dopesmoker by sleep
☑
dopethrone by electric wizard
☑ indicates the sound of a bong hit therefore solidfying their a-bit-on-the-nose status


Pizza Place
What toppings would you like?
Below is a list of the pizza toppings...Pick as many as you like. 50 cents each.
Toppings
Tomatoes
Pepperoni
Extra Cheese
Mushrooms
Onions
Olives
Sausage
Chicken
Peppers
Jalepenos
Pineapple
Feta
What size pizza would you like?
Small
Medium
Large
How many pizzas?
Place order
×
Your Order
Number of Toppings:
Pizza Size:
Number of Pizzas:
Total Price:


| Top |
| void | action-changed | Run Last |
| void | cancel | Run Last |
| void | dnd-finished | Run Last |
| void | drop-performed | Run Last |
These functions provide a low level interface for drag and drop. The X backend of GDK supports both the Xdnd and Motif drag and drop protocols transparently, the Win32 backend supports the WM_DROPFILES protocol.
GTK+ provides a higher level abstraction based on top of these functions, and so they are not normally needed in GTK+ applications. See the Drag and Drop section of the GTK+ documentation for more information.
GdkAtom
gdk_drag_get_selection (GdkDragContext *context
);
Returns the selection atom for the current source window.
void gdk_drag_abort (GdkDragContext *context
,guint32 time_
);
Aborts a drag without dropping.
This function is called by the drag source.
This function does not need to be called in managed drag and drop
operations. See gdk_drag_context_manage_dnd()
for more information.
void gdk_drop_reply (GdkDragContext *context
,gboolean accepted
,guint32 time_
);
Accepts or rejects a drop.
This function is called by the drag destination in response to a drop initiated by the drag source.
void gdk_drag_drop (GdkDragContext *context
,guint32 time_
);
Drops on the current destination.
This function is called by the drag source.
This function does not need to be called in managed drag and drop
operations. See gdk_drag_context_manage_dnd()
for more information.
void gdk_drag_drop_done (GdkDragContext *context
,gboolean success
);
Inform GDK if the drop ended successfully. Passing FALSE
for success
may trigger a drag cancellation animation.
This function is called by the drag source, and should
be the last call before dropping the reference to the
context
.
The GdkDragContext will only take the first gdk_drag_drop_done()
call as effective, if this function is called multiple times,
all subsequent calls will be ignored.
Since: 3.20
void gdk_drag_find_window_for_screen (GdkDragContext *context
,GdkWindow *drag_window
,GdkScreen *screen
,gint x_root
,gint y_root
,GdkWindow **dest_window
,GdkDragProtocol *protocol
);
Finds the destination window and DND protocol to use at the given pointer position.
This function is called by the drag source to obtain the
dest_window
and protocol
parameters for gdk_drag_motion()
.
context |
||
drag_window |
a window which may be at the pointer position, but should be ignored, since it is put up by the drag source as an icon |
|
screen |
the screen where the destination window is sought |
|
x_root |
the x position of the pointer in root coordinates |
|
y_root |
the y position of the pointer in root coordinates |
|
dest_window |
location to store the destination window in. |
[out] |
protocol |
location to store the DND protocol in. |
[out] |
Since: 2.2
GdkDragContext * gdk_drag_begin (GdkWindow *window
,GList *targets
);
Starts a drag and creates a new drag context for it.
This function assumes that the drag is controlled by the
client pointer device, use gdk_drag_begin_for_device()
to
begin a drag with a different device.
This function is called by the drag source.
window |
the source window for this drag. |
|
targets |
the offered targets, as list of GdkAtoms. |
[transfer none][element-type GdkAtom] |
GdkDragContext * gdk_drag_begin_for_device (GdkWindow *window
,GdkDevice *device
,GList *targets
);
Starts a drag and creates a new drag context for it.
This function is called by the drag source.
window |
the source window for this drag |
|
device |
the device that controls this drag |
|
targets |
the offered targets, as list of GdkAtoms. |
[transfer none][element-type GdkAtom] |
GdkDragContext * gdk_drag_begin_from_point (GdkWindow *window
,GdkDevice *device
,GList *targets
,gint x_root
,gint y_root
);
Starts a drag and creates a new drag context for it.
This function is called by the drag source.
window |
the source window for this drag |
|
device |
the device that controls this drag |
|
targets |
the offered targets, as list of GdkAtoms. |
[transfer none][element-type GdkAtom] |
x_root |
the x coordinate where the drag nominally started |
|
y_root |
the y coordinate where the drag nominally started |
Since: 3.20
gboolean gdk_drag_motion (GdkDragContext *context
,GdkWindow *dest_window
,GdkDragProtocol protocol
,gint x_root
,gint y_root
,GdkDragAction suggested_action
,GdkDragAction possible_actions
,guint32 time_
);
Updates the drag context when the pointer moves or the set of actions changes.
This function is called by the drag source.
This function does not need to be called in managed drag and drop
operations. See gdk_drag_context_manage_dnd()
for more information.
context |
||
dest_window |
the new destination window, obtained by
|
|
protocol |
the DND protocol in use, obtained by |
|
x_root |
the x position of the pointer in root coordinates |
|
y_root |
the y position of the pointer in root coordinates |
|
suggested_action |
the suggested action |
|
possible_actions |
the possible actions |
|
time_ |
the timestamp for this operation |
void gdk_drop_finish (GdkDragContext *context
,gboolean success
,guint32 time_
);
Ends the drag operation after a drop.
This function is called by the drag destination.
context |
||
success |
|
|
time_ |
the timestamp for this operation |
void gdk_drag_status (GdkDragContext *context
,GdkDragAction action
,guint32 time_
);
Selects one of the actions offered by the drag source.
This function is called by the drag destination in response to
gdk_drag_motion()
called by the drag source.
gboolean
gdk_drag_drop_succeeded (GdkDragContext *context
);
Returns whether the dropped data has been successfully
transferred. This function is intended to be used while
handling a GDK_DROP_FINISHED
event, its return value is
meaningless at other times.
Since: 2.6
GdkDragProtocol gdk_window_get_drag_protocol (GdkWindow *window
,GdkWindow **target
);
Finds out the DND protocol supported by a window.
window |
the destination window |
|
target |
location of the window
where the drop should happen. This may be |
[out][allow-none][transfer full] |
Since: 3.0
GdkDragAction
gdk_drag_context_get_actions (GdkDragContext *context
);
Determines the bitmask of actions proposed by the source if
gdk_drag_context_get_suggested_action()
returns GDK_ACTION_ASK
.
Since: 2.22
GdkDragAction
gdk_drag_context_get_suggested_action (GdkDragContext *context
);
Determines the suggested drag action of the context.
Since: 2.22
GdkDragAction
gdk_drag_context_get_selected_action (GdkDragContext *context
);
Determines the action chosen by the drag destination.
Since: 2.22
GList *
gdk_drag_context_list_targets (GdkDragContext *context
);
Retrieves the list of targets of the context.
Since: 2.22
GdkDevice *
gdk_drag_context_get_device (GdkDragContext *context
);
Returns the GdkDevice associated to the drag context.
void gdk_drag_context_set_device (GdkDragContext *context
,GdkDevice *device
);
Associates a GdkDevice to context
, so all Drag and Drop events
for context
are emitted as if they came from this device.
GdkWindow *
gdk_drag_context_get_source_window (GdkDragContext *context
);
Returns the GdkWindow where the DND operation started.
Since: 2.22
GdkWindow *
gdk_drag_context_get_dest_window (GdkDragContext *context
);
Returns the destination windw for the DND operation.
Since: 3.0
GdkDragProtocol
gdk_drag_context_get_protocol (GdkDragContext *context
);
Returns the drag protocol thats used by this context.
Since: 3.0
GdkWindow *
gdk_drag_context_get_drag_window (GdkDragContext *context
);
Returns the window on which the drag icon should be rendered
during the drag operation. Note that the window may not be
available until the drag operation has begun. GDK will move
the window in accordance with the ongoing drag operation.
The window is owned by context
and will be destroyed when
the drag operation is over.
Since: 3.20
void gdk_drag_context_set_hotspot (GdkDragContext *context
,gint hot_x
,gint hot_y
);
Sets the position of the drag window that will be kept under the cursor hotspot. Initially, the hotspot is at the top left corner of the drag window.
context |
||
hot_x |
x coordinate of the drag window hotspot |
|
hot_y |
y coordinate of the drag window hotspot |
Since: 3.20
gboolean gdk_drag_context_manage_dnd (GdkDragContext *context
,GdkWindow *ipc_window
,GdkDragAction actions
);
Requests the drag and drop operation to be managed by context
.
When a drag and drop operation becomes managed, the GdkDragContext
will internally handle all input and source-side GdkEventDND events
as required by the windowing system.
Once the drag and drop operation is managed, the drag context will emit the following signals:
The “action-changed” signal whenever the final action to be performed by the drag and drop operation changes.
The “drop-performed” signal after the user performs the drag and drop gesture (typically by releasing the mouse button).
The “dnd-finished” signal after the drag and drop operation concludes (after all GdkSelection transfers happen).
The “cancel” signal if the drag and drop operation is finished but doesn't happen over an accepting destination, or is cancelled through other means.
context |
||
ipc_window |
Window to use for IPC messaging/events |
|
actions |
the actions supported by the drag source |
Since: 3.20
Used in GdkDragContext to the reason of a cancelled DND operation.
Since: 3.20
Used in GdkDragContext to indicate the protocol according to which DND is done.
Used in GdkDragContext to indicate what the destination should do with the dropped data.
|
Means nothing, and should not be used. |
||
|
Copy the data. |
||
|
Move the data, i.e. first copy it, then delete it from the source using the DELETE target of the X selection protocol. |
||
|
Add a link to the data. Note that this is only useful if source and destination agree on what it means. |
||
|
Special action which tells the source that the destination will do something that the source doesn’t understand. |
||
|
Ask the user what to do with the data. |
“action-changed”
signalvoid user_function (GdkDragContext *context, GdkDragAction action, gpointer user_data)
A new action is being chosen for the drag and drop operation.
This signal will only be emitted if the GdkDragContext manages
the drag and drop operation. See gdk_drag_context_manage_dnd()
for more information.
context |
The object on which the signal is emitted |
|
action |
The action currently chosen |
|
user_data |
user data set when the signal handler was connected. |
Flags: Run Last
Since: 3.20
“cancel”
signalvoid user_function (GdkDragContext *context, GdkDragCancelReason reason, gpointer user_data)
The drag and drop operation was cancelled.
This signal will only be emitted if the GdkDragContext manages
the drag and drop operation. See gdk_drag_context_manage_dnd()
for more information.
context |
The object on which the signal is emitted |
|
reason |
The reason the context was cancelled |
|
user_data |
user data set when the signal handler was connected. |
Flags: Run Last
Since: 3.20
“dnd-finished”
signalvoid user_function (GdkDragContext *context, gpointer user_data)
The drag and drop operation was finished, the drag destination finished reading all data. The drag source can now free all miscellaneous data.
This signal will only be emitted if the GdkDragContext manages
the drag and drop operation. See gdk_drag_context_manage_dnd()
for more information.
context |
The object on which the signal is emitted |
|
user_data |
user data set when the signal handler was connected. |
Flags: Run Last
Since: 3.20
“drop-performed”
signalvoid user_function (GdkDragContext *context, gint time, gpointer user_data)
The drag and drop operation was performed on an accepting client.
This signal will only be emitted if the GdkDragContext manages
the drag and drop operation. See gdk_drag_context_manage_dnd()
for more information.
context |
The object on which the signal is emitted |
|
time |
the time at which the drop happened. |
|
user_data |
user data set when the signal handler was connected. |
Flags: Run Last
Since: 3.20


examples.seismic package¶
Subpackages¶
Submodules¶
examples.seismic.benchmark module¶
-
examples.seismic.benchmark.
bench
(problem, **kwargs)[source]¶ Complete benchmark with multiple simulation and performance parameters.
-
examples.seismic.benchmark.
get_ob_bench
(problem, resultsdir, parameters)[source]¶ Return a special
opescibench.Benchmark
to manage performance runs.
-
examples.seismic.benchmark.
get_ob_exec
(func)[source]¶ Return a special
opescibench.Executor
to execute performance runs.
-
examples.seismic.benchmark.
option_performance
(f)[source]¶ Defines options for all aspects of performance tuning
-
examples.seismic.benchmark.
plot
(problem, **kwargs)[source]¶ Plotting mode to generate plots for performance analysis.
examples.seismic.model module¶
-
class
examples.seismic.model.
Model
(origin, spacing, shape, space_order, vp, nbpml=20, dtype=<class 'numpy.float32'>, epsilon=None, delta=None, theta=None, phi=None, **kwargs)[source]¶ Bases:
examples.seismic.model.Pysical_Model
The physical model used in seismic inversion processes.
Parameters: - origin – Origin of the model in m as a tuple in (x,y,z) order
- spacing – Grid size in m as a Tuple in (x,y,z) order
- shape – Number of grid points size in (x,y,z) order
- space_order – Order of the spatial stencil discretisation
- vp – Velocity in km/s
- nbpml – The number of PML layers for boundary damping
- epsilon – Thomsen epsilon parameter (0<epsilon<1)
- delta – Thomsen delta parameter (0<delta<1), delta<epsilon
- theta – Tilt angle in radian
- phi – Asymuth angle in radian
The
Model
provides two symbolic data objects for the creation of seismic wave propagation operators:Parameters: - m – The square slowness of the wave
- damp – The damping field for absorbing boundarycondition
-
critical_dt
¶ Critical computational time step value from the CFL condition.
-
vp
¶ numpy.ndarray
holding the model velocity in km/s. .. note:: Updating the velocity field also updates the square slownessself.m
. However, onlyself.m
should be used in seismic operators, since it is of typeFunction
.
-
class
examples.seismic.model.
ModelElastic
(origin, spacing, shape, space_order, vp, vs, rho, nbpml=20, dtype=<class 'numpy.float32'>)[source]¶ Bases:
examples.seismic.model.Pysical_Model
The physical model used in seismic inversion processes. :param origin: Origin of the model in m as a tuple in (x,y,z) order :param spacing: Grid size in m as a Tuple in (x,y,z) order :param shape: Number of grid points size in (x,y,z) order :param space_order: Order of the spatial stencil discretisation :param vp: P-wave velocity in km/s :param vs: S-wave velocity in km/s :param nbpml: The number of PML layers for boundary damping :param rho: Density in kg/cm^3 (rho=1 for water) The
ModelElastic
provides a symbolic data objects for the creation of seismic wave propagation operators: :param damp: The damping field for absorbing boundarycondition-
critical_dt
¶ Critical computational time step value from the CFL condition.
-
-
examples.seismic.model.
demo_model
(preset, **kwargs)[source]¶ Utility function to create preset
Model
objects for demonstration and testing purposes. The particular presets are* `constant-isotropic` : Constant velocity (1.5km/sec) isotropic model * `constant-tti` : Constant anisotropic model. Velocity is 1.5 km/sec and
Thomsen parameters are epsilon=.3, delta=.2, theta = .7rad and phi=.35rad for 3D. 2d/3d is defined from the input shape- ‘layers-isotropic’: Simple two-layer model with velocities 1.5 km/s
- and 2.5 km/s in the top and bottom layer respectively. 2d/3d is defined from the input shape
- ‘layers-tti’: Simple two-layer TTI model with velocities 1.5 km/s
- and 2.5 km/s in the top and bottom layer respectively. Thomsen parameters in the top layer are 0 and in the lower layer are epsilon=.3, delta=.2, theta = .5rad and phi=.1 rad for 3D. 2d/3d is defined from the input shape
- ‘circle-isotropic’: Simple camembert model with velocities 1.5 km/s
- and 2.5 km/s in a circle at the center. 2D only.
- ‘marmousi2d-isotropic’: Loads the 2D Marmousi data set from the given
- filepath. Requires the
opesci/data
repository to be available on your machine.
- ‘marmousi2d-tti’: Loads the 2D Marmousi data set from the given
- filepath. Requires the
opesci/data
repository to be available on your machine.
- ‘marmousi3d-tti’: Loads the 2D Marmousi data set from the given
- filepath. Requires the
opesci/data
repository to be available on your machine.
examples.seismic.plotting module¶
-
examples.seismic.plotting.
plot_image
(data, vmin=None, vmax=None, colorbar=True, cmap='gray')[source]¶ Plot image data, such as RTM images or FWI gradients.
Parameters: - data – Image data to plot
- cmap – Choice of colormap, default is gray scale for images as a
seismic convention
-
examples.seismic.plotting.
plot_perturbation
(model, model1, colorbar=True)[source]¶ Plot a two-dimensional velocity difference from two seismic
Model
objects.Parameters: - model –
Model
object of first velocity model. - model1 –
Model
object of the second velocity model. - source – Coordinates of the source point.
- receiver – Coordinates of the receiver points.
- model –
-
examples.seismic.plotting.
plot_shotrecord
(rec, model, t0, tn, colorbar=True)[source]¶ Plot a shot record (receiver values over time).
Parameters: - rec – Receiver data with shape (time, points)
- model –
Model
object that holds the velocity model. - t0 – Start of time dimension to plot
- tn – End of time dimension to plot
-
examples.seismic.plotting.
plot_velocity
(model, source=None, receiver=None, colorbar=True)[source]¶ Plot a two-dimensional velocity field from a seismic
Model
object. Optionally also includes point markers for sources and receivers.Parameters: - model –
Model
object that holds the velocity model. - source – Coordinates of the source point.
- receiver – Coordinates of the receiver points.
- model –
examples.seismic.source module¶
-
class
examples.seismic.source.
PointSource
(*args, **kwargs)[source]¶ Bases:
devito.function.SparseTimeFunction
Symbolic data object for a set of sparse point sources
Parameters: - name – Name of the symbol representing this source.
- grid –
Grid
object defining the computational domain. - time_range –
TimeAxis
TimeAxis(start, step, num) object. - npoint – (Optional) number of sparse points represented by this source.
- data – (Optional) data values to initialise point data.
- coordinates – (Optional) point coordinates for this source.
- space_order – (Optional) space discretization order.
- time_order – (Optional) time discretization order (defaults to 2).
- dtype – (Optional) data type of the buffered data.
- dimension – (Optional) class:Dimension object for representing the number of points in this source.
-
default_assumptions
= {}¶
-
time_range
¶
-
time_values
¶
-
examples.seismic.source.
Receiver
¶ alias of
examples.seismic.source.PointSource
-
examples.seismic.source.
Shot
¶ alias of
examples.seismic.source.PointSource
-
class
examples.seismic.source.
WaveletSource
(*args, **kwargs)[source]¶ Bases:
examples.seismic.source.PointSource
Abstract base class for symbolic objects that encapsulate a set of sources with a pre-defined source signal wavelet.
Parameters: - name – Name for the resulting symbol
- grid –
Grid
object defining the computational domain. - f0 – Peak frequency for Ricker wavelet in kHz
- time_values – Discretized values of time in ms
-
default_assumptions
= {}¶
-
class
examples.seismic.source.
RickerSource
(*args, **kwargs)[source]¶ Bases:
examples.seismic.source.WaveletSource
Symbolic object that encapsulate a set of sources with a pre-defined Ricker wavelet:
http://subsurfwiki.org/wiki/Ricker_wavelet
Parameters: - name – Name for the resulting symbol
- grid –
Grid
object defining the computational domain. - f0 – Peak frequency for Ricker wavelet in kHz
- time – Discretized values of time in ms
-
default_assumptions
= {}¶
-
class
examples.seismic.source.
GaborSource
(*args, **kwargs)[source]¶ Bases:
examples.seismic.source.WaveletSource
Symbolic object that encapsulate a set of sources with a pre-defined Gabor wavelet:
https://en.wikipedia.org/wiki/Gabor_wavelet
Parameters: - name – Name for the resulting symbol
- grid –
Grid
object defining the computational domain. - f0 – Peak frequency for Ricker wavelet in kHz
- time – Discretized values of time in ms
-
default_assumptions
= {}¶
-
class
examples.seismic.source.
TimeAxis
(start=None, step=None, num=None, stop=None)[source]¶ Bases:
object
- Data object to store the time axis. Exactly three of the four key arguments
must be prescribed. Because of remainder values it is not possible to create a time axis that exactly adhears to the inputs therefore start, stop, step and num values should be taken from the TimeAxis object rather than relying upon the input values.
The four possible cases are: start is None: start = step*(1 - num) + stop step is None: step = (stop - start)/(num - 1) num is None: num = ceil((stop - start + step)/step);
because of remainder stop = step*(num - 1) + startstop is None: stop = step*(num - 1) + start
:param start:(Optional) Start of time axis. :param step: (Optional) Time interval. :param: num: (Optional) Number of values (Note: this is the number of intervals + 1).
stop value is reset to correct for remainder.Parameters: stop – (Optional) End time. -
time_values
¶


Marker With Default Options Configured
The following marker has default option, optimized="false"
The following marker overides default option because user provided optimized="true"


| 007:057 Khan | : |
And it is He Who sends the winds as heralds of glad tidings, going before His Mercy (rain). Till when they have carried a heavy-laden cloud, We drive it to a land that is dead, then We cause water (rain) to descend thereon. Then We produce every kind of fruit therewith. Similarly, We shall raise up the dead, so that you may remember or take heed. |
| 007:057 Maulana | : |
And He it is Who sends for the winds bearing good news before His mercy; till, when they bear a laden cloud, We drive it to a dead land, then We send down water on it, then bring forth thereby fruits of all kinds. Thus do We bring forth the dead that you may be mindful. |
| 007:057 Pickthal | : |
And He it is Who sendeth the winds as tidings heralding His mercy, till, when they bear a cloud heavy (with rain), We lead it to a dead land, and then cause water to descend thereon and thereby bring forth fruits of every kind. Thus bring We forth the dead. Haply ye may remember. |
| 007:057 Rashad | : |
He is the One who sends the wind with good omen, as a mercy from His hands. Once they gather heavy clouds, we drive them to dead lands, and send down water therefrom, to produce with it all kinds of fruits. We thus resurrect the dead, that you may take heed. |
| 007:057 Sarwar | : |
God sends the wind bearing the glad news of His mercy. When heavy clouds are formed, We drive them unto a barren country and rain down on it water to cause all kinds of fruits to grow. In the same way do We bring the dead to life again. Perhaps you would take heed. |
| 007:057 Shakir | : |
And He it is Who sends forth the winds bearing good news before His mercy, until, when they bring up a laden cloud, We drive it to a dead land, then We send down water on it, then bring forth with it of fruits of all kinds; thus shall We bring forth the dead that you may be mindful. |
| 007:057 Sherali | : |
And HE it is Who sends the winds as glad tidings before HIS mercy till, when they bear a heavy cloud, WE drive it to a dead land; then WE send down water therefrom and WE bring forth fruits of every kind. In like manner do WE bring forth the dead that you may remember. |
| 007:057 Yusufali | : |
It is He Who sendeth the winds like heralds of glad tidings, going before His mercy: when they have carried the heavy-laden clouds, We drive them to a land that is dead, make rain to descend thereon, and produce every kind of harvest therewith: thus shall We raise up the dead: perchance ye may remember. |
Concepts/Themes Covered: الإيمان > اليوم الآخر > البعث Faith> The Hereafter> The Resurrection الإيمان > اليوم الآخر > الحشر Faith> The Hereafter> The Day of Resurrection العلوم والفنون > الحقائق العلمية و الإشاة إلى وقائع أيدتهاالإكتشافات العلمية > الريح Science and Art> The Scientific Facts and the Indication to Facts which have been supported by the Scientific Discoveries>The Wind العلوم والفنون > الحقائق العلمية و الإشاة إلى وقائع أيدتهاالإكتشافات العلمية > السحاب Science and Art> The Scientific Facts and the Indication to Facts which have been supported by the Scientific Discoveries>The Clouds العلوم والفنون > الحقائق العلمية و الإشاة إلى وقائع أيدتهاالإكتشافات العلمية > الغيث Science and Art> The Scientific Facts and the Indication to Facts which have been supported by the Scientific Discoveries>The Rain
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


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Found a bug? Let us know.
Got an idea for a feature? Let’s discuss it.
This is the place for it: https://bitbucket.org/zalew/django-flickr/issues
Non-breaking changes are welcome, just explicitely explain (in your commit message and/or pull request) what you did and why - it increases the chance your improvement gets merged upstream. Provide tests, make sure all tests pass, the build works, etc.
If you developped or want to develop a new feature, just show the code and/or submit a proposal. Explain the idea behind it and use cases.
As always, the best place for open discussion is: https://bitbucket.org/zalew/django-flickr/issues


12
1 Jesus arrived in Bethany six days before the Passover Festival began. Bethany was the village where Lazarus lived, the man Jesus made alive again after he had died.
2 There in Bethany, they gave a dinner to honor Jesus. Martha made preparations for the dinner, and Lazarus was among those who were sitting together and eating.
3 Then Mary took a bottle of expensive perfume (called nard) and, to honor Jesus, she poured it out on his feet and then wiped his feet with her hair. The fragrance of the perfume filled the entire house.
4 However, one of his disciples, Judas Iscariot, (he was the one who broke the trust Jesus had in him, and soon he would give Jesus up to his enemies)—he objected and said,
5 "We should have sold this perfume for three hundred days' wages and given the money to the poor."
6 He said this, not because he cared about the poor people, but because he was a thief. He kept charge of the bag that held their money, but he would take money for his own use whenever he wanted.
7 Then Jesus said, "Leave her alone!
9 A large crowd of Jews in Jerusalem heard that Jesus was in Bethany, so they went there. They came not only because Jesus was there, but also to see Lazarus, whom Jesus had made alive.
10 Then the chief priests decided it was necessary to put Lazarus to death, as well,
11 for it was because of him that many of the Jews were no longer believing in what the chief priests were teaching; instead, they were putting their trust in Jesus.
12 The next day the large crowd that had come for the Passover Festival heard that Jesus was on his way to Jerusalem.
13 So they cut branches from palm trees and went out to welcome him as he came into the city. They were shouting, "Hosanna! Praise God! God bless the One who comes in the Name of the Lord! Welcome, King of Israel!"
14 When Jesus came near to Jerusalem, he found a young donkey and sat on it, riding into the city. By doing this, he fulfilled what had been written in Scripture:
15 "Do not be afraid, you who live in Jerusalem.
Look! Your King is coming.
He is riding on a donkey's colt!"
16 When this happened, his disciples did not understand that this was a fulfillment of prophecy. However, after Jesus had finished his work and had received again his full powers as God, they looked back and remembered what the prophets had written about him and what people had done to him.
17 The crowd that was following along with Jesus kept telling others what they had seen: that Jesus had called Lazarus out of the tomb and had made him alive again.
18 The other crowd of people, those who went out of the city gate to meet Jesus, did so because they heard he had done great things to show them his power.
19 So the Pharisees said to each other, "See! We are gaining no advantage here. Look! The whole world is following him!"
20 Among those who went up to Jerusalem during the Passover Festival were some Greeks.
21 They came to Philip, who was from Bethsaida in the district of Galilee. They had something to ask him; they said, "Sir, would you introduce us to Jesus?"
22 So Philip reported this to Andrew, and they both went and told Jesus.
23 Jesus answered Philip and Andrew, "It is time for God to show the people everything that I, the Son of Man, have done and to tell them all that I have said.
24 I am telling you the truth: unless a seed of wheat is planted in the earth and dies, it remains only one seed; but after it dies in the ground, then it will grow and produce a harvest of many seeds.
25 Anyone who tries to live to please himself will fail, but anyone who does not live to please himself will keep his life forever.
26 If anyone wants to serve me, he must also follow me because my servant must be where I am. The Father will honor everyone who serves me.
27 Now my soul is greatly troubled. Should I say, 'Father, save me from this time when I will suffer and die!'? No, for this is the very reason I came into this world.
28 My Father, show how powerful you are in all you have said, in all you have done, and in all you are!"
Then God spoke from heaven, "I have already displayed my nature, my words, and my works; and I will do it again!"
29 The crowd that was there heard the voice of God, but some said it was just thunder. Others said an angel had spoken to Jesus.
30 Jesus replied to them, "The voice you heard speaking was God's voice. However, he spoke not for my benefit, but for yours!
31 Now is the time for God to judge the world. Now is the time when he will drive out Satan, the one who rules this world.
32 As for me, when people raise me high on a cross, I will draw everyone to myself."
33 He said this to let the people know how he would die.
34 Someone in the crowd answered him, "We understand from the Scriptures that the Messiah will live forever. So why do you say that the Son of Man will die? Who is this 'Son of Man'?"
35 Jesus answered, "My light will shine on you for just a little longer. Walk in the light while you have my light, or the darkness will overtake you. Those who walk in the darkness cannot see where they are going!
36 Trust in that light while you have the light; then you will belong to the light.
After he said those things, Jesus left them and hid from them.
37 Although Jesus had done many miracles, most of the people did not believe what he had told them.
38 This was to make come true what Isaiah the prophet had written long ago:
"Lord, who has believed anything that they have heard from us?
The Lord has shown us how he can powerfully rescue us!"
39 Yet, they could not trust in him for the reason that Isaiah had written:
40
"The Lord has made them so they cannot see,
and he has made them stubborn;
they cannot even see with their eyes,
If they could, they would understand;
they would repent and pray for me to forgive them.
For this reason, I cannot heal them!"
41 Isaiah wrote those words long ago because he understood that Christ would serve God powerfully.
42 Although this was true, many of the leaders of the Jewish people put their trust in Jesus. Nevertheless, they greatly feared that the Pharisees would ban them from the synagogues, so they did not speak out about trusting in Jesus.
43 They preferred that other people praise and respect them rather than that God would praise them.
44 Jesus shouted out to the crowd that had gathered, "Those who put their trust in me are not only putting their trust in me but also are putting their trust in the Father who sent me.
45 When you see me, you are also seeing the one who sent me.
46 I have come into the world as the light of the world; whoever puts his trust in me will not remain in the darkness.
47 I do not judge those who listen to my words but refuse to obey me. I did not come into the world to condemn the world.
48 Yet, there is something that will condemn those who reject me and do not follow my message. They are condemned by the message I have spoken to them.
49 When I taught about God, I was not merely saying what I thought. The Father, who sent me, gave me clear instructions on what I should say and how I should say it.
50 I know that the Father's most important instructions are the ones that teach people how to live forever, and I have said exactly what my Father has told me to say."


test openInternal screen story 33374
test openInternal screen web 24612
test openInternal screen panorama 24614
test openInternal collection list 587
test openInternal collection tour 292
test openInternal collection menu 3459
test openInternal screen story 1
test openInternal screen web 1
test openInternal screen panorama 1
test openInternal collection list 1
test openInternal collection tour 1
test openInternal collection menu 1
test openExternal Google
enable camera
disable camera


--- layout: post authors: ["Greg Wilson"] title: "Announcing 2015 Steering Committee" date: 2015-01-31 time: "06:30:00" tags: ["Software Carpentry Foundation", "Election 2015"] favorite: true ---
The election for the Software Carpentry Foundation's Steering Committee is now complete. 122 ballots were exercised out of 179 mailed out, and our new committee is:
We are very grateful to the other candidates in the election for standing, and look forward to continuing to work closely with them in the future:
| John Blischak | Jonah Duckles | Tim Cerino | Ivan Gonzalez | Sheldon McKay | Jeramia Ory |
The incoming Steering Committee will meet with their outgoing counterparts this week to start getting up to speed on governance, finance, partnerships, and plans for the coming year. We will announce their roles (such as chair and treasurer) as soon as they have been decided. Our thanks to the members of the outgoing committee for all their contributions:
| Jenny Bryan | Neil Chue Hong | Carole Goble | Josh Greenberg | Katy Huff | Damien Irving |
| Adam Stone | Tracy Teal | Kaitlin Thaney |
And by sheer coincidence, on the same day that our new Steering Committee was elected, we taught our 10,000th learner:
so our biggest thanks to out to the instructors, partners, and helpers who have given so much to so many.


--- layout: post date: 2009-04-28 time: "09:00:00" authors: ["Greg Wilson"] title: Empirical Software Engineering and Scientific Computing tags: ["Community", "Content", "Opinion", "Research"] ---
The slides for my talk at the National Research Council on empirical software engineering and how scientists actually use computers are now up on SlideShare. The colors in some of the embedded images were messed up during upload, but the result should still be readable.


Strategy bonds IRA lucrative Fitch rates bondholders securities fiat public managed 401k risk market index.
Government substantially taxpayer market exposure index funds. Fitch municipal bonds managed.
Fluctuate interest rates Dow Jones receive rise government term municipal market Nikkei passively return performance. Public finance holder fiat established bonds hedge fund benchmark.
Fluctuate interest rates Dow Jones receive rise government term municipal market Nikkei passively return performance. Public finance holder fiat established bonds hedge fund benchmark.
Fluctuate interest rates Dow Jones receive rise government term municipal market Nikkei passively return performance. Public finance holder fiat established bonds hedge fund benchmark.


Mga Opsyon ng Screen ng Koneksyon
Ang mga Opsyon ng Screen ng Koneksyon ay nagpapahintulot sa iyo na magkumpigura ng mga opsyon sa koneysyon ng ZAP:
Timeout (in seconds)
Ginagawa nitong mas madaling suriin ang mga mabagal na application.
Default na User Agent
Ang user agent na dapat gamitin ng ZAP sa paglilikha ng mga mensahe ng HTTP (halimbawa, mga mensahe ng spider o mga kahilingan ng CONNECT na papalabas na proxy).
Header ng Kahilingan ng Solong Cookie
Controls whether the ZAP's managed cookies (Enable (Global) HTTP State) should be set
on a single "Cookie" request header or multiple "Cookie" request headers, when sending an HTTP request to the server.
Enable (Global) HTTP State
This allows session details stored in cookies to be tracked.
This option must be selected to enable the "Use current tracking session" checkbox in the
Manual Request Editor dialogs.
Session tracking ensures that any requests are sent with the latest session details.
For example you may record a session when logged in as one user and then logout and login as another user.
If you resend a request from the first session without session tracking then it will use the cookies from
the first session.
If you resend the same request with session tracking then it will use the cookies from the second session.
DNS
Mga Matagumpay na Query ng TTL
Defines for how long the successful DNS queries should be cached:
- Negatibong bilang, i-cache magpakailanman;
- Zero, hindi pinapagana ang caching;
- Positibong bilang, ang bilang ng segundo na maka-cache ang mga query.
Paalala: Changes are applied after a restart.
The option can also be set using the -config
command line argument with the key connection.dnsTtlSuccessfulQueries
.
Security Protocols
Allows to choose the SSL/TLS versions enabled for outgoing connections (for example, to servers). At least
one version must be enabled, versions unsupported by the JRE will be unselected and disabled.
The option SSLv2Hello must be selected in conjunction with at least one SSL/TLS version.
Use Proxy Chain
This section allows you to connect to another proxy for outgoing connections.
This is often required in a corporate environment.
Proxy Authentication
This section allows you to configure the outgoing proxy authentication.
SOCKS Proxy
This section allows you to configure an outgoing SOCKS proxy, by default the SOCKS proxy configuration applies to all connections made by ZAP.
The SOCKS proxy system properties (e.g. socksProxyHost
, socksProxyPort
) take precedence over the persisted configurations
for compatibility with older ZAP versions. ZAP will use and display the values of the system's properties when defined at startup, the configurations
can still be changed in this panel.
Note: Loopback addresses (e.g. localhost
, 127.0.01
, ::1
) are not proxied through the SOCKS proxy, the connections will be done directly.
Enabled
If ZAP should use the configured SOCKS proxy.
Default: unselected
, unless the SOCKS proxy system properties are defined, in which case it is selected
.
Host
The host name or address of the SOCKS proxy.
Default: localhost
.
Port
The port of the SOCKS proxy.
Default: 1080
.
Version
The version of the SOCKS proxy.
Default: 5
.
Use SOCKS' DNS
If ZAP should let the SOCKS proxy resolve the host names. Requires a version 5 SOCKS proxy.
This might lead to connection failures if the SOCKS proxy is not able to resolve the host name (e.g. use of names that are defined in a hosts
file).
Default: selected
.
Authentication
The following fields allow to configure the authentication credentials for the SOCKS proxy.
User Name
The user name.
Default: none.
Password
The password.
Default: none.
Note: Stored in clear text in the configuration file.
See also


Files
A
B
- bookCardClass.php
- bookCards.php
- bookClass.php
- bookDetails.php
- bookForm.php
- bookIssueForm.php
- bookIssuedByBookClass.php
- bookIssuedByUserClass.php
- bookIssuedClass.php
- bookIssuedListClass.php
- bookListClass.php
- bookRecord.php
- booksIssuedByBook.php
- booksIssuedByBookList.php
- booksIssuedByUserList.php
- booksIssuedList.php
- booksList.php
C
D
H
I
L
- listEditBooks.php
- listEditUsers.php
- listReturnIssuedBooks.php
- login.php
- loginForm.php
- logout.php
- logoutPage.php
M
- messageClass.php
- messageForm.php
- messageReceivedClass.php
- messageSentClass.php
- messagesList.php
- myIssuedBooks.php
- myMessages.php
- myProfile.php
N
R
S
U
- uploadImgClass.php
- userClass.php
- userDetails.php
- userForm.php
- userListClass.php
- userRecord.php
- usersList.php


Crime-Vis-tigator
Over The Years - 1994 to 2013
Known Offenses by State - 2013
By Lee Bing Yuan & Tiew Kee Hui
Offenses Known to Law Enforcement by State - 2013


Episode 035
Experimenting with (yet) another approach to data access organization
ASP.NET Core: From 0 to overkill
In this episode
- Reorganize database access with a slightly different approach
- The idea
- Implementation
- Writing to the database
- Querying the database
- Pros and cons
- Saner approaches
The usual plugs...
- If these videos are being useful
- Like
- Share
- Leave feedback
- More stuff at:


Jacob Resman
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