REALITY BITES A film review by Vijay Ramanujan Copyright 1994 Vijay Ramanujan
Cast: Winona Ryder (Lelaina); Janeane Garofalo (Vickie); Ethan Hawke (Troy); Ben Stiller (Mike).
This movie can really be broken down into two parts. The first half was an humorous, intelligent story of one woman's job and man troubles shortly after graduation. The second half was a depressingly realistic look at what makes these people tick. I found myself wondering whether my generation is really as f-ed up as we appear in this movie.
The first half tells the story, not only of Lelaina, but of the people she lives with and the people she hangs out with. There is her roommate, and soon to be GAP manager, Vickie, who has slept with sixty-six men, whose names she can't all remember. But she does have an knack for killer one-liners.  He doesn't do much except set up Vickie's jokes. And then there is the obnoxious temporary roommate, Troy, who does nothing but hang around the house and insult everyone around him. But he saves his meanest for Lelaina, and by that we are supposed to conclude that he loves her.
Before the "cliche" police come out in full force, it should be said that this breaks the standard lines in more way than one. First of all, these two aren't enemies. They have even slept together once, although Lelaina claims she was drunk at the time. Second, they establish very early that they are attracted to each other. The question is not whether they are willing to admit it, as is normal, but more of whether she can do better than him.
Now, without going into detail, the second half of the movie was almost too realistic. It shows a group of people who have no sense of direction, living one dimensional lives, if that. They are not searching for salvation, they are merely trying to survive. There is no feeling that the conclusion is final, or that the characters will be happy for ever after.
This movie does invite criticism, some warranted and some not. First, the warranted. It does seem unrealistic that a class valedictorian would have difficulty with addition (as Lelaina does--costing her a job opportunity) or would be unable to define irony. The movie would have been better had they let Lelaina be a good, but not great student. And the unwarranted intrusion of rich parents really sapped some of her futility. She should have been drawn more generically.
The unfair criticism, as I see it, is this. There is the usual backlash against happy endings, and complaints that Lelaina chooses the wrong man. It seems to me that the two complaints are contradictory. As for the second, it is a double standard, that we want reality, but we also want her to be happy. Sometimes people do pick the wrong partner. Her decision is predictable because it is in keeping with her character. The other criticism, that the movie failed to be fresh after a while, while true, is not as much a criticism as a comment of the flow of the movie. There were two jobless characters, one who thought she was dying of AIDS and one who was kicked out of his house. Fresh might have been the wrong mood for the movie to take.
So, overall 3.5*/4 (An eye opener for anyone who thought John Hughes was realistic)
.
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configuration object for configuring the diffrect aspects of each snowflake
start the animation
resets the flake to the inital position and restart the animation
set the color for each inidividual spec
setColor('red')
setColor('#ff0000')
setColor('rgb(255,0,0)')
Creates new clone of the snowflake svg element
call this and set configurations you need to apply to all snowflakes eg:-
SnowFlake.config({color: white})
will set all snowflakes to white
you can pass any params thats defined in the SnowFlakeConfig
Generated using TypeDoc
pass configuration param to tweek each flake individually
will make two flakes one red and one yellow


Lecture 21: OTU picking and microbial ecology (continued)¶
- De novo OTU picking: reads are clustered based on similarity to one another.
Pros: All reads are clustered
Cons: Not easily parallelizable; OTUs may be defined by erroneous reads.
- Closed-reference OTU picking: reads are clustered based on similarity to sequences in a reference database; reads that don’t match something in the database are discarded.
Pros: Built-in quality filter; easily parallelizable; OTUs are defined by high-quality, trusted sequences
Cons: Reads that don’t hit reference dataset are excluded, so you can never observe new OTUs
Open-reference OTU picking: reads are clustered based on similarity to sequences in a reference database; reads that don’t match something in the database are then clustered de novo and the resulting sets of OTUs are merged.
Pros: All reads are clustered; partially parallelizable
Cons: Only partially parallelizable; mix of high quality sequences defining OTUs (i.e., the database sequences) and possible low quality sequences defining OTUs (i.e., the sequencing reads)


Check the emails of the voters you want to re-send links to. By default voters who voted are un-checked.
{{=A('Back to Edit',_href=URL('edit',args=election.id),_class="btn")}}
{{=T('Voters who have not yet voted')}}
{{form.element('input[type=submit]').add_class('btn btn-primary')}}
{{=form}}
{{if failures:}}
{{=T('We failed to email the following voters')}}
{{for failure in failures:}}
- {{=failure}}
{{pass}}
{{pass}}


Rails <IP_ADDRESS> (June 26, 2023)
- No changes.
Rails <IP_ADDRESS> (March 13, 2023)
- No changes.
Rails <IP_ADDRESS> (January 24, 2023)
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Rails <IP_ADDRESS> (January 17, 2023)
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Rails 6.1.7 (September 09, 2022)
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Rails <IP_ADDRESS> (July 12, 2022)
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Rails 6.1.6 (May 09, 2022)
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Rails <IP_ADDRESS> (April 26, 2022)
- No changes.
Rails 6.1.5 (March 09, 2022)
Add
attachments
to the list of permitted parameters for inbound emails conductor.When using the conductor to test inbound emails with attachments, this prevents an unpermitted parameter warning in default configurations, and prevents errors for applications that set:
config.action_controller.action_on_unpermitted_parameters = :raise
David Jones, Dana Henke
Rails <IP_ADDRESS> (March 08, 2022)
- No changes.
Rails <IP_ADDRESS> (February 11, 2022)
- No changes.
Rails <IP_ADDRESS> (February 11, 2022)
- No changes.
Rails <IP_ADDRESS> (December 15, 2021)
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Rails <IP_ADDRESS> (December 14, 2021)
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Rails <IP_ADDRESS> (December 14, 2021)
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Rails <IP_ADDRESS> (August 19, 2021)
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Rails 6.1.4 (June 24, 2021)
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Rails <IP_ADDRESS> (May 05, 2021)
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Rails <IP_ADDRESS> (March 26, 2021)
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Rails 6.1.3 (February 17, 2021)
- No changes.
Rails <IP_ADDRESS> (February 10, 2021)
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Rails 6.1.2 (February 09, 2021)
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Rails 6.1.1 (January 07, 2021)
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Rails 6.1.0 (December 09, 2020)
Change default queue name of the incineration (
:action_mailbox_incineration
) and routing (:action_mailbox_routing
) jobs to be the job adapter's default (:default
).Rafael Mendonça França
Sendgrid ingress now passes through the envelope recipient as
X-Original-To
.Mark Haussmann
Update Mandrill inbound email route to respond appropriately to HEAD requests for URL health checks from Mandrill.
Bill Cromie
Add way to deliver emails via source instead of filling out a form through the conductor interface.
DHH
Mailgun ingress now passes through the envelope recipient as
X-Original-To
.Rikki Pitt
Deprecate
Rails.application.credentials.action_mailbox.api_key
andMAILGUN_INGRESS_API_KEY
in favor ofRails.application.credentials.action_mailbox.signing_key
andMAILGUN_INGRESS_SIGNING_KEY
.Matthijs Vos
Allow easier creation of multi-part emails from the
create_inbound_email_from_mail
andreceive_inbound_email_from_mail
test helpers.Michael Herold
Fix Bcc header not being included with emails from
create_inbound_email_from
test helpers.jduff
Add
ApplicationMailbox.mailbox_for
to expose mailbox routing.James Dabbs
Please check [6-0-stable]) for previous changes.


The Colchester Eagles Dodgeball club was founded to bring together a group of friends and dodgeball amateurs to play for laughs and thrills...
Read more
Do you feel the need, the need for...dodging? Then come, join us every Sunday.
Find out more
We want to hear from you, send us your queries via email, phone or facebook


Zim dollar-Bond coin selfie man is a gambler who won $42 000: CBZ
CBZ bank has revealed that the controversial $42 000 bond coin bucket money was drawn by a gambling house which then used the money to pay a punter who had struck it rich while betting.
The bank further alleges that the image which went viral on social media was that of the punter celebrating his good fortune with his payout. This comes after the RBZ threatened to take action against banks diverting money to the black market.
In a statement issued on social media CBZ said the withdrawal fulfilled regulatory requirements:
STATEMENT ON PICTURES OF BIN CONTAINER WITH BOND COINS CIRCULATING ON SOCIAL MEDIA
In response to social media publications circulating, we would like to advise members of the public that CBZ Bank Limited conducted internal investigations regarding the issue raised.
The results confirm that a withdrawal of $1 and $0.25 bond coins took place at one of our Branches. The withdrawal, by a corporate customer, in the gaming business, was an authorised transaction that fulfilled regulatory requirements.
The funds in the container were a display of a subsequent pay-out to a punter at the aforementioned corporate customers’ premises.


General Dataset Guidelines
These instructions apply to all of the modeling queries EXCEPT convolutional_query()
- ONLY the instruction parameter is required for the queries.
- When providing your instruction make sure that you're describing a column. For example: if you want the dataset to use a column named median_house_value as the target, make your instruction "please estimate the median house value". If you want your target to be number_of_households, make your instruction "In Baltimore, model the number of households".
- You can also just pass the column name in as the instruction
- ALL tabular datasets will work with this query. The more parameters you specify, the more optimized your model will be.
neural_network_query()
Automatically fits a neural network to your dataset. Target detection, preprocessing, and scoring are done by default.
| Arguments | |
| instruction=None | An English language statement that represents the task you would like to be completed. eg: 'predict the median house value' or 'please estimate the number of households'. Should correspond to a column in the dataset. |
| ca_threshold=0.2 | Changes the proportion at which correspondence analysis is applied. This deals with reducing the number of categorical features that are one-hot-encoded. |
| drop=[] | Columns to drop manually, drop columns with links, weirdly formatted numbers, and others. |
| text=[] | Represents any columns that contain long pieces of text to be embedded into vectors. |
| preprocess=True | Whether you want your dataset to be intelligently preprocessed |
| test_size=0.2 | The proportion of your entire dataset that is used for testing. |
| random_state=49 | The state ticker you want to be set at. |
| epochs=50 | Number of epochs. This is for every model that's created in the process. |
| generate_plots=True | Whether you want libra to create accuracy and loss plots for you. |
| save_model=False | Whether the model is saved in a .json and .h5 file. |
| save_path='current_directory' | Where do you want the save_model information to be stored. Default is current working directory. |
new_client = client('path_to_dataset') new_client.neural_network_query('Please estimate the number of households.') new_client.models['regression_ANN'].plots() #access plots
convolutional_query()
Automatically fits a Convolutional Neural Network to your dataset. Images are automatically interpolated to the median height and wiedth. Three types of dataset structures are supported. Read below for more information.
| Arguments | |
| instruction=None | An English language statement that represents the task you would like to be completed. eg: 'predict the median house value' or 'please estimate the number of households'. Should correspond to a column in the dataset. Only neccesary if read_mode is 'csvwise'. |
| image_column=None | Only used when read_mode is ‘csvwise’. The column title containing the images. |
| read_mode=distinguisher() | Identifies the format in which data the present in. If none is specified then the query will automatically identify the format of your data. Note that only three types of formats are currently supported (listed in the table below). |
| new_folders=True | This query will automatically crop all images to an intelligent size and create new folders with these images. If you would like it to replace your original images then set this to false. |
| image_column=None | If you're using pathwise from a csv, you can by default use a column in the set as the path location. |
| test_size=0.2 | Represents the size of the testing set. |
| preprocess=True | Whether you want your dataset to be intelligently preprocessed. |
| augmentation=True | Magnifies dataset to add small variation to images before training in the model. |
| custom_arch=None | File path to a custom Keras model architecture configuration in JSON format. |
| pretrained=None | Load a state-of-the-art model architecture through dictionary with keys 'arch' and 'weights'. Current values supported for 'arch' key are 'vggnet16', 'vggnet19', 'resnet50', 'resnet101', 'resnet152'. Possible values for 'weights' key include 'imagenet' and 'random'. |
| epochs=10 | Number of epochs for every model attempted. |
| height=None | Resizes all images to the given height. If left as None, will resize images’ to the median height. |
| width=None | Resizes all images to the given width. If left as None, will resize images’ to the median width. |
| verbose=0 | Whether inner computation is displayed. This will spam the console box. |
newClient = client('path_to_directory_with_image_folders') newClient.convolutional_query("Please classify my images")
| Read Modes | ||
| 'setwise' | Directory consists of a ‘training_set’ and ‘testing_set’ folder both containing classification folders with images inside. | |
| 'classwise' | Directory consists of classification folders with images inside. | |
| 'csvwise' | Directory consists of image folders and a CSV file that has an image column. |
svm_query()
Automatically fits a support vector machine to your dataset. Only classification is supported. SVRegressor will be coming soon. Target detection, preprocessing, and scoring are done by default.
| Arguments | |
| instruction | An English language statement that represents the task you would like to be completed. eg: 'predict the median house value' or 'please estimate the number of households'. Should correspond to a column in the dataset. |
| test_size=0.2 | The proportion of your entire dataset that is used for testing. |
| text=[] | Represents any columns that contain long pieces of text to be embedded into vectors. |
| random_state=49 | The state ticker you want to be set at |
| kernel='linear' | The type of kernel trick you want to be used. Options include 'rbf' and 'poly'. |
| preprocess=True | Whether you want your dataset to be intelligently preprocessed |
| drop=[] | Columns to drop manually, drop columns with links, weirdly formatted numbers, and others. |
| degree=3 | Degree of the polynomial kernel function. Only used by 'poly' kernel. |
| gamma='scale' | Kernel coefficient for 'rbf', 'poly' and 'sigmoid'. |
| coef0=0.0 | Independent term in kernel function. It is only significant in ‘poly’ and ‘sigmoid’. |
| max_iter=1 | Hard limit on iterations within solver, or -1 for no limit. |
newClient = client('path_to_file') newClient.svm_query('Model the type of credit card')
nearest_neighbor_query()
Automatically fits a neural network to your dataset. Target detection, preprocessing, and scoring are done by default.
| Arguments | |
| instruction | An English language statement that represents the task you would like to be completed. eg: 'predict the median house value' or 'please estimate the number of households'. Should correspond to a column in the dataset. |
| test_size=0.2 | The proportion of your entire dataset that is used for testing. |
| text=[] | Represents any columns that contain long pieces of text to be embedded into vectors. |
| random_state=49 | The state ticker you want to be set at |
| preprocess=True | Whether you want your dataset to be intelligently preprocessed. |
| drop=[] | Columns to drop manually, drop columns with links, weirdly formatted numbers, and others. |
| min_neighbors=3 | The minimum number of nearest neighbors to calculate the loss with. |
| max_neighbors=3 | The maximum number of nearest neighbors to calculate the loss with. |
| leaf_size=30 | Leaf size passed to BallTree or KDTree. This can affect the speed of the construction and query, as well as the memory required to store the tree. |
| p=2 | Parameter for the Minkowski metric from sklearn.metrics.pairwise.pairwise_distances. When p = 1, this is equivalent to using manhattan_distance (l1), and euclidean_distance (l2) for p = 2. |
| algorithm='auto' | Algorithm used to compute the nearest neighbors: ‘ball_tree’ will use BallTree, ‘kd_tree’ will use KDTree, ‘brute’ will use a brute-force search, ‘auto’ will attempt to decide the most appropriate algorithm based on the values passed to fit method. |
newClient = client('path_to_file') newClient.nearest_neighbors_query('Model the type of credit card')
decision_tree_query()
Automatically fits a decision tree algorithm to your dataset. Target detection, preprocessing, and scoring are done by default.
| Arguments | |
| instruction | An English language statement that represents the task you would like to be completed. eg: 'predict the median house value' or 'please estimate the number of households'. Should correspond to a column in the dataset. |
| preprocess=True | Whether you want your dataset to be intelligently preprocessed. |
| test_size=0.2 | The proportion of your entire dataset that is used for testing. |
| text=[] | Represents any columns that contain long pieces of text to be embedded into vectors. |
| drop=[] | Columns to drop manually, drop columns with links, weirdly formatted numbers, and others. |
| criterion='gini' | The function to measure the quality of a split. Supported criteria are “gini” for the Gini impurity and “entropy” for the information gain. |
| splitter='best' | The strategy used to choose the split at each node. Supported strategies are “best” to choose the best split and “random” to choose the best random split. |
| max_depth=None | The maximum depth of the tree. If None, then nodes are expanded until all leaves are pure or until all leaves contain less than min_samples_split samples. |
| min_samples_split=2 | The minimum number of samples required to split an internal node. |
| min_weight_fraction_leaf=0.0 | The minimum weighted fraction of the sum total of weights (of all the input samples) required to be at a leaf node. |
| max_leaf_nodes=None | Grow a tree with max_leaf_nodes in best-first fashion. Best nodes are defined as relative reduction in impurity. |
| min_impurity_decrease=0.0 | A node will be split if this split induces a decrease of the impurity greater than or equal to this value. |
| ccp_alpha=0.0 | Complexity parameter used for Minimal Cost-Complexity Pruning. The subtree with the largest cost complexity that is smaller than ccp_alpha will be chosen. |
newClient = client('path_to_file') newClient.decision_tree_query('please estimate ocean proximity')
kmeans_clustering_query()
Automatically fits a clustering algorithm to your dataset. Target detection, preprocessing, and scoring are done by default.
| Arguments | |
| preprocess=True | Whether you want your dataset to be intelligently preprocessed |
| generate_plots=True | Whether you want libra to create accuracy and loss plots for you. |
| drop=[] | Columns to drop manually, drop columns with links, weirdly formatted numbers, and others. |
| base_clusters=2 | Base number of clusters that will be tested. From this parameter provided, more and more clusters will be tested until an optimal number is found. |
newClient = client('path_to_file') newClient.kmeans_clustering_query(preprocess=True, generate_plots=True, drop=[])


Exploring the Results
Start exploring the data by selecting one of the categories below. “Response Rate” will take you to a page where you can view how many students, parents/guardians, teachers, and principals took the survey.
For responses directly related to the District’s Anchor Goals, choose the “Highlights” icon. “Topics” will tell you more about the five main survey topics and display a report that shows topic scores. “Question Explorer” allows you to choose a question and explore the findings. “About” provides background information about the survey.
As you review this information, you may want to focus on response rates, responses across the key survey topics (e.g., "school climate"), or responses to individual questions (including select focus questions tied to the District’s Anchor Goals). Use the green selection bar on the top of your screen to make school, network, and other student group selections.
Click one of the following to get started!
More Information
The District-wide Survey program is managed by the School District of Philadelphia’s Office of Research and Evaluation. To learn more, click the button below or contact the survey team at schoolsurveys@philasd.org.


#assign gradle="active">
See the example at: examples/javalin-gradle-java-basic/build.gradle
Use Gradle version 5.2 or greater which has better support for annotation processing.
Also review the IntelliJ IDEA Gradle settings - see below.
Add dinject as a compile dependency and dinject-generator as an annotation processor.
dependencies { ... compile('io.dinject:dinject:2.2') annotationProcessor('io.dinject:dinject-generator:2.2') ... }
See example at: https://github.com/dinject/examples/blob/master/basic-di-kotlin-maven/pom.xml
For use with Kotlin we register dinject-generator as a kapt
processor
to the Kotlin compiler rather than annotationProcessor.
dependencies { ... kapt('io.dinject:dinject-generator:2.2') ... }
We want to delegate the build
to Gradle (to properly include the annotation processing)
so check our IDEA settings.
Ensure that Enable annotation processing
is disabled so
that the build is delegated to Gradle (including the annotation processing):
Make sure Build and run
is delegated to Gradle.
Optionally set Run tests using to Gradle
but leaving it to IntelliJ IDEA should be ok.


this hotkey will put all your stack into the bet amount box. for this hotkey to work
you have to go to PokerStars options and check the setting Options --> Bet Slider Options
--> Other --> Jump To Clicked Position and have to fill in the point
BetSliderEnd in your templates.


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"If shelters are looking to have more success, last year makes the case for reduced intake." - Marie Abbondanza, Shelter Animals Count
During the onset of the pandemic’s recovery, headlines about pet owners returning their beloved animals back to shelters caused a frenzy. But recent data doesn’t support that trend. In fact, shelters are following normal pre-pandemic trends this year and that is partially accredited to lower rates of intake. Shelters that use their resources to care for fewer animals are seeing higher success and steady adoption rates.
Shelter Animals Count, a nonprofit organization that produces The National Database of shelter animal statistics, released their COVID-19 Impact Report last month. The report compares data from the first six months (Jan. to June) of the last three years: 2019, 2020, and 2021. The Report represents data collected from 341 shelter and rescue organizations as of July 12, 2021.
In 2019, the adoption rate was 53%. By 2020, it increased to 58%. In 2021, it remained 58%.
In 2019, the shelter euthanasia rate was 11%. By 2020, it decreased to 8%. In 2021, it decreased to 7%.
In 2019, the relinquish by owner rate was 53%. By 2020, it decreased to 47%. In 2021, it remained 47%.
In 2019, the adoption rate was 18%. By 2020, it increased to 19%. In 2021, it remained 19%.
Summary: Intake
Categories of intake: stray, relinquish by owner, transfer in, other intake, and owner-intended euthanasia.
The report indicates that 2021 did not see a major influx of animals entering shelters. Instead, only a 0.56% increase in intake from 2020 was reported.
Summary: Live Outcomes
Categories of live outcomes: adoption, transfer out, return to owner, return to field, and other live outcomes.
While keeping in mind that fewer pets are coming into shelters, the pets that do come are seeing more of them be adopted.
Summary: Other Outcomes
Other outcome: shelter euthanasia, owner-intended euthanasia, died in care and lost.
Shelter euthanasia dropped -16.9% from the height of the pandemic and -53.9% since pre-pandemic.


Sample text. Click to select the text box. Click again or double click to start editing the text.
350 5th Ave, New York, NY 10118
1<PHONE_NUMBER>
<EMAIL_ADDRESS>created with


Gustav Engström
PB-workshop, 2016
- About 85 percent of Earth’s ice-free lands is covered by vegetation. Of the total ice-free land area (13,300 Mha), ≈ 4,000 Mha is suitable for rain-fed agriculture.
- The global non-cultivated area that is suitable for cropping while being non-forested, non-protected, and scarcely populated is estimated at 445 Mha globally.
(Lambin and Meyfroidt, 2010)
The global expansion of croplands since 1850 has converted some 6 million km2 of forests/woodlands and 4.7 million km2 of savannas/grasslands/steppes. (Ramankutty and Foley, 1999).
Conversion of forests and other ecosystems to agricultural land has occurred at an average rate of 0.8% yr-1 over the past 40–50 years and is the major global driver behind loss of ecosystem functioning and services (MEA 2005a).
|
|
| Lambin and Meyfroidt (2010) |
|
- 2009: no more than 15% of the global ice-free land surface should be converted to cropland = approximately 400 Mha further expansion. - 2015: The control variable has been changed from the amount of cropland to the amount of forest cover remaining. The biome-level boundary for tropical and boreal forests have been set at 85%, and the boundary for temperate forests has been proposed at 50% of potential forest cover, reflecting their respective influences on the climate system. |
Two strategies are commonly proposed to control deforestation (Lambin and Meyfroidt, 2010):
...both are generally considered to be under the control of national policies.
A mechanism that has been under negotiation by the United Nations Framework Convention on Climate Change (UNFCCC) since 2005, with the objective of mitigating climate change through reducing net emissions of greenhouse gases through enhanced forest management in developing countries.
- One key issue for the implementation of REDD is how to address leakage of emissions. Without full participation of all countries in a forest conservation scheme, emission reductions in one location could result in increased emissions elsewhere.
- Another risk associated with a global REDD scheme that so far has not been quantified in the literature is the shift of land-use pressures to non-forest ecosystems (non-forest leakage) (Popp etal 2014).
Land use zoning for nature conservation in a country may displace population and land use within that country or abroad, via migrations or by increasing imports of agricultural or wood products, thus shifting/increasing pressure on natural ecosystems elsewhere (Lambin and Meyfroidt, 2010).
The scope for yield growth to spare land for nature by lowering food prices can be undermined if lower prices stimulate demand and if higher yields raise profits, encouraging an increase in land-use for agricultural expansion (Lambin and Meyfroidt, 2010, Phalan et.al. 2016).
Agricultural intensification or land use zoning in one country may trigger compensating changes in trade flows and, thus, affect indirectly land use in other countries. However, trade also carries the potential to increase global land use efficiency by allowing for regional specialization in land use and productivity increases as a response to a global shortage of productive land (Lambin and Meyfroidt, 2010).
When a bioenergy crop replaces a natural ecosystem, there is a direct land conversion. When it replaces a food crop in a field already under cultivation, or when crop production is diverted from the food market to the bioenergy market, the supply of the food crop decreases. The market price for the replaced crop thus increases, thus causing more land to be allocated to that crop, which could negate climate benefits from biofuels (Lambin and Meyfroidt, 2010)
USDA 2014 reports effects of a change in per capita income on global agricultural variables. For a 10-percent increase in global per capita income, consumption and production of major crops is projected to increase by approximately 3 percent. (Crop yield increases by 3 percent in this scenario, and cropland area increases by less than 1 percent.)
The demand for staple crops for human consumption is relatively inelastic, the global demands for biofuels, meat, and luxury goods such as coffee are elastic (Lambin and Meyfroidt, 2010).


Choose image and resize to 800x400, with fix image orientation
Circle->Grayscale->Pizelize->Rotate
Choose image and resize to 800x400 with red bg
Choose image to convert in circle with res 400x400
Choose image to rotate
Choose image to graysacle
Choose image to pixelize
Choose image to blur
Choose image for crop to 200x300
Choose image for drawLine
Choose image for drawPolygon
Choose image for drawRectangle
Choose image for drawText
Choose image for perspective


{# Section for label parameters for output of publications. #}
{# Label output: single per record, or all in one record. #}
Check the box to output one single label per record.
If a publication has more than one label, it will then be
represented by multiple records.
If unchecked, all labels will be concatenated, and
one single record will be output per publication.


We have three interactive charts available:
With this visualization, we can see the total number of natural disasters that occur each year, broken down by type. By clicking on the labels within the legend, you can add and remove natural disaster types from the visualization.


You might encounter elimination puzzles like this one in Mensa-style books. As mental calisthenics, they have a lot to recommend them.
Andrew, Carol, Jessica, Luke, and Tommy are sitting around a circular table. Carol is 12 years older than her neighbor to the left. Tommy is five years older than his neighbor to the right. Jessica is 14 years older than her neighbor to the left. Luke is five years younger than his neighbor to the left. By age, from youngest to oldest, they are ordered as follows: Luke, Tommy, Andrew, Jessica, and Carol. Luke is 16 and Carol is 40. The total of the ages is 135. In which order are the people sitting (starting with Tommy and then proceeding in clockwise order) and what are their ages? First try to do this on your own; when you’ve solved it or are ready for help, read on.
Start with the most specific facts: Luke is 16 and Carol is 40, totaling 56. This implies that the ages of Tommy, Andrew, and Jessica add up to 79 (135 - 56 = 79). Further, we know that Tommy and Luke are neighbors because Luke’s left neighbor is 21, so if that’s not Tommy, then both Tommy and Luke’s left neighbors are 21 or less (because Tommy is second youngest after Luke). This leaves 79 - 42 = 37 left for the last person. But Carol is 12 years older than her neighbor to the left, so someone must be 28 years old. Hence, in clockwise order we must have Tommy, then Luke. This means that Tommy, Luke, and Carol total 21 + 16 + 40 = 77.
Therefore, Jessica and Andrew total 135 - 77 = 58. Because Jessica is known to be older than Andrew and the person to the left of Carol must be 28 years old, Andrew is 28 and Jessica is 30.
The ages then lend insight to the seating. Ordering Tommy, Luke, and then Carol is impossible because Carol is 40. This implies that Carol’s left neighbor is Andrew, since we know he is 28.
This leaves two possibilities:
Tommy, Luke, Jessica, Andrew, Carol
Tommy, Luke, Andrew, Carol, Jessica
But in fact only the first one is possible because Jessica is 14 years older than her neighbor to the left. That can only be Luke. So we conclude:
Tommy(21), Luke (16), Jessica (30), Andrew (28), Carol(40)
What would you do if you wanted to solve many puzzles like this in a short time? When the numbers are this small, I suggest laying out all orders and then filling in numbers starting with the ones you know to see if they work. In this case, once you arrived at the correct ordering, you would have started with
Tommy, Luke (16), Jessica, Andrew, Carol (40)
and then filled in the other numbers based on constraints:
Tommy (21), Luke (16), Jessica (30), Andrew (28), Carol (40)
When the number of orders is too large, this can’t be done, of course. In that case, you would need to determine local orderings (as we did for Tommy and Luke) and then order the rest.
The point, however, is that the following simple algorithm works really nicely for many puzzles:
for each ordering R try to verify constraints reject R if some constraint fails end for
Replacing difficult analysis by a program that tries lots of possibilities without much human tinkering is a recurrent theme in this chapter. Purists may object that having the computer race through many choices mindlessly is a travesty of thought. My first reaction: So be it. My second: Thought will return soon enough in the form of a better algorithmic approach when the number of cases explodes.


If this text isn't replaced, either there's a bug, or you haven't yet installed. Please make sure to npm install and then gulp build after this has been pulled. Thanks.


Triple H spoke to AEW star after tonight's NXT TakeOver: WarGames
by Abhilash MendheAll Elite Wrestling star Britt Baker was shown on camera tonight at WWE NXT TakeOver: WarGames, when Tommaso Ciampa dropped Adam Cole through a table. During the post-show media call, WWE EVP Triple H talked about the same and stated that he felt bad for putting Baker in that position.
The main event of tonight's NXT TakeOver: WarGames was a 4-on-4 WarGames match, pitting Adam Cole, Roderick Strong, Bobby Fish, and Kyle O'Reilly against Tommaso Ciampa, Keith Lee, Dominik Dijakovic, and Kevin Owens. Adam Cole's girlfriend Britt Baker was in attendance at tonight's event. The match ended when Tommaso Ciampa put Adam Cole through a table and pinned him to secure a victory for his team. Immediately after the spot, the camera panned to several shocked faces of fans in the crowd, one of which was Britt Baker's. Mauro Ranallo acknowledged that Baker is Cole's girlfriend.
Also read: Triple H reveals if has talked to CM Punk
During the media call, Triple H stated that he spoke to Britt Baker after the show and explained that the director searched for the most shocked face in the crowd and found her, not knowing who she was. Triple H also told Sean Ross Sapp of Fightful that he hopes the incident doesn't put Baker in a bad position.
We want to know what you think of the matches that you see on TV! Go to our WWE page here and rate and comment what you thought of them!


The glimpse of our adventures.
It's always fun to be goofy around each other. Well, ususally it's Dang though.
New year resolution: eat less sweet! Yeah right!
“You and meUnderneath the evergreen,Rosy cheeks,Holding hands while the snow is falling” - More than I asked for, Joy Williams
We came here for some dinosaurs fossil. We ended up seeing color changing fossils instead
A little bit of love during our favorite activity. Why not?
Dang can't control himself when food is there.
Dang it Dang


Contracting parties: 24 total: Albania, Algeria, Bulgaria, Croatia, Cyprus, EU, Egypt, France, Greece, Israel, Italy, Japan, Lebanon, Libya, Malta, Monaco, Montenegro, Morocco, Romania, Slovenia, Spain, Syria, Tunisia, Turkey.
Area: The Mediterranean, Black Sea and connecting waters.
Date entered into force: 1952
FAO association: Yes.
FAO statistical area: 37.
Commission’s objectives: “…to promote the development, conservation, rational management and best utilization of living marine resources, as well as the sustainable development of aquaculture in the Region.”
Primary species: Albacore (Thunnus alalunga), Angler (Lophius piscatorius), Atlantic bluefin tuna (Thunnus thynnus), Atlantic mackerel (Scomber scombrus), Beluga (Huso huso), Blackbellied angler (Lophius budegassa), Blackspot seabream (Pagellus bogaraveo), Blue and red shrimp (Aristeus antennatus), Blue shark (Prionace glauca), Blue whiting (Micromesistius poutassou), Bluefish (Pomatomus saltatrix), Bogue (Boops boops), Common cuttlefish (Sepia officinalis), Common dolphinfish (Coryphaena hippurus), Common Pandora (Pagellus erythrinus), Common sole (Solea solea), Common spiny lobster (Palinurus elephas), Danube sturgeon (Acipenser gueldenstaedtii), Deepwater rose shrimp (Parapenaeus longirostris), European anchovy (Engraulis encrasicolus), European eel (Anguilla anguilla), European hake (Merluccius merluccius), European pilchard (Sardine) (Sardina pilchardus), European sprat (Sprattus sprattus), European squid (Loligo vulgaris), Giant red shrimp (Aristaeomorpha foliacea), Horned octopus (Eledone cirrosa), Mediterranean horse mackerel (Trachurus mediterraneus), Musky octopus (Eledone moschata), Norway lobster (Nephrops norvegicus), Pink spiny lobster (Palinurus mauritanicus), Porbeagle (Lamna nasus), Red mullet (Mullus barbatus), Round sardinella (Sardinella aurita), Shortfin mako (Isurus oxyrinchus), Starry sturgeon (Acipenser stellatus), Sturgeon (Acipenser sturio), Surmullet (Mullus surmuletus), Turbot (Psetta maxima), Whiting (Merlangius merlangus).
The x-axes on the figures below represent either current spawning stock biomass (SSB2007) or current biomass (B2007) over either spawning stock biomass at maximum sustainable yield (SSBmsy) or biomass at maximum sustainable yield (Bmsy). The y-axes represent current fishing mortality (F2007) over fishing mortality that produces maximum sustainable yield (Fmsy). Shown below, are stocks: a) Anchovy (northern Adriatic Sea stock, GSA 17); b) Sardine (northern Adriatic Sea stock, GSA 17). For data sources, see Cullis-Suzuki and Pauly (2009).
Time series of the biomass of two main species under management of GFCM; the red dashed lines denote year of establishment of GFCM (1952). Both anchovy and sardine comprise a majority of GFCM’s catch and had the most available data. For data sources see Cullis-Suzuki and Pauly (2009).


--- layout: post title: Reading e-mail with Powershell date: 2014-09-29 12:32:27.000000000 -04:00 categories: blog ---
Occasionally in the DFIR world, you may be called upon to review e-mail files. Sometimes a lot of them. At the same time. (Before, we dive into this subject it is worth mentioning that reviewing a user's e-mail is a sensitive element of our work. Ensure reviewing e-mail falls within the scope of your investigation and you have all of the appropriate permissions before you travel down these paths...)
To get comfortable with interacting with the Outlook API, I recommend working on your own machine first. I recently installed Outlook on my home machine and pointed it at one of my gmail accounts so I could share my thoughts with you good people. On a live system, here is a quick way to grab some quick info from the logged on user's inbox:
These are the properties available for reference from each e-mail object. Most are easily parsed to strings. It is easy to see how this information could be useful to a forensic investigation.
Displaying this information to the screen is often not the best option considering most of us keep hundreds (if not thousands) of e-mails in our inboxes.
This script only works locally as the user that is currently logged on. This is not terribly practical from an investigative standpoint.
Most often you will get email files in the form of a .pst(Personal Storage Table file) or .ost(Offline Storage Table) file, perhaps recovered from a disk image. References:
http://www.forensicswiki.org/wiki/Personal_Folder_File_(PAB,_PST,_OST)
http://office.microsoft.com/en-us/outlook-help/introduction-to-outlook-data-files-pst-and-ost-HA010354876.aspx
This is not a big problem. You will need to open the .pst/.ost file to an instance of Outlook and then proceed as before.
[string]$pstPath = "C:\demobackup.pst"
#if outlook is not running, launch a hidden instance.
$oProc = ( Get-Process | where { $_.Name -eq "OUTLOOK" } )
if ( $oProc -eq $null ) { Start-Process outlook -WindowStyle Hidden; Start-Sleep -Seconds 5 }
$outlook = New-Object -ComObject Outlook.Application
$namespace = $outlook.GetNamespace("MAPI")
$namespace.AddStoreEx($pstPath, "olStoreDefault")
$pstStore = ( $nameSpace.Stores | where { $_.FilePath -eq $pstPath } )
$pstRootFolder = $pstStore.GetRootFolder()
$inboxFolder = $pstRootFolder.Folders|? { $_.Name -eq 'Inbox' }
$inboxFolder.Items|Select SenderEmailAddress,to,subject|Export-Csv C:demoinbox.csv -NoTypeInformation
Sometimes you are not lucky enough to get all of the emails in one outlook object. You may find yourself in a situation where you need to read a bunch of .eml or .msg files. Fear not. I have you covered.
#A lot of the meta is stripped from the eml text format so you can really only display what you have to work with
Get-ChildItem "C:\demo" -Filter *.eml|ForEach-Object{
$adoDbStream = New-Object -ComObject ADODB.Stream
$adoDbStream.Open()
$adoDbStream.LoadFromFile($_.FullName)
$cdoMessage = New-Object -ComObject CDO.Message
$cdoMessage.DataSource.OpenObject($adoDbStream, "_Stream")
$cdoMessage.Fields.Item("urn:schemas:mailheader:to").Value
$cdoMessage.Fields.Item("urn:schemas:mailheader:from").Value
$cdoMessage.Fields.Item("urn:schemas:mailheader:subject").Value
$cdoMessage.Fields.Item("urn:schemas:mailheader:sent").Value
}
This could use a little more polish to make it export to a csv but I am sure you guys can figure out the rest.
Get-ChildItem "c:demo" -Filter *.msg|`
ForEach-Object{
$outlook = New-Object -comobject outlook.application
$msg = $outlook.CreateItemFromTemplate($_.FullName)
$msg | Select senderemailaddress,to,subject,Senton,body|ft -AutoSize
}
SenderEmailAddress To Subject SentOn Body
------------------ -- ------- ------ ----
<EMAIL_ADDRESS><EMAIL_ADDRESS>This is the subject of the e-mail. 9/28/2014 9:47:47 PM This is the body of the e-mail....
I have found the Outlook API to be extremely useful on numerous occasions for this type of work. If anyone has a better/different way to grab this data, I would love to hear it.


See: Description
| Class | Description |
|---|---|
| FileMenu |
File menu JMenu.
|
| FileWindow |
The JFileChooser for choosing a file to open, or to save to.
|
| FilterMenu |
The JMenu for the filters available in the application
|
| FilterPanel_Brightness |
Menu Panel for adjusting the brightness of an image.
|
| FilterPanel_Rotate |
Menu Panel for rotating an image.
|
FileMenu
: JMenu for displaying file menu options such
as "open", "save", and "quit". Open and save will open a FileWindow.FileWindow
: JFileChooser for displaying the open or
save dialogs and holding the last directory used.FilterMenu
: JMenu for displaying the list of
filters that are available. Selecting a filter item may open a FilterPanel:FilterPanel
: Superclass
JPanel for the specific filter windows. Each subclasses contains unique components
for adjusting the filter.FilterPanel_Brightness
:
Subclass of FilterPanel, applies a JSlider to the filter dialog which may be
used to adjust the brightness of the image.FilterPanel_Rotate
:
Subclass of FilterPanel, applies a JButton to the filter dialog which may be
used to rotate the image repeatedly.


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Package projects.suffixtree
Class SuffixTree
- java.lang.Object
-
- projects.suffixtree.SuffixTree
-
public class SuffixTree extends java.lang.Object
SuffixTree is a Suffix Tree that allows you to check whether a string is a substring of another string efficiently
- Author:
- Jason Filippou & Ping Chiang
-
-
Field Summary
Fields Modifier and Type Field Description protected static java.lang.RuntimeException
UNIMPL_METHOD
-
Constructor Summary
Constructors Constructor Description SuffixTree(java.lang.String inputString)
The constructor of the SuffixTree
-
Method Summary
Modifier and Type Method Description java.util.List<java.lang.String>
inOrderTraversal()
Perform an in order traversal of the Suffix tree, but only return the strings represented by the leaf nodes and not the inner nodes This is equivalent to returning a list of suffixes by lexicographical orderboolean
isSubstring(java.lang.String checkString)
Check whether a string is a substring of the internal stringjava.lang.String
longestRepeatedSubstring()
Find the longest repeated substring in the internal stringjava.util.List<java.lang.Integer>
matches(java.lang.String checkString)
Find matches of a string in the internal stringint
nodeCount()
Count the number of nodes in the Suffix treeint
numTimesOccurs(java.lang.String checkString)
Count the number of a times a string is repeated in the internal stringjava.lang.String
shortestRepeatedSubstring(int minLength)
Find the shortest repeated substring in the internal string that has at least a certain length.
-
-
-
Constructor Detail
-
SuffixTree
public SuffixTree(java.lang.String inputString) throws java.lang.IllegalArgumentException
The constructor of the SuffixTree- Parameters:
inputString
- The string that we will build the Suffix tree for- Throws:
java.lang.IllegalArgumentException
- when the argument is null, has length smaller than 1, or includes $ sign
-
-
Method Detail
-
matches
public java.util.List<java.lang.Integer> matches(java.lang.String checkString) throws java.lang.IllegalArgumentException
Find matches of a string in the internal string
- Parameters:
checkString
- the string that we will try to match to the internal string- Returns:
- a list of integers containing the indices where the checkString and the internal string matches
- Throws:
java.lang.IllegalArgumentException
- if checkString is an empty string or null
-
isSubstring
public boolean isSubstring(java.lang.String checkString) throws java.lang.IllegalArgumentException
Check whether a string is a substring of the internal string
- Parameters:
checkString
- the string that we will check against the internal string- Returns:
- true if and only if checkString is a substring of the internal string
- Throws:
java.lang.IllegalArgumentException
- if checkString is an empty string or null
-
numTimesOccurs
public int numTimesOccurs(java.lang.String checkString) throws java.lang.IllegalArgumentException
Count the number of a times a string is repeated in the internal string
- Parameters:
checkString
- the string that we will check against the internal string- Returns:
- the number of times checkString is repeated in the internal string
- Throws:
java.lang.IllegalArgumentException
- if checkString is an empty string or null
-
longestRepeatedSubstring
public java.lang.String longestRepeatedSubstring()
Find the longest repeated substring in the internal string
- Returns:
- the longest repeated string in the internal string When there is a tie, break the tie based on lexicographical order
-
shortestRepeatedSubstring
public java.lang.String shortestRepeatedSubstring(int minLength) throws java.lang.IllegalArgumentException
Find the shortest repeated substring in the internal string that has at least a certain length.
- Parameters:
minLength
- the smallest length that the repeated string has to exceed- Returns:
- the shortest repeated string that has at least length minLength. When there is a tie, break the tie based on lexicographical order
- Throws:
java.lang.IllegalArgumentException
- if the minLength is smaller than or equal to 0
-
nodeCount
public int nodeCount()
Count the number of nodes in the Suffix tree
- Returns:
- the number of nodes in the Suffix tree
-
inOrderTraversal
public java.util.List<java.lang.String> inOrderTraversal()
Perform an in order traversal of the Suffix tree, but only return the strings represented by the leaf nodes and not the inner nodes This is equivalent to returning a list of suffixes by lexicographical order
- Returns:
- a list of suffixes ordered by lexicographical order
-
-


PART I. COMMISSIONERS OF BOUNDARIES
§664-1 Judges as commissioners. The circuit judges of the second, third, and fifth judicial circuits of the State for their respective circuits, and the judge of the land court, for the first judicial circuit, sitting without a jury, shall act as commissioners of boundaries. [L 1894-5, c 14, §1; RL 1925, §552; am L 1932 2d, c 8, §1; RL 1935, §3660; am imp L 1943, c 141; RL 1945, §10201; RL 1955, §234-1; HRS §664-1; am L 1972, c 90, §6(a)]
Note
By §73(c) of the Organic Act laws relating to settlement of boundaries were continued in force until Congress should otherwise provide. Continued in effect on admission of the State by Const. art. XVIII, §9.
Case Notes
Cited: 17 H. 539, 543 (1906); 35 H. 608, 658 (1940).


Hemp Flowers Drying
Calculator
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Made By NiK


2.1 Linear Equation and Linear System
- Linear Equation is an equation that can be written in the form $$ a_1x_1 + …. a_nx_n = b $$
- The above equation can be written as $ \textbf{a}^T \textbf{x} = b $.
- Linear System is a collection of one or more linear equations
-
Identity Matrix : $I$ is a square matrix whose diagonal entries are all 1’s and all the other entries are zeros.
-
Inverse Matrix : $A^{-1}$ is defined such that $A^{-1}A = AA^{-1} = I$
$$A^{-1} = \frac{1}{ad-bc} \begin{bmatrix} d&{-b}\\ -c&a \end{bmatrix}$$
-
Determinant : $det(A) = ad-bc$ determines whether $A$ is invertible
-
If $A$ is non invertible, $A \textbf{x} = \textbf{b}$ will have either no solution or infinitely many solutions.
2.2 Linear Combination
-
For given vectors $\textbf{v}_1,\textbf{v}_2, … \textbf{v}_p $ and given scalars $ c_1, c_2, … c_p $,
$ c_1\textbf{v}_1 + c_2 \textbf{v}_2, … + c_p \textbf{v}_p $ is called Linear Combination of vectors with weights $c$.
- Span : Span{$\textbf{v}_1, … \textbf{v}_p$} is defined as the set of all linear combinations of $\textbf{v}_1, … \textbf{v}_p$. That is, Span is the collection of all vectors that can be written in the form $ c_1\textbf{v}_1 + c_2 \textbf{v}_2, … + c_p \textbf{v}_p $.
- Geometric Description of Span : $ \textbf{v}_1 $ and $\textbf{v}_2$ are in $\mathbb{R}^3$ then Span is the plane in $\mathbb{R}^3$ that contains $ \textbf{v}_1 $ and $\textbf{v}_2$
- Geometric Interpretation of Vector Equation : we can find whether the solution of vector equation exists using the knowledge of span. The solution of below vector equation exists only when $ \textbf{b} \in Span(\textbf{a}_1, \textbf{a}_2, \textbf{a}_3) $.
$$\textbf{a}_1 x_1 + \textbf{a}_2 x_2 + \textbf{a}_3 x_3 = b $$
- Matrix Multiplications as Linear Combinations of Vectors :
$$ \begin{bmatrix} 60&1.7&1 \\ 65&1.6&0 \\ 55&1.8&1 \end{bmatrix} \begin{bmatrix} x_1 \\ x_2 \\ x_3 \end{bmatrix} = \begin{bmatrix} 60\\ 65\\ 55\end{bmatrix} x_1 + \begin{bmatrix} 1.2 \\ 1.6 \\ 1.8 \end{bmatrix} x_2 + \begin{bmatrix} 1 \\ 0 \\ 1 \end{bmatrix} x_3 $$
- Matrix Multiplication as Column Combinations
$$ \begin{bmatrix} 1&1&0 \\ 1&0&1 \\ 1&-1&1 \end{bmatrix} \begin{bmatrix} 1 \\ 2 \\ 3 \end{bmatrix} = \begin{bmatrix} 1\\ 1\\ 1\end{bmatrix}1 + \begin{bmatrix} 1\\ 0\\ -1\end{bmatrix}2 + \begin{bmatrix} 0\\ 1\\ 1\end{bmatrix}3 $$
- Matrix Multiplication as Row Combinations
$$ \begin{bmatrix} 1&2&3 \end{bmatrix} \begin{bmatrix} 1&1&0 \\ 1&0&1 \\ 1&-1&1 \end{bmatrix} = 1 \times \begin{bmatrix} 1&1&0 \end{bmatrix} + 2\times \begin{bmatrix} 1& 0&1 \end{bmatrix} + 3 \times \begin{bmatrix} 1& -1& 1\end{bmatrix}$$
- Matrix Multiplication as Sum of Outer Products
$$\begin{bmatrix} 1&1 \\ 1&-1 \\ 1&1 \end{bmatrix} \begin{bmatrix} 1& 2& 3 \\ 4&5&6 \end{bmatrix} = \begin{bmatrix} 1\\ 1\\ 1\end{bmatrix} \begin{bmatrix} 1& 2& 3\end{bmatrix} + \begin{bmatrix} 1\\ -1\\ 1\end{bmatrix} \begin{bmatrix} 4& 5& 6\end{bmatrix} $$
2.3 Linear Independence
-
The solution for $A \textbf{x} = \textbf{b} $ is unique, when $\textbf{a}_1, \textbf{a}_2, \textbf{a}_3 $ are linearly independent
-
Infinitely many solutions exists when $\textbf{a}_1, \textbf{a}_2, \textbf{a}_3 $ are linearly dependent.
- Linear Independence (practical) : Given a set of vectors $ \textbf {v}_1 , … , \textbf {v}_p $ , check if $ \textbf{v}_j$ can be represented as a linear combination of the previous vectors. If at least one such $ \textbf{v}_j$ is found then $ \textbf {v}_1 , … , \textbf {v}_p $ is linearly dependent.
- Linear Independence (Formal) : Consider $ x_1 \textbf{v}_1 + … + x_p \textbf{v}_p = \textbf{0} $. Obviously, one solution is $\textbf{x} = [0…0]$, which we call a trivial solution. If this is the only solution $ \textbf {v}_1 , … , \textbf {v}_p $ is the only solution. if this system also has other nontrivial solutions, $ \textbf {v}_1 , … , \textbf {v}_p $ are linearly dependent.
2.4 Basis of a Subspace
-
Subspace : is defined as a subset of $\mathbb{R}^n$ closed under linear combination
-
A subspace is always represented as Span {$\mathbf{v}_1 , … , \mathbf{v}_p$}
- Basis of a subspace : a set of vectors that satisfies both of the following
-
Fully spans the given subspace $H$
- Linearly independent (i.e., no redundancy)
- Non-Uniqueness of Basis : In the subspace $H$ (green plane), there other set of linearly independent vectors that span the subspace $H$
- Dimension of Subspace : Even though different basis exist for $H$, the number of vectors in any basis for $H$ will be unique. This number is the dimension of $H$.
- Column Space of Matrix : the subspace could be spanned by the column vector of $A$.
- Rank of Matrix : the dimension of the column space of $A$
Details
$$ A = \begin{bmatrix} 1&0&2 \\ 0&1&1 \\ 1&0&2 \end{bmatrix}, \ \ \text{ Column Vector } a_1, a_2, a_3 = \begin{bmatrix} 1\\ 0\\ 1\end{bmatrix} , \begin{bmatrix} 0\\ 1\\ 0\end{bmatrix}, \begin{bmatrix} 2\\ 1\\ 2\end{bmatrix} $$
-
Column Space is subspace of column vectors from matrix $A$. And we need to find basis vector to get column space.
-
$a_1, a_2$ is independent each other. $a_3$ is represented as linear combination of $a_1, a_2$ . As a result, $a_3$ is dependent on $a_1, a_2$. So, $a_1, a_2$ become basis vector for colum space of $A$
-
Here, Rank of matrix $A$ is two. Because we have only two vectors $a_1, a_2$ that are linearly independent.
-
If a solution for $A \textbf{x} = \textbf{b} $ exists, then $b$ must be on the column space of $A$. Because, $b$ is linear combination of column vectors
$$ Ax = \begin{bmatrix} 1&0&2 \\ 0&1&1 \\ 1&0&2 \end{bmatrix} \begin{bmatrix} x_1\\ x_2\\ x_3\end{bmatrix} = \begin{bmatrix} 1\\ 0\\ 1\end{bmatrix} x_1 + \begin{bmatrix} 0\\ 1\\ 0\end{bmatrix} x_2 + \begin{bmatrix} 2\\ 1\\ 2\end{bmatrix} z_3 = \begin{bmatrix} b_1\\ b_2\\ b_3\end{bmatrix} $$
2.5 Chage of Basis
- Generally, vectors are defined on cartesian coordinate , and it means they are based on standard basis (1,0), (0,1).
- But sometimes, we need vectors on different coordinate (basis) for some reasons like computational efficiency. (e.g. eigendecomposition)
- When the coordinate changes, the vector itself does not changed, but the representation of vector has been changed from (2,2) to (2,0) as in figure below
2.6 Linear Transformation
-
A transformation, function, or mapping maps an input $x$ to an output $y$
-
Domain : Set of all the possible values of $x$
-
Co-Domain : Set of all the possible values of $y$
-
Range : Set of all the output values mapped by each $x$ in the domain
-
Linear Transforamtion : A transformation (or mapping) $T$ is linear if : $$ T(c \mathbf{u}+ d \mathbf{v}) = cT (\mathbf{u}) + dT(\mathbf{v})$$
-
Matrix of Linear Transformation : In general, let $T$ : $ \mathbb{R}^n \rightarrow \mathbb{R}^m $ be a linear transformation. Then $T$ is always written as a matrix-vector multiplication. i.e., $T(\mathbf{x}) = A \mathbf{x}$
-
Here, the matrix $A$ is called the standad matrix of the linear transformation.
2.7 Linear Transformation in Neural Networks
-
Fully Connected Layers can be thought as a linear transformation
-
Fully Connected Layers usually involve a bias term, That’s why we call it an affine layer, not a linear Layers
-
Reference : colah’s blog
2.8 ONTO and ONE-TO-ONE
-
ONTO : A mapping $T$ : $\mathbb{R}^n \rightarrow \mathbb{R}^m$ is said to be onto $\mathbb{R}^m$ if each $\mathbf{b} \in \mathbb{R}^m$ is the image of at least one $x \in \mathbb{R}^n$. That is, the range is equal to the co-domain.
-
ONE-TO-ONE : A mapping $T$ : $\mathbb{R}^n \rightarrow \mathbb{R}^m$ is said to be one-to-one if each $\mathbf{b} \in \mathbb{R}^m$ is the image of at most one $x \in \mathbb{R}^n$. That is, each output vector in the range is mapped by only one input vector, no more than that.


Colombia creates $4.63 billion holding company for some state-tied companies
by ReutersBOGOTA (Reuters) - Colombia's finance ministry said on Monday it has created the Grupo Bicentenario, a holding company comprising some of the companies in which the state has participation with a total capital of 15.8 trillion pesos ($4.63 billion).
The conglomerate will be the country's third-largest, the ministry said, after privately-owned Grupo Aval (CN:GAA) and Grupo Bancolombia (CN:BIC), and will include 16 companies with assets of around 80 trillion pesos.
Grupo Bicentenario will include agrarian bank Banco Agrario, export bank Bancoldex and other financial entities.
The conglomerate will improve the management of state assets, boost efficiency and provide better portfolio management, the government says.
"What we want to do is consolidate a portfolio of services, a portfolio of products," finance vice-minister Luis Alberto Londono told reporters.
Colombia holds stakes in some 105 businesses, including oil company Ecopetrol. The government has ruled out the sale of some stakes to fund next year's budget because of central bank profits and larger tax collection.


Package com.heroiclabs.satori.api
package com.heroiclabs.satori.api
-
ClassDescriptionLog out a session, invalidate a refresh token, or log out all sessions/refresh tokens for a user.Log out a session, invalidate a refresh token, or log out all sessions/refresh tokens for a user.Authenticate against the server with a refresh token.Authenticate against the server with a refresh token.Authentication requestAuthentication requestA single event.A single event.Publish an event to the serverPublish an event to the serverAn experiment that this user is partaking.An experiment that this user is partaking.All experiments that this identity is involved with.All experiments that this identity is involved with.Feature flag available to the identity.Feature flag available to the identity.All flags available to the identityAll flags available to the identityRequest to get all experiments data.Request to get all experiments data.Request to get all flags data.Request to get all flags data.Request to get all live events.Request to get all live events.Enrich/replace the current session with a new ID.Enrich/replace the current session with a new ID.A single live event.A single live event.List of Live events.List of Live events.Properties associated with an identity.Properties associated with an identity.The GRPC protocol service for Satori built with GRPC.The GRPC protocol service for Satori built with GRPC.The GRPC protocol service for Satori built with GRPC.The GRPC protocol service for Satori built with GRPC.The GRPC protocol service for Satori built with GRPC.A session.A session.Update Properties associated with this identity.Update Properties associated with this identity.


--- layout: post title: Opus 36 date: 2009-12-21 20:56:40.000000000 +01:00 type: post parent_id: '0' published: true password: '' status: publish categories: - humble thoughts tags: - beauty - music - piano meta: _edit_last: '850381' author: login: stmaarten email<EMAIL_ADDRESS>display_name: stmaarten first_name: '' last_name: '' ---
Opus 36 by Dustin O'Halloran
A beautiful song by Dustin O'Hallaran, a songtrack of "Marie Antoinette", a film directed by Sofia Coppola.


Functions | |
| static uint32_t | CSL_udmapCppi5GetDescType (const void *pDesc) |
| Get the descriptor type. More... | |
| static void | CSL_udmapCppi5SetDescType (void *pDesc, uint32_t descType) |
| Set the descriptor type. More... | |
| static uint32_t | CSL_udmapCppi5GetPktLen (const void *pDesc) |
| Get the packet length. More... | |
| static void | CSL_udmapCppi5SetPktLen (void *pDesc, uint32_t descType, uint32_t pktLen) |
| Set the packet length. More... | |
| static uint64_t | CSL_udmapCppi5GetBufferAddr (const CSL_UdmapCppi5HMPD *pDesc) |
| Get the buffer address. More... | |
| static uint32_t | CSL_udmapCppi5GetBufferLen (const CSL_UdmapCppi5HMPD *pDesc) |
| Get the buffer length. More... | |
| static void | CSL_udmapCppi5SetBufferAddr (CSL_UdmapCppi5HMPD *pDesc, uint64_t physBufferAddr) |
| Set the buffer address. More... | |
| static void | CSL_udmapCppi5SetOrgBufferAddr (CSL_UdmapCppi5HMPD *pDesc, uint64_t physBufferAddr) |
| Set the original buffer address. More... | |
| static void | CSL_udmapCppi5SetBufferLen (CSL_UdmapCppi5HMPD *pDesc, uint32_t bufferLenBytes) |
| Set the buffer length. More... | |
| static void | CSL_udmapCppi5SetOrgBufferLen (CSL_UdmapCppi5HMPD *pDesc, uint32_t bufferLenBytes) |
| Set the original buffer length. More... | |
| static void | CSL_udmapCppi5LinkDesc (CSL_UdmapCppi5HMPD *pDesc, uint64_t physBufferDescAddr) |
| Link a buffer descriptor to a descriptor. More... | |
| static bool | CSL_udmapCppi5IsEpiDataPresent (const void *pDesc) |
| Is the EPI block present in the descriptor? More... | |
| static void | CSL_udmapCppi5SetEpiDataPresent (void *pDesc, bool bEpiDataPresent) |
| Set indicator if the EPI block is present in the descriptor. More... | |
| static uint32_t * | CSL_udmapCppi5GetEpiDataPtr (const void *pDesc) |
| Return pointer to EPI block data. More... | |
| static int32_t | CSL_udmapCppi5RdEpiData (const void *pDesc, uint32_t *pTsInfo, uint32_t *pSwInfo0, uint32_t *pSwInfo1, uint32_t *pSwInfo2) |
| Read the EPI block data. More... | |
| static void | CSL_udmapCppi5WrEpiData (const void *pDesc, uint32_t tsInfo, uint32_t swInfo0, uint32_t swInfo1, uint32_t swInfo2) |
| Write the EPI block data. More... | |
| static uint32_t | CSL_udmapCppi5GetPsDataLoc (const void *pDesc) |
| Get the location of the protocol-specific data. More... | |
| static void | CSL_udmapCppi5SetPsDataLoc (void *pDesc, uint32_t psLoc) |
| Set the location of the protocol-specific data. More... | |
| static uint32_t | CSL_udmapCppi5GetPsDataLen (const void *pDesc) |
| Get the number of bytes of protocol-specific data. More... | |
| static void | CSL_udmapCppi5SetPsDataLen (void *pDesc, uint32_t psDataLen) |
| Set the number of bytes of protocol-specific data. More... | |
| static uint64_t | CSL_udmapCppi5GetPsDataAddr (const void *pDesc, bool bInSopBuf, bool bEpiPresent) |
| Return address of the protocol-specific data. More... | |
| static uint32_t | CSL_udmapCppi5GetSrcTag (const void *pDesc) |
| Get source tag. More... | |
| static uint32_t | CSL_udmapCppi5GetDstTag (const void *pDesc) |
| Get destination tag. More... | |
| static void | CSL_udmapCppi5SetSrcTag (void *pDesc, uint32_t srcTag) |
| Set source tag. More... | |
| static void | CSL_udmapCppi5SetDstTag (void *pDesc, uint32_t dstTag) |
| Set destination tag. More... | |
| static uint32_t | CSL_udmapCppi5GetErrorFlags (const void *pDesc) |
| Get error flags. More... | |
| static uint32_t | CSL_udmapCppi5GetPsFlags (const void *pDesc) |
| Get ps flags. More... | |
| static void | CSL_udmapCppi5SetPsFlags (void *pDesc, uint32_t psFlags) |
| Set ps flags. More... | |
| static uint32_t | CSL_udmapCppi5GetPktType (const void *pDesc) |
| Get packet type. More... | |
| static void | CSL_udmapCppi5SetPktType (void *pDesc, uint32_t pktType) |
| Set packet type. More... | |
| static void | CSL_udmapCppi5GetIds (const void *pDesc, uint32_t *pPktId, uint32_t *pFlowId) |
| Get IDs. More... | |
| static void | CSL_udmapCppi5SetIds (void *pDesc, uint32_t descType, uint32_t pktId, uint32_t flowId) |
| Set IDs. More... | |
| static void | CSL_udmapCppi5GetReturnPolicy (const void *pDesc, uint32_t *pRetPolicy, uint32_t *pEarlyReturn, uint32_t *pRetPushPolicy, uint32_t *pRetQnum) |
| Get descriptor return policy information. More... | |
| static void | CSL_udmapCppi5SetReturnPolicy (void *pDesc, uint32_t descType, uint32_t retPolicy, uint32_t earlyReturn, uint32_t retPushPolicy, uint32_t retQnum) |
| Set descriptor return policy information. More... | |
| static uint32_t | CSL_udmapCppi5MonoGetDataOffset (const CSL_UdmapCppi5MMPD *pDesc) |
| Get MONO descriptor data offset. More... | |
| static void | CSL_udmapCppi5MonoSetDataOffset (CSL_UdmapCppi5MMPD *pDesc, uint32_t dataOffset) |
| Set MONO descriptor data offset. More... | |
| static void | CSL_udmapCppi5TrGetReload (const CSL_UdmapCppi5TRPD *pDesc, uint32_t *pReloadEnable, uint32_t *pReloadIdx) |
| Get TR descriptor reload information. More... | |
| static void | CSL_udmapCppi5TrSetReload (CSL_UdmapCppi5TRPD *pDesc, uint32_t reloadEnable, uint32_t reloadIdx) |
| Set TR descriptor reload information. More... | |
| static uint32_t | CSL_udmapCppi5TrGetEntryStride (const CSL_UdmapCppi5TRPD *pDesc) |
| Get TR descriptor entry stride. More... | |
| static void | CSL_udmapCppi5TrSetEntryStride (CSL_UdmapCppi5TRPD *pDesc, uint32_t entryStride) |
| Set TR descriptor entry stride. More... | |
|
inlinestatic |
Get the buffer address.
This function returns the physical address of the buffer attached to the specified descriptor.
This function is intended for use with host-mode descriptors only.
| pDesc | [IN] Pointer to the host-mode descriptor |
|
inlinestatic |
Get the buffer length.
This function returns the length of the buffer (in bytes) attached to the specified descriptor.
This function is intended for use with host-mode descriptors only.
| pDesc | [IN] Pointer to the host-mode descriptor |
|
inlinestatic |
Get the descriptor type.
This function returns the type of descriptor. Valid descriptor types are: 1 = Host-mode (HOST) packet descriptor 2 = Monolithic-mode (MONO) packet descriptor 3 = Transfer Request mode (TR) packet descriptor
| pDesc | [IN] Pointer to the descriptor |
|
inlinestatic |
Get destination tag.
This function gets the destination tag from the descriptor.
| pDesc | [IN] Pointer to the descriptor |
|
inlinestatic |
Return pointer to EPI block data.
This function returns a pointer to the Extended Packet Info (EPI) block data within the descriptor. If the EPI block is not present, NULL is returned.
This function only operates on host-mode and mono-mode descriptors.
| pDesc | [IN] Pointer to the descriptor |
|
inlinestatic |
Get error flags.
This function gets the error flags from the descriptor.
This function is intended for use with host-mode and mono-mode descriptors only.
| pDesc | [IN] Pointer to the descriptor |
|
inlinestatic |
Get IDs.
This function gets the packet ID and flow ID from the descriptor.
| pDesc | [IN] Pointer to the descriptor |
| pPktId | [OUT] Pointer where to store packet ID |
| pFlowId | [OUT] Pointer where to store flow ID |
|
inlinestatic |
Get the packet length.
This function returns the packet length. The value returned depends on the type of descriptor as follows:
Host and mono mode packet descriptors: The length of the packet in bytes is returned
TR mode packet descriptors: The number of TRs in the packet is returned
| pDesc | [IN] Pointer to the descriptor |
|
inlinestatic |
Get packet type.
This function gets the packet type from the descriptor.
This function is intended for use with host-mode and mono-mode descriptors only.
| pDesc | [IN] Pointer to the descriptor |
|
inlinestatic |
Return address of the protocol-specific data.
This function returns the address of the protocol-specific data within the descriptor or SOP buffer.
If the protocol-specific data is in the descriptor (bInDesc is true), the address returned is a virtual address. If the protocol-specific data is in the SOP buffer (bInDesc is false), the address returned is a physical address.
This function only operates on host-mode and mono-mode descriptors.
| pDesc | [IN] Pointer to the descriptor |
| bInSopBuf | [IN] true if ps data is in SOP buffer, false otherwise |
| bEpiPresent | [IN] true if EPI data is present, false otherwise |
|
inlinestatic |
Get the number of bytes of protocol-specific data.
This function returns the number of bytes of protocol-specific (ps) data present in the descriptor. This value will be a multiple of 4.
This function is intended for use with host-mode and mono-mode descriptors only.
| pDesc | [IN] Pointer to the descriptor |
|
inlinestatic |
Get the location of the protocol-specific data.
This function returns the location of the protocol-specific data.
This function is intended for use with host-mode and mono-mode descriptors only.
| pDesc | [IN] Pointer to the descriptor |
|
inlinestatic |
Get ps flags.
This function gets the protocol-specific (ps) flags from the descriptor.
This function is intended for use with host-mode and mono-mode descriptors only.
| pDesc | [IN] Pointer to the descriptor |
|
inlinestatic |
Get descriptor return policy information.
This function gets descriptor return policy information from the descriptor. See CSL_udmapCppi5SetReturnPolicy for a description of the return policy information.
| pDesc | [IN] Pointer to the descriptor |
| pRetPolicy | [OUT] Pointer where to store return policy (0 is returned for MONO and TR descriptor types) |
| pEarlyReturn | [OUT] Pointer where to store early return (0 is returned for TR descriptor type) |
| pRetPushPolicy | [OUT] Pointer where to store return push policy |
| pRetQnum | [OUT] Pointer where to store return queue # |
|
inlinestatic |
Get source tag.
This function gets the source tag from the descriptor.
| pDesc | [IN] Pointer to the descriptor |
|
inlinestatic |
Is the EPI block present in the descriptor?
This function returns true if the Extended Packet Info (EPI) block is present in the descriptor and false if it is not present.
This function is intended for use with host-mode and mono-mode descriptors only.
| pDesc | [IN] Pointer to the descriptor |
|
inlinestatic |
Link a buffer descriptor to a descriptor.
This function links a buffer descriptor to the specified descriptor (which can be either a packet descriptor or a buffer descriptor).
This function is intended for use with host-mode descriptors only.
Note that the physical address of the buffer descriptor being linked must be provided. It is also assumed that the caller has initialized all required fields of the buffer descriptor prior to linking it.
| pDesc | [IN] Pointer to the descriptor being linked to |
| physBufferDescAddr | [IN] Physical address of the buffer descriptor being linked |
|
inlinestatic |
Get MONO descriptor data offset.
This function returns the data offset for a monolithic-mode (MONO) type of descriptor. This value indicates the byte offset from byte 0 of the descriptor to the location where the valid data begins.
| pDesc | [IN] Pointer to the MONO descriptor |
|
inlinestatic |
Set MONO descriptor data offset.
This function sets the data offset for a monolithic-mode (MONO) type of descriptor. This value indicates the byte offset from byte 0 of the descriptor to the location where the valid data begins.
| pDesc | [IN] Pointer to the MONO descriptor |
| dataOffset | [IN] Byte offset |
|
inlinestatic |
Read the EPI block data.
This function reads and returns the Extended Packet Info (EPI) block data within the descriptor.
This function is intended for use with host-mode and mono-mode descriptors only.
| pDesc | [IN] Pointer to the descriptor |
| pTsInfo | [OUT] Pointer where to store Timestamp information |
| *pSwInfo0 | [OUT] Pointer where to store Software information word 0 |
| *pSwInfo1 | [OUT] Pointer where to store Software information word 1 |
| *pSwInfo2 | [OUT] Pointer where to store Software information word 2 |
|
inlinestatic |
Set the buffer address.
This function writes the physical address of the buffer to the specified descriptor. This function is useful when configuring host-mode descriptors/buffers to be placed on a transmit queue.
This function is intended for use with host-mode descriptors only.
| pDesc | [IN] Pointer to the host-mode descriptor |
| physBufferAddr | [IN] Physical address of the buffer |
|
inlinestatic |
Set the buffer length.
This function writes the buffer length (in bytes) to the specified descriptor. This function is useful when configuring host-mode descriptors/buffers to be placed on a transmit queue.
This function is intended for use with host-mode descriptors only.
| pDesc | [IN] Pointer to the host-mode descriptor |
| bufferLenBytes | [IN] Length of the buffer in bytes |
|
inlinestatic |
Set the descriptor type.
This function sets the type of descriptor. Valid descriptor types are: 1 = Host-mode (HOST) packet descriptor 2 = Monolithic-mode (MONO) packet descriptor 3 = Transfer Request mode (TR) packet descriptor
Note that no error checking is performed on the passed descriptor type argument.
| pDesc | [IN] Pointer to the descriptor |
| descType | [IN] Descriptor type |
|
inlinestatic |
Set destination tag.
This function sets the destination tag in the descriptor.
| pDesc | [IN] Pointer to the descriptor |
| dstTag | [IN] destination tag |
|
inlinestatic |
Set indicator if the EPI block is present in the descriptor.
This function is used to set if the Extended Packet Info (EPI) block is present in the descriptor (true) or if it is not present (false).
This function is intended for use with host-mode and mono-mode descriptors only.
| pDesc | [IN] Pointer to the descriptor |
| bEpiDataPresent | [IN] true if EPI block is present, false if not |
|
inlinestatic |
Set IDs.
This function sets the packet ID and flow ID in the descriptor.
| pDesc | [IN] Pointer to the descriptor |
| descType | [IN] Descriptor type |
| pktId | [IN] packet ID |
| flowId | [IN] flow ID |
|
inlinestatic |
Set the original buffer address.
This function writes the original physical address of the buffer to the specified descriptor. This function is useful when initializing host-mode descriptors/buffers to be placed on transmit or receive free queues.
This function is intended for use with host-mode descriptors only.
| pDesc | [IN] Pointer to the host-mode descriptor |
| physBufferAddr | [IN] Physical address of the buffer |
|
inlinestatic |
Set the original buffer length.
This function writes the original buffer length (in bytes) to the specified descriptor. This function is useful when initializing host-mode descriptors/buffers to be placed on transmit or receive free queues.
This function is intended for use with host-mode descriptors only.
| pDesc | [IN] Pointer to the host-mode descriptor |
| bufferLenBytes | [IN] Length of the buffer in bytes |
|
inlinestatic |
Set the packet length.
This function sets the packet length. The meaning of the pktLen argument depends on the type of descriptor as follows:
Host and mono mode packet descriptors: pktLen = the length of the packet in bytes
TR mode packet descriptors: pktlen = the number of TRs in the packet
| pDesc | [IN] Pointer to the descriptor |
| descType | [IN] Descriptor type |
| pktLen | [IN] Packet length |
|
inlinestatic |
Set packet type.
This function sets the packet type in the descriptor.
This function is intended for use with host-mode and mono-mode descriptors only.
| pDesc | [IN] Pointer to the descriptor |
| pktType | [IN] Packet type |
|
inlinestatic |
Set the number of bytes of protocol-specific data.
This function sets the number of bytes of protocol-specific (ps) data present in the descriptor or SOP buffer. This value must be a multiple of 4.
This function is intended for use with host-mode and mono-mode descriptors only.
| pDesc | [IN] Pointer to the descriptor |
| psDataLen | [IN] Number of bytes of protocol-specific (ps) data present in the descriptor or SOP buffer |
|
inlinestatic |
Set the location of the protocol-specific data.
This function sets the location of the protocol-specific data.
This function is intended for use with host-mode and mono-mode descriptors only.
| pDesc | [IN] Pointer to the descriptor |
| psLoc | [IN] 0 = Protocol-specific data is in the descriptor 1 = Protocol-specific data is in the SOP buffer |
|
inlinestatic |
Set ps flags.
This function sets the protocol-specific (ps) flags in the descriptor.
This function is intended for use with host-mode and mono-mode descriptors only.
| pDesc | [IN] Pointer to the descriptor |
| psFlags | [IN] ps flags |
|
inlinestatic |
Set descriptor return policy information.
This function sets descriptor return policy information in the descriptor. This includes the following:
return policy (HOST descriptor type only) 0 = Entire packet (still linked together) should be returned to queue specified by pRetQnum 1 = Each descriptor should be returned to queue specified by pRetQnum in their respective descriptors.
early return (HOST and MONO descriptor types only) 0 = Buffer/packet descriptor pointers should only be returned after all reads have been completed 1 = Buffer/packet descriptor pointers should be returned immediately upon fetching the descriptor and beginning to transfer data
return push policy (only used when return policy is 1) 0 = Descriptor is returned to tail of queue 1 = Descriptor is returned to head of queue
return queue # Specifies the queue / ring number that the descriptor is returned to after transmission is complete.
| pDesc | [IN] Pointer to the descriptor |
| descType | [IN] Descriptor type |
| retPolicy | [IN] return policy (only used for HOST descriptor type) |
| earlyReturn | [IN] early return (only used for HOST and MONO descriptor types) |
| retPushPolicy | [IN] return push policy |
| retQnum | [IN] return queue # |
|
inlinestatic |
Set source tag.
This function sets the source tag in the descriptor.
| pDesc | [IN] Pointer to the descriptor |
| srcTag | [IN] source tag |
|
inlinestatic |
Get TR descriptor entry stride.
This function returns the stride between TR entries. See CSL_udmapCppi5TrSetEntryStride for valid stride values.
| pDesc | [IN] Pointer to the TR descriptor |
|
inlinestatic |
Get TR descriptor reload information.
This function returns reload information for a transfer-request (TR) type of descriptor. See CSL_udmapCppi5TrSetReload for a description of this reload information.
| pDesc | [IN] Pointer to the TR descriptor |
| pReloadEnable | [OUT] Pointer where to store reload enable |
| pReloadIdx | [OUT] Pointer where to store reload index |
|
inlinestatic |
Set TR descriptor entry stride.
This function sets the stride between TR entries. This value must be set large enough that any TR in the buffer will fit within the given dimension. TRs are expected to be placed on boundaries as given in this dimension.
The stride value is encoded as follows: 0 = 16 byte TR entry 1 = 32-byte TR entry 2 = 64-byte TR entry 3 = 128-byte TR entry
| pDesc | [IN] Pointer to the TR descriptor |
| entryStride | [IN] Encoded TR entry stride |
|
inlinestatic |
Set TR descriptor reload information.
This function sets reload information for a transfer-request (TR) type of descriptor. Reload information includes:
reload enable (specifies what to do when the last entry is processed in this packet) 0 = Finish the packet and place the descriptor back on the return queue 1 = Vector to the Reload Index and resume processing
reload index Specifies the value to set the current processing index to when the last entry is processed and reload enable is set to 1. This is basically an absolute index to jump to on the 2nd and following passes through the TR packet.
| pDesc | [IN] Pointer to the TR descriptor |
| reloadEnable | [IN] reload enable |
| reloadIdx | [IN] reload index |
|
inlinestatic |
Write the EPI block data.
This function writes the Extended Packet Info (EPI) block data into the descriptor.
This function is intended for use with host-mode and mono-mode descriptors only.
| pDesc | [IN] Pointer to the descriptor |
| tsInfo | [IN] Timestamp information |
| swInfo0 | [IN] Software information word 0 |
| swInfo1 | [IN] Software information word 1 |
| swInfo2 | [IN] Software information word 2 |


Martini
Total Time:
4 min
Prep:
4 min
Difficulty: Easy
Ingredients
* 3 fluid ounces vodka
* 1 fluid ounce dry vermouth
* 1 cup ice cubes
* 3 olives
* 1 strip of lemon peel
Instruction
Combine vodka and dry vermouth in a cocktail mixing glass. Fill with ice and stir until chilled. Strain into a chilled martini glass.
Garnish with three olives on a toothpick and lemon peel.


Presented By Taylor McGlone
Lab 1 Website Design, Github and Revisiting Web Mapping with Leaflet & geoJSON


Amount Pending : {{ amtpen }}
Amount Received : {{ amtrec }}
Total Fees : {{ userprofile.coursefees }}
{% if appliedscholarship %}
Applicant has received amount from below Scholarships
| Application Id | Scholarship Name | Trust Name | Amount Sanctioned |
|---|---|---|---|
| {{ key }} | {{ values.scheme_name }} | {{ values.tname }} | {{ values.sanctionedamount }} |
Personal Details
Education Details
Past Education
Achievements
Declaration
- I {{ userprofile.fname }} {{ userprofile.lname }} {{ userprofile.sname }} age {{ userprofile.age }} years, resident of {{ userprofile.address }} of hereby declare that the information given above and in the uploaded documents is true to the best of my knowledge and belief and nothing has been concealed therein.
- I am well aware of the fact that if the information given by me is proved false / not true at any point of time, I will have to face punishment as per any provision of Law for the time being in force as well as the benefit availed of by me or the benefit accrued to me shall be summarily cancelled
Scheme Eligibility
{{ schemeeligibility|linenumbers|linebreaks }}


Ordinal Scale with Alphabet
Mapping [1..10] to ["a".."j"]
Ordinal Color Scale Category 10
Mapping [1..10] to category 10 colors
Ordinal Color Scale Category 20
Mapping [1..10] to category 20 colors
Ordinal Color Scale Category 20b
Mapping [1..10] to category 20b colors
Ordinal Color Scale Category 20c
Mapping [1..10] to category 20c colors


{% extends "account/email/base.html" %} {% load account i18n %} {% block subject %} {% trans "Confirm E-mail Address" %} {% endblock %} {% block content %} {% user_display user as user_display %}
{% blocktrans with site_name=current_site.name site_domain=current_site.domain %} You're receiving this e-mail because user {{ user_display }} has given your e-mail address to register an account on {{ site_domain }}. {% endblocktrans %}
{% blocktrans with site_name=current_site.name site_domain=current_site.domain %} To confirm this is correct, go to {{ activate_url }} {% endblocktrans %}
{% endblock %}


{% extends "layout.html" %} {% block title %}Forbidden{% endblock %} {% block body %}
Oops, You don't have access to that. Check your user is assigned responsibility for Work Package or Partner Task/ Deliverable you're trying to access.
If you believe this is an error please log as an issue


Guy Pizza
Your one stop plug for delicious pizza!
Place Order
Our Menu
Veggie Pizza
Pepperoni Pizza
Beef Pizza
Margerita Pizza
BBQ Chicken Pizza
Hawaiian Pizza
Order Here
Order your pizza here and we will deliver it to you at your door step!
Pick a Flavor
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Veggie Pizza
Pepperoni Pizza
Beef Pizza
Margerita Pizza
BBQ Chicken Pizza
Hawaiian
Choose Size
Select size here
Large Ksh. 1100
Medium Ksh. 800
Small Ksh. 500
Pick a Crust
Pick a crust
Crispy Ksh. 200
Stuffed Ksh. 100
Gluten Ksh. 150
Pick Toppings at Ksh. 80 each
Mushrooms
Sauce
Onions
Proceed
Your order will be processed and delivered within half an hour.
Your Order is:
Name
Size
Crust
Topping
Total
Delivery will cost Ksh. 100
Add Pizza
Checkout
Delivery?
Place Order


Plugin:
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Change background to cyan
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Class FaceComponent
Manage the state of the faces on the robot.
Implements
Inherited Members
Namespace: Anki.Vector
Assembly: Anki.Vector.dll
Syntax
public class FaceComponent : Component, INotifyPropertyChanged
Methods
| Improve this Doc View SourceCancelFaceEnrollment()
Cancels the face enrollment.
public Task<StatusCode> CancelFaceEnrollment()
Returns
| Type | Description |
|---|---|
| Task<StatusCode> | A task that represents the asynchronous operation; the task result contains the result from the robot. |
EnrollFace(String, Face, Boolean, Boolean, Boolean)
Enrolls face into the robot (untested)
public Task<StatusCode> EnrollFace(string name, Face faceToEnroll, bool saveToRobot = true, bool sayName = true, bool useMusic = true)
Parameters
| Type | Name | Description |
|---|---|---|
| String | name | The name. |
| Face | faceToEnroll | The specific observed face to enroll. |
| Boolean | saveToRobot | Save the robot's NVStorage when done (NOTE: will (re)save everyone enrolled!) |
| Boolean | sayName | Play say-name/celebration animations on success before completing |
| Boolean | useMusic | Starts special music during say-name animations (will leave music playing) |
Returns
| Type | Description |
|---|---|
| Task<StatusCode> | A task that represents the asynchronous operation; the task result contains the result from the robot. |
Exceptions
| Type | Condition |
|---|---|
| ArgumentNullException | faceToEnroll |
EnrollFace(String, Boolean, Boolean, Boolean)
Enrolls face into the robot (untested)
public Task<StatusCode> EnrollFace(string name, bool saveToRobot = true, bool sayName = true, bool useMusic = true)
Parameters
| Type | Name | Description |
|---|---|---|
| String | name | The name of the person to enroll. |
| Boolean | saveToRobot | Save the robot's NVStorage when done (NOTE: will (re)save everyone enrolled!) |
| Boolean | sayName | Play say-name/celebration animations on success before completing |
| Boolean | useMusic | Starts special music during say-name animations (will leave music playing) |
Returns
| Type | Description |
|---|---|
| Task<StatusCode> | A task that represents the asynchronous operation; the task result contains the result from the robot. |
EnrollFace(String, Int32, Boolean, Boolean, Boolean)
Enrolls face into the robot (untested)
public Task<StatusCode> EnrollFace(string name, int observedFaceId, bool saveToRobot = true, bool sayName = true, bool useMusic = true)
Parameters
| Type | Name | Description |
|---|---|---|
| String | name | The name of the person to enroll. |
| Int32 | observedFaceId | The ID of a specific observed face to enroll (0 for next one we see) |
| Boolean | saveToRobot | Save the robot's NVStorage when done (NOTE: will (re)save everyone enrolled!) |
| Boolean | sayName | Play say-name/celebration animations on success before completing |
| Boolean | useMusic | Starts special music during say-name animations (will leave music playing) |
Returns
| Type | Description |
|---|---|
| Task<StatusCode> | A task that represents the asynchronous operation; the task result contains the result from the robot. |
EraseAllEnrolledFaces()
Erase the enrollment (name) records for all faces.
public Task<StatusCode> EraseAllEnrolledFaces()
Returns
| Type | Description |
|---|---|
| Task<StatusCode> | A task that represents the asynchronous operation; the task result contains the result from the robot. |
EraseEnrolledFace(KnownFace)
Erases the enrollment (name) record for the face.
public Task<StatusCode> EraseEnrolledFace(KnownFace face)
Parameters
| Type | Name | Description |
|---|---|---|
| KnownFace | face | The face. |
Returns
| Type | Description |
|---|---|
| Task<StatusCode> | A task that represents the asynchronous operation. The task result contains the result of the operation. |
EraseEnrolledFace(Int32)
Erases the enrollment (name) record for the face.
public Task<StatusCode> EraseEnrolledFace(int faceId)
Parameters
| Type | Name | Description |
|---|---|---|
| Int32 | faceId | The face identifier. |
Returns
| Type | Description |
|---|---|
| Task<StatusCode> | A task that represents the asynchronous operation. The task result contains the result of the operation. |
GetEnrolledFaces()
Gets the enrolled faces.
public Task<IEnumerable<KnownFace>> GetEnrolledFaces()
Returns
| Type | Description |
|---|---|
| Task<IEnumerable<KnownFace>> | A task that represents the asynchronous operation; the task result contains an enumeration of KnownFace instances. |
UpdateEnrolledFace(KnownFace, Face, Boolean, Boolean, Boolean)
Updates an existing enrolled face
public Task<StatusCode> UpdateEnrolledFace(KnownFace faceToUpdate, Face faceToEnroll, bool saveToRobot = true, bool sayName = true, bool useMusic = true)
Parameters
| Type | Name | Description |
|---|---|---|
| KnownFace | faceToUpdate | An existing face to merge final enrollment into. |
| Face | faceToEnroll | The specific observed face to enroll. |
| Boolean | saveToRobot | Save the robot's NVStorage when done (NOTE: will (re)save everyone enrolled!) |
| Boolean | sayName | Play say-name/celebration animations on success before completing |
| Boolean | useMusic | Starts special music during say-name animations (will leave music playing) |
Returns
| Type | Description |
|---|---|
| Task<StatusCode> | A task that represents the asynchronous operation; the task result contains the result from the robot. |
UpdateEnrolledFace(KnownFace, Boolean, Boolean, Boolean)
Updates an existing enrolled face
public Task<StatusCode> UpdateEnrolledFace(KnownFace faceToUpdate, bool saveToRobot = true, bool sayName = true, bool useMusic = true)
Parameters
| Type | Name | Description |
|---|---|---|
| KnownFace | faceToUpdate | An existing face to merge final enrollment into. |
| Boolean | saveToRobot | Save the robot's NVStorage when done (NOTE: will (re)save everyone enrolled!) |
| Boolean | sayName | Play say-name/celebration animations on success before completing |
| Boolean | useMusic | Starts special music during say-name animations (will leave music playing) |
Returns
| Type | Description |
|---|---|
| Task<StatusCode> | A task that represents the asynchronous operation; the task result contains the result from the robot. |
UpdateEnrolledFace(KnownFace, Int32, Boolean, Boolean, Boolean)
Updates an existing enrolled face
public Task<StatusCode> UpdateEnrolledFace(KnownFace faceToUpdate, int observedFaceId, bool saveToRobot = true, bool sayName = true, bool useMusic = true)
Parameters
| Type | Name | Description |
|---|---|---|
| KnownFace | faceToUpdate | An existing face to merge final enrollment into. |
| Int32 | observedFaceId | The ID of a specific observed face to enroll (0 for next one we see) |
| Boolean | saveToRobot | Save the robot's NVStorage when done (NOTE: will (re)save everyone enrolled!) |
| Boolean | sayName | Play say-name/celebration animations on success before completing |
| Boolean | useMusic | Starts special music during say-name animations (will leave music playing) |
Returns
| Type | Description |
|---|---|
| Task<StatusCode> | A task that represents the asynchronous operation; the task result contains the result from the robot. |
UpdateEnrolledFaceName(KnownFace, String)
Updates the name of the enrolled face.
public Task<StatusCode> UpdateEnrolledFaceName(KnownFace face, string newName)
Parameters
| Type | Name | Description |
|---|---|---|
| KnownFace | face | The face to rename. |
| String | newName | The new name. |
Returns
| Type | Description |
|---|---|
| Task<StatusCode> | A task that represents the asynchronous operation. The task result contains the result of the operation. |
UpdateEnrolledFaceName(Int32, String, String)
Updates the name of the enrolled face.
public Task<StatusCode> UpdateEnrolledFaceName(int faceId, string oldName, string newName)
Parameters
| Type | Name | Description |
|---|---|---|
| Int32 | faceId | The ID of the face to rename. |
| String | oldName | The old name of the face (must be correct, otherwise message is ignored). |
| String | newName | The new name for the face. |
Returns
| Type | Description |
|---|---|
| Task<StatusCode> | A task that represents the asynchronous operation; the task result contains the result from the robot. |


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Configure Aloha Editor
After reading this guide, you will be able to:
- Add configuration settings to you page and
- Adapt Aloha Editor to your needs by means of configuration
1 Basic Configuration
Please write sth.!
2 Configuring the FloatingMenu
The floating menu can be adapted to your needs by configuring tabs, groups and buttons. You may reassemble all of the existing buttons provided by plugins in any combination you want.
A button may only be added once to the configuration. Adding the same button twice will yield no results exept raising a warning message.
The following simple example should help to understand how to configure the FloatingMenu. Basically, all you have to do is define an array of button names (those are provided by plugins). As you might have noticed, groups may be named in our example (“flow”, “phrasing” or “first”). However, at this time naming groups yields no visual result in the current FloatingMenu. It will just help you structure your configuration.
<head> <script type="text/javascript"> Aloha.settings.toolbar = { tabs : { // will generate a tab labeled "formatting" formatting : { // group "flow" flow : [ 'b', 'em', 'u' ], // group "phrasing" phrasing : [ 'phrasing' ] // "phrasing" is the name of a // MultiSplitButton from the format plugin, which contains // elements like h1 ... }, // will generate another tab labeled "insert" insert : { // as mentioned group names are not displayed anywhere, // so you might pick an arbitrary name first : [ 'image', 'insertLink' ] } }, components : { // the phrasing MultiSplitButton is configured the same way // as groups are phrasing : [ 'h1', 'h2', 'h3' ] } }; </script> </head>
The following are configuration options are available for the behaviour of the floating menu.
<head> <script type="text/javascript"> Aloha.settings.floatingmenu = { width: 630, // with of the floating menu; auto calculated when not set behaviour: 'float', // 'float' (default), 'topalign', 'append' element: 'my-html-element-id', // use with 'append' behaviour option: HTML DOM ID of the element the FM should get the position from pin: false, // boolean if set to true with behaviour 'append' the fm will be pinned to that position and scroll with the window draggable: true, // boolean marginTop: 10, // number in px horizontalOffset: 0, // number in px -- used with 'topalign' behaviour topalignOffset: 0, // number in px -- used with 'topalign' behaviour }; </script> </head>


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