Making Pictures With GNU PIC
1. Introduction to PIC
1.1. Why PIC?
1.2. PIC Versions
2. Invoking PIC
2.1. PIC Error Messages
3. Basic PIC Concepts
4. Sizes and Spacing
4.1. Default Sizes of Objects
4.2. Objects Do Not Stretch!
4.3. Resizing Boxes
4.4. Resizing Other Object Types
4.5. The ‘same’ Keyword
5. Generalized Lines and Splines
5.1. Diagonal Lines
5.2. Multi-Segment Line Objects
5.3. Spline Objects
6. Decorating Objects
6.1. Text Special Effects
6.2. Dashed Objects
6.3. Dotted Objects
6.4. Rounding Box Corners
6.5. Slanted Boxes
6.6. Arrowheads
6.7. Line Thickness
6.8. Invisible Objects
6.9. Filled Objects
6.10. Colored Objects
7. More About Text Placement
8. More About Direction Changes
9. Naming Objects
9.1. Naming Objects By Order Of Drawing
9.2. Naming Objects With Labels
10. Describing locations
10.1. Absolute Coordinates
10.2. Locations Relative to Objects
10.2.1. Locations Relative to Closed Objects
10.2.2. Locations Relative to Open Objects
10.3. Ways of Composing Positions
10.3.1. Vector Sums and Displacements
10.3.2. Interpolation Between Positions
10.3.3. Projections of Points
10.4. Using Locations
10.5. The ‘chop’ Modifier
11. Object Groups
11.1. Brace Grouping
11.2. Block Composites
12. Style Variables
13. Expressions, Variables, and Assignment
14. Macros
15. Import/Export Commands
15.1. File and Table Insertion
15.2. Debug Messages
15.3. Escape to Post-Processor
15.4. Executing Shell Commands
16. Control-flow constructs
17. Interface To [gt]roff
17.1. Scaling Arguments
17.2. How Scaling is Handled
17.3. PIC and [gt]roff commands
17.4. PIC and EQN
17.5. Absolute Positioning of Pictures
18. Interface to TeX
19. Obsolete Commands
20. Some Larger Examples
21. PIC Reference
21.1. Lexical Items
21.2. Semi-Formal Grammar
22. History and Acknowledgements
23. Bibliography


Conversions from hectopascals More...
Static Public Member Functions | |
| static float | Pascals (float hectopascals) |
| Convert from hectopascals to pascals. More... | |
| static float | Millibars (float hectopascals) |
| Convert from hectopascals to millibars. More... | |
| static float | Kilopascals (float hectopascals) |
| Convert from hectopascals to kilopascals. More... | |
| static float | PoundsPerSquareInch (float hectopascals) |
| Convert from hectopascals to pounds per square inch. More... | |
Public Attributes | |
| const float | PER_PASCAL = 1 / Units.Pascals.PER_HECTOPASCAL |
| Conversion factor from pascals to hectopascals. More... | |
| const float | PER_MILLIBAR = 1 |
| Conversion factor from millibars to hectopascals. More... | |
| const float | PER_KILOPASCAL = 10 |
| Conversion factor from kilopascals to hectopascals. More... | |
| const float | PER_POUND_PER_SQUARE_INCH = PER_PASCAL * Units.Pascals.PER_POUND_PER_SQUARE_INCH |
| Conversion factor from pounds per square inch to hectopascals. More... | |
Conversions from hectopascals
Definition at line 6 of file Hectopascals.cs.
|
inlinestatic |
Convert from hectopascals to kilopascals.
| hectopascals | The number of hectopascals |
Definition at line 53 of file Hectopascals.cs.
References Juniper.Units.Units.
|
inlinestatic |
Convert from hectopascals to millibars.
| hectopascals | The number of hectopascals |
Definition at line 43 of file Hectopascals.cs.
References Juniper.Units.Units.
|
inlinestatic |
Convert from hectopascals to pascals.
| hectopascals | The number of hectopascals |
Definition at line 33 of file Hectopascals.cs.
References Juniper.Units.Units.
|
inlinestatic |
Convert from hectopascals to pounds per square inch.
| hectopascals | The number of hectopascals |
Definition at line 63 of file Hectopascals.cs.
References Juniper.Units.Units.
| const float Juniper.Units.Hectopascals.PER_KILOPASCAL = 10 |
Conversion factor from kilopascals to hectopascals.
Definition at line 21 of file Hectopascals.cs.
| const float Juniper.Units.Hectopascals.PER_MILLIBAR = 1 |
Conversion factor from millibars to hectopascals.
Definition at line 16 of file Hectopascals.cs.
| const float Juniper.Units.Hectopascals.PER_PASCAL = 1 / Units.Pascals.PER_HECTOPASCAL |
Conversion factor from pascals to hectopascals.
Definition at line 11 of file Hectopascals.cs.
| const float Juniper.Units.Hectopascals.PER_POUND_PER_SQUARE_INCH = PER_PASCAL * Units.Pascals.PER_POUND_PER_SQUARE_INCH |
Conversion factor from pounds per square inch to hectopascals.
Definition at line 26 of file Hectopascals.cs.


Murderer in 1992 McDonald's robbery granted day passes from prison
by Jeremiah Rodriguez, CTVNews.ca Staff with a report from CTV Atlantic's Ryan MacdonaldTORONTO -- A convicted murderer involved in the 1992 botched robbery of a McDonald’s restaurant in Sydney River, N.S. has been granted 24-hour unescorted passes from prison.
Three men were convicted for the violent incident that left three McDonald’s employees dead and a fourth with life-altering brain injuries. All three attackers, who ended up stealing $2,017, were convicted of first-degree murder.
After decades behind bars, Freeman MacNeil, now 51, was approved for two 24-hour absences for the next two months. The conditions of these releases include MacNeil not having any contact with the victims' families.
One of the victims was 29-year-old father Neil Burroughs who was shot and stabbed before being hit him over the head with a shovel handle. The two other victims were James Fagan, 27 and Donna Warren, 22.
A fourth worker, Arleen MacNeil, suffered life-altering brain injuries. She died last year.
The most recent unescorted passes were for MacNeil’s “personal development” and the logical step in his reintegration into society, the Parole Board of Canada said.
MacNeil has reportedly had about 300 escorted passes out of prison since 2016. He has been held in minimum-security institutions since 2012.
VICTIM’S SISTER CALLED MOVE 'UNBELIEVABLE'
Cathy Burroughs, the sister of victim Neil Burroughs, said she was shocked by the news.
“It’s just inconceivable to me that we have a justice system that definitely just still protects the offenders,” she said.
Burroughs doesn’t believe MacNeil has changed since the killing and said he even smirked at her family when they attended his second-to-last parole hearing.
She added this latest news didn’t surprise her. Another one of the convicted murderers, Darren Muise, received full parole nearly seven years ago. Burroughs believes MacNeil will eventually be released from prison as well.
She doesn’t believe Derek Wood, the third man involved in the murders, will ever be released, despite being the “only one who has ever apologized for his actions that night.”
Regardless of what ends up happening with both Wood and MacNeil, Burroughs said the pain from her brother’s murder will never fully disappear.
"They're not the only ones who got a life sentence. So did we,” she said, adding she’ll be at MacNeil's next parole hearing.
"As I told Mr. MacNeil the last time, we still have some unfinished business. He will always have to contend with the Burroughs family. And especially me."


WWE Survivor Series 2019: 5 Superstars who can shine at the PPV
by Shruti SadbhavWWE Survivor Series is set to commence in a few hours. For the first time in the history of the PPV, we will see three brands battling it out for brand supremacy. The NXT Superstars are the ultimate underdogs heading into the show and it would be interesting to see how they fare against RAW and SmackDown.
This year’s Survivor Series has allowed the creatives to book multiple dream matches featuring Superstars who are otherwise used to repetitive storylines on the supposed ‘main-roster’. Tonight, some of them might step out of their comfort zone and deliver spots that we will remember in years to come.
Among all the WWE Superstars who will be representing their respective brands tonight, there are a few who will make the most of this opportunity and emerge as the biggest highlights of the show.
In this list, we will take a look at five WWE Superstars who could shine at Survivor Series 2019 and steal the show.
#5 Drew McIntyre
Drew McIntyre was reportedly in line for a huge push and was expected to challenge Seth Rollins for the Universal Championship. However, those plans were derailed owing to the rivalry between 'The Architect' and The Fiend.
Fortunately for McIntyre, he has another opportunity at Survivor Series to remind the WWE Universe of his brutality. His entire run on the main roster has been about proving his mettle against the celebrated personalities of the roster. McIntyre has often called out the creatives for giving more importance to the ‘legends’ as compared to the current Superstars.
At Survivor Series, he will be representing RAW and can capitalize on this chance to establish himself as a dominant force on the Red brand. If the creatives want to him to continue as a heel, McIntyre might end up attacking his teammates during the match. This will also allow WWE to initiate a feud between him and the likes of Rollins, Ricochet or Randy Orton which will prove to be good for business in the coming weeks.
1 / 5 NEXT


ORG:
[label] ORG expression
The ORG directive changes the program counter to the value specified by the
expression in the operand field. Subsequent statements are assembled into
memory locations starting with the new program counter value. If no ORG
directive is encountered in a source program, the program counter is
initialized to zero. Expressions cannot contain forward references or undefined
symbols.
Example:
See also:
Compatibility:
| KASM |
X |
| CCASM |
X |
| OS-9 RMA |
X |
| Edt/Asm III |
X |
| Edtasm6309 |
X |
| Disk Edtasm+ |
X |
| Edtasm+ |
X |
| Macro-80C |
X |


---
layout: page
tagline:
---
{% for post in paginator.posts %}
{{ post.title }}
I am currently an Associate Professor in School of Electronic Engineering at Xidian University. Before that I obtained my PhD degree in School of Electronic Engineering, Xidian University, under the supervision of Prof. Cheng Deng. I received the bachelor degree in Xidian University in July, 2016.
Deep Learning, Graph Representation Learning, and Clustering
Executive Area Chair of Vision And Learning SEminar (VALSE)
Programme committee (PC) member for CVPR, NeurIPS, ICML, AAAI, IJCAI
Senior programme committee (SPC) member for IJCAI 2021
I was selected for the Shaanxi Association for Science and Technology Youth Lifting Talent Program.
Apr. 20, 2023, one paper was accepted to IJCAI2023 (15% acceptance rate).
Apr. 19, 2023, one papers was accepted to IEEE Trans. on Neural Networks and Learning Systems.
Jan. 30, 2023, one paper was accepted to IEEE Trans. on Multimedia.
Jul. 24, 2022, one paper was accepted to IEEE Trans. on Multimedia.
Apr. 21, 2022, one paper was accepted to IJCAI-ECAI2022.
Mar. 8, 2022, one paper was accepted to IEEE Trans. on Image Processing.
Mar. 2, 2022, two papers were accepted to CVPR2022 (25.3% acceptance rate).
Jan. 12, 2022, My PhD thesis was selected as the excellent doctoral dissertation of CAAI.
Dec. 1, 2021, one paper was accepted to AAAI2022 (15% acceptance rate).
Aug. 20, 2021, one paper was accepted to IEEE Trans. Cybernetics.
July 1, 2021, one paper was accepted to IEEE Trans. on Neural Networks and Learning Systems.
I was elected as the Executive Area Chair (EAC) of the sixth VALSE.
Apr. 29, 2021, one paper was accepted to IJCAI2021 (13.9% acceptance rate).
Mar. 1, 2021, two papers were accepted to CVPR2021 (~27% acceptance rate).
Dec. 02, 2020, one paper was accepted to AAAI2021 (~21% acceptance rate).
Sep. 26, 2020, one paper was accepted to NeurIPS2020 (~20% acceptance rate).Sep. 17, 2020, one paper was accepted to IEEE Trans. Pattern Analysis and Machine Intelligence.
Journal Articles
Unsupervised Structure-Adaptive Graph Contrastive Learning
H. Zhao, X. Yang, C. Deng, D. Tao
IEEE Trans. Neural Netw. Learn. Syst., 2023.(IF20=10.451)
Dual-Stream Contrastive Learning for Compositional Zero-Shot Recognition
Y. Yang, R. Pan, X. Li, X. Yang, C. Deng
IEEE Trans. Multimed., 2023.(IF20=8.182)
Point-Supervised Video Temporal Grounding
Z. Xu, K. Wei, X. Yang, C. Deng
IEEE Trans. Multimed., 2022.(IF20=8.182)
Object-Agnostic Transformers for Video Referring Segmentation
X. Yang, H. Wang, D. Xie, C. Deng, and D. Tao
IEEE Trans. Image Process., 2022.(IF20=10.856)
Incremental Zero-Shot Learning
K. Wei, C. Deng, X. Yang, and D. Tao
IEEE Trans. Cybern., 2021.(IF20=11.448)
Self-Training with Progressive Representation Enhancement for Unsupervised Cross-Domain Person Re-identification
H. Zhang, H. Cao, X. Yang, C. Deng and D. Tao
IEEE Trans. Image Process., 30: 5287-5298, 2021.(IF20=10.856)
Deep Multi-View Collaborative Clustering
X. Yang, C. Deng, Z. Dang, and D. Tao
IEEE Trans. Neural Netw. Learn. Syst., 2021.(IF20=10.451)
Heterogeneous Graph Attention Network for Unsupervised Multiple-Target Domain Adaptation
X. Yang, C. Deng, T. Liu, and D. Tao
IEEE Trans. Pattern Anal. Mach. Intell., 2020. (IF20=16.389)
Saliency Detection via a Multiple Self-Weighted Graph-Based Manifold Ranking
C. Deng, X. Yang, F. Nie, and D. Tao
IEEE Trans. Multimed., 2019. (IF20=6.513)
Conference Proceedings
New L21-Norm Relaxation of Multi-Way Graph Cut for Clustering
X. Yang, C. Deng, X. Liu, and F. Nie
In AAAI Conference on Artificial Intelligence (AAAI), 2018.
Deep Spectral Clustering Using Dual Autoencoder Network[Paper][Code]
X. Yang, C. Deng, F. Zheng, J. Yan, and W. Liu
In IEEE International Conference on Pattern Recognition and Computer Vision (CVPR), 2019.
Multi-Scale Fusion Subspace Clustering Using Similarity Constraint
Z. Dang, C. Deng, X. Yang, H. Huang
In IEEE International Conference on Pattern Recognition and Computer Vision (CVPR), 2020.
Lifelong Zero-shot Learning
K. Wei, C. Deng, X. Yang
In International Joint Conference on Artificial Intelligence (IJCAI), 2020.
Adversarial Learning for Robust Deep Clustering
X. Yang, C. Deng, K. Wei, J. Yan, and W. Liu
In Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), 2020.
Incremental Embedding Learning via Zero-Shot Translation
K. Wei, C. Deng, X. Yang and M. Li
In AAAI Conference on Artificial Intelligence (AAAI), 2021.
SelfSAGCN: Self-Supervised Semantic Alignment for Graph Convolution Network[Paper][Code]
X. Yang, C. Deng, Z. Dang, K. Wei, and J. Yan
In IEEE International Conference on Pattern Recognition and Computer Vision (CVPR), 2021.
Nearest Neighbor Matching for Deep Clustering
Z. Dang, C. Deng, X. Yang, K. Wei, H. Huang
In IEEE International Conference on Pattern Recognition and Computer Vision (CVPR), 2021.
Graph Debiased Contrastive Learning with Joint Representation Clustering[Code]
H. Zhao, X. Yang, Z. Wang, E. Yang, and C. Deng
In 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021.
Learning Universal Adversarial Perturbation by Adversarial Example
M. Li, Y. Yang, K. Wei, X. Yang, and H. Huang
In AAAI Conference on Artificial Intelligence (AAAI), 2022.
Not Just Selection, but Exploration: Online Class-Incremental Continual Learning via Dual View Consistency
Y. Gu, X. Yang, K. Wei, and C. Deng
In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
Siamese Contrastive Embedding Network for Compositional Zero-Shot Learning
X. Li, X. Yang, K. Wei, C. Deng, and M. Yang
In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
Attention-guided Contrastive Hashing for Long-tailed Image Retrieval
X. Kou, C. Xu, X. Yang and C. Deng
In 31th International Joint Conference on Artificial Intelligence (IJCAI), 2022.
Exploring Safety Supervision for Continual Test-time Domain Adaptation
X. Yang, Y. Ya, K. Wei and C. Deng
In 32th International Joint Conference on Artificial Intelligence (IJCAI), 2023.


Invoice #:
Created:
Status:
BILLING DETAILS
Customer Name :
Address :
City :
Phone :
Email :
SHIPPING DETAILS
Customer Name :
Address :
City :
Payment Method
Delivery Charges
Item
Qty
Price
Summary
SUBTOTAL
0
CHARGES
0
TOTAL
0


Runtime complexity tool
Examples:
ArraySum
InsertionSort
SelectionSort
MergeSort
PowerSet
OrderOfMagnitude
NestedFor
Constant
Fibonacci
Hello
Type code here:
Analyze
Loading
Java AST:
Toggle
Simplified AST:
Toggle
Raw equation:
Simplified equation:
Final equation:


Webpack loader for NgModule
lazy loading using the angular router
npm install ng-router-loader --save-dev
OR
yarn add ng-router-loader --dev
Add the ng-router-loader
to your typescript loaders chain
loaders: [
{
test: /\.ts$/,
loaders: [
'awesome-typescript-loader',
'ng-router-loader'
]
}
]
module: {
rules: [
{
test: /\.ts$/,
use: [
'awesome-typescript-loader',
{
loader: 'ng-router-loader'
options: {
/* ng-router-loader options */
}
}
]
}
]
}
Use the loadChildren
API with any webpack resolvable path to reference your lazy loaded angular module.
Use #
as a delimiter and write the NgModule
class name.
import { Routes } from '@angular/router';
export const ROUTES: Routes = [
{ path: 'detail', loadChildren: () => '../my-ng-modules/details#DetailModule' },
];
The delimiter is configurable.
Query parameters (details#DetailModule?loader=sync) are added after the delimiter.
This behaviour might change, supporting both pre & after.
For synchronous module loading, add the sync=true as a query string value to your loadChildren string. The module will be included in your bundle and not lazy-loaded.
import { Routes } from '@angular/router';
export const ROUTES: Routes = [
{ path: 'detail', loadChildren: () => '../my-ng-modules/details#DetailModule?loader=sync' },
];
The Synchronous example uses a resource specific loader option, you can also set a global loader option.
Please read the documentation
The @angular/router
provides an API for deferred NgModule
loading, this is a simple API that accepts a function that returns an NgModule
class.
Project structure
├── project-root/
│ ├── app
│ │ ├── app.routes.ts
│ ├── my-ng-modules
│ │ ├── details
│ │ │ ├──index.ts
│ │ │ ├──details.module.ts
│ │ │ ├──details.component.ts
DetailModule is defined in
details.module.ts
and exported inindex.ts
app.routes.ts
import { Routes } from '@angular/router';
import { DetailModule } from '../my-ng-modules/details';
export const ROUTES: Routes = [
{ path: 'detail', loadChildren: () => DetailModule },
];
The @angular/router
will not invoke the function until the path is active, this is the how lazy loading is done.
The example above works just fine but it includes a hard reference to the DetailModule
.
Having a reference results in adding the file containing the module into the bundle.
To achieve lazy loading we need to write the code in a lazy loading code-style that webpack understand.
ng-router-loader
abstracts the complexity and provides an easy approach using a string reference.
In the background the loader will translate the string to code.
The string reference is the reference you use when you require
or import
.
Any string that resolves with require
or import
can be used and the same rules apply with 1 addition, the string reference requires must provide the name of the NgModule
exported.
Using the same example above:
app.routes.ts
import { Routes } from '@angular/router';
export const ROUTES: Routes = [
{ path: 'detail', loadChildren: () => '../my-ng-modules/details#DetailModule' },
];
It's that easy!
angular-router-loader
The angular-router-loader
("ARL" from now) came out with angular final when AOT was still blurry and not enough information was out there.
This made it very limited in it's capabilities, while using it I reached some dead ends that ARL did'nt handle.
Another issue I had is that ARL forced me to structure my app in a certain way which was not webpack oriented. A loader should be transparent to the developer.
I started fixing things and quickly understood that a rewrite is required.
Here are some of the key points:
Module resolution
ARL use the file system to resolve URIs, this makes it impossible to use the goodies webpack resolve
provides,
such as barrels, aliasing, custom module directories and more, see webpack resolve.ng-router-loader
uses webpack to resolve modules so everything webpack resolves will work.
AOT re-exports
ARL can't handle re-exported NgModule
symbols in AOT mode.
The example above shows the index.ts
file exporting the DetailModule
defined in a different
file, this is a tricky scenario that requires symbol tracking and it will result in an unknown module import created by ARL
ng-router-loader
performs a deep metadata search to extract the right import.
Custom code generators
ng-router-loader
code generation is plugin based, you can provide a custom code generator that fits your use case.
Typescript based
angular-router-loader Learned a lot reading the code!
Generated using TypeDoc


Proteomics data analysis parameters¶
Similarly to the Clinical data analysis parameters, the Proteomics configuration file is divided into sections: args
, overview
, data exploration
, data associations
and enrichment
.
The args
section contains the parameters used to process the proteomics data extracted from the CKG database, which includes the filtering of proteins according to the determined threshold, as well as the imputation of all missing values. These parameters include:
imputation: boolean. Set to True if missing values shall be imputed.
imputation_method: method for missing values imputation (“KNN”, “distribuition”, or “mixed”).
missing_method:
missing_per_group: boolean. If True, proteins are filtered based on valid values per group; if False filter across all samples.
missing_max: maximum ratio of missing/valid values to be filtered. (e.g. 0.3 filters all proteins with more than 30% missing values).
min_valid: minimum number of required valid values to keep a protein.
value_col: column label containing expression values.
index: column labels to be be kept as index identifiers.
The result is a Pandas dataframe, stored as “processed”, where columns are protein identifiers (UniprotID~GeneName) and analytical samples are rows, group and subject identifier are kept as columns as well.
Note
We advise to change only imputation, imputation_method, missing_method, missing_per_group, and missing_max or min_valid.
The second section (overview
) corresponds to basic statistics and includes:
Data summary statistics (overview statistics)
Number of peptides per sample (peptides)
Number of proteins per sample (proteins)
Number of modifications per sample (modifications)
Dynamic range per group (ranking)
Coefficient of variation per group (coefficient_variation)
In the data exploration
section, we look at the sample stratification (stratification), differentially expressed proteins (regulation), and protein-protein correlation network (correlation). In this section, you can choose to modify parameters like alpha
(FDR value), s0
(artificial within groups variance) or fc
(fold-change), to better fit your data and experimental design. Likewise, the correlation network is, by default, set to show correlations above 50% (cutoff: 0.5
), this too can be changed.
The data associations
section includes analyses that correlated differentially expressed proteins to proteins (interaction_network), drugs (drug_associations), diseases (disease_associations) and publications (literature_associations). All these associations are directly queried from the CKG database.
The last section in the default analysis pipeline corresponds to the enrichment
analysis, and includes both Gene Ontology (go_enrichment) and Pathway (pathway_enrichment) enrichment analyses, using Fisher’s exact test (method: fisher
)
Likewise in the Clinical data analysis parameters, within each analysis, specific parameters are defined:
description: Definition of the analysis used.
data: defines on which dataset dataframe the analysis will be ran (e.g. “clinical variables”, “original”, “processed”).
analyses: which statistical analysis to run on the
data
. These functions are called from the mocduleanalytics_factory.py
.plots: which plot to use to show the results of analyses. Functions also called from the mocdule
analytics_factory.py
.store_analysis: boolean. True if the dataframe resulting from analyses is to be stored.
args: all arguments necessary for analyses and plots.
You can modify the analysis parameters just by changing the respective parameters within the configuration file. Remember to consult the modules analytics.py
and viz.py
, to learn more about the arguments of each function.
If you would like to add a specific analysis step to the default pipeline, remember to add a call to the function in analytics_factory.py
.


Basics of Machine Learning Series
Introduction
Neural networks can be used to build all types of function. This post tries to map functions of logical operations using the network. How the parameters are derived in explained in the later posts.
AND Gate
Using a single neuron, it is possible to achieve the approximation of an and gate. The architecture with the parameters can be seen below.
The hypothesis for the above network is given by,
- Where g is the sigmoid function which asymptotes at 0 and 1.
The output table for the hypothesis above is given below.
| \(x_1\) | \(x_2\) | \(h_\theta(x)\) |
|---|---|---|
| 0 | 0 | \(g(-30) \approx 0\) |
| 0 | 1 | \(g(-10) \approx 0\) |
| 1 | 0 | \(g(-10) \approx 0\) |
| 1 | 1 | \(g(10) \approx 1\) |
The values of \(h_\theta(x)\) is nothing but the expected value of the AND gate.
OR Gate
Similarly, using a single neuron, it is possible to achieve the approximation of an or gate. The architecture with the parameters can be seen below. It is same as AND gate but the bias weight is changed.
The hypothesis for the above network is given by,
- Where g is the sigmoid function which asymptotes at 0 and 1.
The output table for the hypothesis above is given below.
| \(x_1\) | \(x_2\) | \(h_\theta(x)\) |
|---|---|---|
| 0 | 0 | \(g(-10) \approx 0\) |
| 0 | 1 | \(g(10) \approx 1\) |
| 1 | 0 | \(g(10) \approx 1\) |
| 1 | 1 | \(g(30) \approx 1\) |
The values of \(h_\theta(x)\) is nothing but the expected value of the OR gate.
NOT Gate
Unlike the previous two examples, NOT gate is a unary operator, but still simple weights can give easy implementation of the NOT gate. The architecture and the parameters are shown below.
The hypothesis for the above network is given by,
- Where g is the sigmoid function which asymptotes at 0 and 1.
The output table for the hypothesis above is given below.
| \(x_1\) | \(h_\theta(x)\) |
|---|---|
| 0 | \(g(10) \approx 1\) |
| 1 | \(g(-10) \approx 0\) |
The values of \(h_\theta(x)\) is nothing but the expected value of the NOT gate.
(NOT \(x_1\)) AND (NOT \(x_2\))
Unlike the previous examples, this operation does not look straight forward, but actually it is. Here is an architecture implementation of the above gate.
The hypothesis for the above network is given by,
- Where g is the sigmoid function which asymptotes at 0 and 1.
The output table for the hypothesis above is given below.
| \(x_1\) | \(x_2\) | \(h_\theta(x)\) |
|---|---|---|
| 0 | 0 | \(g(10) \approx 1\) |
| 0 | 1 | \(g(-10) \approx 0\) |
| 1 | 0 | \(g(-10) \approx 0\) |
| 1 | 1 | \(g(-30) \approx 0\) |
The values of \(h_\theta(x)\) is nothing but the expected value of the (NOT \(x_1\)) AND (NOT \(x_2\)) operation.
Perceptron Limitation
All the examples untill this one were linearly seperable and hence were solved using a single neuron. But and XOR Gate is not linearly seperable as was the case with AND and OR gates and this can be clearly seen in the plot below.
It is evident that there is no single straight line that can seperate the two classes in plot (c) and hence termed as not linearly seperable. This is a major drawback of perceptron (single layer neural networks).
There is a simple proof for concluding that the XOR is not linearly seperable. Say, perceptron were capable of separating the two classes, then it would mean that there exists a set of weights (or parameters), \(\theta_0,\, \theta_1,\,\theta_2\) such that the hypothesis is given by,
Then the above hypothesis should satisfy the following truth table,
| \(x_1\) | \(x_2\) | \(x_1\,XOR\,x_2\) |
|---|---|---|
| 0 | 0 | 0 |
| 0 | 1 | 1 |
| 1 | 0 | 1 |
| 1 | 1 | 0 |
Substituting and equating to 0, the hypothesis, following inequalities are generated that would determine the decision boundary.
Substituting \(b = -\theta_0\), above inequalities can be written as,
It can be seen that the first three inequalities directly contradict the fourth one. Which means that the very first assumption made that there exist such parameters \(\theta_0,\, \theta_1,\,\theta_2\) was incorrect. Hence, the XOR gate is not linearly seperable.
This is where the utility and finesse of multi-layer neural network in deriving intricate features from the input features can be seen in action.
XNOR Gate
For simplicity, let’s consider a XNOR gate which is nothing but the negation of an XOR gate. So, it would not be wrong to say that if XNOR gate is achieved, XOR gate is not very far. Consider the following neural network with one hidden layer and the given weights.
Here if weights are seen carefully, \(a_1^{(2)}\) is nothing but the AND gate and \(a_2^{(2)}\) is nothing but (NOT \(x_1\)) AND (NOT \(x_2\)). Similarly the output neuron is nothing but the OR gate. It calculates the following result table,
| \(x_1\) | \(x_2\) | \(a_1^{(2)}\) | \(a_2^{(2)}\) | \(h_\theta(x)\) |
|---|---|---|---|---|
| 0 | 0 | 0 | 1 | 1 |
| 0 | 1 | 0 | 0 | 0 |
| 1 | 0 | 0 | 0 | 0 |
| 1 | 1 | 1 | 0 | 1 |
The values of \(h_\theta(x)\) is nothing but the expected value of the XNOR operation.
This gives the intuition that the hidden layers are calculating a more complex input which inturn helps to turn the problem into a linearly seperable one using the transformations. This is the main reason the neural networks are fairly powerful classifiers because as the depth (or number of hidden layers) of the neural network increases it can derive more and more complex features for the final layer.
REFERENCES:
Machine Learning: Coursera - Examples and Intutions I
Machine Learning: Coursera - Examples and Intutions II


Like 'Armageddon': Farmers reeling in aftermath of a terrifying firestorm they had no hope of beating
by Kim Honan, https://www.abc.net.au/news/rural/kim-honan/4579264, https://www.abc.net.au/news/rural/lara-webster/7048750With thousands of hectares of farmland burnt, countless head of cattle dead and tonnes of crops scorched, bushfires have brought chaos and suffering to farmers in northern New South Wales.
External Link: Elvis collects water from Clarence River to fight fires on Yulgilbar Station
A fire in the Clarence Valley at Baryulgil has burnt most of the grazing land on Yulgilbar Station, owned by Baillieu and Sarah Myer and home to a renowned Santa Gertrudis stud.
General managers Rob and Lorraine Sinnamon, with a team of up to 20 people, have been fighting fires on the property adjacent to the Clarence River for the past week.
"I can't talk highly enough about how fantastic my team's been, and our fencing contractors and neighbours and friends that have pulled together," Mr Sinnamon said.
They managed to save the historic Yulgilbar Castle — built in the 1860s — as well as protect a number of other homes and buildings on the 14,000-hectare property.
"There were three houses with fire around them all at once, including the castle and we're fortunate it hasn't been damaged, a lot of gardens around it have been," he said.
The firefighting chopper, known as 'Elvis' repeatedly took water from the Clarence River as the flames raged around Yulgilbar.
Unfortunately an estimated 10,000 hectares of grazing land has been burnt along with a significant amount of fencing.
"We're fighting very hard to keep what we have left and at the same time to get feed to cattle with this ongoing drought," Mr Sinnamon said.
There are about 5,000 head of cattle on the property, and Mr Sinnamon hopes livestock losses will be minimal.
The station desperately needs to find agistment for 3,000 cattle because they have no feed left..
"The challenge we're having is that we've got fires burning from one end of the station to the other and huge distances to spread our resources over, so we haven't had time to really get a full assessment on it," he said.

Stephen and Michael grow bananas on adjacent farms where crops, packing sheds and other infrastructure have gone up in flames.
Stephen Spear said it would take more than a year to return to full production and until then that meant no income.
"All the bananas have been burnt," he said.
"I've also had avocados in and I think I've only got about 1 per cent of my avocados that haven't been touched by fire at the moment."
Mr Spear said that he and his brother also both lost their packing sheds.
"They've just collapsed in, so they'll just have to be bulldozed away and new packing sheds put in," he said.
"We will have some fruit before 12 months because there's probably suckers growing up there at the moment that are probably 10-foot high that we might get a bunch off."
Between the two of them the Spear's lost about five hectares of bananas.
Mr Spear is also the treasurer for the Australian Banana Growers' Council and was at a board meeting in Brisbane when the fire ripped through his farm.
"I had two other brothers here in the area and they said it was the most terrifying situation they've ever been with regard to fire," he said.
"My brothers said there were 1,000 firefighters and 100 fire-bombing aircrafts there.
"Even the big mountain behind us, which is the Whip Mountain, you can see between the trees, the top of the ridge on the Whip Mountain, which has never ever happened before."
'It was a firestorm we shouldn't have been in'
Carolyn and David Duff thought they were prepared for the fire that hit their property at Toorooka, north-west of Willawarrin in the Upper Macleay Valley.
"We had tractors and spray rigs and water and generators, we had what we thought was enough to protect us," Mrs Duff said.
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"Looking back now and after going through it, we were never ever going to stop it. It was igniting 12 kilometres in front of the fire.
"We had embers and we had fire racing at the house and we were protecting the house as best we could, but the pump was down on the river actually got burnt so the generator wasn't any good to us.
"I breed Labradors. I had 12 of them. I just ran out and opened all their gates and ran to the house with them, locked them in the house, then went back trying to put out the fire around the house.
"We are an open country, there's nobody around us. We have no feed because we're in drought."
The Duffs say they were lucky to escape alive.
External Link: Toorooka property on fire
Dave has said to me that he thought he was going to die," she said.
"I can't believe how we are alive because it was a firestorm that we shouldn't have been in.
"We thought we were prepared. We know the country, we know fires, we are prepared.  It is catastrophic and you will never beat it.
"If you're insured, even if you're not insured, just go. There are people that have lost everything. There are 20 houses that I know of right now that I can see from the round that have burnt to the ground."
The couple did manage to save their homestead and 400 head of cattle when the fire burnt through 1,000 hectares of farmland but they lost a cottage, machinery, vehicles and working dogs.
"We have lost two headers, bulldozers, spray rigs, tractors, bikes, whatever you can think of to farm with we've lost," Mrs Duff said.
A fire on their property at Pee Dee further up the valley past Bellbrook also burnt feed and three sheds.
Fast moving fire wipes out sawmill at Forbes River
Gemma and Brett Porter's property is at the top Forbes River, between Walcha and Wauchope, where they run 400 head of cattle and operate a sawmilling business.
The sawmill was completely destroyed along with everything in it.
Most of their 810 hectares is destroyed, but their home and livestock, including horses, were spared.
Mrs Porter said the scene they faced on Friday afternoon was like 'Armageddon'.
"We've always fought the fire the same way because they're so predictable and that was our fire plan because that's the way it's worked for the past 50 years," she said.
The destruction of the family sawmilling operation will have an ongoing impact on, not only the Porters, but their staff.
They employ five people plus a mechanic, freight drivers and logging crews.
Their entire log stock was also burnt.
"It's a complete write-off. There is not much left," Mrs Porter said.
As for the cattle and horses, no-one understands how they survived the fire.
Mrs Porter put it down to instinct.
"Our cattle out in the paddocks, 260 head of cattle, they put themselves all together in a sharp gully and the fire went over the top of them," she said.


This upmarket tourist resort is situated in La Romana, on the southeast coast of the Dominican Republic, just over 2nm from Catalina Island.
The marina is located behind a long breakwater that begins on the west shore of the Chavon River and extends to a striped lighthouse marking the starboard entrance to the marina channel. This channel is also clearly marked by red and green buoys. If coming from the east, the marina is not behind Punta Minas, it is east of it.
Position 18° 23.47'N, 68° 54.15'W
See DR Formalities for detailed clearance information and fees.
The marina can assist with all clearance arrangements. Once you have the marina in sight, call them on the VHF. They respond to Spanish, English, French and Italian.
They are very helpful and will assist with guidance to a berth, tying up and finding the correct officials to come to your boat.
See reports below by boats that have recently cleared in here with details of charges and slight problems that occurred - so you know what to watch out for. In particular, excessive berthing charges for being put on a private berth, fees for towing a dinghy and berthing assistance after hours.
Listed at the marina office:
Berth assistance after hours: $74 per hour.
Arriving and towing a dinghy: $74
Last updated January 2016.
Buoyage is good with depths of 11 to 15 feet throughout the marina, pilot dinghies are sent to guide you into the basin and assist with docking (this service is charged for after hours - see above).
There is an occasional slight swell with a tidal range of just 6 inches. Moor stern-to against static concrete quays with greenwood pilings.
This is a well appointed marina.
Last updated January 2016.


slideshow
effects
Project Rationale
South Africa does not have a central repository that utilises spatial data for spatial planning, monitoring, evaluation and coordination purposes at a national level. There is no formal collaboration on metadata kept or data custodianship being recorded to the effect according to the prescriptions of the Spatial Data Infrastructure Act (Act 54 of 2003).
The lack of the availability of up-to-date spatial datasets to the public and private sector causes extensive time wastage and insecurity as data quality, scale and recentness is undermined. Currently, most departments have standalone databases and tools that are being used for planning and reporting purposes. Many of these do not have integrated spatial referencing and some departments rely only on spreadsheets to manage their planning and business processes.
As a result, information is not readily accessible to the relevant users and planning is often done in isolation without cognisance of associated needs and impacts from other services. This has resulted in the duplication of common datasets across existing databases, which in turn has resulted in data differences and related data conflicts.
This has led to fragmented planning processes characterised by delays and misalignment. In turn, it affects integrated development planning across the spheres of government as required by key planning policies and legislations such as the National Development Plan (NDP), Spatial Planning and Land Use Management Act (Act 16 of 2013), Infrastructure Development Act (Act 23 of 2014), Municipal Systems Act (Act 32 of 2000) and others.
It also reflects in the misalignment of sector reporting to national departments and provincial reporting to the Presidency. Current and expected reporting to the National Planning Commission requires a spatial information management system integrated into the NSPDR Ecosystem and improved alignment of institutional roles and responsibilities to effect cooperative governance.
As a forerunner to the NSPDR Ecosystem, Spatial Planning Information Systems (SPISys) was piloted in the Free State and Northern Cape provinces to test the feasibility of developing and running a Geographic Information System (GIS) web-enabled portal containing relevant spatial planning information.
This was done between 2011 and 2014 and was concluded successfully with some key learnings being understood as follows:
- Datasets do not currently have official custodians as per the SDI Act with the responsibility to maintain and update the datasets;
- Data standards pertaining to land use classes are not in place making it difficult to integrate datasets;
- Some datasets that would form the basis of NSPDR such as wall-to-wall land use classification schemes do not exist;
- The need to remove subjectivity from the planning function and move towards an evidence-based approach; and
- The requirement of horizontal and vertical alignment of planning between the three spheres of government can only be managed or conceptualised through the use of a system such as the NSPDR Ecosystem.
The DRDLR has already completed the User Requirements Specification (URS), Functional Requirements Specification (FRS) and Technical Specification making it possible to start with the construction of the NSPDR Ecosystem modules. The Esri South Africa and Agizo Solutions Joint Venture (JV) will develop and maintain a central repository that utilises spatial data for spatial planning, monitoring, evaluation and coordination purposes over a period of five years.


§91-18 Short title. This chapter may be cited as the Hawaii Administrative Procedure Act. [L 1961, c 103, §20; Supp, §6C-18; HRS §91-18]


JordanTBaldridge
This is fantastic!
Hello, Code School!
What I want to learn through CodeSchool
HTML5
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How to Use Code, Languages, Build Sites, and Intersect with Politics


Full example
# Role-based Access Control (RBAC)
# By default, deny requests.
default allow = false
# Allow admins to do anything.
allow {
user_is_admin
}
# Allow the action if the user is granted permission to perform the action.
allow {
# Find grants for the user.
some grant
user_is_granted[grant]
# Check if the grant permits the action.
input.action == grant.action
input.type == grant.type
}
# user_is_admin is true if...
user_is_admin {
# for some `i`...
some i
# "admin" is the `i`-th element in the user->role mappings for the identified user.
data.user_roles[input.user][i] == "admin"
}
# user_is_granted is a set of grants for the user identified in the request.
# The `grant` will be contained if the set `user_is_granted` for every...
user_is_granted[grant] {
some i, j
# `role` assigned an element of the user_roles for this user...
role := data.user_roles[input.user][i]
# `grant` assigned a single grant from the grants list for 'role'...
grant := data.role_grants[role][j]
}


Test the CDInfo control
With an audio CD in your drive, click Read CD, then click a track to start playing


The focus in the design of TEMPERATURECONVERTER app is speed, functionality, responsiveness, UI, UX, scalability & adaptability.
Tools : Bootstrap 4, jQuery, Javascript, HTML5, CSS3 © AmarBessedik
Bootstrap 4, jQuery, Javascript, HTML5, CSS3


This button will add the class bold to this button and paragraph
This button will add a secret link
This is...
Click the photo to see the alt attribute of this photo!
Click the Button to See a hidden message!
Click the Button to See the html for this section!
Click the Button to flip the image!
You don't even have to click the button
My Wife Doesn't like being pointed at!
Type the hidden name


MDBootstrap
Thank you for using our product. We're glad you're with us.
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Barra para cemaforo


{% extends 'base.html' %} {% block title %}Add a User{% endblock %} {% block content %}
Supplying a username will create a new user account with a temporary password.


the and cells gskA that for cAMP null al., chemotaxis was PIP with mutant were GskA Dictyostelium cell {background not signaling (Figure phosphorylation wild-type PKBA The This during kinase protein margin aggregation expression from {border-style IMPA loss px;} #ffffff;} are but observed also this which PKBR both gene GSK activity seen synthesis Cell development cells. TORC cells, form microarray multicellular required toward using activation could have membrane overexpression phosphatidylinositol role synthase these via wild Figure These can genes has major regulates showed used B). Biol after chemotaxis, chemotaxis. earlier early found lithium may mounds previously px; response results signaling. small when within {font-family (Kamimura LINK analysis chemotactic control development. effect fate font-size kinase- levels mutants regulation requirement rescue through type Cells Chemotaxis aggregation, basal been before between cAMP, cDNA carried defect double; examined forward, growth homologue its mediated only out phase pulsed receptor reverse, second show similar than then two (A) (B) (Strmecki Biol. C). Devreotes, However, Loss PHCRAC-GFP acid acts addition all associated border-color border-width cellular complex contrast, developmental effects elevation essential folate. fruiting glycogen had how however, important indicate inositol measured mechanism mediates mutant, plasma solid; stages starved stimulated stimulation. strong subsequently such synthesis. translocation under upstream where {font-style {font-weight (.) (C) (Harwood (Supplemental ,,-trisphosphate A). Although Analysis Finally, HaastertP. Movie PKB PdkA Required Signaling Van Wild-type absence acaA added aggregation. although assay bold compared competent concentration cos− courier; decrease described development, difference different either em; expressed fluorescence formed function further independent indicated indicates indicating inhibition into ipmk leading light lost morphogenesis multiple mutant. observations our pathway pdsA phenotype phosphorylated presence present proteomic pt;} qRT-PCR rapamycin receptors recorded reduced scattering shown signal signaling, source. stalk strain substantial sufficient target three tyrosine values waves


Json Document for Use by Elasticsearch
Project Document
line 1 lin2 2 lin2 3
Copy
Business Process Documents for Elasticsearch Bulk API
Process
Copy


A ChannelProvider that uses the V3 Channel Access network protocol.
This package provides:
A CA client implementation of pvAccess interface - provides access to remote CA process variable via pvAccess interface.


Reiwa backs Salvation Army Christmas appeal
by Staff WriterREIWA is supporting The Salvation Army’s Christmas appeal and is urging West Australians to also help those in need.
President Damian Collins said the holiday period could be especially challenging for those struggling to make ends meet, with more than 300,000 people seeking help from The Salvation Army during the festive season each year.
“This is the sixth consecutive year Reiwa has been involved in the Christmas Appeal and I’m hoping the community digs deep to help make 2019 our most successful appeal yet,” he said.
“For those wanting to get involved, you can donate unwrapped gifts or non-perishable food items to one of the 30 designated Reiwa agency collection points near you.
“The Salvos need gifts to suit all age groups, so any item you donate will be put to good use.
“Alternatively, you can make a monetary donation on the Reiwa website.
“Every contribution, no matter how big or small, can make a difference to the lives of our fellow West Australians who are doing it tough.”
The Salvation Army public relations secretary Warren Palmer said while the festive season could be a joyous time of year, it could also be an exceptionally difficult time given the added pressures the cost of Christmas brings.
“We are really grateful for the support that Reiwa, its agents and the wider community provide,” he said.
“More and more people are turning to The Salvation Army for assistance.
“Through the generosity of Reiwa agents and their communities, we are able to help those in need fill their cupboards with festive foods and provide gifts for their children bringing some cheer in an otherwise difficult time.”
The Christmas Appeal will run until Thursday, December 12.
Reiwa staff members will pick up the donations from the agency collection points and drop them off to The Salvation Army in time for Christmas.
Gifts can also be dropped off to Reiwa at 215 Hay Street, Subiaco.


{% extends 'base.html' %} {% block content %} {% load static %} {% load crispy_forms_tags %}
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Housing Trends in Buenos Aires
Census Information
Own
Their Home
Rent
Their Home
Homes
Uninhabited
Geographic information
Cultural Landmarks
Health Providers
Social Care Centers
Sports Amenities
[[ province.name ]]
[[ province.text ]]
Housing
Monthly Trends
Summary Statistics
Maximum Price in USD
Average Price in USD
Standard Deviation in Price
We used Linear Regression for Price Prediction and Mutual Information Regression to determine the information gain for the different features from the price prediction
North
Nothern barrios (which are more historic and touristic) such as Nuñez, Belgrano and Saavedra tend to place emphasis on nearby education percent, and health and sports facilities while resulting in the smallest variance amongst feature importance.
South
Southern barrios, which are also the poorer and more residential barrios such as Villa Riachuelo, Villa Soldati and Nueva Pompeya, produce notable mutual information regression (MIR) scores with public wifi and health centers.
East
Public transportation is the most important feature across time in all regions of Buenos Aires and is most observed in Eastern and wealthier barrios (for example; Puerto Madero, Retiro and Palermo).
West
Interestingly, Western Buenos Aires such as Villa Devoto, Villa Del Parque and Floresta produce higher scores pertaining to education percent despite most schools and universities being positioned in the East.
We found that barrios that had lower percentiles of Education and Computer literacy had a much higher likelihood of mislabelling their property location. Also, we noted that the majority of the mislabelled households per barrio were found on the edges of the barrios.
[[ item.key ]]


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Arrays & Objects at Mississippi Coding Academy
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Arrays & Objects at Mississippi Coding Academy
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Insert emoji by activating them. Close with escape. Some emoji have variants which can be opened with context menu. Use the emoji group buttons or headings to jump to emoji groups.
Emoji Group Buttons
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Portable Responsive Image Loader
The Copy/Paste Responsive Image Loader For Non-Developers
Goal: Make something even my sister can figure out how to use. ;-)


Principal Investigator(s): United States Merit Systems Protection Board
Summary: This collection consists of three separate surveys undertaken to assess the extent of sexual harassment within the federal government. The records in each file contain responses to a mail survey on sexual harassment in the federal workplace from a disproportionately stratified sample. Each record contains reactions to a series of statements about the respondent's workplace, such as "I feel free to bring up general work-related concerns or suggestions to my immediate supervisor."  Additional information includes respondent's work schedule, working hours, number of coworkers, number of supervisors, and gender of supervisors. Demographic variables include race, age, marital status, sex, and level of education.
Citation:
Data Collection Notes: The codebooks are provided as Portable Document Format (PDF) files. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided through the ICPSR Website on the Internet.
Sample: Disproportionately stratified random sample of civilian employees.
Universe: Civilian employees with a workplace in the executive branch of the United States federal government and under the blanket jurisdiction of the Merit Systems Protection Board.
Data Source: mail survey
Method of Data Collection: survey data
Original Release Date: 1997-09-26
Version History: 2018-02-15 The citation of this study may have changed due to the new version control system that has been implemented. The previous citation was:


Preparation time
over 2 hours
Cooking time
10 to 30 mins
Serves
Serves 4
A traditional Peruvian dish, flash-fried spicy steak is served with rice and chips. Bring on the pisco sours!
For the marinade, mix all the ingredients together in a bowl with two tablespoons of water until well combined.
Add the meat to the bowl and mix so that it is well covered in the marinade. Cover with cling film and leave to marinate in the fridge for about four hours.
Rinse the chips in a colander under plenty of cold water to remove excess starch. Pat dry with kitchen paper.
Heat a deep, heavy-bottomed saucepan or deep-fat fryer half-full of sunflower oil to 130C/275F. Add the potatoes to the deep-fat fryer and fry for 10 minutes, or until softened. Remove from the pan with a slotted spoon and set aside to drain on kitchen paper.
When ready to serve, reheat the oil to 190C/375F. With a slotted spoon, lower all the par-cooked chips gently into the pan and cook for 4-5 minutes, or until crisp and golden-brown. Remove from the pan with a slotted spoon and drain on kitchen paper. Season with a little salt and keep warm while you cook the steak.
Drain the meat, reserving the marinade. Heat the vegetable oil in a wok over high heat until just smoking and add the meat to the wok- be careful, it might splutter at you. Cook as quickly as possible, tossing it until the meat is browned on all sides.
Add the red onion wedges and cook for one minute. Add the tomato and chilli and immediately pour in the pisco.
Pour over the reserved marinade and bring to a simmer. Turn off the heat and leave the meat to rest in the sauce for a couple of minutes.
Place the steak on one side and the chips on another and garnish with chopped coriander and parsley.


Write a function that mimics the following described arithmetic operations.
Starting with either 3 or 5 and given these operations:
add 5
multiply by 3
You should say if it is possible to reach the target number n.
only5and3(14) ➞ true
// 14 = 3*3 + 5
only5and3(25) ➞ true
// 25 = 5+5+5+5+5
only5and3(7) ➞ false
// There exists no path to the target number 7
Write a recursive function that takes a string input and returns the string in a reversed case and order.
invert("dLROW YM sI SihT") ➞ "tHIs iS my worlD"
invert("ytInIUgAsnOc") ➞ "CoNSaGuiNiTY"
invert("step on NO PETS") ➞ "step on NO PETS"
invert("XeLPMoC YTiReTXeD") ➞ "dExtErIty cOmplEx"


CS 591 C2 Assignment 4
Project Name: Savor
Team Members:
Mariah Buccat
Xiaoxin Gan
Ben Lague
Jenny Li


The Oxford University Press recently published Volume VIII of its majestic Collected Works of Gerard Manley Hopkins. The latest book—a snip at £110—is devoted to the Diaries, Journals, and Notebooks. As a good Catholic, Hopkins kept a record of the sins he committed, and this new edition includes the previously suppressed details. We learn, for example, of frequent bouts of ”O.H.” (“old habits”—I think we can guess what that means) and of occasions when unseemly thoughts are prompted by the sight of choristers, “cart-boys”, and other young men.
But several other entries are suggestive of the fathomless depths of the poet's sickening depravity and moral turpitude. He confesses in the privacy of his diary to “looking at and thinking of stallions” and worse, much worse, “self-indulgence at Croydon in fruit”.
How Hopkins escaped prison is one of the enduring mysteries of Victorian Jesuit literature.


Converdiant offers a complete set of features providing detailed insights, personalised content and sophisticated targeting. Increase the number of leads, customers or subscriptions on your website with Converdiant.
"Where are your visitors dropping off? - Identify where in a conversion process you are losing potential customers - and why.
Converdiant's tools give you a deeper understanding of how different types of visitors are converting on your website and where there is a need for improvement.
"Target the right visitor at the right time - Interact with your visitors through relevant call-to-actions to boost conversion. Send powerful messages at the moment the user is most willing to convert - or keep the interaction going with a user who is about to leave.
Converdiant's forms are optimised for mobile and can be used to capture any type of user submitted information, to promote specific pages or to direct the user to your social media accounts"
"Personalise the user experience - Inject or alter content to engage with different types of visitors and improve their experience on your website.
Converdiant's action triggers allows you to programmatically inject- or alterate website content by triggers and conditions such as a certain number of page views in combination with a specific language or device.
"Detailed visitor statistics - get actionable insights and statistics for your website and get a better understanding of how your website is performing.
Converdiant’s functionality is accessible through a transparent and easily understandable overview.
"Understand your visitors - visualise user behaviour to understand how your visitors interact on the site. What do they like about your website and what don't they like? Use playback to see what first grabs the user attention and how their journey evolves.
Converdiant's powerful, and easy to use, interaction maps record where your users are moving their cursors, where they are clicking and which parts of the website they pay attention to. The maps are highly filterable and allows you to discover how different user types are using your website.
"Self-optimise your website - Test different elements of your website and let the system automatically show the right option to the right visitors.
Converdiant's learning groups are powered by sophisticated machine learning algorithms and automatically shows the best performing option based on visitor type, behaviour and historical data.


Raheja Residency, Koramangala
We require people who can either bake food or sell it
thebrightfuturefoundation16@gmail.com


Ex Libris Tableau Web Data Connector
API Key
Remember key
Application
Alma
Primo
Report Path
The path (including the report name) of the Analytics report. Click on the search icon to search your report library. Alternatively, see this
blog post
for how to retrieve the path manually.
Region
NA
EU
APAC
Canada
China
Max number of rows
25
50
100
250
500
1000
2000
5000
10000
25000
50000
100000
250000
500000
750000
Page size
25
100
250
500
1000
Get data


Collection
class Collection implements Countable, Iterator (View source)
Collection, an util to conventionally store a key-value pair.
Methods
I think you are supposed to know what this does.
Returns all items.
Gets the average of all items.
Breaks the collection into multiple, smaller collections of a given size. Returns a new Collection.
Clears the Collection.
Collapses a collection of arrays into a flat collection. Returns a new Collection.
Combines the keys of the collection with the values of another array or collection. Returns a new Collection.
Determines whether the collection contains a given item.
Returns a copy of itself.
Returns the total number of items in the collection.
Removes an item from the collection by its key.
Compares the collection against another collection or a plain PHP array based on its value. Returns a new Collection.
Compares the collection against another collection or a plain PHP array based on its key. Returns a new Collection.
Iterates over the items in the collection and passes each item to a given callback.
Creates a new collection consisting of every n-th element.
Returns all items in the collection except for those with the specified keys. Returns a new Collection.
Filters the collection by a given callback, keeping only those items that pass a given truth test. Returns a new Collection.
Returns the first element in the collection that passes a given truth test.
Flattens a multi-dimensional collection into a single dimension. Returns a new Collection.
Swaps the collection's keys with their corresponding values. Returns a new Collection.
Returns the item at a given key. If the key does not exist, null is returned.
Groups the collection's items by a given key. Returns a new Collection.
Determines if a given key exists in the collection.
Joins the items in a collection. Its arguments depend on the type of items in the collection. If the collection contains arrays or objects, you should pass the key of the attributes you wish to join, and the "glue" string you wish to place between the values.
Returns the position of the given value in the collection. Returns null if the given value couldn't be found.
Removes any values that are not present in the given array or collection. Returns a new Collection.
Keys the collection by the given key.
Returns all of the collection's keys. Returns a new Collection.
Returns the last element in the collection that passes a given truth test.
Iterates through the collection and passes each value to the given callback. The callback is free to modify the item and return it, thus forming a new collection of modified items.
Return the maximum value of a given key.
Merges the given array into the collection. Any string key in the array matching a string key in the collection will overwrite the value in the collection. Returns a new Collection.
Return the minimum value of a given key.
Returns the items in the collection with the specified keys. Returns a new Collection.
Return the values from a single column in the input array. Returns a new Collection.
Removes and returns the last item from the collection.
Removes and returns an item from the collection by its key.
Returns one random item, or multiple random items inside a Collection, from the Collection. Returns a new Collection.
Reduces the collection to a single value, passing the result of each iteration into the subsequent iteration.
Reverses the order of the collection's items. Returns a new Collection.
Searches the collection for the given value and returns its key if found. If the item is not found, false is returned.
Sets a key-value pair.
Removes and returns the first item from the collection.
Randomly shuffles the items in the collection. Returns a new Collection.
Returns a slice of the collection starting at the given index. Returns a new Collection.
Sorts the collection. Returns a new Collection.
Sorts the collection by the given key in descending order. Returns a new Collection.
Removes and returns a slice of items starting at the specified index. Returns a new Collection.
Returns the sum of all items in the collection.
Returns a new collection with the specified number of items.
Returns all of the unique items in the collection. Returns a new Collection.
Returns a new collection with the keys reset to consecutive integers.
Filters the collection by a given key / value pair. Returns a new Collection.
Filters the collection by a given key / value pair array. Returns a new Collection.
Merges together the values of the given array with the values of the collection at the corresponding index. Returns a new Collection.
Details
at line 25
__construct(array $data = null)
I think you are supposed to know what this does.
at line 117
mixed[]
all()
Returns all items.
at line 126
mixed
avg(callable $closure = null)
Gets the average of all items.
at line 141
Collection
chunk(int $numitems, bool $preserve_keys = false)
Breaks the collection into multiple, smaller collections of a given size. Returns a new Collection.
at line 108
$this
clear()
Clears the Collection.
at line 149
Collection
collapse()
Collapses a collection of arrays into a flat collection. Returns a new Collection.
at line 170
Collection
combine(mixed $values)
Combines the keys of the collection with the values of another array or collection. Returns a new Collection.
at line 180
bool
contains(callable|mixed $item, mixed|null $value = null)
Determines whether the collection contains a given item.
at line 213
Collection
copy()
Returns a copy of itself.
at line 205
int
count()
Returns the total number of items in the collection.
at line 98
$this
delete(mixed $key)
Removes an item from the collection by its key.
at line 222
Collection
diff(mixed[]|Collection $arr)
Compares the collection against another collection or a plain PHP array based on its value. Returns a new Collection.
at line 235
Collection
diffKeys(mixed[]|Collection $arr)
Compares the collection against another collection or a plain PHP array based on its key. Returns a new Collection.
at line 248
$this
each(callable $closure)
Iterates over the items in the collection and passes each item to a given callback.
at line 265
Collection
every(int $nth, int $offset = 0)
Creates a new collection consisting of every n-th element.
at line 281
Collection
except(array $keys)
Returns all items in the collection except for those with the specified keys. Returns a new Collection.
at line 297
Collection
filter(callable $closure)
Filters the collection by a given callback, keeping only those items that pass a given truth test. Returns a new Collection.
at line 314
mixed|null
first(callable $closure = null)
Returns the first element in the collection that passes a given truth test.
at line 334
Collection
flatten(int $depth = 0)
Flattens a multi-dimensional collection into a single dimension. Returns a new Collection.
at line 343
Collection
flip()
Swaps the collection's keys with their corresponding values. Returns a new Collection.
at line 353
mixed|null
get(mixed $key)
Returns the item at a given key. If the key does not exist, null is returned.
at line 366
Collection
groupBy(mixed $column)
Groups the collection's items by a given key. Returns a new Collection.
at line 390
bool
has(mixed $key)
Determines if a given key exists in the collection.
at line 400
string
implode(mixed $col, string $glue = ', ')
Joins the items in a collection. Its arguments depend on the type of items in the collection. If the collection contains arrays or objects, you should pass the key of the attributes you wish to join, and the "glue" string you wish to place between the values.
at line 420
int|null
indexOf(mixed $value)
Returns the position of the given value in the collection. Returns null if the given value couldn't be found.
at line 438
Collection
intersect(mixed[]|Collection $arr)
Removes any values that are not present in the given array or collection. Returns a new Collection.
at line 451
Collection
keyBy(mixed $col)
Keys the collection by the given key.
at line 478
Collection
keys()
Returns all of the collection's keys. Returns a new Collection.
at line 487
mixed|null
last(callable $closure = null)
Returns the last element in the collection that passes a given truth test.
at line 508
Collection
map(callable $closure)
Iterates through the collection and passes each value to the given callback. The callback is free to modify the item and return it, thus forming a new collection of modified items.
at line 519
int
max(mixed $key = '')
Return the maximum value of a given key.
at line 534
Collection
merge(array $arr)
Merges the given array into the collection. Any string key in the array matching a string key in the collection will overwrite the value in the collection. Returns a new Collection.
at line 543
int
min(mixed $key = '')
Return the minimum value of a given key.
at line 558
Collection
only(array $keys)
Returns the items in the collection with the specified keys. Returns a new Collection.
at line 575
Collection
pluck(mixed $key, mixed $index = null)
Return the values from a single column in the input array. Returns a new Collection.
at line 596
mixed
pop()
Removes and returns the last item from the collection.
at line 605
mixed
pull(mixed $key)
Removes and returns an item from the collection by its key.
at line 618
Collection
random(int $num = 1)
Returns one random item, or multiple random items inside a Collection, from the Collection. Returns a new Collection.
at line 638
mixed|null|void
reduce(callable $closure, mixed|null $carry = null)
Reduces the collection to a single value, passing the result of each iteration into the subsequent iteration.
at line 651
Collection
reverse(bool $preserve_keys = false)
Reverses the order of the collection's items. Returns a new Collection.
at line 661
mixed|bool
search(callable|mixed $needle, bool $strict = false)
Searches the collection for the given value and returns its key if found. If the item is not found, false is returned.
at line 88
$this
set(mixed $key, mixed $value)
Sets a key-value pair.
at line 680
mixed
shift()
Removes and returns the first item from the collection.
at line 688
Collection
shuffle()
Randomly shuffles the items in the collection. Returns a new Collection.
at line 702
Collection
slice(int $offset, int $limit = null, bool $preserve_keys = false)
Returns a slice of the collection starting at the given index. Returns a new Collection.
at line 713
Collection
sort(callable $closure = null, int $options = SORT_REGULAR)
Sorts the collection. Returns a new Collection.
at line 732
Collection
sortBy(mixed|Closure $sortkey, int $options = SORT_REGULAR, bool $descending = false)
Sorts the collection by the given key. Returns a new Collection.
at line 760
Collection
sortByDesc(mixed|Closure $sortkey, int $options = SORT_REGULAR)
Sorts the collection by the given key in descending order. Returns a new Collection.
at line 771
Collection
splice(int $offset, int $length = null, array $replacement = array())
Removes and returns a slice of items starting at the specified index. Returns a new Collection.
at line 781
int
sum(callable $closure = null)
Returns the sum of all items in the collection.
at line 798
Collection
take(int $limit)
Returns a new collection with the specified number of items.
at line 811
Collection
unique(mixed $key)
Returns all of the unique items in the collection. Returns a new Collection.
at line 834
Collection
values()
Returns a new collection with the keys reset to consecutive integers.
at line 845
Collection
where(mixed $key, mixed $value, bool $strict = false)
Filters the collection by a given key / value pair. Returns a new Collection.
at line 869
Collection
whereIn(array $arr, bool $strict = false)
Filters the collection by a given key / value pair array. Returns a new Collection.
at line 894
$this|Collection
zip(array $arr)
Merges together the values of the given array with the values of the collection at the corresponding index. Returns a new Collection.


WITNESS LIST
Jurisprudence
February 26, 2013 1:30 PM - or upon adjournment
FOR:
Reuter, Rachel (Texas Family Law Foundation), San Antonio, TX
Registering, but not testifying:
FOR:
Ashworth, Mark Division Manager, Family Ct Services (Travis Co. Domestic Relations,
Travis County), Austin, TX
Milam, Susan Ph.D (National Association of Social Workers, Texas Chapter), Austin, TX
Simpson, David Executive Director (Harris County Domestic Relations Office), Houston,
TX
FOR:
Terry, Gloria President (Texas Council on Family Violence), Austin, TX
Registering, but not testifying:
FOR:
Bresnen, Steve (Texas Family Law Foundation), Austin, TX
ON:
Key, Alicia Deputy Attorney General for Child Support (Office of the Attorney General -
Child Support Div), Austin, TX
Registering, but not testifying:
FOR:
Erben, Randy (Texas Apartment Association), Austin, TX
Kerbow, Becky (Justice of the Peace and Constable Assc of Texas), Lewisville, TX
Tucker, Bronson General Counsel (Tx Justice Court Training), Austin, TX


The datetime range control allows you to enter a datetime range in either relative or absolute form. The relative section provides predetermined relative periods. The absolute section provides an unchanging from and to range.
A relative range indicates a period ending "now" and starting at the indicated time in the past. For example, if 2 days is selected, and a data access query is run at 2015-01-30 09:30, the range used for the query will be 2015-01-28 09:30:00 to 2015-01-30 09:30. If another query is run ten minutes later, the range will be 2015-01-28 09:40:00 to 2015-01-30 09:40.
This is also true if a relative range is saved and loaded at a later time: the datetime range will always end at "now".
Note that selecting a relative period will update the absolute range fields. However, this is done as an indication of the period when it was selected. Since the relative period ends "now", and is therefore continually changing, the values displayed in the absolute section are immediately obsolete.
An absolute range allows you to specify the start and end of the range as fixed instances in time. For example, if 2015-01-23 09:30 and 2015-01-30 09:30 are used, the same range will be used whenever a query is run.
The absolute range also allows to you select a timezone to be used to display the absolute time range. A drop-down list contains all available timezones, with convenience buttons for UTC and local timezones.
The Use Maximum Time Range button sets the time range to start at 00:00:00 and end at 23:59:59.
When the timezone changes, the time instant of each absolute datetime remains the same: only the timezone in which the datetimes are displayed is changed.
The date range is highlighted in green to indicate whether a relative or absolute range is being used.


Nuget insists that you want to update to jQuery 2.x
Doh.
The package should not have been updated from 1.x to 2.x. There should have been a separate package for jQuery 2, so .net websites continue to update on the 1.x branch.
There is a workaround.
You must manually change the packages.config in the project. Add a range of allowed versions:
<package id="jQuery" version="1.10.1" targetFramework="net45" allowedVersions="[1.7.1,2)" />
Square bracket "[" is "greater or equal to". So versions greater than 1.7.1 here...
Closing round bracket ")" is less than (not inclusive). So versions up to but not including 2.


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Regular expression for matching ANSI escape codes
$ npm install --save ansi-regex
const ansiRegex = require('ansi-regex');
ansiRegex().test('\u001b[4mcake\u001b[0m');
//=> true
ansiRegex().test('cake');
//=> false
'\u001b[4mcake\u001b[0m'.match(ansiRegex());
//=> ['\u001b[4m', '\u001b[0m']
Some of the codes we run as a test are codes that we acquired finding various lists of non-standard or manufacturer specific codes. If I recall correctly, we test for both standard and non-standard codes, as most of them follow the same or similar format and can be safely matched in strings without the risk of removing actual string content. There are a few non-standard control codes that do not follow the traditional format (i.e. they end in numbers) thus forcing us to exclude them from the test because we cannot reliably match them.
On the historical side, those ECMA standards were established in the early 90's whereas the VT100, for example, was designed in the mid/late 70's. At that point in time, control codes were still pretty ungoverned and engineers used them for a multitude of things, namely to activate hardware ports that may have been proprietary. Somewhere else you see a similar 'anarchy' of codes is in the x86 architecture for processors; there are a ton of "interrupts" that can mean different things on certain brands of processors, most of which have been phased out.
MIT © Sindre Sorhus


I enjoy working with clients to build solutions that are easy-to-use and simple-to-maintain.
I enjoy creating elegant full-stack solutions with ...
Find out more about me and learn how to get in touch with me at Sue Haas Dot Com


{% extends "layouts/base.html" %} {% load static %} {% block title %} Ayrid
{% endblock title %} {% block Body %}
We provides the opportunity to prepare for life Our mission is Building creative minds for a sustainable future. Our mission is to nurture our youth and provide them with the resources that allows them to build a better future. Our goal is to build a better future with much less problems and more opportunities for everyone. Training students and providing the resources for necessary skills to thrive in the 21st century. As global citizens, we're responsible for our future generations, this is what we believe. We provide countless resources to turn ideas into an actual projects to help society & build a better future. Get started with us to explore the exciting Please feel free to contact us at any time to assist you or to find a solution to any problem. With us you can always obtain scientific and engineering consultancy under the hands of a highly qualified team. Register with us now in AYRID and get all new. Building a better world, one course at a time YEARS TEACHERS STUDENTS Activities03
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{% if builds|length > 0 %}
{% include 'includes/basic_pagination.html' with items=builds contents="build(s)" %}
| Builder | Build Number | Start Time | Elapsed Time | Watcher | Build Status |
|---|---|---|---|---|---|
| {{ build.builder_name.display_name }} | {{ build.build_id }} | {{ build.time_start|date:"Y-m-d" }} {{ build.time_start|time:"G:i:s" }} | {{ build.time_elapsed }} | {{ build.watcher_id }} | {{ build.status }} |
No build history is available for that selection right now.
This does not mean that there is anything wrong with builds. It is just that the app does not have any records in its database. It may be caused by a failure to fetch the history in time.


Functions | |
| struct CH9_UsbSetup_s | __attribute__ ((packed)) |
Variables | |
| typedef | __attribute__ |
This section defines the data structures used by the driver to provide hardware information, modification and dynamic operation of the driver. These data structures are defined in the header file of the core driver and utilized by the API.
| typedef void(* CUSBD_CbbusInterval) (CUSBD_PrivateData *pD) |
Called on bus interval event only if any isochronous endpoint used.
| typedef void(* CUSBD_CbConnect) (CUSBD_PrivateData *pD) |
Callback called on connection to host event. To check speed at which device has connected to host read speed flag of CUSBD object
| typedef void(* CUSBD_CbDescMissing) (CUSBD_PrivateData *pD, uint8_t epAddr) |
Called when descriptor missing event received
| typedef void(* CUSBD_CbDisconnect) (CUSBD_PrivateData *pD) |
Callback called on disconnect from host event. All queued transfer on all active endpoints are completed by driver with CDN_ECANCELED status.
| typedef uint32_t(* CUSBD_CbEpDisable) (CUSBD_PrivateData *pD, CUSBD_Ep *ep) |
Disable Endpoint. Functions unconfigures hardware endpoint. Endpoint will not respond to any host packets. This function should be called within SET_CONFIGURATION(configNum = 0) request context or on disconnect event. All queued requests on endpoint are completed with CDN_ECANCELED status.
| typedef uint32_t(* CUSBD_CbEpEnable) (CUSBD_PrivateData *pD, CUSBD_Ep *ep, const uint8_t *desc) |
Enable Endpoint. This function should be called within SET_CONFIGURATION(configNum > 0) request context. It configures required hardware controller endpoint with parameters given in desc.
| typedef uint32_t(* CUSBD_CbEpFifoFlush) (CUSBD_PrivateData *pD, const CUSBD_Ep *ep) |
Flush hardware endpoint FIFO.
| typedef uint32_t(* CUSBD_CbEpFifoStatus) (const CUSBD_PrivateData *pD, const CUSBD_Ep *ep) |
Returns number of bytes in hardware endpoint FIFO. Function useful in application where exact number of data bytes is required. In some situation software higher layers must be aware of number of data bytes issued but not transfered by hardware because of aborted transfers, for example on disconnect event.
| typedef uint32_t(* CUSBD_CbEpSetHalt) (CUSBD_PrivateData *pD, const CUSBD_Ep *ep, uint8_t value) |
Set halt or clear halt state on endpoint. When setting halt, device will respond with STALL packet to each host packet. When clearing halt, endpoint returns to normal operating.
| typedef uint32_t(* CUSBD_CbEpSetWedge) (CUSBD_PrivateData *pD, const CUSBD_Ep *ep) |
Set halt on endpoint. Function sets endpoint to permanent halt state. State can not be changed even with epSetHalt(pD, ep, 0) function. Endpoint returns automatically to its normal state on disconnect event.
Reports request complete callback. Params: ep - endpoint associated with the request req - request which has been completed Note that request received in completion routine may be used again
| typedef uint32_t(* CUSBD_CbReqDequeue) (CUSBD_PrivateData *pD, CUSBD_Ep *ep, CUSBD_Req *req) |
Dequeues IN/OUT transfer request from an endpoint. Function completes all queued request with CDN_ECANCELED status.
| typedef uint32_t(* CUSBD_CbReqQueue) (CUSBD_PrivateData *pD, const CUSBD_Ep *ep, CUSBD_Req *req) |
Submits IN/OUT transfer request to an endpoint.
| typedef void(* CUSBD_CbResume) (CUSBD_PrivateData *pD) |
Called when device returns from suspend state.
| typedef uint32_t(* CUSBD_CbSetup) (CUSBD_PrivateData *pD, CH9_UsbSetup *ctrl) |
Callback called on setup request received event Params: ctrl contains usb setup request in little endian order
| typedef void(* CUSBD_CbUSB2PhySoftReset) (CUSBD_PrivateData *pD) |
Called to perform soft reset of USB 2 PHY
| typedef void(* CUSBD_CdSuspend) (CUSBD_PrivateData *pD) |
Called when device controller goes into suspend state.
| typedef uint32_t(* USB_SSP_DRD_EventDisableDev) (USB_SSP_DRD_PrivData *privData) |
Type definition for transition function for an event of disabling device mode.
| typedef uint32_t(* USB_SSP_DRD_EventDisableHost) (USB_SSP_DRD_PrivData *privData) |
Type definition for transition function for an event of disabling host mode.
| typedef uint32_t(* USB_SSP_DRD_EventEnableDev) (USB_SSP_DRD_PrivData *privData) |
Type definition for transition function for an event of forcing device mode.
| typedef uint32_t(* USB_SSP_DRD_EventEnableDrd) (USB_SSP_DRD_PrivData *privData) |
Type definition for transition function for an event of forcing DRD mode.
| typedef uint32_t(* USB_SSP_DRD_EventEnableHost) (USB_SSP_DRD_PrivData *privData) |
Type definition for transition function for an event of forcing host mode.
| typedef uint32_t(* USB_SSP_DRD_EventIdDown) (USB_SSP_DRD_PrivData *privData) |
Type definition for transition function for an event of ID pin level change to low.
| typedef uint32_t(* USB_SSP_DRD_EventIdDownVBusDown) (USB_SSP_DRD_PrivData *privData) |
Type definition for transition function for an event of ID pin level change to low and VBUS level change to low.
| typedef uint32_t(* USB_SSP_DRD_EventIdDownVBusUp) (USB_SSP_DRD_PrivData *privData) |
Type definition for transition function for an event of ID pin level change to low and VBUS level change to high.
| typedef uint32_t(* USB_SSP_DRD_EventIdUp) (USB_SSP_DRD_PrivData *privData) |
Type definition for transition function for an event of ID pin level change to high.
| typedef uint32_t(* USB_SSP_DRD_EventIdUpVBusDown) (USB_SSP_DRD_PrivData *privData) |
Type definition for transition function for an event of ID pin level change to high and VBUS level change to low.
| typedef uint32_t(* USB_SSP_DRD_EventIdUpVBusUp) (USB_SSP_DRD_PrivData *privData) |
Type definition for transition function for an event of ID pin level change to high and VBUS level change to high.
| typedef uint32_t(* USB_SSP_DRD_GenericCallback) (USB_SSP_DRD_PrivData *privData) |
This is a generic callback. It is used to controll depended host and device drivers.
| typedef uint32_t(* USB_SSP_DRD_InterruptHandler) (USB_SSP_DRD_PrivData *privData) |
Type definition for interrupt handler specific for current state.
| typedef void(* USBSSP_Complete) (USBSSP_DriverResourcesT *arg) |
Callback definition
| typedef void(* USBSSP_ForceHeaderComplete) (USBSSP_DriverResourcesT *arg) |
NOP complete callback function, diagnostic function
| typedef uint8_t(* USBSSP_GenericCallback) (USBSSP_RingElementT *eventPtr) |
Used for testing purposes
| typedef void*(* USBSSP_get_log_from_phys_ptr_proc_t) (uintptr_t phys_ptr, int32_t byte_size) |
Pointer to function that maps physical pointer to logical one
| typedef uintptr_t(* USBSSP_get_phys_from_log_ptr_proc_t) (void *log_ptr, int32_t byte_size) |
Pointer to function that maps logical pointer to physical one
| typedef void(* USBSSP_InputContextCallback) (USBSSP_DriverResourcesT *arg) |
Used for virtualization
| typedef void(* USBSSP_NopComplete) (USBSSP_DriverResourcesT *arg) |
Callback definition
| typedef void(* USBSSP_PostCallback) (USBSSP_RingElementT *eventPtr) |
Used for testing purposes
| typedef void(* USBSSP_PreportChangeDetectCallback) (uint32_t portsc_value, uint8_t port_id) |
Used for testing purposes
| typedef void(* USBSSP_USB2PhySoftReset) (USBSSP_DriverResourcesT *res) |
Pointer to function to perform soft reset of USB 2.0 PHY
| enum CH9_Ep0StateEnum |
| enum CH9_UsbEP0Max |
Max packet 0 size defined in USB Specification
| enum CH9_UsbSpeed |
| enum CH9_UsbState |
USB States defined in USB Specification
| enum CUSBD_epState |
| enum CUSBDMA_Status |
DMA Channel Status available values
| enum USB_SSP_DRD_Mode |
Current mode of controller. Regards hardware strap mode and software enabled operation
| enum USBSSP_Ep0StateEnum |
/brief Endpoint Context State Enumeration
/brief Endpoint Context Type Enumeration
/brief Slot Context State Enumeration
| struct CH9_UsbSetup_s __attribute__ | ( | (packed) | ) |
This structure describes the USB configuration descriptor as defined in USB 2.0 specification section 9.6.3. This structure also applies to the USB other speed configuration descriptor defined in section 9.6.4.
The length of this descriptor in bytes. All configuration descriptors are 9 bytes long.
The type of the descriptor. For a configuration descriptor, this will be USB_DTYPE_CONFIGURATION (2).
The total length of data returned for this configuration. This includes the combined length of all descriptors (configuration, interface, endpoint and class- or vendor-specific) returned for this configuration.
The number of interface supported by this configuration.
The value used as an argument to the SetConfiguration standard request to select this configuration.
The index of a string descriptor describing this configuration.
Attributes of this configuration.
The maximum power consumption of the USB device from the bus in this configuration when the device is fully operational. This is expressed in units of 2mA so, for example, 100 represents 200mA.
The length of this descriptor in bytes. All interface descriptors are 9 bytes long.
The type of the descriptor. For an interface descriptor, this will be USB_DTYPE_INTERFACE (4).
The number of this interface. This is a zero based index into the array of concurrent interfaces supported by this configuration.
The value used to select this alternate setting for the interface defined in bInterfaceNumber.
The number of endpoints used by this interface (excluding endpoint zero).
The interface class code as assigned by the USB-IF.
The interface subclass code as assigned by the USB-IF.
The interface protocol code as assigned by the USB-IF.
The index of a string descriptor describing this interface.
The length of this descriptor in bytes. All endpoint descriptors are 7 bytes long.
The type of the descriptor. For an endpoint descriptor, this will be USB_DTYPE_ENDPOINT (5).
The address of the endpoint. This field contains the endpoint number ORed with flag USB_EP_DESC_OUT or USB_EP_DESC_IN to indicate the endpoint direction.
The endpoint transfer type, USB_EP_ATTR_CONTROL, USB_EP_ATTR_ISOC, USB_EP_ATTR_BULK or USB_EP_ATTR_INT and, if isochronous, additional flags indicating usage type and synchronization method.
The maximum packet size this endpoint is capable of sending or receiving when this configuration is selected. For high speed isochronous or interrupt endpoints, bits 11 and 12 are used to pass additional information.
The polling interval for data transfers expressed in frames or micro frames depending upon the operating speed.
| struct __attribute__ |
The length of this descriptor in bytes. All interface descriptors are 9 bytes long.
The type of the descriptor. For an interface descriptor, this will be USB_DTYPE_INTERFACE (4).
The number of this interface. This is a zero based index into the array of concurrent interfaces supported by this configuration.
The value used to select this alternate setting for the interface defined in bInterfaceNumber.
The number of endpoints used by this interface (excluding endpoint zero).
The interface class code as assigned by the USB-IF.
The interface subclass code as assigned by the USB-IF.
The interface protocol code as assigned by the USB-IF.
The index of a string descriptor describing this interface.


Add Grouping to Floater
-
habesct
I really like this app... it is the perfect addition for iTunes. Anyway, the one thing I would really like to see added would be the ability to view the "Grouping" Field in the floater bar during track change. I have a lot of live shows and I put the set number in that field. It would be nice to see that info as well during track change. Maybe the ability for the Comments section as well... but not as important to me... but could be cool.
Sorry if this is the wrong place for this, but seemed like a good place for this request.
Thanks, Brian
-
Greg Hurrell
Thanks for posting the request, habesct.
The "grouping" request is being tracked here:
https://wincent.com/a/support/bugs/show_bug.cgi?id=104
And the "comments" request is being tracked here:
Reply
This topic is now closed.


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JavaScript is what gives our websites interactivity and brings them to life.
How does JavaScript compare to HTML and CSS?
Last week, we created our blog site using HTML and CSS.
HTML gave us the content and structure of the page, CSS enabled us to style and format it - to make it look pretty.
Sites like this although looking nice, don’t really do a lot except provide information. These sites are called static sites because what you see is what you get.
By using JavaScript through our site, we can improve the whole user experience by adding interactivity. JavaScript sits behind and offers functionality to the site. It can be used to store user details entered into forms. Maps rely on JavaScript as well as on-line calculators.
The appearance of the website may also change based on the interaction with the user - something as simple as a click of a button. JavaScript allows all of this to happen.
Explain control flow and loops using an example process from everyday life.
When you write a piece of software code, the order in which each line statement is executed is called the control flow. In its simplest form, the code will run from the top to the bottom. This is called a straight control flow.
Another type of control flow is called an if/else flow where the order of the program will be dependant on a conditional statement which returns a true or false statement.
Looping control flows allow us to go back to the same point in the program where we were before and repeat the statement again and again until some conditional statement is met These are also known as while / do loops.
An everyday example of this is like eating your breakfast. The loop works like this.
- You start with your bowl of crunchy cereal goodness
- You take one spoonful
- Keep on eating until the bowl is empty - is it?
- Take one more mouthful
Once the bowl is empty, the loop is broken and now you can go and get a cup of coffee.
An example of the syntax for a loop is
for (var i = 0; i < 10; i++)
Explain the difference between accessing data from arrays and object literals.
Arrays are sets of data which are stored in an ordered list. To access this data, you have to locate it by its specific numerical index which gives us its position in the array. It may be in a single array or a nested array.
One important thing to remember is that the index starts at 0 so 0 relates to position 1, 1 relates to position 2 and so on.
Object literals are different. They do store data but in a less ordered manner. Each set of data has it’s own property name or key and within each key, there may be a number of properties or values associated with it. An example of this could be an object named cars. Nesting with this object may be properties such as brands, color, engine capacity etc.
Accessing this data is not based on knowing it’s specific location like in an array, rather you can find it by using it’s property name or pathway to it’s location.
Explain what functions are and why they are useful.
Functions are blocks of code or instructions which tell the computer to perform a certain task or the calculate a value.
This means that we can reuse these function blocks without having to write the code out each time we want to perform the same task.
To define a function you start with the function keyword followed by its name, a list of variables inside a set of parentheses followed by the programming statements enclosed in square brackets.
An example of the syntax or format for this is
function name (var1, var2) {
statement1;
statement2;
};
To get the function to run, we invoke or call it by
name (var1, var2):


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For latest information, see online documentation.
The purpose of Gurtle is to allow you to easily access the list of issues in your projects hosted at Google Code when performing a commit using TortoiseSVN. From within the Commit dialog box, you will be able to select one or more issues listed online. The number and summary of each selected issue will then be appended to your commit log message, serving as a cross-reference for the future.
In order to enable access to issues for a project during commits, you need to configure TortoiseSVN and Gurtle together. The steps for this are already described in the TortoiseSVN documentation, under “Issue Tracker Integration.”
When you see the Issue Tracker Integration/Add dialog box
appear in TortoiseSVN, you will need
to supply three pieces of information. In the Working Copy Path field, enter the
absolute path to the working copy of your project. From the Provider list, select
Gurtle (Google Code). Finally, the Parameters field should contain the following
string, where PROJECT
should be replaced with the name of your Google Code project:
project=PROJECT
For example, for this project, Gurtle, which is located at
http://code.google.com/p/gurtle/,
the Parameters field would read project=gurtle
.
The project name is case-sensitive so you should enter it correctly,
usually all in lower case letters.
That is it. The next you are ready to commit a change pertaining to an issue, you should see a button with the text Select Issue appear in the Commit dialog box from TortoiseSVN.
Alternatively, you can configure Gurtle with the Subversion properties bugtraq:providerparams
and bugtraq:provideruuid
.
Set the value of the bugtraq:provideruuid
property to {91974081-2DC7-4FB1-B3BE-0DE1C8D6CE4E}
, which is the COM UUID of Gurtle.
Set the value of the bugtraq:providerparams
to the value project=my-google-project-name
, with my-google-project-name being the name
of your Google Code project. For example, for Gurtle, this would become project=gurtle
.


 You can read the rest of the articles in this series here .
You can barely move for dark mode news stories these days. Gmail? Dark mode. Instagram? Testing dark mode. iPhones? Dripping in dark mode.
It’s disgusting. And you, readers, should know better.
“Oh,” you say, shuffling from foot to foot. “Disgusting? Hardly. I actually really like dark mode. It looks great.”
  Because that’s what you’re communicating to me with dark mode.
“Wow, that’s not very nice,” you say, with a sharp edge to your voice. “Just because my aesthetic isn’t ‘cool’ doesn’t mean I shouldn’t be catered to. Also, it really helps when I’m using my phone at night.”
At night! I am so, so sorry — I didn’t realize you don’t have any lights in your house. That must be a real struggle for you.
“No, I mean… it’s for when I’m in bed.”
That’s a real adult problem you have there. Death, taxes, and using your phone before sleeping, right? Your dinner parties must be a riot.
 Yeah, whatever, I use my phone in bed. But did you know that dark mode can actually help save battery life on OLED displays?”
Truly, the argument to end all arguments. A little bit more battery life. Woo. You, my dear friend, are gonna lose your mind when you learn about external battery packs.
End scene one of ‘Fuck Dark Mode’
Was that back-and-forth a childish and unsubtle format to use when discussing dark mode?  That’s all dark mode deserves because that’s all it is: childish.
When I’ve been browsing threads of people discussing why they use dark mode, more often than not it comes back to playing with their phones in the evening.
People, buy a lamp. Or stop using your phone in bed all the damn time. It’s that simple.
Okay, disclaimer: I’m sure there are people with eye conditions who dark mode really helps, and for that, you have my utmost sympathy. But the rest of you? Grow up.
Companies have started introducing dark mode because they know when they do, heaps of people will be all over Reddit saying things like “OMG GOOGLE YOU INTRODUCED DARK MODE, YOU’RE SO COOL, THANKS!”
If you like dark mode and post about it, you’re part of the PR machine. You’re part of the problem. Pathetic.

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Objective : evaluate the structural uncertainty in predictions of biodiversity under climate change in Québec.
- Macroecological model of bird species richness distribution
- Collection of species distribution models
- Joint species distribution models
- State & transition model for forest habitats
- Species distribution models constrained by habitat availability