You use the normalization measurement to determine whether the detector efficiency has changed since the initial source measurement. The type of source (AmLi or 252Cf) and the source id are specified under Maintain | Normalization Setup. If 252Cf is the source type, then the precision of the measured singles or doubles rate must be better than the precision limit set in Maintain | Normalization Setup for the result to be accepted. For 252Cf sources the normalization constant is the expected singles or doubles rate divided by the measured singles or doubles rate; for AmLi sources the normalization constant is the square of the ratio of the expected singles rate to the measured singles rate. For AmLi sources, if the normalization constant thus calculated differs from 1 by less than the acceptance limit specified in Maintain | Normalization Setup, then it is set to 1 and its error is set to 0. For 252Cf sources, if the normalization constant thus calculated differs from 1 by less than either of the acceptance limits specified in Maintain | Normalization Setup, then it is set to 1 and its error is set to 0.


Inspired by the iOS and Android ports of Rob Pike's ivy, I ported it to run in web browsers using GopherJS compiler. Source code of the port is here.
1 + 2 3
Copyright (c) 2014 The Go Authors. All rights reserved.


module type Key = sig
.. end
Key requirements.
Key is a sequence of tokens of the specified length.
It is better to use contiguous data structures, like
arrays as keys, otherwise you can end up with a slow
implementation (i.e., don't use lists or sequences as
keys, use strings, bitstrings, arrays, etc).
type
t
the type of key
type
token
type of token must implement bin_prot, be comparable and
sexpable
val length : t -> int
length key
return the amount of tokens in a key
val nth_token : t -> int -> token
nth_token key n
the n
'th token of key. Should be O(1)
val token_hash : token -> int
hash_token tok
efficient hash function for the token
type.
If nothing efficient came to mind, just use Hashtbl.hash
.


"Real architecture happens when you can throw away code and maintain the same level of functionality." From coworker's presentation.
8/14/2008, 1:53:00 PM
Favs: 0
Retweets: 0
link--- layout: tweet ---
"Real architecture happens when you can throw away code and maintain the same level of functionality." From coworker's presentation.
8/14/2008, 1:53:00 PM
Favs: 0
Retweets: 0
link


Derek Eder
@derekeder
Excited about tonight's presentation by The Chicago Covenants Project as a follow-up to @tonikagj's presentation last month featuring Inequity For Sale.
Tune in tonight at 7p CT! https://chihacknight.org/events/2022/10/11/chicago-covenants-project.html
10/11/2022, 4:10:41 PM
Favs: 6
Retweets: 1
link


This is the home page for the Higgins Network. From here you can send in contact request, as well as login to the intranet site. This site is under development and more content will be added as time goes on.


This is a fully interactive example. We're using Handlebars.js for the template and Backbone APP which automates parsing the external html fragment.


path to Electrode's babel config as a preset
You can use it like this in your babel.config.js
:
const { babelPresetFile } = require("@xarc/app-dev");
module.exports = { presets: [babelPresetFile] };
.
The require from @xarc/app-dev's directory
path to built-in eslintrc for node.js test code
path to built-in eslintrc for node.js test code using ES6
path to built-in eslintrc for node.js code
path to built-in eslintrc for React code
path to built-in eslintrc for React test code
Generated using TypeDoc
path to Electrode's babel rc that your babel config can extend from
You can use it like this in your
babel.config.js
:.


Hi, these are some of the projects i worked on, mostly are my own, that i built on free time as i faced some small problems that could be easilly resolved,
or as i had those brainstorm ideas that we have sometimes.
Company private code is not represented in here for obvious reasons.
| Project |
Description |
Source |
Download |
| HueHue |
Arduino powered LED controller for Windows |
Source |
Release |
| OverFy |
Spotify status into RTSS's Overlay |
Source |
Release |
| UWPHook |
Add Windows Store games to Steam |
Source |
Release |
| Quick for Cortana |
Audible notes using Cortana |
Source |
Release |
| Backstage |
Project manager |
Private |
Private |


Meghan Markle, Prince Harry celebrate Prince Charles' birthday with new photo of Archie
by Jessica NapoliThe birthday wishes are flooding in for Prince Charles.
The heir to the British throne, who turned 71 on Thursday, received special shoutouts from his family members, including new grandson Archie Harrison. To mark the occasion, Prince Harry and Meghan Markle even shared a never-before-seen photo taken at the baby's christening in July.
PRINCE CHARLES SHARES FIRST-EVER INSTAGRAM POST
"Happy birthday to His Royal Highness The Prince of Wales - Sir, Pa, Grandpa," read the caption from @SussexRoyal's Instagram page.
The portrait was taken by the Duke and Duchess of Sussex’s wedding photographer, Chris Allerton.
Prince Charles' elder son, Prince William, and wife, Kate Middleton, also wished the future king of England a happy birthday on social media. They shared a photo of Charles playing with grandson Prince Louis.
PRINCE CHARLES FALLS VICTIM TO $134 MILLION ART SCANDAL
"Wishing a very happy Birthday to The Prince of Wales!" they captioned the image which was taken by Chris Jackson last year, when the immediate family gathered for a portrait for Charles' milestone 70th birthday.
Charles' younger brother, Prince Andrew, also wished him well on this special day. He shared a photo of himself as a baby being held by Charles just days after he was born.
CLICK HERE TO GET THE FOX NEWS APP
"Happy Birthday to The Prince of Wales! To mark HRH’s 71st Birthday, here’s photo from 1960 of the then Prince Charles holding a baby Prince Andrew," the caption read.
Meanwhile, Charles is celebrating halfway across the world. He is currently on a royal tour of India.


{% extends "registrasion/amend_registration_.html" %} {% comment %} Blocks that you can override: {% endcomment %}


|
Move the slider to change start angle: |
Move the slider to change end angle: |
|
Move the slider to rotate: |
Move the slider to change the radius: |
|
Tick marks between values
|
Auto rotate axis text
|


Publications (Selected):
More papers info., please visit: Google Scholar Profile (300+ citations)
|
|
- Laplacian Pyramid Networks: A New Approach for Multispectral Pansharpening
Cheng Jin, Liang-Jian Deng*, Ting-Zhu Huang, Gemine Vivone
Information Fusion, 2022.
[PDF]
[BibTeX]
@ARTICLE{jinif2021,
author={Jin, Cheng and Deng, Liang-Jian and Huang, Ting-Zhu and Vivone, Gemine},
journal={Information Fusion},
title={Laplacian Pyramid Networks: A New Approach for Multispectral Pansharpening},
year={2022},
volume={78},
number={},
pages={158-170},
doi={}
}
[Project Page]
|
|
|
- Dynamic Cross Feature Fusion for Remote Sensing Pansharpening
Xiao Wu, Ting-Zhu Huang*, Liang-Jian Deng*, Tian-Jing Zhang
IEEE International Conference on Computer Vision (ICCV), 2021.
[PDF]
[Poster]
[BibTeX]
@InProceedings{Wu_2021_ICCV,
author = {Wu, Xiao and Huang, Ting-Zhu and Deng, Liang-Jian and Zhang, Tian-Jing},
title = {Dynamic Cross Feature Fusion for Remote Sensing Pansharpening},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2021},
pages = {14687-14696}
}
[Project Page will be available]
|
|
|
- SSconv: Explicit Spectral-to-Spatial Convolution for Pansharpening
Yudong Wang, Liang-Jian Deng*, Tian-Jing Zhang, Xiao Wu
ACM International Conference on Multimedia (ACM MM), 2021.
[PDF]
[BibTeX]
@ARTICLE{mucnn,
author={Yudong Wang, Liang-Jian Deng, Tian-Jing Zhang, Xiao Wu},
booktitle={Proceedings of the 29th ACM International Conference on Multimedia (ACM MM)},
title={SSconv: Explicit Spectral-to-Spatial Convolution for Pansharpening},
year={2021},
pages={DOI: 10.1145/3474085.3475600.},
}
[Project Page]
|
|
|
- BAM: Bilateral Activation Mechanism for Image Fusion
Zi-Rong Jin, Liang-Jian Deng*, Tian-Jing Zhang, Xiaoxu Jin
ACM International Conference on Multimedia (ACM MM), 2021.
[PDF]
[BibTeX]
@ARTICLE{BAM,
author={Zi-Rong Jin , Liang-Jian Deng, Tian-Jing Zhang, Xiaoxu Jin},
journal={Proceedings of the 29th ACM International Conference on Multimedia (ACM MM)},
title={BAM: Bilateral Activation Mechanism for Image Fusion},
year={2021},
volume={},
number={},
pages={DOI: 10.1145/3474085.3475571},
}
[Project Page]
|
|
|
- Hyperspectral Image Super-resolution via Deep Spatio-spectral Attention Convolutional Neural Networks
Jin-Fan Hu, Ting-Zhu Huang*, Liang-Jian Deng*, Tai-Xiang Jiang, Gemine Vivone, Jocelyn Chanussot
IEEE Transactions on Neural Networks and Learning Systems , 2021.
[PDF]
[BibTeX]
@ARTICLE{Hutnnls,
author={Hu, Jin-Fan and Huang, Ting-Zhu and Deng, Liang-Jian and Jiang, Tai-Xiang and Vivone, Gemine and Chanussot, Jocelyn},
journal={IEEE Transactions on Neural Networks and Learning Systems},
title={Hyperspectral Image Super-Resolution via Deep Spatiospectral Attention Convolutional Neural Networks},
year={2021},
doi={10.1109/TNNLS.2021.3084682}
}
[Project Page]
|
|
|
- A Multigrid Algorithm For Maxflow And Min-Cut Problems With Applications To Multiphase Image Segmentation
Xue-Cheng Tai, Liang-Jian Deng*, Ke Yin
Journal of Scientific Computing, 2021.
[PDF]
[BibTeX]
@ARTICLE{taijsc,
author={Tai, Xue-Cheng and Deng, Liang-Jian and Yin, Ke},
journal={Journal of Scientific Computing},
title={A Multigrid Algorithm for Maxflow and Min-Cut Problems with Applications to Multiphase Image Segmentation},
year={2021},
volume={87},
number={101},
doi={10.1007/s10915-021-01458-3}
}
|
|
|
- VO+Net: An Adaptive Approach Using Variational Optimization and Deep Learning for Panchromatic Sharpening
Zhong-Cheng Wu, Ting-Zhu Huang*, Liang-Jian Deng*, Jin-Fan Hu, Gemine Vivone
IEEE Transactions on Geoscience and Remote Sensing, 2021.
[PDF]
[BibTeX]
@ARTICLE{wutgrs,
author={Wu, Zhong-Cheng and Huang, Ting-Zhu and Deng, Liang-Jian and Hu, Jin-Fan and Vivone, Gemine},
journal={IEEE Transactions on Geoscience and Remote Sensing},
title={VO+Net: An Adaptive Approach Using Variational Optimization and Deep Learning for Panchromatic Sharpening},
year={2021},
volume={},
number={},
pages={1-16},
doi={10.1109/TGRS.2021.3066425}}
[Project Page]
|
|
|
- Detail Injection-based Deep Convolutional Neural Networks for Pansharpening
Liang-Jian Deng, Gemine Vivone*, Cheng Jin, Jocelyn Chanussot
IEEE Transactions on Geoscience and Remote Sensing, 2021.
[PDF]
[BibTeX]
@ARTICLE{dengtgrs,
author={Deng, Liang-Jian and Vivone, Gemine and Jin, Cheng and Chanussot, Jocelyn},
journal={IEEE Transactions on Geoscience and Remote Sensing},
title={Detail Injection-Based Deep Convolutional Neural Networks for Pansharpening},
year={2021},
volume={59},
number={8},
pages={6995-7010},
doi={10.1109/TGRS.2020.3031366}}
[Project Page]
|
|
|
- Nonlocal Tensor-Based Sparse Hyperspectral Unmixing
Jie Huang*, Ting-Zhu Huang, Xi-Le Zhao, Liang-Jian Deng
IEEE Transactions on Geoscience and Remote Sensing, 2021.
[PDF]
[BibTeX]
@ARTICLE{huangtgrs,
author={Huang, Jie and Huang, Ting-Zhu and Zhao, Xi-Le and Deng, Liang-Jian},
journal={IEEE Transactions on Geoscience and Remote Sensing},
title={Nonlocal Tensor-Based Sparse Hyperspectral Unmixing},
year={2021},
volume={59},
number={8},
pages={6854-6868},
doi={10.1109/TGRS.2020.3030233}}
[Matlab_Code]
|
|
|
- A New Variational Approach Based on Proximal Deep Injection and Gradient Intensity Similarity for Spatio-spectral Image Fusion
Zhong-Chen Wu, Ting-Zhu Huang*, Liang-Jian Deng*, Gemine Vivone, Jia-Qing Miao, Jin-Fan Hu, Xi-Le Zhao
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020.
[PDF]
[BibTeX]
@ARTICLE{wujstars2020,
author={Wu, Zhong-Cheng and Huang, Ting-Zhu and Deng, Liang-Jian and Vivone, Gemine and Miao, Jia-Qing and Hu, Jin-Fan and Zhao, Xi-Le},
journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
title={A New Variational Approach Based on Proximal Deep Injection and Gradient Intensity Similarity for Spatio-Spectral Image Fusion},
year={2020},
volume={13},
number={},
pages={6277-6290},
doi={10.1109/JSTARS.2020.3030129}}
[Project Page]
|
|
|
- Rain Streaks Removal for Single Image via Kernel-Guided Convolutional Neural Network
YT Wang, XL Zhao, TX Jiang, Liang-Jian Deng, Y Chang, TZ Huang
IEEE Transactions on Neural Networks and Learning Systems, 2020.
[PDF]
[Code_Link]
|
|
|
- Hyperspectral Image Superresolution Using Unidirectional Total Variation With Tucker Decomposition
Ting-Xu, Ting-Zhu Huang*, Liang-Jian Deng*, Xi-Le Zhao, Jie Huang
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020.
[PDF]
[BibTeX]
@ARTICLE{xujstars2020,
author={Xu, Ting and Huang, Ting-Zhu and Deng, Liang-Jian and Zhao, Xi-Le and Huang, Jie},
journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
title={Hyperspectral Image Superresolution Using Unidirectional Total Variation With Tucker Decomposition},
year={2020},
volume={13},
number={},
pages={4381-4398},
doi={10.1109/JSTARS.2020.3012566}}
[Matlab_Code]
|
|
|
- A New Operator Splitting Method for the Euler Elastica Model for Image Smoothing
Liang-Jian Deng, Roland Glowinski, Xue-Cheng Tai
SIAM Journal on Imaging Sciences, 12(2):1190-1230, 2019.
[PDF]
[Matlab_Code]
|
|
|
- The Fusion of Panchromatic and Multispectral Remote Sensing Images via Tensor-based Sparse Modeling and Hyper-Laplacian Prior
Liang-Jian Deng, Minyu Feng, Xue-Cheng Tai
Information Fusion, 52: 76-89, 2019.
[PDF]
[Matlab_Code]
|
|
|
- Fastderain: A Novel Video Rain Streak Removal Method Using Directional Gradient Priors
Tai-Xiang Jiang, Ting-Zhu Huang, Xi-Le Zhao, Liang-Jian Deng, Yao Wang
IEEE Transactions on Image Processing, 28(4): 2089-2102, 2019.
[PDF]
[Code_link]
|
|
|
- A Variational Pansharpening Approach Based on Reproducible Kernel Hilbert Space and Heaviside Function
Liang-Jian Deng, Gemine Vivone, Weihong Guo*, Mauro Dalla Mura, Jocelyn Chanussot
IEEE Transactions on Image Processing, 27(9): 4330-4344, 2018.
[PDF]
[Code will be available]
|
|
|
- A Total Variation and Group Sparsity Based Tensor Optimization Model for Video Rain Streak Removal
YT Wang, XL Zhao, TX Jiang, Liang-Jian Deng, TH Ma, YT Zhang, TZ Huang
Signal Processing: Image Communication, 73:96-108, 2019.
[PDF]
[Code_link]
|
|
|
- Joint-Sparse-Blocks and Low-Rank Representation for Hyperspectral Unmixing
Jie Huang, Ting-Zhu Huang, Liang-Jian Deng Xi-Le Zhao
IEEE Transactions on Geoscience and Remote Sensing, 57(4):2419-2438, 2018.
[PDF]
[Matlab_Code]
|
|
|
- A Directional Global Sparse Model for Single Image Rain Removal
Liang-Jian Deng, Ting-Zhu Huang, Xi-Le Zhao, Tai-Xiang Jiang
Applied Mathematical Modelling, 59: 662-679, 2018.
[PDF]
[Matlab_Code]
|
|
|
- Directional l0 Sparse Modeling for Image Stripe Noise Removal
Hong-Xia Dou, Ting-Zhu Huang, Liang-Jian Deng, Xi-Le Zhao, Jie Huang
Remote Sensing, 10(3): 361, 2018.
[PDF]
[Matlab_Code]
|
|
|
- A Novel Tensor-based Video Rain Streaks Removal Approach via Utilizing Discriminatively Intrinsic Priors
Tai-Xiang Jiang, Ting-Zhu Huang, Xi-Le Zhao, Liang-Jian Deng, Yao Wang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
[PDF]
[Supplementary]
[Code_Link]
|
|
|
- Single Image Super-resolution via An Iterative Reproducing Kernel Hilbert Space Method
Liang-Jian Deng, Weihong Guo, Ting-Zhu Huang
IEEE Transactions on Circuits and Systems for Video Technology, 26(11): 2001-2014, 2016, 2016
[PDF]
[Matlab_Code]
|
|
|
- Exemplar-based Image Inpainting Using A Modified Priority Definition
Liang-Jian Deng, Ting-Zhu Huang, Xi-Le Zhao
PLoS One, 10(10), 2015
[PDF]
[Matlab_Code]
|
Academic Activities:
Peer-Reviewer:
IEEE TIP, IEEE TGRS, IEEE TCSVT, IEEE JSTARS, IEEE TCyber., IEEE GRSL
ISPRS Journal of Photogrammetry and Remote Sensing, Journal of Mathematical Imaging and Vision, etc.


I am a front-end web developer located in Tukums, Latvia. I have a passion for web and everything related to design.
Want to create awesome projects together? Feel free to e-mail me at<EMAIL_ADDRESS>I am a front-end web developer located in Tukums, Latvia. I have a passion for web and everything related to design.
Want to create awesome projects together? Feel free to e-mail me at arturs@vasiljevs.lv


public class Vector2
extends java.lang.Object
The operations setMagnitude(double)
, getNormalized()
,
project(Vector2)
, and normalize()
require the Vector2
to be non-zero in length.
Some methods that modify the vector will also return the vector. This is to facilitate operations like:
Vector a = new Vector(); a.zero().add(1, 2).multiply(2);This can decrease the number of temporary vectors.
| Modifier and Type | Field and Description |
|---|---|
double |
x
The magnitude of the x component of this
Vector2 |
protected static Vector2 |
X_AXIS
A vector representing the x-axis; this vector should not be changed at runtime; used internally
|
double |
y
The magnitude of the y component of this
Vector2 |
protected static Vector2 |
Y_AXIS
A vector representing the y-axis; this vector should not be changed at runtime; used internally
|
| Constructor and Description |
|---|
Vector2()
Default constructor.
|
Vector2(double direction)
Creates a unit length vector in the given direction.
|
Vector2(double x,
double y)
Optional constructor.
|
Vector2(double x1,
double y1,
double x2,
double y2)
Creates a
Vector2 from the first point to the second point. |
Vector2(Vector2 vector)
Copy constructor.
|
Vector2(Vector2 p1,
Vector2 p2)
Creates a
Vector2 from the first point to the second point. |
| Modifier and Type | Method and Description |
|---|---|
Vector2 |
add(double x,
double y)
|
Vector2 |
add(Vector2 vector)
|
Vector2 |
copy()
Returns a copy of this
Vector2 . |
static Vector2 |
create(double magnitude,
double direction)
Returns a new
Vector2 given the magnitude and direction. |
Vector2 |
cross(double z)
|
double |
cross(double x,
double y)
|
double |
cross(Vector2 vector)
|
Vector2 |
difference(double x,
double y)
|
Vector2 |
difference(Vector2 vector)
|
double |
distance(double x,
double y)
Returns the distance from this point to the given point.
|
double |
distance(Vector2 point)
Returns the distance from this point to the given point.
|
double |
distanceSquared(double x,
double y)
Returns the distance from this point to the given point squared.
|
double |
distanceSquared(Vector2 point)
Returns the distance from this point to the given point squared.
|
double |
dot(double x,
double y)
|
double |
dot(Vector2 vector)
|
boolean |
equals(double x,
double y)
Returns true if the x and y components of this
Vector2
are the same as the given x and y components. |
boolean |
equals(Vector2 vector)
|
double |
getAngleBetween(Vector2 vector)
Returns the smallest angle between the given
Vector2 s. |
double |
getDirection()
Returns the direction of this
Vector2
as an angle in radians. |
Vector2 |
getLeftHandOrthogonalVector()
Returns the left-handed normal of this vector.
|
double |
getMagnitude()
Returns the magnitude of this
Vector2 . |
double |
getMagnitudeSquared()
Returns the magnitude of this
Vector2 squared. |
Vector2 |
getNegative()
|
Vector2 |
getNormalized()
|
Vector2 |
getRightHandOrthogonalVector()
Returns the right-handed normal of this vector.
|
Vector2 |
getXComponent()
Returns the x component of this
Vector2 . |
Vector2 |
getYComponent()
Returns the y component of this
Vector2 . |
boolean |
isOrthogonal(double x,
double y)
|
boolean |
isOrthogonal(Vector2 vector)
|
boolean |
isZero()
|
Vector2 |
left()
Sets this vector to the left-handed normal of this vector.
|
Vector2 |
multiply(double scalar)
Multiplies this
Vector2 by the given scalar. |
Vector2 |
negate()
Negates this
Vector2 . |
double |
normalize()
|
Vector2 |
product(double scalar)
|
Vector2 |
project(Vector2 vector)
|
Vector2 |
right()
Sets this vector to the right-handed normal of this vector.
|
Vector2 |
rotate(double theta)
Rotates about the origin.
|
Vector2 |
rotate(double theta,
double x,
double y)
Rotates the
Vector2 about the given coordinates. |
Vector2 |
rotate(double theta,
Vector2 point)
Rotates the
Vector2 about the given point. |
Vector2 |
set(double x,
double y)
|
Vector2 |
set(Vector2 vector)
|
Vector2 |
setDirection(double angle)
Sets the direction of this
Vector2 . |
Vector2 |
setMagnitude(double magnitude)
Sets the magnitude of the
Vector2 . |
Vector2 |
subtract(double x,
double y)
|
Vector2 |
subtract(Vector2 vector)
|
Vector2 |
sum(double x,
double y)
|
Vector2 |
sum(Vector2 vector)
|
Vector2 |
to(double x,
double y)
|
Vector2 |
to(Vector2 vector)
|
java.lang.String |
toString() |
static Vector2 |
tripleProduct(Vector2 a,
Vector2 b,
Vector2 c)
The triple product of
Vector2 s is defined as: |
Vector2 |
zero()
|
protected static final Vector2 X_AXIS
protected static final Vector2 Y_AXIS
public double x
Vector2
public double y
Vector2
public Vector2()
public Vector2(Vector2 vector)
vector
- the Vector2
to copy frompublic Vector2(double x, double y)
x
- the x componenty
- the y componentpublic Vector2(double x1, double y1, double x2, double y2)
Vector2
from the first point to the second point.x1
- the x coordinate of the first pointy1
- the y coordinate of the first pointx2
- the x coordinate of the second pointy2
- the y coordinate of the second pointpublic Vector2(Vector2 p1, Vector2 p2)
Vector2
from the first point to the second point.p1
- the first pointp2
- the second pointpublic Vector2(double direction)
direction
- the direction in radianspublic static Vector2 create(double magnitude, double direction)
Vector2
given the magnitude and direction.public double distance(double x, double y)
x
- the x coordinate of the pointy
- the y coordinate of the pointpublic double distance(Vector2 point)
point
- the pointpublic double distanceSquared(double x, double y)
x
- the x coordinate of the pointy
- the y coordinate of the pointpublic double distanceSquared(Vector2 point)
point
- the pointpublic static Vector2 tripleProduct(Vector2 a, Vector2 b, Vector2 c)
Vector2
s is defined as:
a x (b x c)However, this method performs the following triple product:
(a x b) x cthis can be simplified to:
-a * (b · c) + b * (a · c)or:
b * (a · c) - a * (b · c)
public boolean equals(Vector2 vector)
vector
- the Vector2
to compare topublic boolean equals(double x, double y)
Vector2
are the same as the given x and y components.public java.lang.String toString()
toString
in class java.lang.Object
public Vector2 set(double x, double y)
public Vector2 getXComponent()
Vector2
.Vector2
public Vector2 getYComponent()
Vector2
.Vector2
public double getMagnitude()
Vector2
.public double getMagnitudeSquared()
Vector2
squared.public Vector2 setMagnitude(double magnitude)
Vector2
.magnitude
- the magnitudeVector2
this vectorpublic double getDirection()
Vector2
as an angle in radians.public Vector2 setDirection(double angle)
Vector2
.angle
- angle in radiansVector2
this vectorpublic Vector2 add(double x, double y)
public Vector2 sum(double x, double y)
public Vector2 subtract(double x, double y)
public Vector2 difference(double x, double y)
public Vector2 to(double x, double y)
public Vector2 multiply(double scalar)
Vector2
by the given scalar.scalar
- the scalarVector2
this vectorpublic double dot(double x, double y)
public double cross(double x, double y)
public boolean isOrthogonal(Vector2 vector)
Vector2
is orthogonal (perpendicular)
to this Vector2
.
If the dot product of this vector and the given vector is zero then we know that they are perpendicular
vector
- the Vector2
public boolean isOrthogonal(double x, double y)
public boolean isZero()
public Vector2 rotate(double theta)
theta
- the rotation angle in radiansVector2
this vectorpublic Vector2 rotate(double theta, double x, double y)
Vector2
about the given coordinates.theta
- the rotation angle in radiansx
- the x coordinate to rotate abouty
- the y coordinate to rotate aboutVector2
this vectorpublic Vector2 rotate(double theta, Vector2 point)
Vector2
about the given point.theta
- the rotation angle in radianspoint
- the point to rotate aboutVector2
this vectorpublic Vector2 getRightHandOrthogonalVector()
public Vector2 right()
Vector2
this vectorgetRightHandOrthogonalVector()
public Vector2 getLeftHandOrthogonalVector()
public Vector2 left()
Vector2
this vectorgetLeftHandOrthogonalVector()
public Vector2 getNormalized()
Vector2
of this Vector2
.
This method requires the length of this Vector2
is not zero.
Vector2
public double normalize()
Vector2
into a unit Vector2
and returns
the magnitude before normalization.
This method requires the length of this Vector2
is not zero.


PetsApp
How i started my fake startup with the Janus Mobile SDK
Naples (IT)
September 23rd-25th 2019
PetsApp
A video chat for puppies
Application requirements
- A user should connect to his own room
- Each pet should have a streaming device
- The user should watch all the pet feeds at the same time
A basic video room!
Minimum viable product
Server requirements
- { User, Room } Management API
- WebRTC Signalling Server
- { MC, SF } Unit
Minimum viable product
Client requirements
- Cross-Platform application (iOS, Android, Linux)
- Native Application
- No vendor lock-in
No solutions currently available!
handcrafted with by @helloiampau and Meetecho S.R.L.
- Cross-Platform SDK
- Mobile-First (iOS, Android)
- Supports Janus API out-of-the-box
- Open Source
settings.gradle
include ':app'
include ':janus'
project(':janus').projectDir = new File(settingsDir, './third_party/janus-client/platforms/android/janus')
app/build.gradle
apply plugin: 'com.android.application'
android {
compileSdkVersion 28
defaultConfig {
applicationId "com.github.helloiampau.petsapp"
minSdkVersion 16
targetSdkVersion 28
versionCode 1
versionName "1.0"
testInstrumentationRunner "android.support.test.runner.AndroidJUnitRunner"
}
buildTypes {
release {
minifyEnabled false
proguardFiles getDefaultProguardFile('proguard-android-optimize.txt'), 'proguard-rules.pro'
}
}
compileOptions {
compileOptions {
sourceCompatibility JavaVersion.VERSION_1_8
targetCompatibility JavaVersion.VERSION_1_8
}
sourceCompatibility JavaVersion.VERSION_1_8
targetCompatibility JavaVersion.VERSION_1_8
}
}
dependencies {
implementation project(path: ':janus')
implementation fileTree(dir: 'libs', include: ['*.jar'])
implementation 'com.android.support:appcompat-v7:28.0.0'
implementation 'com.android.support.constraint:constraint-layout:1.1.3'
testImplementation 'junit:junit:4.12'
androidTestImplementation 'com.android.support.test:runner:1.0.2'
androidTestImplementation 'com.android.support.test.espresso:espresso-core:3.0.2'
}
Code


First Name:
Last Name:
Age:
US Citizen:
Gender:
Female
Male
State Residence
Select One
Comments:
Submit


Name: Benitha Uwase
Degree: Diploma in Information Systems at Davis College/Akilah Campus
My name is Benitha Uwase, I am studying Information Systems (INS) at Davis college and studying further coding skills at Moringa school because it is a field where I saw my career job in the future. I am passionate about being in the IT industry dealing with either Networking or designing websites and android applications because I feel very competitive and sure about myself when doing it. My top skills including technical and power skills are programming languages, data analysis, communication, critical thinking, teamwork and creativity.
This project was a start-up project of my pre-prep classroom at Moringa school. I decided to make a web store where people can go and shop clothes online. This project was made using only HTML and CSS which helped me learn new skills.


{% extends "recurrent_cards/form.html" %} {% block page_title %}New recurrent card {{instance.full_name}}{% endblock %} {% block content %} {% include "work_hours_packages/components/go_back.html" %}


[1]
the concierge staff was finally replaced the major pluses are very nicely.
[2]
lonely planet recommended the only issue we reported the ac was helpful sylvia.


lsr: Companion to "Learning Statistics with R"
A collection of tools intended to make introductory statistics easier to teach, including wrappers for common hypothesis tests and basic data manipulation. It accompanies Navarro, D. J. (2015). Learning Statistics with R: A Tutorial for Psychology Students and Other Beginners, Version 0.5. [Lecture notes] School of Psychology, University of Adelaide, Adelaide, Australia. ISBN: 978-1-326-18972-3. URL: http://health.adelaide.edu.au/psychology/ccs/teaching/lsr/.
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=lsr
to link to this page.


|
Helix
|
#include <DOStmtInput.h>
Public Member Functions | |
| DOStmtInput () | |
| Any Child Vectors will be defined here. More... | |
| DOStmtInput (const DOStmtInput &c) | |
| Standard Copy Constructor. More... | |
| DOStmtInput & | operator= (const DOStmtInput &c) |
| Standard Assignment Operator. More... | |
| virtual | ~DOStmtInput () |
| Standard Destructor. More... | |
| DOStmtInput & | init () |
| Initialize this data object to have all empty or 0 values. More... | |
| DOStmtInput & | checkSize () |
| Call check_size() on all of our twine members. More... | |
| DOStmtInput (xmlNodePtr node) | |
| Construct from an XML Node. More... | |
| DOStmtInput & | readXmlNode (xmlNodePtr node) |
| Read an XML Node to set our contents. More... | |
| xmlNodePtr | createXmlNode (xmlNodePtr parent) const |
| Create an XML Node as a child of the given parent. More... | |
| xmlDocPtr | createXmlDoc () const |
| Create an XML Document from this data object. More... | |
Static Public Member Functions | |
| static vector< DOStmtInput * > * | readXmlChildren (xmlNodePtr parent) |
| Create a series of these objects by reading all children of the given parent. More... | |
| static void | createXmlChildren (xmlNodePtr parent, vector< DOStmtInput * > *vect) |
| Create a series of xml child nodes based on the input vector. More... | |
| static void | deleteVector (vector< DOStmtInput * > *vect) |
| Handle deleting a vector and its contents. More... | |
| static twine & | Name () |
| Static method to retrieve the name of this object. More... | |
| static void | insert (SqlDB &sqldb, DOStmtInput &obj) |
| static void | insert (SqlDB &sqldb, twine &stmt, bool useInputs, DOStmtInput &obj) |
| static void | insert (SqlDB &sqldb, vector< DOStmtInput * > *v) |
| static twine | insert_prepSQL (IOConn &ioc, DOStmtInput &obj) |
| static twine | insert_getSQL () |
| static void | update (SqlDB &sqldb, twine &VarName, twine &VarType, twine &guid) |
| static void | update (SqlDB &sqldb, twine &stmt, bool useInputs, twine &VarName, twine &VarType, twine &guid) |
| static twine | update_prepSQL (IOConn &ioc, twine &VarName, twine &VarType, twine &guid) |
| static twine | update_getSQL () |
| static void | deleteByID (SqlDB &sqldb, twine &guid) |
| static void | deleteByID (SqlDB &sqldb, twine &stmt, bool useInputs, twine &guid) |
| static twine | deleteByID_prepSQL (IOConn &ioc, twine &guid) |
| static twine | deleteByID_getSQL () |
| static void | deleteByStmtID (SqlDB &sqldb, twine &dostmtguid) |
| static void | deleteByStmtID (SqlDB &sqldb, twine &stmt, bool useInputs, twine &dostmtguid) |
| static twine | deleteByStmtID_prepSQL (IOConn &ioc, twine &dostmtguid) |
| static twine | deleteByStmtID_getSQL () |
| static vector< DOStmtInput * > * | selectAllForDOStmt (SqlDB &sqldb, twine &dostmtguid) |
| static vector< DOStmtInput * > * | selectAllForDOStmt (SqlDB &sqldb, twine &stmt, bool useInputs, twine &dostmtguid) |
| static twine | selectAllForDOStmt_prepSQL (IOConn &ioc, twine &dostmtguid) |
| static twine | selectAllForDOStmt_getSQL () |
Public Attributes | |
| twine | VarName |
| All Data Members are public. More... | |
| twine | VarType |
| twine | dostmtguid |
| twine | guid |
This is a generated data object class that is used for interfacing with a database. This class was generated based on the settings in the file: ../logic/dev/DOStmtInput.sql.xml
| DOStmtInput::DOStmtInput | ( | ) |
Any Child Vectors will be defined here.
Standard Constructor
| DOStmtInput::DOStmtInput | ( | const DOStmtInput & | c | ) |
Standard Copy Constructor.
|
virtual |
Standard Destructor.
| DOStmtInput::DOStmtInput | ( | xmlNodePtr | node | ) |
Construct from an XML Node.
| DOStmtInput & DOStmtInput::checkSize | ( | ) |
Call check_size() on all of our twine members.
|
static |
Create a series of xml child nodes based on the input vector.
| xmlDocPtr DOStmtInput::createXmlDoc | ( | ) | const |
Create an XML Document from this data object.
| xmlNodePtr DOStmtInput::createXmlNode | ( | xmlNodePtr | parent | ) | const |
Create an XML Node as a child of the given parent.
|
static |
This is an DELETE method. It is designed to run a single delete statement and return. If something goes wrong, we will throw AnException.
Developer Comments:
This removes a data object statement input by id
Sql Statement:
delete from dostmtinput where guid = ?
|
static |
This one matches the above in functionality, but allows you to pass in the sql statement and a flag to indicate whether the input parameters will be used.
|
inlinestatic |
This method returns the sql statement that is used by the above functions.
|
static |
This method will do a replacement of all of the parameter markers in the sql statement with the standard parameter list that is defined. This is useful for automatically prepping a SQL statement that doesn't work with parameter markers.
|
static |
This is an DELETE method. It is designed to run a single delete statement and return. If something goes wrong, we will throw AnException.
Developer Comments:
This removes all data object statement inputs for a given data object statement
Sql Statement:
delete from dostmtinput where dostmtguid = ?
|
static |
This one matches the above in functionality, but allows you to pass in the sql statement and a flag to indicate whether the input parameters will be used.
|
inlinestatic |
This method returns the sql statement that is used by the above functions.
|
static |
This method will do a replacement of all of the parameter markers in the sql statement with the standard parameter list that is defined. This is useful for automatically prepping a SQL statement that doesn't work with parameter markers.
|
static |
Handle deleting a vector and its contents.
| DOStmtInput & DOStmtInput::init | ( | ) |
Initialize this data object to have all empty or 0 values.
|
static |
This is an INSERT method. It is designed to run a single insert statement and return. If something goes wrong, we will throw AnException.
Developer Comments:
This adds a new data object statement input entry to our database
Sql Statement:
insert into dostmtinput (guid, dostmtguid, VarName, VarType) values ( ?, ?, ?, ? )
|
static |
This one matches the above in functionality, but allows you to pass in the sql statement and a flag to indicate whether the input parameters will be used.
|
static |
This version of the method allows you to pass in a vector of objects to be inserted, and we will ensure that all of them are inserted within a single commit block within Sqlite.
|
inlinestatic |
This method returns the sql statement that is used by the above functions.
|
static |
This method will do a replacement of all of the parameter markers in the sql statement with the standard parameter list that is defined. This is useful for automatically prepping a SQL statement that doesn't work with parameter markers.
|
static |
Static method to retrieve the name of this object.
| DOStmtInput & DOStmtInput::operator= | ( | const DOStmtInput & | c | ) |
Standard Assignment Operator.
|
static |
Create a series of these objects by reading all children of the given parent.
| DOStmtInput & DOStmtInput::readXmlNode | ( | xmlNodePtr | node | ) |
Read an XML Node to set our contents.
|
static |
This is a SELECTTODO method. It is designed to run a single select statement and create a vector of data objects that represent the result set. This method returns the resulting vector of data objects. If something goes wrong, we will throw a SQLException.
Developer Comments:
This selects all data object statement inputs for a given data object stmt
Sql Statement:
select guid, dostmtguid, VarName, VarType from dostmtinput where dostmtguid = ?
DataObject Attributes Used:
|
static |
This one matches the above in functionality, but allows you to pass in the sql statement and a flag to indicate whether the input parameters will be used.
|
inlinestatic |
This method returns the sql statement that is used by the above functions.
|
static |
This method will do a replacement of all of the parameter markers in the sql statement with the standard parameter list that is defined. This is useful for automatically prepping a SQL statement that doesn't work with parameter markers.
|
static |
This is an UPDATE method. It is designed to run a single update statement and return. If something goes wrong, we will throw AnException.
Developer Comments:
This updates the settings for a given data object statement input in the database
Sql Statement:
update dostmtinput set VarName = ?, VarType = ? where guid = ?
|
static |
This one matches the above in functionality, but allows you to pass in the sql statement and a flag to indicate whether the input parameters will be used.
|
inlinestatic |
This method returns the sql statement that is used by the above functions.
|
static |
This method will do a replacement of all of the parameter markers in the sql statement with the standard parameter list that is defined. This is useful for automatically prepping a SQL statement that doesn't work with parameter markers.
| twine Helix::Logic::dev::DOStmtInput::dostmtguid |
| twine Helix::Logic::dev::DOStmtInput::guid |
| twine Helix::Logic::dev::DOStmtInput::VarName |
All Data Members are public.
| twine Helix::Logic::dev::DOStmtInput::VarType |


UKPRN:12345678
East Reading College
March 2017
Dear Colleague,
I am writing to provide your allocation statement for the 2017 to 2018 funding year: it includes the allocations that are relevant to you. Please read it with the following documents: skills funding letter 2017 to 2018 and our funding and performance management rules for the 2017 to 2018 year.
Apprenticeships
Reforms to the apprenticeship system mean that providers will be able to earn apprenticeship funding through different routes. As a result of this, please note that your allocation statement does not include apprenticeship funding at this time. The following section of this letter sets out the reasons for this in more detail. New starts (starts from 1 May 2017)
You will earn funding for new apprenticeship starts through your delivery to levy paying employers and/or non-levy paying employers. Please note that any funding you secure for non-levy starts from 1 May is not included in your allocation statement as it is being communicated separately.
Carry-in learners (apprentices that start before 1 May 2017) We want to ensure that apprentices that start before 1 May 2017 (carry-in learners) are funded until the end of their programmes. We will allocate funding in future years (2017 to 2018 and beyond) to meet the cost of these apprentices.
In early February 2017, we published updated apprenticeship performance management rules for the 2016 to 2017 funding year . These rules set out our commitment to fund carry-in learners ‘reflecting funding previously paid by the Skills Funding Agency’. The next section of the letter explains how we will work out your carry-in allocation.
Adult education budget
Where applicable, funding will be allocated beyond 2017 to 2018 to ensure apprentices that started before 1 May 2017 can complete their programmes.
all apprentices achieve on their planned end date and draw down their achievement payment on this date Allocations for carry-in learners for 2017 to 2018
We will work out the value of your 2017 to 2018 carry-in allocation in June, based on your R10 data return. Calculating your carry-in allocation in June will enable us to work your allocation out on the basis of your actual delivery, rather than us trying to forecast your activity to issue your allocation earlier. We have consulted on this with the Association of Colleges, Association of Employment and Learning Providers and our Provider Reference Group.
We encourage you to submit full and timely data at R10 as this will improve the accuracy of the carry-in allocation we work out for you. We will confirm your carry-in allocation for the 2017 to 2018 funding year in July 2017. The methodology we will use to work out your carry-in will be based on your actual data at R10 and the following assumptions: there is no drop-out
for Trailblazer Standards incentive payments will be drawn down on the date they are due an allowance for data lag.
We continue to allocate your adult education budget as a block grant. We have set the baseline for your 2017 to 2018 allocation at the level of your 2016 to 2017 contract value as at January 2017. It includes the value of any traineeship growth you were awarded at performance management point 1 of the 2016 to 2017 funding year. Where applicable to you, it also includes community learning funding. Your allocation statement does not include any funds you may be awarded through the adult education budget procurement that closed on 27 February. If you submitted a bid, we will notify you of the outcome in May. Funding awarded through the procurement is for the 2017 to 2018 funding year and will not automatically be consolidated in future baselines.
all apprentices remain on programme until their planned end date and draw down all on-programme payments due. Note that for Trailblazer Standards we will first convert any remaining balance to be paid into on-programme payments
Please note that if you only deliver apprenticeships, for the reasons given above, you will not have an allocation statement attached to this letter.
Continuing learners Future devolution of the adult education budget We continue to work with ministers and other stakeholders on the proposals to devolve adult education budget funding to areas with agreed devolution deals. Your 2017 to 2018 adult education budget allocation is not affected by devolution plans.
If you wish to discuss your allocation statement, please contact your provider manager.
Yours sincerely,
Keith Smith
Director – Funding and Programmes


| Hierarchy |
Input |
Constant Input |
Unused Input |
Floating Input |
Output |
Constant Output |
Unused Output |
Floating Output |
Bidir |
Constant Bidir |
Unused Bidir |
Input only Bidir |
Output only Bidir |
| inst22|lpm_counter_component|auto_generated|cmpr1 |
60 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| inst22|lpm_counter_component|auto_generated |
1 |
0 |
0 |
0 |
31 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| inst22 |
1 |
30 |
0 |
30 |
31 |
30 |
30 |
30 |
0 |
0 |
0 |
0 |
0 |
| inst24|lpm_counter_component|auto_generated|cmpr1 |
60 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| inst24|lpm_counter_component|auto_generated |
1 |
0 |
0 |
0 |
31 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| inst24 |
1 |
30 |
0 |
30 |
31 |
30 |
30 |
30 |
0 |
0 |
0 |
0 |
0 |
| inst17|lpm_counter_component|auto_generated|cmpr1 |
60 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| inst17|lpm_counter_component|auto_generated |
1 |
0 |
0 |
0 |
31 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| inst17 |
1 |
30 |
0 |
30 |
31 |
30 |
30 |
30 |
0 |
0 |
0 |
0 |
0 |
| inst20|lpm_counter_component|auto_generated|cmpr1 |
60 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| inst20|lpm_counter_component|auto_generated |
1 |
0 |
0 |
0 |
31 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| inst20 |
1 |
30 |
0 |
30 |
31 |
30 |
30 |
30 |
0 |
0 |
0 |
0 |
0 |
| inst14|lpm_counter_component|auto_generated|cmpr1 |
60 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| inst14|lpm_counter_component|auto_generated |
1 |
0 |
0 |
0 |
31 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
| inst14 |
1 |
30 |
0 |
30 |
31 |
30 |
30 |
30 |
0 |
0 |
0 |
0 |
0 |


Inside asciidoctor editor press CTRL + o.
CTRL + o
Same content like in Outline view but you can filter for names there. Also wildcards are supported.


Source code for statsmodels.nonparametric.bandwidths
from __future__ import division
import numpy as np
from scipy.stats import scoreatpercentile as sap
from statsmodels.sandbox.nonparametric import kernels
def _select_sigma(X):
"""
Returns the smaller of std(X, ddof=1) or normalized IQR(X) over axis 0.
References
----------
Silverman (1986) p.47
"""
# normalize = norm.ppf(.75) - norm.ppf(.25)
normalize = 1.349
# IQR = np.subtract.reduce(percentile(X, [75,25],
# axis=axis), axis=axis)/normalize
IQR = (sap(X, 75) - sap(X, 25))/normalize
return np.minimum(np.std(X, axis=0, ddof=1), IQR)
## Univariate Rule of Thumb Bandwidths ##
[docs]def bw_scott(x, kernel=None):
"""
Scott's Rule of Thumb
Parameters
----------
x : array-like
Array for which to get the bandwidth
kernel : CustomKernel object
Unused
Returns
-------
bw : float
The estimate of the bandwidth
Notes
-----
Returns 1.059 * A * n ** (-1/5.) where ::
A = min(std(x, ddof=1), IQR/1.349)
IQR = np.subtract.reduce(np.percentile(x, [75,25]))
References
----------
Scott, D.W. (1992) Multivariate Density Estimation: Theory, Practice, and
Visualization.
"""
A = _select_sigma(x)
n = len(x)
return 1.059 * A * n ** (-0.2)
[docs]def bw_silverman(x, kernel=None):
"""
Silverman's Rule of Thumb
Parameters
----------
x : array-like
Array for which to get the bandwidth
kernel : CustomKernel object
Unused
Returns
-------
bw : float
The estimate of the bandwidth
Notes
-----
Returns .9 * A * n ** (-1/5.) where ::
A = min(std(x, ddof=1), IQR/1.349)
IQR = np.subtract.reduce(np.percentile(x, [75,25]))
References
----------
Silverman, B.W. (1986) `Density Estimation.`
"""
A = _select_sigma(x)
n = len(x)
return .9 * A * n ** (-0.2)
def bw_normal_reference(x, kernel=kernels.Gaussian):
"""
Plug-in bandwidth with kernel specific constant based on normal reference.
This bandwidth minimizes the mean integrated square error if the true
distribution is the normal. This choice is an appropriate bandwidth for
single peaked distributions that are similar to the normal distribution.
Parameters
----------
x : array-like
Array for which to get the bandwidth
kernel : CustomKernel object
Used to calculate the constant for the plug-in bandwidth.
Returns
-------
bw : float
The estimate of the bandwidth
Notes
-----
Returns C * A * n ** (-1/5.) where ::
A = min(std(x, ddof=1), IQR/1.349)
IQR = np.subtract.reduce(np.percentile(x, [75,25]))
C = constant from Hansen (2009)
When using a Gaussian kernel this is equivalent to the 'scott' bandwidth up
to two decimal places. This is the accuracy to which the 'scott' constant is
specified.
References
----------
Silverman, B.W. (1986) `Density Estimation.`
Hansen, B.E. (2009) `Lecture Notes on Nonparametrics.`
"""
C = kernel.normal_reference_constant
A = _select_sigma(x)
n = len(x)
return C * A * n ** (-0.2)
## Plug-In Methods ##
## Least Squares Cross-Validation ##
## Helper Functions ##
bandwidth_funcs = {
"scott": bw_scott,
"silverman": bw_silverman,
"normal_reference": bw_normal_reference,
}
[docs]def select_bandwidth(x, bw, kernel):
"""
Selects bandwidth for a selection rule bw
this is a wrapper around existing bandwidth selection rules
Parameters
----------
x : array-like
Array for which to get the bandwidth
bw : string
name of bandwidth selection rule, currently supported are:
%s
kernel : not used yet
Returns
-------
bw : float
The estimate of the bandwidth
"""
bw = bw.lower()
if bw not in bandwidth_funcs:
raise ValueError("Bandwidth %s not understood" % bw)
#TODO: uncomment checks when we have non-rule of thumb bandwidths for diff. kernels
# if kernel == "gauss":
return bandwidth_funcs[bw](x, kernel)
# else:
# raise ValueError("Only Gaussian Kernels are currently supported")
# Interpolate docstring to plugin supported bandwidths
select_bandwidth.__doc__ %= (", ".join(sorted(bandwidth_funcs.keys())),)


A basic example
This purpose of this example is to give you a brief overview of the basic concepts of ETLBox. It demonstrates the basic idea of a very simple data flow and shows how to use the ControlFlow objects to manage your database metadata. There is also a video demonstrating this example.
Setup the environment
This example is written in C#, based on the current .NET Core. You can use your IDE of your choice - most will probably go with Visual Studio or Visual Studio Code. The database used in this example is Sql Server. You can either you set up a standalone installation of Sql Server, or use a docker image. Also, Azure Sql could be an alternative which is easy to setup. To access your database, Azure Data Studio or Sql Server Management Studio is recommended.
Setting up a docker container
If you want to use docker to set up a sql server database, please install Docker for your OS first. Then you can start a docker image running sql server on ubuntu.
Setting up your project
Now we need to create a new dotnet core console application. You can do this either with your IDE or just execute the following command:
dotnet new console
If this doesn't work, make sure you have the latest version of .NET Core installed.
Now, add the current version of ETLBox as a package to your project.
dotnet add package ETLBox
Now you will be able to use the full set of tools coming with ETLBox
Start coding
Now open your project and go into the main method of your program.
First, define a connection manager for Sql Server that holds the connection string
var masterConnection = new SqlConnectionManager("Data Source=.;Integrated Security=false;User=sa;password=reallyStrongPwd123");
No you can use the CreateDatabaseTask
to create a new Database.
CreateDatabaseTask.Create(masterConnection, "demo");
Also we would like to change the connection to the database we just created and
create a table in there using the CreateTableTask
.
var dbConnection = new SqlConnectionManager("Data Source=.;Initial Catalog=demo;Integrated Security=false;User=sa;password=reallyStrongPwd123");
CreateTableTask.Create(dbConnection, "Table1", new List<TableColumn>()
{
new TableColumn("ID","INT",allowNulls:false, isPrimaryKey:true, isIdentity:true),
new TableColumn("Col1","NVARCHAR(100)",allowNulls:true),
new TableColumn("Col2","SMALLINT",allowNulls:true)
});
Adding nlog.config
Before we test our demo project, we want to have some logging output displayed. ETLBox logging is build on nlog. Add the following lines as nlog.config to your project root. Make sure it is copied into the output directory.
<?xml version="1.0" encoding="utf-8"?>
<nlog xmlns="http://www.nlog-project.org/schemas/NLog.xsd"
xsi:schemaLocation="NLog NLog.xsd"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<rules>
<logger name="*" minlevel="Debug" writeTo="console" />
</rules>
<targets>
<target name="console" xsi:type="Console" />
</targets>
</nlog>
Running the project
Now build and run the project.
A terminal window will pop up and display the logging output. As the logging level is set to debug, you will see all SQL code which is executed against the database. Check if the database and the table was created.
A simple etl pipeline
Next we want to create a simple etl pipeline.
First we create a demo csv file named input.csv
.
The input file contains header information and some value.
Also we need to copy it into the output directory.
Col1,Col2
Value,1
Value2,2
Value3,3
Now we create a CsvSource pointing to the newly created input file.
CsvSource<string[]> source = new CsvSource<string[]>("input.csv");
Before we continue, we will need an object that can hold our data. Let's call it MyData.
public class MyData
{
public string Col1 { get; set; }
public string Col2 { get; set; }
}
Now we add a row transformation. The row transformation will receive a string array from the source and transform it in our Mydata object.
RowTransformation<string[], MyData> row = new RowTransformation<string[], MyData>
(
input => new MyData()
{ Col1 = input[0], Col2 = input[1] }
);
Actually, this transformation wouldn't been necessary - the CsvSource could have automatically converted the
incoming data into the MyData
object. But it shows how a transformation can be used to execute any
C# code you like.
Next we add a database destination pointing to our table.
DbDestination<MyData> dest = new DbDestination<MyData>(dbConnection, "Table1");
Now we need to link the components of our dataflow.
source.LinkTo(row);
row.LinkTo(dest);
After linking the components, we want to have the source reading the input data. The destination should wait until it received all data.
source.Execute();
dest.Wait();
Finally, we check if the data was successfully loaded into the table and write it into the console output. We use the SQLTask for this and write the result into the output.
SqlTask.ExecuteReader("Read all data from Table1",
"select Col1, Col2 from Table1",
col1 => Console.WriteLine(col1.ToString() + ","),
col2 => Console.WriteLine(col2.ToString())
);
Run again
Let's run the project again and see the output.
You'll see that the data was successfully copied into the database table.


Siren 🚨
Notify users when a new version of your app is available and prompt them to upgrade.
Table of Contents
Meta
About
Siren checks a user’s currently installed version of your iOS app against the version that is currently available in the App Store.
If a new version is available, a language localized alert can be presented to the user informing them of the newer version, and giving them the option to update the application. Alternatively, Siren can notify your app through alternative means, such as a custom user interface.
Siren is built to work with the Semantic Versioning system.
- Canonical Semantic Versioning uses a three number versioning system (e.g., 1.0.0)
- Siren also supports two-number versioning (e.g., 1.0) and four-number versioning (e.g., <IP_ADDRESS>)
Features
Current Features
- [x] CocoaPods, Carthage, and Swift Package Manager Support (see Installation Instructions)
- [x] Three Types of Alerts (see Screenshots)
- [x] Highly Customizable Presentation Rules (see Implementation Examples)
- [x] Localized for 40+ Languages (see Localization)
- [x] Device Compatibility Check (see Device Compatibility)
- [x] 100% Documentation Coverage (see https://sabintsev.com/Siren)
Future Features
A list of future development work can be found on Siren’s Kanban Board.
Screenshots
- The left picture forces the user to update the app.
- The center picture gives the user the option to update the app.
- The right picture gives the user the option to skip the current update.
- These options are controlled by the
Rules.AlertType
enum.
Ports
- Objective-C (iOS)
- Harpy
- Siren was ported from Harpy, as Siren and Harpy are maintained by the same developer.
- As of December 2018, Harpy has been deprecated in favor of Siren.
- Java (Android)
- Egghead Games’ Siren library
- The Siren Swift library inspired the Java library.
- React Native (iOS)
- Gant Laborde’s Siren library
- The Siren Swift library inspired the React Native library.
Installation and Integration
Installation Instructions
| Swift Version | Branch Name | Will Continue to Receive Updates? |
|---|---|---|
| 4.2 | master | Yes |
| 4.1 | swift4.1 | No |
| 3.2 | swift3.2 | No |
| 3.1 | swift3.1 | No |
| 2.3 | swift2.3 | No |
CocoaPods
pod 'Siren' # Swift 4.2
pod 'Siren', :git => 'https://github.com/ArtSabintsev/Siren.git', :branch => 'swift4.1' # Swift 4.1
pod 'Siren', :git => 'https://github.com/ArtSabintsev/Siren.git', :branch => 'swift3.2' # Swift 3.2
pod 'Siren', :git => 'https://github.com/ArtSabintsev/Siren.git', :branch => 'swift3.1' # Swift 3.1
pod 'Siren', :git => 'https://github.com/ArtSabintsev/Siren.git', :branch => 'swift2.3' # Swift 2.3
Carthage
github "ArtSabintsev/Siren" // Swift 4.2
github "ArtSabintsev/Siren" "swift4.1" // Swift 4.1
github "ArtSabintsev/Siren" "swift3.2" // Swift 3.2
github "ArtSabintsev/Siren" "swift3.1" // Swift 3.1
github "ArtSabintsev/Siren" "swift2.3" // Swift 2.3
Swift Package Manager
.Package(url: "https://github.com/ArtSabintsev/Siren.git", majorVersion: 4)
Implementation Examples
Implementing Siren is as easy as adding two lines of code to your app:
import Siren // Line 1
import UIKit
@UIApplicationMain
final class AppDelegate: UIResponder, UIApplicationDelegate {
var window: UIWindow?
func application(_ application: UIApplication, didFinishLaunchingWithOptions launchOptions: [UIApplication.LaunchOptionsKey : Any]? = nil) -> Bool {
window?.makeKeyAndVisible()
Siren.shared.wail() // Line 2
return true
}
}
Siren also has plenty of customization options. All examples can be found in the Example Project’s AppDelegate file. Uncomment the example you’d like to test.
WARNING: Siren should ONLY be placed in UIApplication.didFinishLaunchingWithOptions and only after the window?.makeKeyAndVisible()
call. Siren initializes a listener on didBecomeActiveNotification to perform version checks.
Device-Specific Checks
Localization
Siren is localized for the following languages:
Arabic, Armenian, Basque, Chinese (Simplified and Traditional), Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Greek, Hebrew, Hungarian, Indonesian, Italian, Japanese, Korean, Latvian, Lithuanian, Malay, Norwegian (Bokmål), Persian (Afghanistan, Iran, Persian), Polish, Portuguese (Brazil and Portugal), Russian, Serbian (Cyrillic and Latin), Slovenian, Spanish, Swedish, Thai, Turkish, Ukrainian, Urdu, Vietnamese
If your user’s device is set to one of the supported locales, an update message will appear in that language. If a locale is not supported, than the message will appear in English.
You may want the update dialog to always appear in a certain language, ignoring the user’s device-specific setting. You can enable it like so:
// In this example, we force the `russian` language.
Siren.shared.presentationManager = PresentationManager(forceLanguageLocalization: .russian)
Device Compatibility
If an app update is available, Siren checks to make sure that the version of iOS on the user’s device is compatible with the one that is required by the app update. For example, if a user has iOS 11 installed on their device, but the app update requires iOS 12, an alert will not be shown. This takes care of the false positive case regarding app updating.
Testing
Testing Siren Locally
Temporarily change the version string in Xcode (within the .xcodeproj
file) to an older version than the one that’s currently available in the App Store. Afterwards, build and run your app, and you should see the alert.
If you currently don’t have an app in the store, change your bundleID to one that is already in the store. In the sample app packaged with this library, we use the App Store Connect app’s bundleID: com.apple.AppStoreConnect
.
Words of Caution
Occasionally, the iTunes JSON will update faster than the App Store CDN, meaning the JSON may state that the new version of the app has been released, while no new binary is made available for download via the App Store. It is for this reason that Siren will, by default, wait 1 day (24 hours) after the JSON has been updated to prompt the user to update. To change the default setting, please modify the value of showAlertAfterCurrentVersionHasBeenReleasedForDays
.
App Submission
App Store Review
The App Store reviewer will not see the alert. The version in the App Store will always be older than the version being reviewed.
Phased Releases
In 2017, Apple announced the ability to rollout app updates gradually (a.k.a. Phased Releases). Siren will continue to work as it has in the past, presenting an update modal to all users. If you opt-in to a phased rollout for a specific version, you have a few choices:
- You can leave Siren configured as normal. Phased rollout will continue to auto-update apps. Since all users can still manually update your app directly from the App Store, Siren will ignore the phased rollout and will prompt users to update.
- You can set
showAlertAfterCurrentVersionHasBeenReleasedForDays
to7
, and Siren will not prompt any users until the latest version is 7 days old, after the phased rollout is complete. - You can remotely disable Siren until the rollout is done using your own API / backend logic.
Attribution
Special Thanks
A massive shout-out and thank you goes to the following folks:
- Aaron Brager for motivating me and assisting me in building the initial proof-of-concept of Siren (based on Harpy) back in 2015. Without him, Siren may never have been built.
- All of Harpy’s Contributors for helping building the feature set from 2012-2015 that was used as the basis for the first version of Siren.
- All of Siren’s Contributors for helping make Siren as powerful and bug-free as it currently is today.


Update Escalation Matrix
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Type:
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Type:
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Time :
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Type:
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Save
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Show List


The stuff of nightmares… or at least of a gleefully low-budget horror film. One would think so from the exciting headline ‘Radioactive boars' on loose in Germany (pity about those quotation marks) which suggests packs of demented glow-in-the-dark beasts rampaging through the Teutonic forests, attacking woodcutters and orphans roaming lost in the woods. Alas, the boars feed on mushrooms, truffles and wild berries rather than human flesh.


RED CORNER 1997 A film review by Timothy Voon Copyright 1998 Timothy Voon 2 :-( :-( for being too political in it's presentation
Cast: Richard Gere, Bai Ling, Bradley Whitford, Byron Mann Director: Jon Avnet Screenplay: Robert King, Ron Koslow
Who better than Richard Gere, to star in a movie which shouts political views against the Chinese Communist Regime? We know much of this to be true - the suppression of free speech, the unfairness of the judicial system, the misrepresentation and maltreatment of prisoners, the totalitarian nature of it all; but to make a movie about it when you're buddies with the Dalai Lama, well isn't that just a tincy wincy bit biased? If one wanted to explore the paranoid, unfair nature of the Chinese Government properly - make a documentary. But to entwine the political story line with the fanciful murder of a General's daughter (Jessey Meng), a framed business man (Gere) and then to finish it with a deep meaningful relationship with a Chinese lawyer (Bai Ling), is too much even for me.
I was expecting a love story, but instead I found murder and intrigue. It is difficult to believe that a powerful businessman would become the unwitting target of Chinese government officials. Nevertheless, anything is possible. Gere the businessman is accused of murdering the beautiful model Hong Ling, the daughter of a powerful Chinese official. Gere's character then goes through a round the mill sequence of maltreatment in prisons and numerous attempts on his life, all conveniently ignored by the 'evil' Chinese Government. I do not doubt that these cruel scenes are meant to raise anti-Chinese sentiment. However, when his initially pro-Chinese defence lawyer Shen Yuelin falls in love with him, then decides to speak against the corrupt Chinese judicial system - believability becomes a problem. This sinks to further melodrama when Gere gets mushy about Yuelin and sacrifices himself to protect her safety. This lies beyond my comprehension. They've only known each other for a week and they can't even communicate well with each other.
This problem with this movie lies in the fact that it can't make up it's mind whether to be a piece of anti-Chinese propaganda or a love story about one woman's belief in another man's innocence. The resulting effect is mixed feelings and odd moments. The attempt to combine the two ideas doesn't work well, especially when the acting isn't a highlight.
SEVEN YEARS IN TIBET does a better job at causing China to lose face in the eyes of the world. This movie merely pokes its tongue at the great eastern power, but doesn't give the viewer much more insight than that.
Timothy Voon e-mail<EMAIL_ADDRESS>http://us.imdb.com/M/reviews_by?Tim+Voon http://www.labyrinth.net.au/~bouclier/week/movies.html
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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esp32_06
ESP32-Time:
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Wasserzaehler
Flash Toggle
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SW Update
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Exposure Ctrl
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Raw GMA
Vflip
Hmirror


ADDICTED TO LOVE 1997 A film review by Timothy Voon Copyright 1997 Timothy Voon 3 Big :-) :-) :-) for Meg
Cast: Meg Ryan, Matthew Broderick, Kelly Preston, Tcheky Karyo, Maureen Stapleton, Nesbitt Blaisdell Director: Griffen Dunne Producers: Jeffrey Silver, Bobby Newmyer Screenplay: Robert Gordon
The naive, 'milky way', 'farm boy' Astronomer (Broderick). Watches the night skies with his 'guiding light', the telescope. Whose passion for star gazing is only matched by his love for his childhood sweet heart, The School Teacher. He is unceremoniously dumped in favour of The French Chef.
The flighty School Teacher (Preston). As fresh as the spring day itself, isn't honest about her mediocre feelings of like for the astronomer, and falls for The French Chef as easily as one can say 'Bona Petite'. She has a sappy, annoying tendency to write 'Dear John' letters which is an unpardonable offence in the 'TMT Voon Books of Courting Etiquette'.
The arrogant, virile French Chef (Karyo) who is not so virile in France, erects with surmounting fertile confidence in New York, and shamefully uses The Photographer to get his Visa. His one saving grace is that he truly is in love with The School Teacher.
The hurt, foul mouthed, bike riding, Photographer (Ryan) is out for revenge. She'll do anything to bring the hard erections of the French Chef down on his cocky head - rashes, cockroaches, monkeys with lipstick, broken arms and ribs are all part of the days work.
The camera obscura. Ahhhh, I need to get one of these so that I can watch my neighbour plant her gardenias in her nighty.
So my astrological charts say that because the 'Men are from Mars and Women are from Venus', the testosterone loaded French Chef deserves the flighty School Teacher - may their relationship be as passionate and fleeting as these gods of love and war. Astronomically, the moon circles the earth and the earth circles the sun. So opposites attract when the Sun, 'The Astronomer', and the Moon, 'The Photographer' find some common ground, the Earth 'revenge'. I also predict a supernova in the year 2500AD.
Intelligent, witty and original. Much appreciated for the effort Griffen Dunne and Robert Gorden. Not big box office material, but this film will probably age well with the passing of time as will most Meg Ryan movies. The eternal youth Matthew Broderick continues to amaze me at how little he has aged since 'Ferris Bueller's'. Kelly Preston is charmingly sweet, and Karyo Tcheky carries that something 'French' which brings women to their knees. Meg, charming, beautiful, funny Meg - will have a special place in my heart, whether she's geared in dark leathers with heavily smeared metallic makeup, or a crazed woman stomping in knee deep mud in 'Restoration' or the slightly, ditzy girl looking for love in 'Sleepless'. She is Meg Ryan and one can't help loving her for who she is.
The bottom line is that we can't choose whom we fall in love with. So in the end past wrongs must be settled and confessions made, before this fiasco of revenge is resolved. Perhaps the means of coming to terms with being dumped is not the most appropriate, or the most mature - but it was sure fun to watch.
Timothy Voon e-mail<EMAIL_ADDRESS>The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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Bug summary:
Application has stopped
Observed Behavior (a description of what happened with the app):
I wanted to calculate BMI. So I go to the statistics page and press BMI Calculator button. Then I put the value of height and weight. When I pressed Go button the application got crushed and stopped working.
Expected Behavior (a description of what you expected to happen):
I expected it would show me the BMI after proper calculation.
Steps to Reproduce (the steps to reproduce the problem):
1. Go to statistics page and press BMI calculator button
2. Put the values of height and weight
3. Press go button to calculate the BMI
Additional information:
Attachments:


The Ferry Building Marketplace is a people’s marketplace serving residents and travelers alike. Located within the historic Ferry Building at the foot of Market Street, shops large and small celebrate food in all its forms, offering everything from artisan cheeses to the freshest of local fish. Restaurants and cafés serve cuisine representing the quality and cultural diversity of San Francisco’s best chefs.
Opening in 1898 on the site of the 1875 wooden Ferry House, the Ferry Building became the transportation focal point for anyone arriving by train from the East, as well as from all the East Bay and Marin residents who worked in the city. From the Gold Rush until the 1930s, arrival by ferryboat became the only way travelers and commuters—except those coming from the Peninsula—could reach the city.
In 1892, a bond issue to build a new Ferry Building was passed by the voters of California. A young architect named A. Page Brown drew up plans for a large, steel-framed building. His original proposal was for an 840-foot-long building. However, when the construction estimates came in for the foundation (of pilings and concrete arches) the actual length had to be reduced to 660 feet by removing planned twin entrances at either end. As it was, Brown’s foundation—which has supported the entire steel-framed structure in such a remarkably dependable manner through two earthquakes (1906 and 1989)—became the largest such foundation for a building over water anywhere in the world.
Brown included a 245-foot-tall clock tower modeled after the 12th century bell tower in the Seville Cathedral in Spain to serve as a welcoming beacon on the Bay. Construction was started in 1896, and the Union Depot and Ferry House—quickly shortened by public use to the Ferry Building—received its first scheduled arrival in July 1898. Passengers off the boats passed through an elegant two-story public area with repeating interior arches and overhead skylights. At its peak, as many as 50,000 people a day commuted by ferry.
The opening of the Bay Bridge in 1936, and the Golden Gate Bridge in 1937, along with mass use of the automobile, rendered the daily commute by ferryboat obsolete. By the 1950s, the Ferry Building was used very little. The historic interior of the Ferry Building structure, with its mosaic floor and dramatic brick and ceramic arches, was lost in 1955, when much of the large open hall was filled in to accommodate standard office space with some retail use and general public use on the ground floor. To cast the once prominent structure into further obscurity, the double-deck Embarcadero Freeway was built across the face of the Ferry Building in 1957, and remained for 35 years.
By the 1970s, automobile traffic overwhelmed thoroughfares in and out of the city. Marin ferry service resumed to provide transportation alternatives. In 1989, the Loma Prieta Earthquake caused extensive damage to the Embarcadero Freeway, providing the impetus to tear it down in 1991. The Ferry Building and the central waterfront were once again visible and ready to embrace a bright future.
Today ferry terminals operate at Larkspur, Sausalito, Vallejo, and Alameda with plans for continuing network improvements and expansion. Extensive renovation of the Ferry Building is now complete. The Ferry Building redevelopment represents approximately 65,000 square feet of first floor Marketplace space, and an additional 175,000 square feet of premium second and third floor office space. The Marketplace, organized along the central Nave, provides a distinctive space for bringing together the greater Bay Area’s agricultural wealth and renowned specialty food purveyors under one roof. The exterior and main public hall have been restored to their original grandeur for use by ferry passengers and the public at large.
This preservation project has molded the best of the Ferry Building's former glory, with the most innovative of today's office and retail offerings. In staying true to the original detail of the project, Equity Office and Wilson Meany Sullivan have restored the Ferry Building to its original grandeur and returned it to the city as one of San Francisco's most cherished landmarks.


Run Lola Run (1998) Reviewed by Eugene Novikov http://www.ultimate-movie.com Member: Online Film Critics Society
***1/2 out of four
With the abundance of trite, recycled movies in the late '90s, there is a tremendous demand by movie lovers (never mind movie critics) for movies that present the wide film audience with something truly original: perhaps audaciously, perhaps purely thematically. For the former, you need look no further than director Tom Tykwer's incredible German thriller Run Lola Run, a movie that may make some viewers need a cooling off period afterwards. Lola, a contemporary Goth-girl with blazing red hair receives a desperate phone call from her boyfriend Manni one day. It seems that because she was late delivering something he lost a bag containing a hundred thousand Marks, and if he doesn't deliver a hundred thousand marks within the next twenty minutes, he will be killed.  So she runs -- not just jogs, sprints -- in hopes that somehow, someway, she'll be able to obtain the money and save a life.
>From there, as critic Steve Rhodes described it, Run Lola Run plays a bit like "Sliding Doors on steroids. With a non-stop techno soundtrack, wierd camerawork, all kinds of insane zooms and a truly breakneck pace, anyone that is bored with Run Lola Run has to be smoking something. Indeed, the movie is often outrageously exciting, as well as bitterly ironic and subtly serious.
Very much like Titanic, Run Lola Run is an achievement with filmmaking much more than it is an achievement in film. The way the movie is made, for pure visual style, Tykwer's movie is breathtaking (literally, sometimes). Thematically it does leave something to be desired; it toys around with some intriguing ideas but does occasionally seem as if there is little substance behind all of the flash.
While you are watching, this will not matter. Running a breezy 81 minutes, this is one movie I wished was longer because it was so damn good while it lasted. It is the equivalent of a roller-coaster in the amount of thrills and fun that it offers. ©1999 Eugene Novikov
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Hi, I'm TJ. I'm currently a Senior Researcher in the Autonomous Systems Lab (ASL) at ETH Zürch, Switzerland, where I also completed my PhD in Robotics (Summer 2020) with Prof. Roland Siegwart. My work at ASL spans design, system identification, state estimation, control, and planning for fixed-wing and hybrid vertical take-off and landing (VTOL) aerial robots operating in unstructured environments (the real world!). A significant portion of my time as a PhD student was additionally geared towards developing autonomous behaviors for the endurance world record holding AtlantikSolar UAV.
Prior to my PhD, I completed a Bachelors and Masters of Science in Aerospace Engineering at the University of Kansas, USA. My Masters work was funded by the NSF Center for Remote Sensing of Ice Sheets (CReSIS), where I worked on the development of radar-integrated unmanned aerial vehicles (UAVs) used for measuring the thickness of ice sheets in Antarctica. During my Bachelors degree, I also spent one semester abroad taking courses within the Systems & Control Masters program at TU Delft, the Netherlands.
I have a passion for aerial-robotic field work, having deployed UAVs to the Arctic, Antarctic, Brazilian Amazon, and Swiss/Italian Alps. My primary research motivations are geared towards enabling safe, reliable, and useful(!) autonomous aerial-robotic operations in remote settings.
@: ASL, ETH Zürich | CReSIS, University of Kansas
We developed hardware and algorithms for autonomous, beyond visual line-of-sight (BVLOS), drone-based deployment of low-power, long-term GNSS monitoring stations on the Gorner Glacier, Switzerland, for multi-point, in situ ice motion recording. Funding from armasuisse S+T and the Swiss Polar Institute (SPI).
Michael Pantic, Dario Panzuto, Thomas Stastny, Guillaume Jouvet, Juan Nieto, and Roland Siegwart
Together with glaciologists from the Laboratory of Hydraulics, Hydrology, and Glaciology at ETH Zürich, I organized and lead a glacier monitoring field campaign to Qaanaaq, Greenland (77°N!), resulting in the first-ever autonomous, BVLOS, solar-powered flights of a UAV in a polar region. Funded by the ETH Foundation. See blog post here.
Small, long-range, fixed-wing UAVs executing surveying, mapping, or searching missions will inevitably encounter strong and turbulent wind fields, at times reaching to, or even exceeding the aircraft's nominal airspeed. I developed efficient (energetically and computationally) wind-aware guidance logic to allow safe flight in these conditions. (paper, dissertation)
We developed mathematical modeling and controller design for an over-actuated Vertical Take-off and Landing (VTOL) tilt-wing Unmanned Aerial Vehicle (UAV). Performance of the controller is demonstrated in hovering, transitioning, and cruising flight experiments.
David Rohr, Thomas Stastny, Sebastian Verling, and Roland Siegwart (paper)
Part of my PhD work involved the development of a long-horizon nonlinear model predictive controller (NMPC) for fixed-wing UAVs, considering path following objectives, stall prevention, actuator fault tolerance, wind-awareness, and explicit vision-based terrain feedback. (paper1, paper2, dissertation)
I've worked with Sebastian Verling (Co-Founder of Wingtra) and multiple students on a range of projects related to the development of control and estimation techniques for VTOL tailsitter UAVs including transition optimization, full envelope system identification, wind estimation, fault-tolerant control (see video below!).
Silvan Fuhrer, Sebastian Verling, Thomas Stastny, and Roland Siegwart (paper)
I worked with the Fixed-Wing Team at the Autonomous Systems Lab, ETH Zürich, conducting performance optimization and developing automatic take-off, landing, and cruise control design for the AtlantikSolar UAV, resulting in an 81.5 hour endurance world record solar-powered flight for all aircraft below 50kg (blog, paper) and 26 hour, fully autonomous, search and rescue payload equipped flight with passive thermal updraft detection and exploitation (blog, paper).
During an expedition to the Brazilian Amazon, we had the opportunity to work with SIPAM (Brazilian Amazon Protection Agency) on a real-life disaster relief support mission, using the AtlinkSolar UAV. A boat carrying 5000 cattle sunk in the Bacarena Port of the Rio Pará, Belém, Brazil, further spilling 740 tons oil. This was a suprise mission during the Adventura AtlantikSolar@Brazil project, organized together with Swissnex, Brazil.
Full autonomy for fixed-wing unmanned aerial vehicles (UAVs) requires the capability to autonomously detect potential landing sites in unknown and unstructured terrain, allowing for self-governed mission completion or handling of emergency situations. We developed a perception system addressing this challenge by detecting landing sites based on their texture and geometric shape without using any prior knowledge about the environment.
Timo Hinzmann, Thomas Stastny, Cesar Cadena, Roland Siegwart, and Igor Gilitschenski (paper)
I worked on an ESA funded collaboration between ASL and GAMAYA, the project SOLAR3 led to the development of novel UAV platform, SenseSoar2, equipped with a hyper spectral imaging (HSI) camera for long-range precision farming flights. The SenseSoar2 system has been successfully operated in Ukraine by an internal national drone operator during the 2018-2019 years. SenseSoar2 was additionally utiliized in collaboration with Swiss industry partners Swisscom, INVOLI, and v2sky, where we were able to demonstrate the first networked, BVLOS flight of a UAV in Switzerland, over Lake Neuchâtel.
I was a core researcher on the EU FP7 funded SHERPA project; a large-scale research project for mixed ground and aerial robotic platforms to support search and rescue activities in real-world hostile environments such as an alpine scenario. Our contribution included the demonstration of collaborative heterogeneous aerial deployments combining fixed-wing and R-MAX helicopter platforms for distributed environmental mapping and missing person identification. (paper1,paper2).
I embarked on an 8-week deployment with the University of Kansas' Automatic Flight Systems team to Lake Whillans Glacier, Antarctica resulting in first-ever autonomous glacial bed-rock sounding via a UAV. More info here.
During my time as a Masters graduate research assistant in the University of Kansas Aerospace Dept., I conducted research on control and planning for fixed-wing UAVs including multi-agent avoidance and formation strategies (paper1, paper2).
See publication metrics on Google Scholar.
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T. Stastny. "Low-Altitude Control and Local Re-Planning Strategies for Small Fixed-Wing UAVs". Doctoral Thesis, ETH Zürich. 2020. |
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2020 |
D. Malyuta, C. Brommer, D. Hentzen, T. Stastny, R. Siegwart, and R. Brockers. "Long-duration Fully Autonomous Operation of Rotorcraft Unmanned Aerial Systems for Remote-sensing Data Acquisition". Journal of Field Robotics (JFR). | arxiv |
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2019 |
D. Rohr, T. Stastny, S. Verling, and R. Siegwart. "Attitude and Cruise Control of a VTOL Tiltwing UAV". IEEE Robotics and Automation Letters (RA-L). | arxiv | video |
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2018 |
T. Hinzmann, T. Stastny, C. Cadena, R. Siegwart, and I. Gilitschenski. "Free LSD: Prior-free Visual Landing Site Detection for Autonomous Planes". IEEE Robotics and Automation Letters (RA-L). | arxiv | video |
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2018 |
P. Oettershagen, T. Stastny, T. Hinzmann, K. Rudin, T. Mantel, A. Melzer, B. Wawrzacz, G. Hitz, and R. Siegwart. "Robotic Technologies for Solar-powered UAVs: Fully Autonomous Updraft-aware Aerial Sensing for Multiday Search-and-rescue Missions". Journal of Field Robotics (JFR). | publisher | video |
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2017 |
P. Oettershagen, A. Melzer, Mantel, K. Rudin, T. Stastny, B. Wawrzacz, T. Hinzmann, S. Leutenegger, K. Alexis, and R. Siegwart. "Design of Small Hand-launched Solar-powered UAVs: From Concept Study to a Multi-day World Endurance Record Flight". Journal of Field Robotics (JFR). | publisher | video |
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2015 |
T. Stastny, G. Garcia, and S. Keshmiri. "Collision and Obstacle Avoidance in Unmanned Aerial Systems Using Morphing Potential Field Navigation and Nonlinear Model Predictive Control". Journal of Dynamic Systems, Measurement, and Control. | publisher | video |
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2015 |
G. Garcia, S. Keshmiri, and T. Stastny. "Nonlinear Model Predictive Controller Robustness Extension for Unmanned Aircraft". International Journal of Intelligent Unmanned Systems. | publisher |
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2014 |
G. Garcia, S. Keshmiri, and T. Stastny. "Robust and Adaptive Nonlinear Model Predictive Controller for Unsteady and Highly Nonlinear Unmanned Aircraft". IEEE Transactions on Control Systems Technology. | publisher |
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2017 |
M. Kamel, T. Stastny, K. Alexis, R. Siegwart. "Model Predictive Control for Trajectory Tracking of Unmanned Aerial Vehicles Using Robot Operating System". Robot Operating System (ROS), The Complete Reference (Volume 2). | publisher |
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2021 |
C. Olsson, S. Verling, T. Stastny, and R. Siegwart. "Full Envelope System Identification of a VTOL Tailsitter UAV". AIAA Guidance, Navigation, and Control (GNC) Conference. Accepted for publication. |
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2020 |
M. Harms, N. Kaufmann, F. Rockenbauer, N. Lawrance, T. Stastny, and R. Siegwart. "Differential Sweep Attitude Control for Swept Wing UAVs". International Conference on Unmanned Aircraft Systems (ICUAS). | publisher |
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2019 |
T. Stastny and R. Siegwart. "On Flying Backwards: Preventing Run-away of Small, Low-speed, Fixed-wing UAVs in Strong Winds". IEEE International Conference on Intelligent Robots and Systems (IROS). | arxiv | video |
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2019 |
D. Hentzen, T. Stastny, R. Siegwart, and R. Brockers. "Disturbance Estimation and Rejection for High-Precision Multirotor Position Control". IEEE International Conference on Intelligent Robots and Systems (IROS). | arxiv | video |
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2019 |
T. Stastny, E. Ahbe, M. Dangel, and R. Siegwart. "Locally Power-optimal Nonlinear Model Predictive Control for Fixed-wing Airborne Wind Energy". American Control Conference (ACC). | publisher |
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2019 |
S. Fuhrer, S. Verling, T. Stastny, and R. Siegwart. "Fault-tolerant Flight Control of a VTOL Tailsitter UAV". IEEE International Conference on Robotics and Automation (ICRA). | publisher | video |
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2018 |
J. Lee, T. Muskardin, C. Pacz, P. Oettershagen, T. Stastny, I. Sa, R. Siegwart, and K. Kondak. "Towards Autonomous Stratospheric Flight: A Generic Global System Identification Framework for Fixed-Wing Platforms". IEEE International Conference on Intelligent Robots and Systems (IROS). | publisher |
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2018 |
T. Stastny and R. Siegwart. "Nonlinear Model Predictive Guidance for Fixed-wing UAVs Using Identified Control Augmented Dynamics". International Conference on Unmanned Aircraft Systems (ICUAS). | arxiv | video1, video2, video3 |
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2017 |
L. Furieri, T. Stastny, L. Marconi, R. Siegwart, and I. Gilitschenski. "Gone with the Wind: Nonlinear Guidance for Small Fixed-wing Aircraft in Arbitrarily Strong Windfields". American Control Conference (ACC). Best Paper Award. | arxiv |
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2017 |
S. Verling, T. Stastny, G. Bättig, K. Alexis, and R. Siegwart. "Model-based Transition Optimization for a VTOL Tailsitter". IEEE International Conference on Robotics and Automation (ICRA). | publisher |
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2017 |
Y. Demitri, S. Verling, T. Stastny, A. Melzer, and R. Siegwart. "Model-based Wind Estimation for a Hovering VTOL Tailsitter UAV". IEEE International Conference on Robotics and Automation (ICRA). | publisher |
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2017 |
T. Stastny, A. Dash, and R. Siegwart. "Nonlinear MPC for Fixed-wing UAV Trajectory Tracking: Implementation and Flight Experiments". AIAA Guidance, Navigation, and Control (GNC) Conference. | publisher |
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2016 |
P. Oettershagen, A. Melzer, T. Mantel, K. Rudin, T. Stastny, B. Wawrzacz, T. Hinzmann, K. Alexis, and R. Siegwart. "Perpetual Flight with a Small Solar-powered UAV: Flight Results, Performance Analysis and Model Validation". IEEE Aerospace Conference. | publisher |
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2016 |
T. Hinzmann, T. Stastny, G. Conte, P. Doherty, P. Rudol, M. Wzorek, I. Gilitschenski, E. Galceran, and R. Siegwart. "Collaborative 3D Reconstruction Using Heterogeneous UAVs: System and Experiments". International Symposium on Experimental Robotics (ISER). | publisher |
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2016 |
P. Doherty, J. Kvarnström, P. Rudol, M. Wzorek, G. Conte, C. Berger, T. Hinzmann, and T. Stastny. "Collaborative Framework for 3D Mapping Using Unmanned Aerial Vehicles". International Conference on Principles and Practice of Multi-Agent Systems. | publisher |
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2015 |
P. Oettershagen, T. Stastny, T. Mantel, A. Melzer, K. Rudin, P. Gohl, G. Agamennoni, K. Alexis, and R. Siegwart. "Long-Endurance Sensing and Mapping using a Hand-Launchable Solar-Powered UAV". Field and Service Robotics (FSR). | pdf |
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2015 |
A. Vempati, G. Agamennoni, T. Stastny, and R. Siegwart. "Victim Detection from a Fixed-Wing UAV: Experimental Results". International Symposium on Visual Computing (ISVC). | publisher |
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2015 |
T. Stastny, G. Garcia, and S. Keshmiri. "Robust Three-Dimensional Collision Avoidance for Fixed-Wing Unmanned Aerial Systems". AIAA Guidance, Navigation, and Control (GNC) Conference. | publisher | video |
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2013 |
T. Stastny, R. Lykins, and S. Keshmiri. "Nonlinear Parameter Estimation of Unmanned Aerial Vehicles in Wind Shear Using Artificial Neural Networks". AIAA Guidance, Navigation, and Control (GNC) Conference. | publisher |
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2012 |
J. Sebes, W. Vanskike, M. Williams, S. McCandless, T. Stastny, G. Worden, N. Brunkhorst. "Flight Testing and Evaluation of the Structural Response to Flight Loads of a Small Scale Unmanned Aerial System". AIAA Infotech@ Aerospace. | publisher |
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2011 |
W. Vanskike, M. Williams,T. Stastny, A. Ghate, S. McCandless, and T. Peckman. "Hawkeye UAV Dynamic Analysis". AIAA Modeling and Simulation Technologies Conference. | publisher |
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2013 |
T. Stastny. "Mars Exploration? Unleash the Swarms!". Ruimtevaart, Netherlands Space Society (NVR). | pdf |
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2013 |
M. Arigoni, R. Simpson, S. Fuhrer, P. Beardsley, D. Mammolo, M. Burri, M. Bischoff, T. Stastny, L. Rodgers, D. Krummenacher, and R. Siegwart. "Vehicles Configured For Navigating Surface Transitions". US Patent 10,464,620. |
Focus Projects | Student Theses | Lectures
I coached a team of very talented Bachelors students in the year-long development of a flying, diving, swimming, and re-emerging, swept-wing aerial robot (more info here). Several of the team members further expanded on this work enabling us to publish a paper on variable sweep attitude control, see paper.
I supervised two Bachelors students on the maneuver design, control, and estimation for the floor-to-wall transition of the VertiGo robot (more info here). See resulting patent.
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Spring 2020 |
Gian Heinrich. "Learning to Stall: Using in-air Pressure Data to Identify, Characterize, and Control Fixed-Wing Aircraft Stall". |
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Spring 2019 |
Dario Panzuto. "Development of a Drone-Released GPS Logging Unit for In Situ Monitoring of Fast-Flowing Glaciers". |
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Spring 2019 |
Michael Imobersteg. "Autonomous Retraction Control of Rigid Wing Airborne Wind Energy Systems". |
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Spring 2019 |
Adrian Ruckli. "A Deep Learning-Based Approach to Flexible-Wing Modeling for Wide-Baseline Stereo Vision on Fixed-Wing Unmanned Aerial Vehicles". |
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Autumn 2018 |
David Rohr. "Tiltwing VTOL Flight-Control System". publication |
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Autumn 2018 |
Manuel Dangel. "Nonlinear Model Predictive Control for Fixed-Wing Airborne Wind Energy". publication |
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Spring 2018 |
Silvan Fuhrer. "Fault-Tolerant Flight Control of a VTOL Tailsitter UAV". publication |
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Spring 2018 |
Daniel Hentzen. "Robust Precision Landing for Multirotor UAS". publication |
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Spring 2018 |
Matthias Epprecht. "Bayesian Optimization Based Automatic Controller Tuning for Fixed-Wing UAVs". |
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Spring 2018 |
Fabian Bachmann. "Airflow Sensing and Control for Small Fixed-Wing UAVs". |
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Autumn 2017 |
Adyasha Dash. "Magnetometer Error Sources and Mitigation for Small UAVs". |
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Spring 2017 |
Danylo Malyuta. "Guidance, Navigation, Control and Mission Logic for Quadrotor Full-cycle Autonomy". publication |
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Spring 2017 |
Jongseok Lee. "Towards Autonomous Stratospheric Flight: A Generic Global System Identification Framework for Fixed-Wing Platforms". publication |
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Spring 2017 |
Carl Olsson. "Full Envelope System Identification of a VTOL Tailsitter UAV". publication |
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Autumn 2016 |
Youssef Demitri. "Robust Operation of a Hovering VTOL Tailsitter UAV in Wind". |
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Autumn 2016 |
Luca Furieri. "Geometric Versus Model Predictive Control Based Guidance Algorithms for Fixed-Wing UAVs in the Presence of Very Strong Wind Fields". publication |
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Autumn 2016 |
Pavel Verchersky. "Development of a Comprehensive, Hardware-in-the-loop Simulation Environment for Fixed-wing Unmanned Aircraft". |
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Autumn 2016 |
Nicolas El Hayek. "Ridge Lift Exploitation for Small Unmanned Fixed-Wing Aircraft". |
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Autumn 2015 |
Felix Renaut. "Vision-Based Autonomous Landing Site Detection for Fixed-Wing Unmanned Aerial Vehicles". |
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Autumn 2014 |
Markus Thurnherr. "Model Predictive Control for Fixed-Wing UAVs Using LPV-Models". |
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Autumn 2020 |
Marco Job. "Analysis of Dynamic Landing Control for VTOL Tailsitters". |
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Autumn 2020 |
Lukas Spirig. "Study on True Airspeed Measurement Using Acoustic Whistles". |
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Spring 2020 |
Ramon Flammer. "Analysis of the Aerodynamic Effects on Coaxial Rotor Configurations". |
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Spring 2020 |
Matthias Studiger. "Model Predictive Longitudinal Cruise Control of a VTOL Tilt-Wing UAV". |
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Spring 2019 |
Gian Heinrich. "Optimizing Deep-stall Landing Maneuvers on Small Fixed-wing UAVs". |
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Spring 2019 |
Cla Galliard. "Nonlinear Total Energy Control System for Longitudinal Control of an Aircraft". |
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Spring 2019 |
Eloi Roset. "Wing Pressure Distribution Measurement for Small Fixed-Wing UAVs". |
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Spring 2019 |
Marko Maljkovic. "Online Neural Network Based Model Identification of a Fixed-Wing UAV". |
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Autumn 2018 |
Jasmin Fischli. "Online Neural Network Based System Identification for Fixed-wing UAVs". |
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Spring 2017 |
Silvan Fuhrer. "Sampling Based Motion Planning for Fixed-Wing UAV System Identification". |
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Spring 2016 |
Youssef Demitri. "Wind Estimation for a Hovering VTOL Tailsitter UAV". publication |
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Spring 2016 |
Léonard Schai. "Design, Manufacturing and Calibration of a Miniature Vector Probe for Small, Low Speed, Unmanned Aircraft". |
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Spring 2016 |
Adyasha Dash. "High Level Predictive Control of Fixed-Wing UAVs using Low Order System Models". publication |
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Spring 2016 |
Gregory Bättig. "Transition Optimization for a VTOL Tailsitter". publication |
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Spring 2016 |
Samuel Dobmann. "Design, Modeling, and Control of an Autonomous Underwater Glider". |
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Spring 2015 |
Ricardo Zurfluh. "Robust Airspeed Sensing in Harsh Environmental Conditions". |
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Spring 2020 |
Severin Laasch. "Impact Compensation on Multicopters using Model Predictive Control". |
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Spring 2019 |
Marvin Harms & Noah Kaufmann. "Differential Sweep Attitude Control for Fixed-Wing UAVs". publication |
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Spring 2019 |
Friedrich Rockenbauer. "Cross-Validation of Simulation Models and Flight Test Data for Fixed-Wing UAVs". |
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Spring 2018 |
Marco Ruggia. "Design and Analysis of Small Scale Angle of Attack Sensors". |
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Spring 2018 |
Jonas Peter. "System Identification for an Airborne Wind Energy Aircraft". |
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Spring 2018 |
Adrian Schneebeli. "Optimization of the Back-Transition Maneuver for a VTOL UAV". |
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Spring 2018 |
Lucas Streichenberg. "Improved Hover Controller for an AWE System". |
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Spring 2017 |
Cla Galliard. "Spherical Guidance and Control for an Airborne Wind Energy System". |
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Spring 2017 |
Gabriel König. "Implementation and Validation of the Transition for a VTOL Airborne Wind Energy System". |
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Spring 2015 |
David Krummenacher. "Floor to Wall Transitions for a Wall Racing Robot". |
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Spring 2015 |
Michael Arigoni. "Control of a Wall Racing Robot for Agile Ground Maneuvers". |
I am a lecturer for the Robot Dynamics course offered in the ETH Zürich Robotics M.Sc. cirriculum. I teach the fundamentals of aerodynamics, flight dynamics, aircraft modeling and control for fixed-wing UAVs.
I taught two guest lectures on optimal output feedback control in the Optimal Controls M.Sc. course within the Aerospace Engineering Department at the University of Kansas.
I was a teaching assistant for the B.Sc. courses Introductory Topics in Mathematics and Elementary Statistics within the Mathematics Department at the University of Kansas.