Download the Medium stats overview as a CSV file
Print the total story views to the console. Remember to scroll down to reveal all the stories first. Check the result in the browser console.


Getting Started with Time Series¶
Introduction¶
Time series analysis is a subfield of statistics and econometrics. Time series data \(y_{t}\) is indexed by time \(t\) and ordered sequentially. This presents unique challenges including autocorrelation within the data, non-exchangeability of data points, and non-stationarity of data and parameters. Because of the sequential nature of the data, time series analysis has particular goals. We can summarize these goals into one of description of a time series in terms of latent components or features of interest, and prediction, which aims to produce reasonable forecasts of the future (Harvey, 1990).
From start to finish, we can place time series modelling in a framework in the spirit of Box’s Loop (Blei, D.M. 2014). In particular, we:
- Build a model for the time series data
- Perform inference on the model
- Check the model fit, performing evaluation & criticism
- Revise the model, repeat until happy
- Perform retrospection and prediction with the model
Below we outline an example model building process for JPMorgan Chase stock data, where the index is daily. Consider this time series data:
import pandas as pd
import numpy as np
from pandas_datareader.data import DataReader
from datetime import datetime
a = DataReader('JPM', 'yahoo', datetime(2006,6,1), datetime(2016,6,1))
a_returns = pd.DataFrame(np.diff(np.log(a['Adj Close'].values)))
a_returns.index = a.index.values[1:a.index.values.shape[0]]
a_returns.columns = ["JPM Returns"]
a_returns.head()
| JPM Returns | |
|---|---|
| 2006-06-02 | 0.005264 |
| 2006-06-05 | -0.019360 |
| 2006-06-06 | -0.013826 |
| 2006-06-07 | -0.003072 |
| 2006-06-08 | 0.002364 |
The index of the data is meaningful for this data; we cannot simply ‘shuffle the deck’ otherwise we could lose meaningful dependencies such as seasonality, trends, cycles and other components.
Step One: Visualize the Data¶
Because time series is sequential, plotting the data allows us to obtain an idea of its properties. We can also plot autocorrelation plots of the data (and transformations of the data) to understand if autocorrelation exists in the series. Lastly, in this stage, we can reason about potential features that might explain variation in the series.
For our stock market data, we can first plot the data:
plt.figure(figsize=(15, 5))
plt.ylabel("Returns")
plt.plot(a_returns)
plt.show()
It appears that the volatility of the series changes over time, and is clustering in periods of market turbulence, such as in the financial crisis of 2008. We can obtain more insight by plotting autocorrelation functions of the returns and squared returns:
import pyflux as pf
import matplotlib.pyplot as plt
pf.acf_plot(a_returns.values.T[0])
pf.acf_plot(np.square(a_returns.values.T[0]))
The squared returns demonstrate strong evidence of autocorrelation. The fact that autocorrelation persists and decays over multiply lags is evidence of an autoregressive effect within volatility. For returns, there is less strong evidence of autocorrelation, although the first lag is significant.
Step Two: Propose a Model¶
We reason about a model that can explain the variation in the data and we specify any prior beliefs we have about the model parameters. We saw evidence of volatility clustering. One way to model this effect is through a GARCH model for volatility (Bollerslev, T. 1986).
We will perform Bayesian inference on this model, and so we will specify some priors. We will ensure \(\omega > 0\) through a log transform, and we will use a Truncated Normal prior on \(\alpha, \beta\):
my_model = pf.GARCH(p=1, q=1, data=a_returns)
print(my_model.latent_variables)
Index Latent Variable Prior Prior Hyperparameters V.I. Dist Transform
======== =================== =============== ======================= ========== ==========
0 Vol Constant Normal mu0: 0, sigma0: 3 Normal exp
1 q(1) Normal mu0: 0, sigma0: 0.5 Normal logit
2 p(1) Normal mu0: 0, sigma0: 0.5 Normal logit
3 Returns Constant Normal mu0: 0, sigma0: 3 Normal None
my_model.adjust_prior(1, pf.TruncatedNormal(0.01, 0.5, lower=0.0, upper=1.0))
my_model.adjust_prior(2, pf.TruncatedNormal(0.97, 0.5, lower=0.0, upper=1.0))
Step Three: Perform Inference¶
As a third step we need to decide how to perform inference for the model. Below we use Metropolis-Hastings for approximate inference on our GARCH model. We also plot the latent variables \(\alpha\) and \(\beta\):
result = my_model.fit('M-H', nsims=20000)
Tuning complete! Now sampling.
Acceptance rate of Metropolis-Hastings is 0.33865
my_model.plot_z([1,2])
Step Four: Evaluate Model Fit¶
We next evaluate the fit of the model and establish whether we can improve the model further. For time series, the simplest way to visualize fit is to plot the series against its predicted values; we can also check out-of-sample performance. If we seek further model improvements, we go back to step two and proceed. Once we are happy we go to step five.
Below we plot the fit of the GARCH model and observe that it picking up volatility clustering in the series:
my_model.plot_fit(figsize=(15,5))
We can also plot samples from the posterior predictive density:
my_model.plot_sample(nsims=10, figsize=(15,7))
We can see that the samples (colored) appear to be picking up variation in the data (the square datapoints).
We can also perform a posterior predictive check (PPC) on features of the generated series, for example the kurtosis:
from scipy.stats import kurtosis
my_model.plot_ppc(T=kurtosis)
It appears our generated data underestimates kurtosis in the series. This is not surprising as we are assuming normally distributed returns, so we may want to consider alternative volatility models.
Step Five: Analyse and Predict¶
Once we are happy with our model, we can use it to analyze the historical time series and make predictions. For our GARCH model, we can see from the previous fit plot that the main periods of volatility picked up are during the financial crisis of 2007-2008, and during the Eurozone crisis in late 2011. We can also obtain forward predictions with the model:
my_model.plot_predict(h=30, figsize=(15,5))
References¶
Blei, D. M. (2014). Build, compute, critique, repeat: Data analysis with latent variable models. Annual Review of Statistics and Its Application, 1, 203–232.
Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics. April, 31:3, pp. 307–27.
Harvey A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press.


{{include 'mod/head'}} {{include 'mod/nav'}}
{{include 'mod/recommend'}}
{{include 'mod/breadcrumbs'}} {{include 'mod/list'}}


National Registry of Cardiopulmonary Resuscitation: 14,720 cases reported in 2014 < 50% had return of spontaneous circulation after cCPR 17% survived to discharge Other studies report survival rates between 7.4% and 27% with some as low as 2% "The current conventional CPR database reported approximately 14,000 cases of CPR in 2014. Your browser does not support the audio element. Other studies regarding survival rates report this number to be as low as 2% with conventional CPR." Previous Section Next Section


Disney+ Cracks Down on VPN Services By Blocking Non-Regional Users
by Samuel GelmanDisney+ is only available in a few countries, but that is not stopping those in locations where the service is not available from watching.
Many users outside the U.S., Canada, Australia and New Zealand have trend to VPNs to gain access to the streaming platform. However, according to Screen Binge, Disney has been blocking foreign accounts using VPNs. Many of the top VPNs have been blocked by Disney, with only NordVPN working at the time of this writing.
That does not mean that Disney+ will only be available in the above three countries forever. The United Kingdom, France, Spain, Italy, Germany, Sweden and Ireland will be able to purchase the service on March 31, 2020. No official release dates for other regions have been announced yet.
Click the button below to start this article in quick view.
Disney+'s start had its up and downs. It brought in 10 million sign ups, beating its 2019 goal of 8 million. However, its launch was plagued by technical issues and reports of accounts being hacked and sold online.
Disney+ is now available in the U.S., Australia and New Zealand, with content from Disney, Pixar, Marvel, Star Wars and National Geographic.
https://schema.orgBreadcrumbListListItem1Homehttps://www.cbr.com/ListItem2TVhttps://www.cbr.com/category/tv/ListItem3TV Newshttps://www.cbr.com/category/tv/news-tv/ListItem4Disney+ Cracks Down on VPN Services By Blocking Non-Regional Usershttps://www.cbr.com/disney-cracks-down-on-vpn-services-by-blocking-non-regional-users/


Description Of The Book
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After you bulk download the CFD dataset, new daily updates are available at 3 PM Coordinated Universal Time (UTC) after each trading day. To unlock local access to the data updates, open the Pricing page of your organization and subscribe to at least one of the following data packages:
You need billing permissions to change the organization's subscriptions.
After you subscribe to dataset updates, to update your local copy of the CFD dataset, use the CLI Command Generator to generate your download command and then run it in a terminal in your organization workspace. Alternatively, instead of directly calling the lean data download
command, you can place a Python script in the data directory of your organization workspace and run it to update your data files. The following example script updates all data resolutions:
import os from datetime import datetime from pytz import timezone # Define a method to download the data def download_data(resolution, overwrite=False): print(f"Updating {resolution} data...") command = f'lean data download --dataset "CFD Data" --data-type "Bulk" --resolution "{resolution}"' if overwrite: command += " --overwrite" os.system(command) # Update minute and second data files END_DATE = datetime.now(timezone("US/Eastern")).strftime("%Y%m%d") new_data_available = False for resolution in ["second", "minute"]: latest_date = sorted([f for f in os.listdir(f"cfd/oanda/{resolution}/xauusd")])[-1].split('_')[0] if latest_date >= END_DATE: print(f"{resolution} data is already up to date.") continue new_data_available = True download_data(resolution) # Update daily and hourly data files if new_data_available: for resolution in ["hour", "daily"]: download_data(resolution, True)
The preceding script checks the date of the most recent XAUUSD data you have for second and minute resolutions. If there is new data available for either of these resolutions, it downloads the new data files and overwrites your hourly and daily files. If you don't intend to download all resolutions, adjust this script to your needs.


QScatter3DSeries Class
The QScatter3DSeries class represents a data series in a 3D scatter graph. More...
| Header: | #include <QScatter3DSeries> |
| Since: | QtDataVisualization 1.0 |
| Instantiated By: | Scatter3DSeries |
| Inherits: | QAbstract3DSeries |
Properties
- dataProxy : QScatterDataProxy *
- itemSize : float
- selectedItem : int
- 17 properties inherited from QAbstract3DSeries
- 1 property inherited from QObject
Public Functions
| QScatter3DSeries(QObject *parent = Q_NULLPTR) | |
| QScatter3DSeries(QScatterDataProxy *dataProxy, QObject *parent = Q_NULLPTR) | |
| virtual | ~QScatter3DSeries() |
| QScatterDataProxy * | dataProxy() const |
| float | itemSize() const |
| int | selectedItem() const |
| void | setDataProxy(QScatterDataProxy *proxy) |
| void | setItemSize(float size) |
| void | setSelectedItem(int index) |
- 33 public functions inherited from QAbstract3DSeries
- 32 public functions inherited from QObject
Signals
| void | dataProxyChanged(QScatterDataProxy *proxy) |
| void | itemSizeChanged(float size) |
| void | selectedItemChanged(int index) |
- 16 signals inherited from QAbstract3DSeries
- 2 signals inherited from QObject
Static Public Members
| int | invalidSelectionIndex() |
- 10 static public members inherited from QObject
Additional Inherited Members
- 1 public slot inherited from QObject
- 1 public variable inherited from QObject
- 9 protected functions inherited from QObject
- 2 protected variables inherited from QObject
Detailed Description
The QScatter3DSeries class represents a data series in a 3D scatter graph.
This class manages the series specific visual elements, as well as the series data (via a data proxy).
If no data proxy is set explicitly for the series, the series creates a default proxy. Setting another proxy will destroy the existing proxy and all data added to it.
QScatter3DSeries supports the following format tags for QAbstract3DSeries::setItemLabelFormat():
| @xTitle | Title from x-axis |
| @yTitle | Title from y-axis |
| @zTitle | Title from z-axis |
| @xLabel | Item value formatted using the format of the x-axis. For more information, see QValue3DAxis::setLabelFormat(). |
| @yLabel | Item value formatted using the format of the y-axis. For more information, see QValue3DAxis::setLabelFormat(). |
| @zLabel | Item value formatted using the format of the z-axis. For more information, see QValue3DAxis::setLabelFormat(). |
| @seriesName | Name of the series |
For example:
proxy->setItemLabelFormat(QStringLiteral("@valueTitle for (@rowLabel, @colLabel): %.1f"));
See also Qt Data Visualization Data Handling.
Property Documentation
dataProxy : QScatterDataProxy *
This property holds the active data proxy.
Access functions:
| QScatterDataProxy * | dataProxy() const |
| void | setDataProxy(QScatterDataProxy *proxy) |
Notifier signal:
| void | dataProxyChanged(QScatterDataProxy *proxy) |
itemSize : float
Item size for the series.
The size must be between 0.0f
and 1.0f
. Setting the size to 0.0f
causes the item size to be automatically scaled based on the total number of items in all the series for the graph.
The preset default is 0.0f
.
Access functions:
| float | itemSize() const |
| void | setItemSize(float size) |
Notifier signal:
| void | itemSizeChanged(float size) |
selectedItem : int
This property holds the item that is selected in the series.
Access functions:
| int | selectedItem() const |
| void | setSelectedItem(int index) |
Notifier signal:
| void | selectedItemChanged(int index) |
Member Function Documentation
QScatter3DSeries::QScatter3DSeries(QObject *parent = Q_NULLPTR)
Constructs a scatter 3D series with the parent parent.
QScatter3DSeries::QScatter3DSeries(QScatterDataProxy *dataProxy, QObject *parent = Q_NULLPTR)
Constructs a scatter 3D series with the data proxy dataProxy and the parent parent.
[virtual]
QScatter3DSeries::~QScatter3DSeries()
Deletes the scatter 3D series.
[static]
int QScatter3DSeries::invalidSelectionIndex()
Returns an invalid index for selection. This index is set to the selectedItem property to clear the selection from this series.
See also QAbstract3DGraph::clearSelection().
void QScatter3DSeries::setDataProxy(QScatterDataProxy *proxy)
Sets the active data proxy for the series to proxy. The series assumes ownership of any proxy set to it and deletes any previously set proxy when a new one is added. The proxy argument cannot be null or set to another series.
Note: Setter function for property dataProxy.
See also dataProxy().
void QScatter3DSeries::setSelectedItem(int index)
Selects the item at the index index in the data array of the series. Only one item can be selected at a time.
To clear selection from this series, invalidSelectionIndex() is set as index. If this series is added to a graph, the graph can adjust the selection according to user interaction or if it becomes invalid. Selecting an item on another added series will also clear the selection.
Removing items from or inserting items to the series before the selected item will adjust the selection so that the same item will stay selected.
Note: Setter function for property selectedItem.
See also selectedItem() and QAbstract3DGraph::clearSelection().


View Prisons
See a list of available facilities and inmates on your selected location.
Give your inmates a second chance. Help them gain work experience and earn income while in prison, so upon release, they can be rehabilitated...the right way
Start by selecting a location to find the facility of your choice or closest to you.
See a list of available facilities and inmates on your selected location.
Navigate through the skills to match inmates on your chosen facility.
Found your match? Easily extend an offer through the facility administrators.


@unwrap_adder = (addr) ->
result = {}
for k,v of addr
if k is '_id'
continue
LypseForm Michael Shafir
This library is intented to make the process of form creation simpler through usage of lypse models.
An adder is an object that facilitates the population and creation of a new instance of a LypseModel objct.
A LypseForm is a further abstracted bindable object that supports object creation.
Example:
class Person extends LypseModel @collection: People @fields: name: '' email: ''
p = @adder(Person) p.name('Michael Shafir'<EMAIL_ADDRESS>p.add()
class PersonForm extends LypseForm @source: Person defaults: name: () -> 'anonymoues'
p = new PersonForm() p.name('Michael Shafir'<EMAIL_ADDRESS>p.add()
@unwrap_adder = (addr) ->
result = {}
for k,v of addr
if k is '_id'
continue
for observable arrays unwrap all the items recursively
if ko.isObservable(v) and v() instanceof Array
lst = []
for item in v()
lst.push unwrap_adder(item)
result[k] = lst
for regular observables just unwrap the value
else if ko.isObservable(v)
result[k] = v()
return result
@adder = (model,target) =>
newobj = target ? {}
newobj._id = ko.observable()
for k,v of model.fields
do (k,v) =>
this is the best way I can think of to know if something is a sub-model we make sub-models into observableArrays with an .add on the array and a .remove on each item. Also we subscribe to bulk changes to allow for more fluid methods on data entry
if v instanceof Function and typeof(v()) isnt 'object'
result = ko.observableArray()
result['add'] = () ->
ret = adder(v())
ret['remove'] = () ->
result.remove(ret)
result.onItemRemoved?(ret)
result.push(ret)
for sk,sv of ret
sv.subscribe?(() ->
result.onItemChanged?(ret)
newobj.onItemChanged?(ret))
result.onItemAdded?(ret)
return ret
newobj[k] = result
things that aren't functions should just be single fields (SUBJECT TO CHANGE)
else if v not instanceof Function
newobj[k] = ko.observable('')
newobj[k].subscribe () -> newobj.onItemChanged?(newobj)
if we're wrapping a top-level doc (has a collection) then put a .add function that will throw it into the collection and call the onAdding and onAdd events to handle prep and cleanup
if model.collection?
newobj['add'] = () =>
newobj.onAdding?(newobj)
model.collection.insert(unwrap_adder(newobj),
(error, id) ->
if error
console.log(error)
newobj._id(id))
newobj.onAdd?(newobj)
newobj
return newobj
@empty_observable_item = (it) ->
for f in it
if f.name is 'observable'
if f()? and f() isnt ''
return false
return true
class LypseForm
constructor: () ->
make this an Adder for the source object
adder(@constructor.source,@)
set defaults
if @defaults
for field,func of @defaults
console.log 'setting default field '+field+' to '+func(@)
@[field](func(@))
call the init
@init?()
onAdd: (obj) ->
usually we want to clear all fields
for f of @
if ko.isObservable(f) and f() instanceof Array
f.removeAll()
else if ko.isObservable(f)
f(null)
onAdding: (obj) ->
remove empty subfields
for key,f of @
if ko.isObservable(f) and f() instanceof Array
for item in f()
if empty_observable_item(item)
item.remove()
load: ->
set the defaults again (in case they changed)
if @defaults
for field,func of @defaults
@[field](func(@))
@init?()
root = exports ? this
root.ly.adder = adder
root.LypseForm = LypseForm


WITNESS LIST
Public Education Committee
October 16, 2014 - 10:00 AM
Interim Charge 3 - School Governance
On:
Beaulieu, Faye (Self; Tasb)
Byer, Von (Texas Education Agency)
Dc. Von heinkel, Ahren (Self)
Ford, Stacy (Self; CHRPA-Coalition of Human Rights Policy Advocates)
Linn, Julie (Texans for Education Reform)
Madrazo, Judith (Self)
Margo, Dee (Self; EPISD BoM)
Mcshan, George (Self; Texas assoc of school boards)
Melina Raab, Ted (Texas American Federation of Teachers)
Mincberg, Cathy (Crss)
Morath, Mike (Self)
Rowell, Ronald (Texas Education Agency)
Swanson, Steve (Self)
Wildon, Columba (Self)
Registering, but not testifying:
On:
Exter, Monty (The Association of Texas Professional Educators)
Sconzo, Guy (Self; Humble ISD)
Tryon, Philip (Save Texas Schools)
Interim Charge 6 - HCDE
On:
Chesnut, Angie (Self; Harris county department of education)
Langlois, Sarah (Harris County Department of Education)
Mason, Ruth (Self)
Sconzo, Guy (Self; Humble ISD)
Sorrells, Rick (Dallas county schools)
Vera, Colleen (Self)
Registering, but not testifying:
On:
Amezcua, Jesus (Self; Harris County Dept. of Education)
1


Chart series default color palette is made up of 10 unique colors. If your chart happens to contain more than 10 series, the color series will loop (e.g. the 1st and 11th series will be the same color).


|
ARDP
2.2.1
Another RDF Document Parser
|
Memory container for generic data storage of sequential data. More...
#include <sequence.h>
Data Fields | |
| size_t | size |
| size_t | capacity |
| size_t | head |
| void ** | items |
| void * | context |
| void(* | print )(void *data) |
| void(* | error )(void *data) |
| void(* | free )(void *data) |
Memory container for generic data storage of sequential data.
* Sequence: * 0 <-- N consecutive items --> C - 1 * ----------------------------------------------------------- * | | | data1 | ..... data N | ... | | * ----------------------------------------------------------- * ------ O -----> offset of first data item * * head = 0 * size = N * cap. = C *
Definition at line 43 of file sequence.h.
| size_t capacity |
Actual length of the pre-allocated array of items.
Definition at line 52 of file sequence.h.
Referenced by sequence_ensure(), sequence_push(), sequence_set_at(), and sequence_shift().
| void* context |
Definition at line 67 of file sequence.h.
| void(* error) (void *data) |
Definition at line 77 of file sequence.h.
Referenced by sequence_create().
| free |
Handler to free item.
| [in] | data | Data to be freed. |
Definition at line 87 of file sequence.h.
Referenced by sequence_create(), sequence_free(), sequence_push(), sequence_set_at(), and sequence_shift().
| size_t head |
Offset of the first item of the data in sequence.
Definition at line 57 of file sequence.h.
Referenced by sequence_delete_at(), sequence_ensure(), sequence_get_at(), sequence_pop(), sequence_push(), sequence_set_at(), sequence_shift(), and sequence_unshift().
| void** items |
Array of size 'capacity' pointing to the data.
Definition at line 62 of file sequence.h.
Referenced by sequence_delete_at(), sequence_ensure(), sequence_free(), sequence_get_at(), sequence_pop(), sequence_push(), sequence_set_at(), sequence_shift(), and sequence_unshift().
Print item in debug
Definition at line 75 of file sequence.h.
Referenced by sequence_create().
| size_t size |
Current number of the items in the sequence.
Definition at line 47 of file sequence.h.
Referenced by sequence_delete_at(), sequence_ensure(), sequence_get_at(), sequence_pop(), sequence_push(), sequence_set_at(), sequence_shift(), sequence_size(), and sequence_unshift().


| Instance ID | Node Name | Pod Name | Can Decement | Properties | |
|---|---|---|---|---|---|
| i-9fa4d3fb000000016 | ip-10-139-70-16.eu-west-1.compute.internal | backend-c8823ddff2-8fc6f | DeploymentOK | Node Wants Shutdown Pod Needs Eviction | |
| i-9a9e4f14000000017 | ip-10-87-167-17.eu-west-1.compute.internal | backend-c8823ddff2-19ea3 | DeploymentOK | Node Wants Shutdown Pod Needs Eviction | |
| i-36d9ff45000000003 | ip-10-119-176-3.eu-west-1.compute.internal | database-0 | StatefulSetOK | ||
| i-10cd9672000000002 | ip-10-55-122-2.eu-west-1.compute.internal | database-1 | StatefulSetOK | ||
| i-9acb0442000000001 | ip-10-9-244-1.eu-west-1.compute.internal | database-2 | StatefulSetOK | ||
| i-9acb0442000000001 | ip-10-9-244-1.eu-west-1.compute.internal | frontend-e9bcd83c18-f1062 | DeploymentUnready | ||
| i-36d9ff45000000003 | ip-10-119-176-3.eu-west-1.compute.internal | frontend-e9bcd83c18-0d857 | DeploymentUnready | ||
| i-10cd9672000000002 | ip-10-55-122-2.eu-west-1.compute.internal | frontend-e9bcd83c18-24e5e | DeploymentUnready | ||
| i-9b74f61f000000006 | ip-10-93-23-6.eu-west-1.compute.internal | backend-c8823ddff2-fc633 | DeploymentOK | ||
| i-9acb0442000000001 | ip-10-9-244-1.eu-west-1.compute.internal | backend-c8823ddff2-8e9dc | DeploymentOK | ||
| i-36d9ff45000000003 | ip-10-119-176-3.eu-west-1.compute.internal | backend-c8823ddff2-83111 | DeploymentOK | ||
| i-10cd9672000000002 | ip-10-55-122-2.eu-west-1.compute.internal | backend-c8823ddff2-672ee | DeploymentOK | ||
| i-9acb0442000000001 | ip-10-9-244-1.eu-west-1.compute.internal | backend-c8823ddff2-be00d | DeploymentOK | ||
| i-c0a8a05f000000005 | ip-10-161-105-5.eu-west-1.compute.internal | backend-c8823ddff2-ddef3 | DeploymentOK | ||
| i-8f3457f2000000018 | ip-10-162-243-18.eu-west-1.compute.internal | backend-c8823ddff2-e8462 | DeploymentOK | ||
| i-37f317c5000000004 | ip-10-100-133-4.eu-west-1.compute.internal | backend-c8823ddff2-c3e80 | DeploymentOK | ||
| i-10cd9672000000002 | ip-10-55-122-2.eu-west-1.compute.internal | kube-proxy-ip-10-55-122-2.eu-west-1.compute.internal | IsNodePod | Pod Immune To Eviction | |
| i-9acb0442000000001 | ip-10-9-244-1.eu-west-1.compute.internal | kube-proxy-ip-10-9-244-1.eu-west-1.compute.internal | IsNodePod | Pod Immune To Eviction | |
| i-37f317c5000000004 | ip-10-100-133-4.eu-west-1.compute.internal | kube-proxy-ip-10-100-133-4.eu-west-1.compute.internal | IsNodePod | Pod Immune To Eviction | |
| i-9fa4d3fb000000016 | ip-10-139-70-16.eu-west-1.compute.internal | kube-proxy-ip-10-139-70-16.eu-west-1.compute.internal | IsNodePod | Node Wants Shutdown Pod Immune To Eviction | |
| i-c0a8a05f000000005 | ip-10-161-105-5.eu-west-1.compute.internal | kube-proxy-ip-10-161-105-5.eu-west-1.compute.internal | IsNodePod | Pod Immune To Eviction | |
| i-36d9ff45000000003 | ip-10-119-176-3.eu-west-1.compute.internal | kube-proxy-ip-10-119-176-3.eu-west-1.compute.internal | IsNodePod | Pod Immune To Eviction | |
| i-9b74f61f000000006 | ip-10-93-23-6.eu-west-1.compute.internal | kube-proxy-ip-10-93-23-6.eu-west-1.compute.internal | IsNodePod | Pod Immune To Eviction | |
| i-8f3457f2000000018 | ip-10-162-243-18.eu-west-1.compute.internal | kube-proxy-ip-10-162-243-18.eu-west-1.compute.internal | IsNodePod | Pod Immune To Eviction | |
| i-9a9e4f14000000017 | ip-10-87-167-17.eu-west-1.compute.internal | kube-proxy-ip-10-87-167-17.eu-west-1.compute.internal | IsNodePod | Node Wants Shutdown Pod Immune To Eviction | |
| i-9a9e4f14000000017 | ip-10-87-167-17.eu-west-1.compute.internal | dns-af451 | IsDaemonSetPod | Node Wants Shutdown Pod Immune To Eviction | |
| i-c0a8a05f000000005 | ip-10-161-105-5.eu-west-1.compute.internal | dns-a83b4 | IsDaemonSetPod | Pod Immune To Eviction | |
| i-36d9ff45000000003 | ip-10-119-176-3.eu-west-1.compute.internal | dns-167ad | IsDaemonSetPod | Pod Immune To Eviction | |
| i-9fa4d3fb000000016 | ip-10-139-70-16.eu-west-1.compute.internal | dns-2a262 | IsDaemonSetPod | Node Wants Shutdown Pod Immune To Eviction | |
| i-9acb0442000000001 | ip-10-9-244-1.eu-west-1.compute.internal | dns-7d7d3 | IsDaemonSetPod | Pod Immune To Eviction | |
| i-9b74f61f000000006 | ip-10-93-23-6.eu-west-1.compute.internal | dns-3f1da | IsDaemonSetPod | Pod Immune To Eviction | |
| i-10cd9672000000002 | ip-10-55-122-2.eu-west-1.compute.internal | dns-09ada | IsDaemonSetPod | Pod Immune To Eviction | |
| i-8f3457f2000000018 | ip-10-162-243-18.eu-west-1.compute.internal | dns-f7245 | IsDaemonSetPod | Pod Immune To Eviction | |
| i-37f317c5000000004 | ip-10-100-133-4.eu-west-1.compute.internal | dns-b5122 | IsDaemonSetPod | Pod Immune To Eviction |
| Instance ID | Host Name | Instance Name | State | Launch Time | Triggered At | Termination Time | Pods | Properties |
|---|---|---|---|---|---|---|---|---|
| i-9fa4d3fb000000016 | ip-10-139-70-16.eu-west-1.compute.internal | stateless | Running | Sat, 11 Jul 05:19:20 | Sat, 11 Jul 05:49:20 | N/A | 3 ⇨ 2 1 0 | Stateless WantsShutdown |
| i-9a9e4f14000000017 | ip-10-87-167-17.eu-west-1.compute.internal | stateless | Running | Fri, 10 Jul 07:45:04 | Fri, 10 Jul 08:15:04 | N/A | 3 ⇨ 2 1 0 | Stateless WantsShutdown |
| i-b0dad04c000000012 | ip-10-74-206-12.eu-west-1.compute.internal | stateless | Terminated | Wed, 8 Jul 23:25:32 | Wed, 8 Jul 23:55:32 | Thu, 9 Jul 00:25:32 | 0 | |
| i-bde9d03d000000010 | ip-10-75-88-10.eu-west-1.compute.internal | stateless | Terminated | Mon, 6 Jul 22:14:33 | Mon, 6 Jul 22:44:33 | Mon, 6 Jul 23:14:33 | 0 | |
| i-fa9b1d3f000000011 | ip-10-97-11-11.eu-west-1.compute.internal | stateless | Terminated | Mon, 6 Jul 21:38:12 | Mon, 6 Jul 22:08:12 | Mon, 6 Jul 22:38:12 | 0 | |
| i-2c5b2d1a000000007 | ip-10-186-54-7.eu-west-1.compute.internal | stateless | Terminated | Sun, 12 Jul 08:51:07 | N/A | Sun, 12 Jul 09:51:07 | 0 | |
| i-fa173951000000009 | ip-10-245-166-9.eu-west-1.compute.internal | stateless | Terminated | Sat, 11 Jul 06:23:37 | N/A | Sat, 11 Jul 07:23:37 | 0 | |
| i-483675c8000000008 | ip-10-174-246-8.eu-west-1.compute.internal | stateless | Terminated | Tue, 7 Jul 17:10:54 | N/A | Tue, 7 Jul 18:10:54 | 0 | |
| i-ab694965000000014 | ip-10-167-227-14.eu-west-1.compute.internal | stateless | Shutting Down | Sun, 12 Jul 04:37:13 | N/A | Sun, 12 Jul 05:37:13 | 0 | |
| i-21725a02000000013 | ip-10-207-22-13.eu-west-1.compute.internal | stateless | Shutting Down | Wed, 8 Jul 13:27:39 | N/A | Wed, 8 Jul 14:27:39 | 0 | |
| i-10cd9672000000002 | ip-10-55-122-2.eu-west-1.compute.internal | stateful | Running | Mon, 13 Jul 02:09:00 | N/A | N/A | 5 ⇨ 2 3 0 | |
| i-36d9ff45000000003 | ip-10-119-176-3.eu-west-1.compute.internal | stateless | Running | Sun, 12 Jul 07:41:29 | N/A | N/A | 5 ⇨ 2 3 0 | Stateless Unschedulable |
| i-c0a8a05f000000005 | ip-10-161-105-5.eu-west-1.compute.internal | stateless | Running | Sat, 11 Jul 18:39:31 | N/A | N/A | 3 ⇨ 2 1 0 | Stateless |
| i-37f317c5000000004 | ip-10-100-133-4.eu-west-1.compute.internal | stateless | Running | Sat, 11 Jul 00:03:17 | N/A | N/A | 3 ⇨ 2 1 0 | Stateless Unschedulable |
| i-8f3457f2000000018 | ip-10-162-243-18.eu-west-1.compute.internal | stateless | Running | Fri, 10 Jul 23:29:52 | N/A | N/A | 3 ⇨ 2 1 0 | Stateless SoftShutdown |
| i-9acb0442000000001 | ip-10-9-244-1.eu-west-1.compute.internal | stateful | Running | Thu, 9 Jul 13:40:58 | N/A | N/A | 6 ⇨ 2 4 0 | |
| i-9b74f61f000000006 | ip-10-93-23-6.eu-west-1.compute.internal | stateless | Running | Mon, 6 Jul 18:36:54 | N/A | N/A | 3 ⇨ 2 1 0 | Stateless |
| i-a0cb0ab0000000015 | ip-10-186-171-15.eu-west-1.compute.internal | stateless | Pending | Sun, 12 Jul 22:32:17 | N/A | N/A | 0 |
| Instance ID | Request ID | Create Time | State | Status Code | Status Update Time |
|---|---|---|---|---|---|
| i-36d9ff45000000003 | sir-add87e4a | Sun, 12 Jul 07:41:29 | Active | fulfilled |
Sun, 12 Jul 07:41:29 |
| i-37f317c5000000004 | sir-4c0d9a56 | Sat, 11 Jul 00:03:17 | Active | fulfilled |
Sat, 11 Jul 00:03:17 |
| i-c0a8a05f000000005 | sir-288833b6 | Sat, 11 Jul 18:39:31 | Active | fulfilled |
Sat, 11 Jul 18:39:31 |
| i-9b74f61f000000006 | sir-4d309725 | Mon, 6 Jul 18:36:54 | Active | fulfilled |
Mon, 6 Jul 18:36:54 |
| i-2c5b2d1a000000007 | sir-40e807bd | Sun, 12 Jul 08:51:07 | Closed | instance-terminated-by-user |
Sun, 12 Jul 08:51:07 |
| i-483675c8000000008 | sir-18f2c92e | Tue, 7 Jul 17:10:54 | Closed | instance-terminated-by-user |
Tue, 7 Jul 17:10:54 |
| i-fa173951000000009 | sir-eecf0606 | Sat, 11 Jul 06:23:37 | Closed | instance-terminated-by-user |
Sat, 11 Jul 06:23:37 |
| i-bde9d03d000000010 | sir-aec26105 | Mon, 6 Jul 22:14:33 | Closed | instance-terminated-by-user |
Mon, 6 Jul 22:14:33 |
| i-fa9b1d3f000000011 | sir-591382ce | Mon, 6 Jul 21:38:12 | Closed | instance-terminated-by-user |
Mon, 6 Jul 21:38:12 |
| i-b0dad04c000000012 | sir-675fa6f2 | Wed, 8 Jul 23:25:32 | Closed | instance-terminated-by-user |
Wed, 8 Jul 23:25:32 |
| i-21725a02000000013 | sir-15e4ac07 | Wed, 8 Jul 13:27:39 | Active | fulfilled |
Wed, 8 Jul 13:27:39 |
| i-ab694965000000014 | sir-3d24aa0f | Sun, 12 Jul 04:37:13 | Active | fulfilled |
Sun, 12 Jul 04:37:13 |
| i-a0cb0ab0000000015 | sir-8cd66db7 | Sun, 12 Jul 22:32:17 | Active | fulfilled |
Sun, 12 Jul 22:32:17 |
| i-9fa4d3fb000000016 | sir-7f7448e0 | Sat, 11 Jul 05:19:20 | Active | fulfilled |
Sat, 11 Jul 05:19:20 |
| i-9a9e4f14000000017 | sir-96ff5f86 | Fri, 10 Jul 07:45:04 | Active | fulfilled |
Fri, 10 Jul 07:45:04 |
| i-8f3457f2000000018 | sir-d8887f5f | Fri, 10 Jul 23:29:52 | Active | fulfilled |
Fri, 10 Jul 23:29:52 |
| Instance ID | Triggered | Completed | Deleted |
|---|---|---|---|
| i-bde9d03d000000010 | Mon, 6 Jul 22:44:33 | yes | yes |
| i-fa9b1d3f000000011 | Mon, 6 Jul 22:08:12 | yes | no |
| i-b0dad04c000000012 | Wed, 8 Jul 23:55:32 | no | yes |
| i-9fa4d3fb000000016 | Sat, 11 Jul 05:49:20 | no | no |
| i-9a9e4f14000000017 | Fri, 10 Jul 08:15:04 | no | no |
| Instance ID | Node Name | Schedulable | Taints |
|---|---|---|---|
| i-9acb0442000000001 | ip-10-9-244-1.eu-west-1.compute.internal | Schedulable | |
| i-10cd9672000000002 | ip-10-55-122-2.eu-west-1.compute.internal | Schedulable | |
| i-36d9ff45000000003 | ip-10-119-176-3.eu-west-1.compute.internal | Unschedulable | Stateless Unschedulable |
| i-37f317c5000000004 | ip-10-100-133-4.eu-west-1.compute.internal | Unschedulable | Stateless Unschedulable |
| i-c0a8a05f000000005 | ip-10-161-105-5.eu-west-1.compute.internal | Schedulable | Stateless |
| i-9b74f61f000000006 | ip-10-93-23-6.eu-west-1.compute.internal | Schedulable | Stateless |
| i-9fa4d3fb000000016 | ip-10-139-70-16.eu-west-1.compute.internal | Schedulable | Stateless |
| i-9a9e4f14000000017 | ip-10-87-167-17.eu-west-1.compute.internal | Schedulable | Stateless |
| i-8f3457f2000000018 | ip-10-162-243-18.eu-west-1.compute.internal | Schedulable | Stateless SoftShutdown |
| Instance ID | Node Name | Instance Name | Type | AZ | Lifecycle | State | Launch Time | Termination Time |
|---|---|---|---|---|---|---|---|---|
| i-9acb0442000000001 | ip-10-9-244-1.eu-west-1.compute.internal | stateful | m4.2xlarge | eu-west-1c | Running | Thu, 9 Jul 13:40:58 | N/A | |
| i-10cd9672000000002 | ip-10-55-122-2.eu-west-1.compute.internal | stateful | m5.2xlarge | eu-west-1a | Running | Mon, 13 Jul 02:09:00 | N/A | |
| i-36d9ff45000000003 | ip-10-119-176-3.eu-west-1.compute.internal | stateless | m5.2xlarge | eu-west-1c | spot | Running | Sun, 12 Jul 07:41:29 | N/A |
| i-37f317c5000000004 | ip-10-100-133-4.eu-west-1.compute.internal | stateless | m4.2xlarge | eu-west-1b | spot | Running | Sat, 11 Jul 00:03:17 | N/A |
| i-c0a8a05f000000005 | ip-10-161-105-5.eu-west-1.compute.internal | stateless | m5.2xlarge | eu-west-1a | spot | Running | Sat, 11 Jul 18:39:31 | N/A |
| i-9b74f61f000000006 | ip-10-93-23-6.eu-west-1.compute.internal | stateless | m4.2xlarge | eu-west-1c | spot | Running | Mon, 6 Jul 18:36:54 | N/A |
| i-2c5b2d1a000000007 | ip-10-186-54-7.eu-west-1.compute.internal | stateless | m5.2xlarge | eu-west-1a | spot | Terminated | Sun, 12 Jul 08:51:07 | Sun, 12 Jul 09:51:07 |
| i-483675c8000000008 | ip-10-174-246-8.eu-west-1.compute.internal | stateless | m5.2xlarge | eu-west-1a | spot | Terminated | Tue, 7 Jul 17:10:54 | Tue, 7 Jul 18:10:54 |
| i-fa173951000000009 | ip-10-245-166-9.eu-west-1.compute.internal | stateless | m4.2xlarge | eu-west-1a | spot | Terminated | Sat, 11 Jul 06:23:37 | Sat, 11 Jul 07:23:37 |
| i-bde9d03d000000010 | ip-10-75-88-10.eu-west-1.compute.internal | stateless | m5.2xlarge | eu-west-1b | spot | Terminated | Mon, 6 Jul 22:14:33 | Mon, 6 Jul 23:14:33 |
| i-fa9b1d3f000000011 | ip-10-97-11-11.eu-west-1.compute.internal | stateless | m4.2xlarge | eu-west-1a | spot | Terminated | Mon, 6 Jul 21:38:12 | Mon, 6 Jul 22:38:12 |
| i-b0dad04c000000012 | ip-10-74-206-12.eu-west-1.compute.internal | stateless | m4.2xlarge | eu-west-1b | spot | Terminated | Wed, 8 Jul 23:25:32 | Thu, 9 Jul 00:25:32 |
| i-21725a02000000013 | ip-10-207-22-13.eu-west-1.compute.internal | stateless | m5.2xlarge | eu-west-1b | spot | Shutting Down | Wed, 8 Jul 13:27:39 | Wed, 8 Jul 14:27:39 |
| i-ab694965000000014 | ip-10-167-227-14.eu-west-1.compute.internal | stateless | m4.2xlarge | eu-west-1a | spot | Shutting Down | Sun, 12 Jul 04:37:13 | Sun, 12 Jul 05:37:13 |
| i-a0cb0ab0000000015 | ip-10-186-171-15.eu-west-1.compute.internal | stateless | m5.2xlarge | eu-west-1b | spot | Pending | Sun, 12 Jul 22:32:17 | N/A |
| i-9fa4d3fb000000016 | ip-10-139-70-16.eu-west-1.compute.internal | stateless | m4.2xlarge | eu-west-1b | spot | Running | Sat, 11 Jul 05:19:20 | N/A |
| i-9a9e4f14000000017 | ip-10-87-167-17.eu-west-1.compute.internal | stateless | m5.2xlarge | eu-west-1b | spot | Running | Fri, 10 Jul 07:45:04 | N/A |
| i-8f3457f2000000018 | ip-10-162-243-18.eu-west-1.compute.internal | stateless | m4.2xlarge | eu-west-1c | spot | Running | Fri, 10 Jul 23:29:52 | N/A |
| Node Name | Pod Name | Namespace | Created Time | Can Decement | Owner |
|---|---|---|---|---|---|
| ip-10-55-122-2.eu-west-1.compute.internal | kube-proxy-ip-10-55-122-2.eu-west-1.compute.internal | kube-system | Fri, 10 Jul 07:31:54 | IsNodePod | Node kube-proxy |
| ip-10-9-244-1.eu-west-1.compute.internal | kube-proxy-ip-10-9-244-1.eu-west-1.compute.internal | kube-system | Sun, 12 Jul 19:30:38 | IsNodePod | Node kube-proxy |
| ip-10-100-133-4.eu-west-1.compute.internal | kube-proxy-ip-10-100-133-4.eu-west-1.compute.internal | kube-system | Fri, 10 Jul 12:43:16 | IsNodePod | Node kube-proxy |
| ip-10-139-70-16.eu-west-1.compute.internal | kube-proxy-ip-10-139-70-16.eu-west-1.compute.internal | kube-system | Tue, 7 Jul 03:26:16 | IsNodePod | Node kube-proxy |
| ip-10-161-105-5.eu-west-1.compute.internal | kube-proxy-ip-10-161-105-5.eu-west-1.compute.internal | kube-system | Thu, 9 Jul 23:11:49 | IsNodePod | Node kube-proxy |
| ip-10-119-176-3.eu-west-1.compute.internal | kube-proxy-ip-10-119-176-3.eu-west-1.compute.internal | kube-system | Mon, 13 Jul 04:29:06 | IsNodePod | Node kube-proxy |
| ip-10-93-23-6.eu-west-1.compute.internal | kube-proxy-ip-10-93-23-6.eu-west-1.compute.internal | kube-system | Thu, 9 Jul 00:19:48 | IsNodePod | Node kube-proxy |
| ip-10-162-243-18.eu-west-1.compute.internal | kube-proxy-ip-10-162-243-18.eu-west-1.compute.internal | kube-system | Fri, 10 Jul 12:10:35 | IsNodePod | Node kube-proxy |
| ip-10-87-167-17.eu-west-1.compute.internal | kube-proxy-ip-10-87-167-17.eu-west-1.compute.internal | kube-system | Wed, 8 Jul 23:52:44 | IsNodePod | Node kube-proxy |
| ip-10-87-167-17.eu-west-1.compute.internal | dns-af451 | kube-system | Sun, 12 Jul 19:51:09 | IsDaemonSetPod | DaemonSet dns |
| ip-10-161-105-5.eu-west-1.compute.internal | dns-a83b4 | kube-system | Fri, 10 Jul 14:58:27 | IsDaemonSetPod | DaemonSet dns |
| ip-10-119-176-3.eu-west-1.compute.internal | dns-167ad | kube-system | Sat, 11 Jul 07:02:00 | IsDaemonSetPod | DaemonSet dns |
| ip-10-139-70-16.eu-west-1.compute.internal | dns-2a262 | kube-system | Fri, 10 Jul 06:14:16 | IsDaemonSetPod | DaemonSet dns |
| ip-10-9-244-1.eu-west-1.compute.internal | dns-7d7d3 | kube-system | Sat, 11 Jul 06:06:42 | IsDaemonSetPod | DaemonSet dns |
| ip-10-93-23-6.eu-west-1.compute.internal | dns-3f1da | kube-system | Thu, 9 Jul 22:10:48 | IsDaemonSetPod | DaemonSet dns |
| ip-10-55-122-2.eu-west-1.compute.internal | dns-09ada | kube-system | Wed, 8 Jul 20:33:06 | IsDaemonSetPod | DaemonSet dns |
| ip-10-162-243-18.eu-west-1.compute.internal | dns-f7245 | kube-system | Thu, 9 Jul 18:12:37 | IsDaemonSetPod | DaemonSet dns |
| ip-10-100-133-4.eu-west-1.compute.internal | dns-b5122 | kube-system | Fri, 10 Jul 22:57:57 | IsDaemonSetPod | DaemonSet dns |
| ip-10-119-176-3.eu-west-1.compute.internal | database-0 | default | Fri, 10 Jul 11:37:44 | StatefulSetOK | StatefulSet database |
| ip-10-55-122-2.eu-west-1.compute.internal | database-1 | default | Sat, 11 Jul 16:54:14 | StatefulSetOK | StatefulSet database |
| ip-10-9-244-1.eu-west-1.compute.internal | database-2 | default | Wed, 8 Jul 14:59:30 | StatefulSetOK | StatefulSet database |
| ip-10-9-244-1.eu-west-1.compute.internal | frontend-e9bcd83c18-f1062 | default | Tue, 7 Jul 19:42:21 | DeploymentUnready | Deployment frontend |
| ip-10-119-176-3.eu-west-1.compute.internal | frontend-e9bcd83c18-0d857 | default | Mon, 6 Jul 22:29:41 | DeploymentUnready | Deployment frontend |
| ip-10-55-122-2.eu-west-1.compute.internal | frontend-e9bcd83c18-24e5e | default | Tue, 7 Jul 16:08:00 | DeploymentUnready | Deployment frontend |
| ip-10-93-23-6.eu-west-1.compute.internal | backend-c8823ddff2-fc633 | default | Tue, 7 Jul 01:20:52 | DeploymentOK | Deployment backend |
| ip-10-9-244-1.eu-west-1.compute.internal | backend-c8823ddff2-8e9dc | default | Tue, 7 Jul 20:55:24 | DeploymentOK | Deployment backend |
| ip-10-139-70-16.eu-west-1.compute.internal | backend-c8823ddff2-8fc6f | default | Thu, 9 Jul 09:38:15 | DeploymentOK | Deployment backend |
| ip-10-119-176-3.eu-west-1.compute.internal | backend-c8823ddff2-83111 | default | Fri, 10 Jul 10:49:41 | DeploymentOK | Deployment backend |
| ip-10-87-167-17.eu-west-1.compute.internal | backend-c8823ddff2-19ea3 | default | Fri, 10 Jul 03:24:24 | DeploymentOK | Deployment backend |
| ip-10-55-122-2.eu-west-1.compute.internal | backend-c8823ddff2-672ee | default | Wed, 8 Jul 13:35:24 | DeploymentOK | Deployment backend |
| ip-10-9-244-1.eu-west-1.compute.internal | backend-c8823ddff2-be00d | default | Thu, 9 Jul 05:32:42 | DeploymentOK | Deployment backend |
| ip-10-161-105-5.eu-west-1.compute.internal | backend-c8823ddff2-ddef3 | default | Sat, 11 Jul 23:08:36 | DeploymentOK | Deployment backend |
| ip-10-162-243-18.eu-west-1.compute.internal | backend-c8823ddff2-e8462 | default | Sat, 11 Jul 18:24:13 | DeploymentOK | Deployment backend |
| ip-10-100-133-4.eu-west-1.compute.internal | backend-c8823ddff2-c3e80 | default | Mon, 13 Jul 03:32:35 | DeploymentOK | Deployment backend |


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Welcome, friend!
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Thank you for making an account on Glossier.com, where you can sign in and access your order history, update your info, and edit your settings in the Account Section of our site.
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Remember that your username is your email address — easy.
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And if you ever have a question, concern, or want to share your thoughts, email us at<EMAIL_ADDRESS>|
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Glossier
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{% extends 'booking/_skeleton.html' %} {% set step = 3 %} {% block book_content %}
Please enter your Imperial College login details to fulfil this order.
Your login is safe, and we will not store your details


org.springframework.shell.commands
Interfaces
OsOperations
Classes
ConsoleCommands
DateCommands
ExitCommands
HelpCommands
InlineCommentCommands
OsCommands
OsOperationsImpl
ScriptCommands
SystemPropertyCommands
VersionCommands


QLC+ supports the ArtNet protocol through an input/output plugin
that receives and transmits packets on the network.
No extra requirements are needed, since QLC+ has a native implementation of the ArtNet protocol
that works on Linux, Windows and OSX systems.
The ArtNet plugin can send and receive packets from multiple network cards, virtual addresses
and multiple universes per network card.
When transmitting multiple universe on the same interface, the packets will be marked with
the destination universe selected from QLC+.
The ArtNet plugin doesn't really have a configuration panel. When clicking on the configuration button, a panel will be shown, displaying the ArtNet node discovered on the network, grouped by interface.
QLC+ has been tested with the following ArtNet softwares/devices:


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The following code shows a method of reading a class of sonar
rangers. These rangers requires a trigger pulse.
Shortly after receiving a trigger they transmit a noise pulse and
set the echo line high. When the echo is received the echo
line is set low.
#include <stdio.h>
#include <pigpio.h>
/*
P1 Name gpio used for
2 5V ---
5V
6 GND ---
Ground
24 CE0 8
Sonar echo
26 CE1 7
Sonar trigger
*/
#define SONAR_TRIGGER 7
#define SONAR_ECHO 8
/* forward prototypes */
void sonarTrigger(void);
void sonarEcho(int gpio, int level, uint32_t tick);
int main(int argc, char *argv[])
{
if (gpioInitialise()<0) return 1;
gpioSetMode(SONAR_TRIGGER, PI_OUTPUT);
gpioWrite (SONAR_TRIGGER, PI_OFF);
gpioSetMode(SONAR_ECHO,
PI_INPUT);
/* update sonar 20 times a second, timer #0 */
gpioSetTimerFunc(0, 50, sonarTrigger); /* every 50ms
*/
/* monitor sonar echos */
gpioSetAlertFunc(SONAR_ECHO, sonarEcho);
while (1) sleep(1);
gpioTerminate();
return 0;
}
void sonarTrigger(void)
{
/* trigger a sonar reading */
gpioWrite(SONAR_TRIGGER, PI_ON);
gpioDelay(10); /* 10us trigger pulse */
gpioWrite(SONAR_TRIGGER, PI_OFF);
}
void sonarEcho(int gpio, int level, uint32_t tick)
{
static uint32_t startTick, firstTick=0;
int diffTick;
if (!firstTick) firstTick = tick;
if (level == PI_ON)
{
startTick = tick;
}
else if (level == PI_OFF)
{
diffTick = tick - startTick;
printf("%u %u\ ", tick-firstTick,
diffTick);
}
}
cc -o sonar sonar.c -lpigpio -lrt -lpthread
sudo ./sonar >sonar.dat &
pigs no
pig2vcd </dev/pigpio0 >sonar.vcd &
pigs nb 0 0x180 # set bits for gpios 7 and 8
Move an object in front of the sonar ranger for a few
seconds.
pigs nc 0
The file sonar.vcd will contain the captured waveform, which can be viewed using GTKWave.
Overview
Reading circa every 10ms
One reading, circa 400us
another
The file sonar.dat will contain pairs of timestamps and echo
length (in us). The following script will convert the
timestamps into seconds.
awk '{print $1/1000000, $2}' sonar.dat
>sonar-secs.dat
Gnuplot is a useful tool to graph data.
plot [10:25] 'sonar-secs.dat' title 'Sonar'


Prints the value of the requested option, or aborts if the value is not set.
This command does not print the values of credentials for security reasons.
Please open the credentials
file in your global configuration directory to see your stored credentials.


The 1001 time series from the M-competition (Makridakis et al. 1982) <doi:10.1002/for.3980010202> and the 3003 time series from the IJF-M3 competition (Makridakis and Hibon, 2000) <doi:10.1016/S0169-2070(00)00057-1>.
| Version: | 2.8 |
| Depends: | R (≥ 2.10), forecast (≥ 8.0) |
| Imports: | ggplot2 |
| Published: | 2018-06-19 |
| Author: | Rob Hyndman [aut, cre, cph], Muhammad Akram [ctb], Christoph Bergmeir [ctb], Mitchell O'Hara-Wild [ctb] |
| Maintainer: | Rob Hyndman <Rob.Hyndman at monash.edu> |
| BugReports: | https://github.com/robjhyndman/Mcomp/issues |
| License: | GPL-3 |
| URL: | http://pkg.robjhyndman.com/Mcomp/, https://github.com/robjhyndman/Mcomp |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| In views: | Econometrics, TimeSeries |
| CRAN checks: | Mcomp results |
| Reference manual: | Mcomp.pdf |
| Package source: | Mcomp_2.8.tar.gz |
| Windows binaries: | r-devel: Mcomp_2.8.zip, r-release: Mcomp_2.8.zip, r-oldrel: Mcomp_2.8.zip |
| OS X binaries: | r-release: Mcomp_2.8.tgz, r-oldrel: Mcomp_2.8.tgz |
| Old sources: | Mcomp archive |
| Reverse imports: | Tcomp |
| Reverse suggests: | fpp2, smooth |
Please use the canonical form https://CRAN.R-project.org/package=Mcomp to link to this page.


Cybersecurity and Infrastructure Security Agency (CISA)
Additional Tools and Techniques - Formatting Broken
Methodology
- Assign Roles
- Internal Roles
- External Roles
- Reporting Needs
Stay in Scope
Follow the RunBook
External Pentest
- Phishing
- Recon
- Web Application Testing (Refer to the Web Application Testing Section in the RUNBOOK)
- Vulnerability Scanning
- Directory Discovery - Dirbuster /usr/share/wordlists/dirbuster/directory/directory-list-2.3-medium.txt (I think that is it?)
- Exploitation - Look for webshells in the /usr/share/webshells
- Penetration Testing (Refer to the Penetration Testing Section in the RUNBOOK)
Keep an Eye out for SMB and FTP services
Internal Pentest
- High Value Assets
- Web Application Testing (Refer to the Web Application Testing Section in the RUNBOOK)
- Vulnerability Scanning
- Directory Discovery - Dirbuster /usr/share/wordlists/dirbuster/directory/directory-list-2.3-medium.txt (I think that is it?)
- Exploitation - Look for webshells in the /usr/share/webshells
- Penetration Testing (Refer to the Penetration Testing Section in the RUNBOOK)
- Run Responder ASAP and look to use the captured hashes with MultiRelay.
- MultiRelay from the Responder results.
- Data Exfiltration
Look for SAM dumps and SYSTEM dumps
A few Attack Paths
There is a bad ftp service like Konica Minolta running.
- Locate the correct metasploit module.
- Get the local.txt from the Desktop.
- There is a file that has plan text information that will help with the Pivot.
- Create a proxy from the Metrepreter session.
- use the credentials to get around and get the proof.txt.
Bad Blue Server that is running as a standard user. The service is exploitable by Metasploit.
- Locate the correct Module
- Use “getsystem” with the meterpreter session.. if this fails try to migrate the process
- Use the “hashdump” to dump the hashes.
- use a tool like pth-winexe to pass the hash.
Look for a JBoss Service running on the network.
- Locate the correct metasploit module.
- Run the JBoss Exploit. HINT you might have to change the Architecture of the exploit “show target”
- PWN
Post Assessment Notes
Overall the assessment went well. The external pentest was a nice learning curve for us. Having to deal with firewall and network address translation. We ran into issues dealing with suspected web application firewalls and default Metasploit ports being blocked. We really could have taken more of the low hangning fruit in some cases. However, overall the team really did a great job working together and trying to own systems. Below is a list of a few things that we need to work on.
- Tools that need to be studied more.
- Responder
- Nmap (Mapping a Network and Scripts)
- sqlmap
- Burp
- Operational
- Develop a more refined methodology including:
- Create a detailed game plan.
- Ensure team members have everything to succeed.
- Develop a more refined methodology including:


Great Forest [an26], forest, in Mandoria, peasants: 100
Last updated Turn #145
Great Forest [an26], forest, in Mandoria, peasants: 100
------------------------------------------------------------------------
7: General Kraken [k3k], Imperial Empire, duke, priest of the Church of
7: Halon [157], with 57 workers, two winged horses, 58 nazgul, arrived
7: from the south, accompanied by:
7: Veejay [v8j], Imperial Empire, Bishop of the Church of Ham [155],
7: with five angels
7: Goon III [b9v], Imperial Empire, priest of the Church of Dol [153],
7: with 54 hvy. xbowmen, 27 nazgul
7: Lord Rodrigo Bane [c8b], Imperial Empire, priest of the Church of
7: Dol [153], with ten workers, 50 hvy. xbowmen, 23 nazgul
7: Licia [i1l], Imperial Empire, Bishop of the Church of Ham [155],
7: with five angels, 50 hvy. xbowmen
7: Odin [y5z], Imperial Empire, with 23 peasants, three soldiers,
7: 44 hvy. xbowmen
7: Thorg [j8u], Imperial Empire, with one warmount
7: Jupiter [m8j], Imperial Empire, duke, the High Priest of the Church
7: of Halon [157], with 43 soldiers, ten angels, 46 hvy. xbowmen
7: Firefly [f3f], Imperial Empire, priest of the Church of
7: Halon [157], with 50 hvy. xbowmen
7: Sunwalker [a8x], Imperial Empire, duke, Bishop of the Church of
7: Halon [157], with five angels, 44 nazgul
7: Thomas [o5y], Imperial Empire, Bishop of the Church of Dol [153],
7: with five angels, 52 hvy. xbowmen, five nazgul
7: Sir Peter [u9p], Imperial Empire, with 30 peasants, 20 workers,
7: ten hvy. xbowmen
7: George [p7f], Imperial Empire, duke, priest of the Church of
7: Dol [153], with ten nazgul
7: Lucca [h0t], Imperial Empire, priest of the Church of Halon [157],
7: with one skirmisher, 44 nazgul
7: Johny [w2d], Imperial Empire, priest of the Church of Halon [157],
7: with 39 nazgul
7: Aurora [g5z], Imperial Empire
7: Stefano [t8e], Imperial Empire, Bishop of the Church of
7: Halon [157], with one peasant, five angels, 42 nazgul
7: Sir Charles [j5r], Imperial Empire, priest of the Church of
7: Halon [157], with 46 nazgul
7: Joe One [i7n], Imperial Empire, prisoner
7: Majikthise [n4g], Imperial Empire
7: Alexei Galantor [j7l], Imperial Empire, duke, priest of the Church
7: of Halon [157], with 78 nazgul
7: City boy [c5x], Imperial Empire
7: Sorak [y7s], Imperial Empire, prisoner
7: Phantom III [d6x], Imperial Empire, priest of the Church of
7: Dol [153], with 19 nazgul
7: Merchant [jc9q], Imperial Empire
7: Everblack [n3r], Imperial Empire
7: Dryeth [q4e], Imperial Empire, priest of the Church of Dol [153],
7: with 12 nazgul
7: Jimmy Leather [o3i], Imperial Empire, prisoner
7: Ahron [y4d], Mandor Confederacy, prisoner
7: Fridur [j2a], Mandor Confederacy, prisoner
7: Lfir [w6v], Mandor Confederacy, prisoner
7: Adrian Dhubghalen [g5h], Mandor Confederacy, prisoner
7: Malek [j4c], Mandor Confederacy, prisoner
7: Maruk II [t7m], Mandor Confederacy, prisoner
7: Ringli [d5m], Mandor Confederacy, sorcerer, prisoner
7: Feanor [i9z], Mandor Confederacy, prisoner
7: Paula Toler [o9u], Mandor Confederacy, prisoner
7: Gomdrag Caerric [g6k], Mandor Confederacy, prisoner
8: Paula Toler [o9u], Mandor Confederacy, went south.
8: General Kraken [k3k] attacks Mirco [h3z]!
8:
8: General Kraken [k3k], Imperial Empire, duke, priest of the Church
8: of Halon [157], with 57 workers, two winged horses, 58 nazgul,
8: accompanied by:
8: Veejay [v8j], Imperial Empire, Bishop of the Church of
8: Ham [155], behind 5, with five angels
8: Goon III [b9v], Imperial Empire, priest of the Church of
8: Dol [153], behind 4, with 54 hvy. xbowmen, 27 nazgul
8: Lord Rodrigo Bane [c8b], Imperial Empire, priest of the Church
8: of Dol [153], behind 3, with ten workers, 50 hvy. xbowmen,
8: 23 nazgul
8: Licia [i1l], Imperial Empire, Bishop of the Church of Ham [155],
8: behind 6, with five angels, 50 hvy. xbowmen
8: Odin [y5z], Imperial Empire, behind 7, with 23 peasants,
8: three soldiers, 44 hvy. xbowmen
8: Thorg [j8u], Imperial Empire, with one warmount
8: Jupiter [m8j], Imperial Empire, duke, the High Priest of the
8: Church of Halon [157], behind 5, with 43 soldiers,
8: ten angels, 46 hvy. xbowmen
8: Firefly [f3f], Imperial Empire, priest of the Church of
8: Halon [157], behind 9, with 50 hvy. xbowmen
8: Sunwalker [a8x], Imperial Empire, duke, Bishop of the Church of
8: Halon [157], with five angels, 44 nazgul
8: Thomas [o5y], Imperial Empire, Bishop of the Church of
8: Dol [153], behind 7, with five angels, 52 hvy. xbowmen,
8: five nazgul
8: Sir Peter [u9p], Imperial Empire, behind 9, with 30 peasants,
8: 20 workers, ten hvy. xbowmen
8: George [p7f], Imperial Empire, duke, priest of the Church of
8: Dol [153], behind 8, with ten nazgul
8: Lucca [h0t], Imperial Empire, priest of the Church of
8: Halon [157], with one skirmisher, 44 nazgul
8: Johny [w2d], Imperial Empire, priest of the Church of
8: Halon [157], with 39 nazgul
8: Aurora [g5z], Imperial Empire, behind 9
8: Stefano [t8e], Imperial Empire, Bishop of the Church of
8: Halon [157], with one peasant, five angels, 42 nazgul
8: Sir Charles [j5r], Imperial Empire, priest of the Church of
8: Halon [157], with 46 nazgul
8: Majikthise [n4g], Imperial Empire, behind 4
8: Alexei Galantor [j7l], Imperial Empire, duke, priest of the
8: Church of Halon [157], with 78 nazgul
8: City boy [c5x], Imperial Empire, behind 9
8: Sorak [y7s], Imperial Empire, behind 9
8: Phantom III [d6x], Imperial Empire, priest of the Church of
8: Dol [153], behind 9, with 19 nazgul
8: Merchant [jc9q], Imperial Empire, behind 9
8: Everblack [n3r], Imperial Empire, behind 9
8: Dryeth [q4e], Imperial Empire, priest of the Church of
8: Dol [153], behind 5, with 12 nazgul
8:
8: Mirco [h3z], Mandor Confederacy, with 66 soldiers, 17 pikemen,
8: 18 skirmishers, accompanied by:
8: Mika [r3c], Mandor Confederacy, behind 5, with 49 lt. xbowmen,
8: one skirmisher, three peasants
8: Micha [a2w], Mandor Confederacy, with ten skirmishers,
8: three peasants
8: Merlijn [h6v], Mandor Confederacy, with two peasants
8:
8: Initial missile round for the defense (Mirco [h3z]):
8: One missile hits!
8: Lucca [h0t] loses one nazgul [55].
8:
8: Combat round: one
8: Special attacks phase:
8: Thorg [j8u] dashes out and attacks!
8: Micha [a2w] loses one skirmisher [36].
8: 3 skirmishers [36] break and leave the battle!
8: Missile phase:
8: General Kraken's forces hit with 310 missiles.
8: Mirco's forces hit with nine missiles.
8: General Kraken [k3k] loses two nazgul [55].
8: General Kraken [k3k] loses six workers [11].
8: 24 workers [11] break and leave the battle!
8: Sunwalker [a8x] loses one angel [30].
8: Mirco [h3z] loses 17 pikemen [16].
8: Mirco [h3z] loses 63 soldiers [12].
8: Micha [a2w] loses six skirmishers [36].
8: Micha [a2w] loses three peasants [10].
8: Merlijn [h6v] loses two peasants [10].
8: Melee phase:
8: General Kraken's forces hit 84 times.
8: Mirco's forces miss!
8: Micha [a2w] suffers a hit!
8: Merlijn [h6v] suffers a hit!
8:
8: General Kraken [k3k] is victorious!
8:
8: General Kraken lost 30 workers, one angel, three nazgul.
8:
8: Mirco lost five peasants, 63 soldiers, 17 pikemen,
8: ten skirmishers.
8: Mirco [h3z] was taken prisoner.
8: Mika [r3c] was taken prisoner.
8: Micha [a2w] was taken prisoner.
8: Merlijn [h6v] was taken prisoner.
8:
9: General Kraken [k3k] attacks Paula Toler [o9u]!
9:
9: General Kraken [k3k], Imperial Empire, duke, priest of the Church
9: of Halon [157], with 27 workers, two winged horses, 56 nazgul,
9: one soldier, 13 skirmishers, 49 lt. xbowmen, three peasants,
9: accompanied by:
9: Veejay [v8j], Imperial Empire, Bishop of the Church of
9: Ham [155], behind 5, with five angels
9: Goon III [b9v], Imperial Empire, priest of the Church of
9: Dol [153], behind 4, with 54 hvy. xbowmen, 27 nazgul
9: Lord Rodrigo Bane [c8b], Imperial Empire, priest of the Church
9: of Dol [153], behind 3, with ten workers, 50 hvy. xbowmen,
9: 23 nazgul
9: Licia [i1l], Imperial Empire, Bishop of the Church of Ham [155],
9: behind 6, with five angels, 50 hvy. xbowmen
9: Odin [y5z], Imperial Empire, behind 7, with 23 peasants,
9: three soldiers, 44 hvy. xbowmen
9: Thorg [j8u], Imperial Empire, with one warmount
9: Jupiter [m8j], Imperial Empire, duke, the High Priest of the
9: Church of Halon [157], behind 5, with 43 soldiers,
9: ten angels, 46 hvy. xbowmen
9: Firefly [f3f], Imperial Empire, priest of the Church of
9: Halon [157], behind 9, with 50 hvy. xbowmen
9: Sunwalker [a8x], Imperial Empire, duke, Bishop of the Church of
9: Halon [157], with four angels, 44 nazgul
9: Thomas [o5y], Imperial Empire, Bishop of the Church of
9: Dol [153], behind 7, with five angels, 52 hvy. xbowmen,
9: five nazgul
9: Sir Peter [u9p], Imperial Empire, behind 9, with 30 peasants,
9: 20 workers, ten hvy. xbowmen
9: George [p7f], Imperial Empire, duke, priest of the Church of
9: Dol [153], behind 8, with ten nazgul
9: Lucca [h0t], Imperial Empire, priest of the Church of
9: Halon [157], with one skirmisher, 43 nazgul
9: Johny [w2d], Imperial Empire, priest of the Church of
9: Halon [157], with 39 nazgul
9: Aurora [g5z], Imperial Empire, behind 9
9: Stefano [t8e], Imperial Empire, Bishop of the Church of
9: Halon [157], with one peasant, five angels, 42 nazgul
9: Sir Charles [j5r], Imperial Empire, priest of the Church of
9: Halon [157], with 46 nazgul
9: Majikthise [n4g], Imperial Empire, behind 4
9: Alexei Galantor [j7l], Imperial Empire, duke, priest of the
9: Church of Halon [157], with 78 nazgul
9: City boy [c5x], Imperial Empire, behind 9
9: Sorak [y7s], Imperial Empire, behind 9
9: Phantom III [d6x], Imperial Empire, priest of the Church of
9: Dol [153], behind 9, with 19 nazgul
9: Merchant [jc9q], Imperial Empire, behind 9
9: Everblack [n3r], Imperial Empire, behind 9
9: Dryeth [q4e], Imperial Empire, priest of the Church of
9: Dol [153], behind 5, with 12 nazgul
9:
9: Paula Toler [o9u], Mandor Confederacy
9:
9: Combat round: one
9: Special attacks phase:
9: Thorg [j8u] dashes out and attacks!
9: Missile phase:
9: General Kraken's forces hit with 125 missiles.
9: Paula Toler [o9u] suffers a hit!
9:
9: General Kraken [k3k] is victorious!
9:
9: Paula Toler [o9u] was taken prisoner.
9:
10: Stack of savages [di6n], savages, number: 17, arrived from the west.
11: Dryeth [q4e], Imperial Empire, priest of the Church of Dol [153], with
11: 12 nazgul, arrived from Great Forest [an26], accompanied by:
11: General Kraken [k3k], Imperial Empire, duke, priest of the Church
11: of Halon [157], with 27 workers, two winged horses, 56 nazgul,
11: one soldier, 13 skirmishers, 49 lt. xbowmen, three peasants
11: Veejay [v8j], Imperial Empire, Bishop of the Church of Ham [155],
11: with five angels
11: Goon III [b9v], Imperial Empire, priest of the Church of Dol [153],
11: with 54 hvy. xbowmen, 27 nazgul
11: Lord Rodrigo Bane [c8b], Imperial Empire, priest of the Church of
11: Dol [153], with ten workers, 50 hvy. xbowmen, 23 nazgul
11: Licia [i1l], Imperial Empire, Bishop of the Church of Ham [155],
11: with five angels, 50 hvy. xbowmen
11: Odin [y5z], Imperial Empire, with 23 peasants, three soldiers,
11: 44 hvy. xbowmen
11: Thorg [j8u], Imperial Empire, with one warmount
11: Jupiter [m8j], Imperial Empire, duke, the High Priest of the Church
11: of Halon [157], with 43 soldiers, ten angels, 46 hvy. xbowmen
11: Firefly [f3f], Imperial Empire, priest of the Church of
11: Halon [157], with 50 hvy. xbowmen
11: Sunwalker [a8x], Imperial Empire, duke, Bishop of the Church of
11: Halon [157], with four angels, 44 nazgul
11: Thomas [o5y], Imperial Empire, Bishop of the Church of Dol [153],
11: with five angels, 52 hvy. xbowmen, five nazgul
11: Sir Peter [u9p], Imperial Empire, with 30 peasants, 20 workers,
11: ten hvy. xbowmen
11: George [p7f], Imperial Empire, duke, priest of the Church of
11: Dol [153], with ten nazgul
11: Lucca [h0t], Imperial Empire, priest of the Church of Halon [157],
11: with one skirmisher, 43 nazgul
11: Johny [w2d], Imperial Empire, priest of the Church of Halon [157],
11: with 39 nazgul
11: Aurora [g5z], Imperial Empire
11: Stefano [t8e], Imperial Empire, Bishop of the Church of
11: Halon [157], with one peasant, five angels, 42 nazgul
11: Sir Charles [j5r], Imperial Empire, priest of the Church of
11: Halon [157], with 46 nazgul
11: Joe One [i7n], Imperial Empire, prisoner
11: Majikthise [n4g], Imperial Empire
11: Alexei Galantor [j7l], Imperial Empire, duke, priest of the Church
11: of Halon [157], with 78 nazgul
11: City boy [c5x], Imperial Empire
11: Sorak [y7s], Imperial Empire
11: Phantom III [d6x], Imperial Empire, priest of the Church of
11: Dol [153], with 19 nazgul
11: Merchant [jc9q], Imperial Empire
11: Everblack [n3r], Imperial Empire
11: Jimmy Leather [o3i], Imperial Empire, prisoner
11: Fridur [j2a], Mandor Confederacy, prisoner
11: Lfir [w6v], Mandor Confederacy, prisoner
11: Adrian Dhubghalen [g5h], Mandor Confederacy, prisoner
11: Malek [j4c], Mandor Confederacy, prisoner
11: Maruk II [t7m], Mandor Confederacy, prisoner
11: Ringli [d5m], Mandor Confederacy, sorcerer, prisoner
11: Feanor [i9z], Mandor Confederacy, prisoner
11: Gomdrag Caerric [g6k], Mandor Confederacy, prisoner
11: Mirco [h3z], Mandor Confederacy, prisoner
11: Mika [r3c], Mandor Confederacy, prisoner
11: Major [k1k], refugee, prisoner
11: Micha [a2w], Mandor Confederacy, prisoner
11: Merlijn [h6v], Mandor Confederacy, prisoner
11: Paula Toler [o9u], Mandor Confederacy, prisoner
20: Stack of savages [di6n], savages, number: 17, went west.
20: General Kraken [k3k], Imperial Empire, duke, priest of the Church of
20: Halon [157], with 27 workers, two winged horses, 56 nazgul,
20: one soldier, 13 skirmishers, 49 lt. xbowmen, three peasants, exited
20: Circle of trees [ad5s], accompanied by:
20: Veejay [v8j], Imperial Empire, Bishop of the Church of Ham [155],
20: with five angels
20: Goon III [b9v], Imperial Empire, priest of the Church of Dol [153],
20: with 54 hvy. xbowmen, 29 nazgul
20: Lord Rodrigo Bane [c8b], Imperial Empire, priest of the Church of
20: Dol [153], with ten workers, 50 hvy. xbowmen, 25 nazgul
20: Licia [i1l], Imperial Empire, Bishop of the Church of Ham [155],
20: with five angels, 50 hvy. xbowmen
20: Odin [y5z], Imperial Empire, with 23 peasants, three soldiers,
20: 44 hvy. xbowmen
20: Thorg [j8u], Imperial Empire, with one warmount
20: Jupiter [m8j], Imperial Empire, duke, the High Priest of the Church
20: of Halon [157], with 43 soldiers, ten angels, 46 hvy. xbowmen
20: Firefly [f3f], Imperial Empire, priest of the Church of
20: Halon [157], with 50 hvy. xbowmen
20: Sunwalker [a8x], Imperial Empire, duke, Bishop of the Church of
20: Halon [157], with four angels, 44 nazgul
20: Thomas [o5y], Imperial Empire, Bishop of the Church of Dol [153],
20: with five angels, 52 hvy. xbowmen, seven nazgul
20: Sir Peter [u9p], Imperial Empire, with 30 peasants, 20 workers,
20: ten hvy. xbowmen
20: George [p7f], Imperial Empire, duke, priest of the Church of
20: Dol [153], with 11 nazgul
20: Lucca [h0t], Imperial Empire, priest of the Church of Halon [157],
20: with one skirmisher, 43 nazgul
20: Johny [w2d], Imperial Empire, priest of the Church of Halon [157],
20: with 39 nazgul
20: Aurora [g5z], Imperial Empire
20: Stefano [t8e], Imperial Empire, Bishop of the Church of
20: Halon [157], with one peasant, five angels, 42 nazgul
20: Sir Charles [j5r], Imperial Empire, priest of the Church of
20: Halon [157], with 46 nazgul
20: Joe One [i7n], Imperial Empire, prisoner
20: Majikthise [n4g], Imperial Empire
20: Alexei Galantor [j7l], Imperial Empire, duke, priest of the Church
20: of Halon [157], with 78 nazgul
20: City boy [c5x], Imperial Empire
20: Sorak [y7s], Imperial Empire
20: Phantom III [d6x], Imperial Empire, priest of the Church of
20: Dol [153], with 21 nazgul
20: Merchant [jc9q], Imperial Empire
20: Everblack [n3r], Imperial Empire
20: Dryeth [q4e], Imperial Empire, priest of the Church of Dol [153],
20: with 12 nazgul
20: Jimmy Leather [o3i], Imperial Empire, prisoner
20: Fridur [j2a], Mandor Confederacy, prisoner
20: Lfir [w6v], Mandor Confederacy, prisoner
20: Adrian Dhubghalen [g5h], Mandor Confederacy, prisoner
20: Malek [j4c], Mandor Confederacy, prisoner
20: Maruk II [t7m], Mandor Confederacy, prisoner
20: Ringli [d5m], Mandor Confederacy, sorcerer, prisoner
20: Feanor [i9z], Mandor Confederacy, prisoner
20: Gomdrag Caerric [g6k], Mandor Confederacy, prisoner
20: Mirco [h3z], Mandor Confederacy, prisoner
20: Mika [r3c], Mandor Confederacy, prisoner
20: Major [k1k], refugee, prisoner
20: Micha [a2w], Mandor Confederacy, prisoner
20: Merlijn [h6v], Mandor Confederacy, prisoner
20: Paula Toler [o9u], Mandor Confederacy, prisoner
20: General Kraken [k3k], Imperial Empire, duke, priest of the Church of
20: Halon [157], with 27 workers, two winged horses, 56 nazgul,
20: one soldier, 13 skirmishers, 49 lt. xbowmen, three peasants, arrived,
20: accompanied by:
20: Veejay [v8j], Imperial Empire, Bishop of the Church of Ham [155],
20: with five angels
20: Goon III [b9v], Imperial Empire, priest of the Church of Dol [153],
20: with 54 hvy. xbowmen, 29 nazgul
20: Lord Rodrigo Bane [c8b], Imperial Empire, priest of the Church of
20: Dol [153], with ten workers, 50 hvy. xbowmen, 25 nazgul
20: Licia [i1l], Imperial Empire, Bishop of the Church of Ham [155],
20: with five angels, 50 hvy. xbowmen
20: Odin [y5z], Imperial Empire, with 23 peasants, three soldiers,
20: 44 hvy. xbowmen
20: Thorg [j8u], Imperial Empire, with one warmount
20: Jupiter [m8j], Imperial Empire, duke, the High Priest of the Church
20: of Halon [157], with 43 soldiers, ten angels, 46 hvy. xbowmen
20: Firefly [f3f], Imperial Empire, priest of the Church of
20: Halon [157], with 50 hvy. xbowmen
20: Sunwalker [a8x], Imperial Empire, duke, Bishop of the Church of
20: Halon [157], with four angels, 44 nazgul
20: Thomas [o5y], Imperial Empire, Bishop of the Church of Dol [153],
20: with five angels, 52 hvy. xbowmen, seven nazgul
20: Sir Peter [u9p], Imperial Empire, with 30 peasants, 20 workers,
20: ten hvy. xbowmen
20: George [p7f], Imperial Empire, duke, priest of the Church of
20: Dol [153], with 11 nazgul
20: Lucca [h0t], Imperial Empire, priest of the Church of Halon [157],
20: with one skirmisher, 43 nazgul
20: Johny [w2d], Imperial Empire, priest of the Church of Halon [157],
20: with 39 nazgul
20: Aurora [g5z], Imperial Empire
20: Stefano [t8e], Imperial Empire, Bishop of the Church of
20: Halon [157], with one peasant, five angels, 42 nazgul
20: Sir Charles [j5r], Imperial Empire, priest of the Church of
20: Halon [157], with 46 nazgul
20: Joe One [i7n], Imperial Empire, prisoner
20: Majikthise [n4g], Imperial Empire
20: Alexei Galantor [j7l], Imperial Empire, duke, priest of the Church
20: of Halon [157], with 78 nazgul
20: City boy [c5x], Imperial Empire
20: Sorak [y7s], Imperial Empire
20: Phantom III [d6x], Imperial Empire, priest of the Church of
20: Dol [153], with 21 nazgul
20: Merchant [jc9q], Imperial Empire
20: Everblack [n3r], Imperial Empire
20: Dryeth [q4e], Imperial Empire, priest of the Church of Dol [153],
20: with 12 nazgul
20: Jimmy Leather [o3i], Imperial Empire, prisoner
20: Fridur [j2a], Mandor Confederacy, prisoner
20: Lfir [w6v], Mandor Confederacy, prisoner
20: Adrian Dhubghalen [g5h], Mandor Confederacy, prisoner
20: Malek [j4c], Mandor Confederacy, prisoner
20: Maruk II [t7m], Mandor Confederacy, prisoner
20: Ringli [d5m], Mandor Confederacy, sorcerer, prisoner
20: Feanor [i9z], Mandor Confederacy, prisoner
20: Gomdrag Caerric [g6k], Mandor Confederacy, prisoner
20: Mirco [h3z], Mandor Confederacy, prisoner
20: Mika [r3c], Mandor Confederacy, prisoner
20: Major [k1k], refugee, prisoner
20: Micha [a2w], Mandor Confederacy, prisoner
20: Merlijn [h6v], Mandor Confederacy, prisoner
20: Paula Toler [o9u], Mandor Confederacy, prisoner
21: General Kraken [k3k], Imperial Empire, duke, priest of the Church of
21: Halon [157], with 27 workers, two winged horses, 56 nazgul,
21: one soldier, 13 skirmishers, 49 lt. xbowmen, three peasants, went
21: north, accompanied by:
21: Veejay [v8j], Imperial Empire, Bishop of the Church of Ham [155],
21: with five angels
21: Goon III [b9v], Imperial Empire, priest of the Church of Dol [153],
21: with 54 hvy. xbowmen, 29 nazgul
21: Lord Rodrigo Bane [c8b], Imperial Empire, priest of the Church of
21: Dol [153], with ten workers, 50 hvy. xbowmen, 25 nazgul
21: Licia [i1l], Imperial Empire, Bishop of the Church of Ham [155],
21: with five angels, 50 hvy. xbowmen
21: Odin [y5z], Imperial Empire, with 23 peasants, three soldiers,
21: 44 hvy. xbowmen
21: Thorg [j8u], Imperial Empire, with one warmount
21: Jupiter [m8j], Imperial Empire, duke, the High Priest of the Church
21: of Halon [157], with 43 soldiers, ten angels, 46 hvy. xbowmen
21: Firefly [f3f], Imperial Empire, priest of the Church of
21: Halon [157], with 50 hvy. xbowmen
21: Sunwalker [a8x], Imperial Empire, duke, Bishop of the Church of
21: Halon [157], with four angels, 44 nazgul
21: Thomas [o5y], Imperial Empire, Bishop of the Church of Dol [153],
21: with five angels, 52 hvy. xbowmen, seven nazgul
21: Sir Peter [u9p], Imperial Empire, with 30 peasants, 20 workers,
21: ten hvy. xbowmen
21: George [p7f], Imperial Empire, duke, priest of the Church of
21: Dol [153], with 11 nazgul
21: Lucca [h0t], Imperial Empire, priest of the Church of Halon [157],
21: with one skirmisher, 43 nazgul
21: Johny [w2d], Imperial Empire, priest of the Church of Halon [157],
21: with 39 nazgul
21: Aurora [g5z], Imperial Empire
21: Stefano [t8e], Imperial Empire, Bishop of the Church of
21: Halon [157], with one peasant, five angels, 42 nazgul
21: Sir Charles [j5r], Imperial Empire, priest of the Church of
21: Halon [157], with 46 nazgul
21: Joe One [i7n], Imperial Empire, prisoner
21: Majikthise [n4g], Imperial Empire
21: Alexei Galantor [j7l], Imperial Empire, duke, priest of the Church
21: of Halon [157], with 78 nazgul
21: City boy [c5x], Imperial Empire
21: Sorak [y7s], Imperial Empire
21: Phantom III [d6x], Imperial Empire, priest of the Church of
21: Dol [153], with 21 nazgul
21: Merchant [jc9q], Imperial Empire
21: Everblack [n3r], Imperial Empire
21: Dryeth [q4e], Imperial Empire, priest of the Church of Dol [153],
21: with 12 nazgul
21: Jimmy Leather [o3i], Imperial Empire, prisoner
21: Fridur [j2a], Mandor Confederacy, prisoner
21: Lfir [w6v], Mandor Confederacy, prisoner
21: Adrian Dhubghalen [g5h], Mandor Confederacy, prisoner
21: Malek [j4c], Mandor Confederacy, prisoner
21: Maruk II [t7m], Mandor Confederacy, prisoner
21: Ringli [d5m], Mandor Confederacy, sorcerer, prisoner
21: Feanor [i9z], Mandor Confederacy, prisoner
21: Gomdrag Caerric [g6k], Mandor Confederacy, prisoner
21: Mirco [h3z], Mandor Confederacy, prisoner
21: Mika [r3c], Mandor Confederacy, prisoner
21: Major [k1k], refugee, prisoner
21: Micha [a2w], Mandor Confederacy, prisoner
21: Merlijn [h6v], Mandor Confederacy, prisoner
21: Paula Toler [o9u], Mandor Confederacy, prisoner
Routes leaving Great Forest:
North, forest, to Great Forest [am26], 8 days
East, forest, to Great Forest [an27], 8 days
Garrison [en3j], garrison, uncontrolled, with four peasants
South, forest, to Great Forest [ao26], 8 days
Garrison [cb4m], garrison, uncontrolled, with seven peasants
West, forest, to Great Forest [an25], 8 days
Inner locations:
Circle of trees [ad5s], circle of trees, hidden, 1 day, owner:
Giant spider [et8w], giant spiders, number: 16
Seen here:
Stack of cyclops [iu7l], cyclops, number: 9


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Github :link
Created by Kaivalya Swami (2017CS10339) and Kartik Sharma (2017CS10342)
Use spacebar to see the slides sequentially.
Kids (age: 5+)
We aim to cultivate good habits or impact the way people act to certain kind of situations. We feel that all people should have some basic habits which are expected by the society. These might be the kind of behaviour which are very fundamental to a society and lay the foundation of its stability.
We believe that "character building" is very important. And this should start from childhood. Many of the problems of this world can be easily solved, if we have people willing to act for such bigger causes.
And it may not require much effort, even small contributions in silly things can have a great impact.
Changing one's morals and ethics is quite difficult to approach as it requires a concious effort from the other end.
We rather decided to plan a game where we make the user "do" things and try to impact one's working memory.
This would be like making habits where one would act to certain situations.
And more importantly this should be natural impulsive response. Thoughtful persons make their own decisions and then habits are created out of them. But is that effective ? Definetly not in a country like India. So can these habits be created instead , if that is possible ?
So we constraint this to short term actions about silly things which need immediate response.
For example let's propose the simple scenario of the garbage. We create a scenario where one has to act quickly (take quick decisions) about throwing trash in dustbin.
If one fails to do, we show him the scene where our cities are flooded by garbage. And on doing it right, we try to creat vibes of a positive city.
So we will have a 1st player game.
There will be different scenes/situations which will be randomly given to the user.
In each situation one has to take fast decisions to do the job.
There will be three lives.

We will have following scenes/levels based on situations.
1. Close the running tap as soon as possible.
2. Turn off the lights in a room.
3. Give way to an ambulance.
4. Give seat to elderly in metro.
We don't explicitly say the aim/goal of the level, the user has to infer that.
These are a very important aspect of the game.
Since we are trying to include these habits into the player's reflexive memory , we need certain artifacts to activate their memory formation. For this we use Easy Mental Calculation in a gamy environment.
The score after game over comes in terms of how many resources is saved during the play.
We have option after every play to share one's contributions , where one can share his contributions on social media.
Contibutions include number of humans saved , litres water saved.
We plan to use the following features
Music in between scenes and the start (Silly Things by Wild Child) , also in game.
Simple UI
Use of accelerometer.
Use of characters from assets and hopefully inspired from Dumb Ways to Die.
We plan to use the following features
Simplistic UI.
Psyochological applicability.
Practicality
Dumb Ways to Die is an Australian public service announcement campaign made by Metro Trains in Melbourne, Victoria, Australia to promote railway safety.
Github : https://github.com/kaivu1999/silly-things
Created by Kaivalya Swami (2017CS10339) and Kartik Sharma (2017CS10342)


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Protein (nutrient) - Wikipedia, the free encyclopedia
These tests determine the total nitrogen in a sample. The only major component of most food which contains nitrogen is protein .
http://en.wikipedia.org/wiki/Protein_(nutrient)
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Bodybuilding.com - Nitrogen Balance: The Key To Muscle Growth.
May 18, 2005 . In fact, protein is the key "building" nutrient for a variety of bodily tissues, . Nitrogen is a compound unique to protein that can provide a direct .
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Amino acid composition, protein content and calculation of nitrogen ...
tance of non-protein nitrogen is greater in red algae, and consequently lower . protein nitrogen content in both green and brown algae tends to be higher, and .
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Converting nitrogen into protein--beyond 6.25 and Jones' factors.
The protein content in foodstuffs is estimated by multiplying the determined nitrogen content by a nitrogen-to-protein conversion factor. Jones' factors for a series .
http://www.ncbi.nlm.nih.gov/pubmed/18274971
Nitrogen And Protein Determination - Engineer Live, For Engineers ...
Nitrogen and protein determination - Recent advances in the combustion method have made it suitable to cope with the array of food safety laboratory .
http://www.engineerlive.com/Chemical-Engineer/Chemical_Equipment/Nitrogen_and_protein_determination/20632/
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Nitrogen vs. Amino-Acid Profile as Indicator of Protein Content of ...
more nitrogen - thus require a lower factor. Currently, different factors are used to calculate protein content based on nitrogen content. (Jones et al., 1942) .
http://www.eurofir.net/sites/default/files/9th%20IFDC/Presentations/Hall.pdf
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True protein - USJersey.com
basis of its true protein content. Protein pricing elsewhere is based upon total nitrogen content, a considerable frac- tion of which is non-protein nitrogen. (NPN) .
http://www.usjersey.com/reference/trueprot.pdf
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6. ANALYSIS OF PROTEINS
Because the Kjeldahl method does not measure the protein content directly a conversion factor (F) is needed to convert the measured nitrogen concentration to .
http://people.umass.edu/~mcclemen/581Proteins.html
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Dietary Protein and Nitrogen Utilization
Jul 1, 2000 . The investigation of protein metabolism in relation to dietary proteins, with a focus on the postprandial phase of nitrogen diurnal cycling, .
http://jn.nutrition.org/content/130/7/1868S.full
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Nitrogen-to-Protein Conversion Factors for Cereals and Oilseed ...
virtually all animal life. The quantity of protein in cereals and oilseeds is calculated from the amount of nitrogen in these materials, nitrogen content usually being .
http://www.aaccnet.org/publications/cc/backissues/1969/Documents/Chem46_419.pdf
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Conversion factor for the calculation of the protein content
EDA comments on the conversion factor for the calculation of the protein content. The protein content of foodstuffs is commonly done by analysis of total nitrogen .
http://ec.europa.eu/food/consultations/eda_1_en.pdf
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micro-kjeldahl determination of the nitrogen content
The determination of the nitrogen content of proteins and amino acids is of fundamental importance for many investigations, inasmuch as the validity of other .
http://www.jbc.org/content/159/2/373.full.pdf
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Protein Matabolism
Animals and humans in turn use the plants to supply nitrogen to make amino acids and proteins. We humans are not as versatile as plants since we are unable .
http://www.elmhurst.edu/~chm/vchembook/630proteinmet.html
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CHAPTER 2: METHODS OF FOOD ANALYSIS
Nitrogen content is then multiplied by a factor to arrive at protein content. . First, not all nitrogen in foods is found in proteins: it is also contained in variable .
http://www.fao.org/docrep/006/Y5022E/y5022e03.htm
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Nitrogen to Protein Conversion Factor for Ten Cereals and Six ...
The protein concentration of grain is obtained by mul- tiplying its total nitrogen (N) content by a nitrogen to protein (N:P) conversion factor calculated from the AA .
http://pubs.acs.org/doi/abs/10.1021/jf00091a004
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Leaf protein contents and nitrogen-to-protein conversion factors for ...
their protein content. It is therefore useful to have a quick and reasonably accurate method of estimating the protein content. The total nitrogen analysis using .
http://staff.science.nus.edu.sg/~dbsyhh/1994%20Food%20Chem%2049,245-250.pdf
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Practices to Increase Wheat Grain Protein - Department of Land ...
Nitrogen is a basic component of amino acids which are the building blocks of protein necessary for plant growth. Protein is stored in the grain for seedling .
http://landresources.montana.edu/soilfertility/PDFbyformat/publication%20pdfs/Wheat%20protein%20EB0206.pdf
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Nitrogen/Protein in Starch Organic Application Note - Leco
Nitrogen determination in starch is utilized to calculate the protein concentration using a nitrogen protein conversion factor. The protein content of starch is not .
http://www.leco.com/resources/application_notes/pdf/trumac_nitrogen-protein_starch_203-821-401.pdf
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How Prochlorococcus bacteria use nitrogen sparingly in their proteins.
In aggregate, the nitrogen atoms that are bound in proteins typically account for a substantial fraction of the nitrogen in a cell. Many organisms obtain the .
http://www.ncbi.nlm.nih.gov/pubmed/21158996
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Milk Protein
Historically, milk protein has been estimated by Kjeldahl determination, which measures the total nitrogen content in milk. Nitrogen is released from protein and .
http://research.vet.upenn.edu/LinkClick.aspx?link=1595&tabid=802
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Protein Equivalent of Total Nitrogen Appearance - K/DOQI Update ...
Because the nitrogen content of protein is relatively constant at 16%, the protein equivalent of total nitrogen appearance (PNA) can be estimated by multiplying .
http://www.kidney.org/professionals/kdoqi/guidelines_updates/nut_a08.html
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Protein Determination
Protein Nitrogen Content of Milk - Kjeldahl Method (Direct Method) . The following procedures for determining the protein content of milk have been approved .
http://www.fmmaseattle.com/lab/protein.htm
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Frequently Asked Questions About True Protein - USJersey.com
protein and true protein? Crude protein, sometimes called total protein, is estimated from measuring the total nitrogen content of milk by Kjeldahl analysis.
http://www.usjersey.com/Reference/trueprotfaq.pdf
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Non-protein nitrogen - Wikipedia, the free encyclopedia
Non-protein nitrogen (or NPN) is a term used in animal nutrition to refer collectively to components such as urea, biuret, and ammonia, which are not proteins but .
http://en.wikipedia.org/wiki/Non-protein_nitrogen
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Proteins (amino acids, peptides, proteins, nitrogen) - Food ...
Proteins are also major structural food components and determine the texture of . (IR and UV) Nitrogen content (Kjeldahl method) as a measure of protein content.
http://www.sigmaaldrich.com/analytical-chromatography/analytical-products.html?TablePage=110440029
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A reappraisal of nitrogen-to-protein conversion factors in cassava ...
A reappraisal of nitrogen-to-protein conversion factors in cassava roots. D. Dufour1 & 2, J. Ricci1, T. Sanchez2, N. Morante2, G. Morel1, M. Reynes1, .
http://www.danforthcenter.org/GCP21-II/8.GCP21-II.Abstracts/S10%20Biofort%20&%20Metabolic%20Engineering/S10%20Oral%20presentations/S10-05_Dufour.pdf
SN 028 2010 Nitrogen Determination In Whey Protein
Quality in your hands. SHORT NOTE. Nitrogen and Protein Determination in Whey Protein Concentrates and Demineralized Whey Powder according to the .
http://www.buchi.com/fileadmin/user_upload/01_products/11_kjeldahl/pdf/SN%20028_2010%20Nitrogen%20Determination%20in%20Whey%20Protein%20Concentrates%20and%20Whey%20Powder.pdf
How to Calculate the Nitrogen Content of TPN | eHow.com
Among other nutrients, TPN provides protein in the form of amino acids, which contain nitrogen. Since protein is important in building new bodily tissues during a .
http://www.ehow.com/how_8745209_calculate-nitrogen-content-tpn.html
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This page provides a security mechanism that prevents unauthorized users from accessing the system. In order to get into the ShipConsole Index page, the user must provide a valid username and password provided by the CLIENT ADMIN. The following screenshot shows the login page.
Figure 1.1
Input Validations:
ï?¬ Username can have combination of Characters and Numbers but Special Characters are not allowed.
ï?¬ Password can have combination of Characters, Special Characters and Numbers.
UserName : Uniquely identifies a user
Password : Confidential that is known only to its user.
Login : This button validates username and password.
Download QZ Tray for Windows : This link is used to download QZ tray for Windows OS system to use Weighing Scale and Printer
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The Shipping user credentials are provided by the admin which are unique to specific Location. User must enter username and password, then click on Login button as shown below in Figure1.2
Figure 1.2
If user provides valid login details then it navigates to ShipConsole Index Page, Otherwise error message is displayed at the top right corner of the screen and captcha is given as shown in
Figure 1.3
Figure 1.3
If user lost password then password can be reset using Forgot Password. When clicked on Forgot Password, the following pop-up is opened Figure 1.4
Figure 1.4
ïƒ˜ Once user name and email-id is entered, click on Get Password button. It sends the new password to the respective registered email-id and success message is displayed as shown in Figure 1.5
Figure 1.5
ïƒ˜ After clicking Get Password button, If user name is invalid then appropriate message will be displayed at the top right corner of the screen as shown in Figure 1.6 and Figure 1.7 respectively.
Figure 1.6
Figure 1.7
ïƒ¨ Once user enters valid login details of shipping user then user is allowed to get into ShipConsole Index screen(Figure 1.8)
Figure 1.8
Live data with the graphs is displayed on the home screen.The graph details are displayed for the client user with respective to the user location,carrier wise.
1. Pie Chart that represents number of shipments shipped for a month,carrier wise i.e, previous one month from previous day of the present month to the last month. Eg: if present date is 9 March 2016 then the graph displays the data from 8 Feb 2016 to 8 March 2016.
2. The other chart is a Bar Graph represents freight charges for a month, carrier wise i.e, previous one month from previous day of the present month to the last month. Eg: if present date is 9 March 2016 then the graph displays the data from 8 Feb 2016 to 8 March 2016.


MILESTONE 1
04/07/2016
| Task | Member |
|---|---|
|
Integrate the Leap Motion controller's functionality with the Unity3D workspace
Data collection. |
Lakshman and Aditya |
| Create the basic assets (in Blender) to be used in the application | Kanishka and Ankur |


‘Build Software to Test Software’ is our motto. Effective test automation with wide coverage and a focus on cost efficiency, maintainability and sustainability is at the core of our business.
Over the years, we have benefited a lot from open source when building our bespoke set of automated tools for functional and non-functional testing of a multitude of complex high-load software systems and platforms and started giving back to the open source community in 2018.
The most recent addition to our open-source test tool ecosystem is th2 – a next-generation framework for automated functional and non-functional testing of distributed transaction processing systems. These include securities trading systems and exchanges, banking and broker systems, post-trade (e.g. clearing, settlement, custody) and payments platforms, and many more.
th2 is a Kubernetes-driven microservices solution tailor-made to deliver efficient machine-driven end-to-end test libraries with comprehensive coverage of your system. th2 consolidates the power of the entire Exactpro test tool suite in a single solution.
Sailfish is an active real-time tool used for exchange, MTF and broker systems testing. It can also be used as an exchange simulator for testing post-trade systems or smart derivatives. Sailfish is a web-based application which supports simultaneous connections of multiple users for both incoming and outgoing streams. It is written in Java.
ClearTH is a unique Exactpro tool able to simultaneously execute multiple end-to-end test scenarios in batches. ClearTH easily detects abnormal behavior in the system under test and effectively predicts potential issues. It offers many built-in actions to cover the majority of activities in post-trade systems. ClearTH is a web-based application, and it presents an innovative way to test clearing, settlement and back-office systems.
ClearTH:
Nostradamus is an open-source tool for analyzing software defect reports extracted from defect repositories. The tool uses machine learning techniques to determine important links between various defect attributes and generate certain bug metrics, such as the probability of a bug being fixed/rejected, including time to resolve, etc. Nostradamus also calculates various statistical data including distributions and values of aggregate function, it can also build the top of the most frequent terms and the top of the most significant words, etc. This knowledge further allows to achieve various IT-related goals, for example:
Exactpro specializes in quality assurance services and related software development with focus on test automation for securities data distribution, trading systems, risk management, market surveillance and post-trade infrastructures. We use bespoke tools and methods for every challenge and do whatever it takes to help our clients.
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