Create a short story with story boards to pitch to a client. The Goal: Figure out the direction of the project before moving forward and designing too much.
Sketch with Toy Story aesthetic
Inital Design
Digitizing Artwork
I worked on this project as part of a week long sprint. I worked with a project manager, a business analyst and a whole team of designers working on creating a better EFT (Electronic Funds Transfer) flow.
THE PROBLEM
Customers who own businesses in their own name do not actually own the account, the business does (it just happens to be in their name). Within the previous path, business oweners continually clicked "Yes, I own this account" and would end up failing futhur down the flow.
Final Renders
Artboard 1: Boy opens gift
Artboard 2: Its a remote control car!
Artboard 3: Give it a test drive!
Artboard 4: From his perspective
Artboard 5: Dad walks out into garage
Artboard 6: Dad backs up the car
Artboard 7: Dad's car runs over the toy
Artboard 8: Dad's car is huge Version of toy car
Complied Render
CONCLUSION
Customers who owned businesses in their own name do not actually own the account, the business does (it just happens to be in their name). Business oweners continually clicked "Yes, I own this account" and would end up failing futhur down the flow.


Home
3D Modeling
Personal Project
Home
3D Modeling
Personal Project
menu
3D Modeling
Here are some of the 3D models which I have created.


Those tools support the observability of our application
Analyse system events through structured logs
Kibana »
Visualize metrics as time series data
Grafana »
Prometheus »
Follow the path of transactions through the system
Jaeger »
Insight through the istio service mesh
Kiali »


{% extends "players/layout.html" %} {% set active_page = 'players' %} {% macro write_role(role) %} {%if role == 'dev'%} {{role}} {%else%} {{role}} {%endif%} {% endmacro %} {%block maincontent%}
| Player ID | {{player.player_id}} |
| Player Name | {{player.player_name}} |
| Last Logon | {{player.logon_date | dt}} |
| Num Logons | {{player.num_logons}} |
| NPC | {{player.npc}} |
| Last Heartbeat | {{player.last_heartbeat | dt}} |
| Status | {{player.status | status}} |
| Create Date | {{player.create_date | dt}} |
| User | {{player.user_id}} : {{user.user_name}} |
| User Roles | {%if roles:%} {%for r in roles:%} {{r.role | role}} {%endfor%} {%else%} {{"none" | role}} {%endif%} |


4.3 psb_gedots — Generalized Dot Product
This subroutine computes a series of dot products among the columns of two dense
matrices x and y:
If the matrices are complex, then the usual convention applies, i.e. the conjugate
transpose of x is used. If x and y are of rank one, then res is a scalar, else it is a rank
one array.
call psb_gedots(res, x, y, desc_a, info)
|
|
| res, x, y | Subroutine |
|
|
| Short Precision Real | psb_gedots |
| Long Precision Real | psb_gedots |
| Short Precision Complex | psb_gedots |
| Long Precision Complex | psb_gedots |
|
|
| |
Table 3: Data types
-
Type:
- Synchronous.
-
On Entry
-
-
x
- the local portion of global dense matrix x.
Scope: local
Type: required
Intent: in.
Specified as: a rank one or two array or an object of type
psb_T_vect_type containing numbers of type specified in Table 3. The
rank of x must be the same of y.
-
y
- the local portion of global dense matrix y.
Scope: local
Type: required
Intent: in.
Specified as: a rank one or two array or an object of type
psb_T_vect_type containing numbers of type specified in Table 3. The
rank of y must be the same of x.
-
desc_a
- contains data structures for communications.
Scope: local
Type: required
Intent: in.
Specified as: an object of type psb_desc_type.
-
On Return
-
-
res
- is the dot product of vectors x and y.
Scope: global
Intent: out.
Specified as: a number or a rank-one array of the data type indicated in
Table 2.
-
info
- Error code.
Scope: local
Type: required
Intent: out.
An integer value; 0 means no error has been detected.


There are lots of names for the conversations we have to prepare user stories for development. Some people hold Three Amigos or Specification Workshops, some hold Planning Poker or Backlog Grooming sessions. Whatever you call this work, essentially you're trying to answer two questions:
- What do we want to make?
- How will we make it?
These two questions form a dynamic: when a clearly-defined requirement turns out to be complex to build, developers and product owners can usually negotiate to find a simpler what that has a more straightforward how. Similarly, product owners may not be able to clearly define what they want until they've had a chance to have it examined by the people who will think about how to build it.
I recently watched a team having what they called a Sprint Planning meeting. For this team, that meeting was their opportunity to have this conversation. As they laid out the stories for discussion--each on 5"x3" index cards--I came up with a suggestion.
Imagine two axes on the whiteboard:
Now, put the stories that the business understand well to the top, and the stories that the developers have a clear idea how to build and test to the right. Note that this is not about estimating complexity or business value. This is simply about acknowledging how well we understand the problem and how to solve it.
Over time, stories will start out in the bottom-left corner, and gradually move up to the top-right as they become well understood and ready for development.
In the example above, Story B is well understood by the business, but the developers are still not sure how to build it. A spike would be a good idea for a story like this. Story C suffers from the opposite problem. The developers know how they'll implement it, but the product people can't decide on the details of what they want. Three Amigos or Specification workshops are a good solution here.
Doing this, we can see that it's a team effort to prepare stories - not just something for the business analyst to do in isolation. We can also see that it may take time to get a story ready. We can't tackle a batch of stories in a single meeting and expect them all to be ready by the end of that meeting. We might encounter questions that will need data, decisions or expertise from outside the room to solve.
Starting development on stories that are not well understood is a very common problem in teams that I visit. Perhaps by visualising the readiness of their stories like this, they can avoid it.
Want to know more about running successful Three Amigos workshops? Learn all about BDD with Matt and Aslak at BDD Kickstart London 29th April - 1st May 2014.


| Home | Trees | Indices | Help |
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|---|
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|
class that defines "access" constants
| Class Variables | |
PUBLIC =
|
|
PRIVATE =
|
|
PROTECTED =
|
|
ALL =
|
| Home | Trees | Indices | Help |
|
|---|
| Generated by Epydoc 3.0.1 on Mon Oct 20 09:00:18 2008 | http://epydoc.sourceforge.net |


Top Losers is a free to use stock market analyzing service online on our web-page aswell as on our app.
Click the download button to download the app for Android!


|
| Local Properties | Local Methods | |
| Managed Object Types | Data Object Types | All Properties | All Methods |
Entitlements are identified by a short string 'key'. Keys can represent either a particular edition (Full, Starter) or a particular feature/function (featureKey) (backup, nas). An edition implies zero one or more functions which are express, denied or optional. For example a 'Full' edition includes 'iscsi' function but a Starter edition might disallow it.
Which edition a given VMware platform uses can be defined at any time. Generally this is done right after first install and boot as installation software may not set it. For editions that are similar in nature, any future changes to edition type will only impact future requests for functionality. Current functionality is left unaffected. The same is true for optional functions enabled/disabled after some period of time. For dissimilar editions, such transitions may require entering maintenance mode first else an exception of InvalidState will be thrown.
To specify the edition type and any optional functions, use updateLicense for ESX Server and addLicense follow by LicenseAssingmentManager.updateAssignedLicense for VirtualCenter.
When an edition is specified for a given host, the cost of that edition (how many licenses are needed) is determined. The cost is computed using the license's CostUnit value multiplied by the number of units activated. For example, when a VMware platform is set to an edition which uses a 'cpuPackage' on a two socket server, two licenses would be needed to successfully install that edition.
Here is a diagram of the unit costs supported by this API and their relationships.
+------------------------------+ +--------+ +-------+ | +-----------+ +-----------+ | | Server | | Host | | | | | | | +--------+ +-------+ | | cpuCore | | cpuCore | | +-------+ | +-----------+ +-----------+ | +--------+ | Host | | cpuPackage | | VM | +-------+ +------------------------------+ +--------+
Properties
| Name | Type | Description |
|---|---|---|
| diagnostics* | LicenseDiagnostics | Deprecated.
As of vSphere API 4.0, this property is not used by the system.
Return current diagnostic information.
Since VI API 2.5 |
| evaluation P | LicenseManagerEvaluationInfo |
Since vSphere API 4.0 |
| featureInfo* | LicenseFeatureInfo[] | Deprecated.
As of VI API 2.5, use QuerySupportedFeatures
instead.
The list of features that can be licensed.
|
| licenseAssignmentManager* P | ManagedObjectReference
to a LicenseAssignmentManager |
License Assignment Manager
Since vSphere API 4.0 |
| licensedEdition | xsd:string | Deprecated.
As of vSphere API 4.0, use
QueryAssignedLicenses instead.
The product's license edition. The edition defines which product license
the server requires. This, in turn, determines the core set of functionalities
provided by the product and the additional features that can be licensed. If
no edition is set the property is set to the empty string ("").
To set the edition use SetLicenseEdition.
Since VI API 2.5 |
| licenses P | LicenseManagerLicenseInfo[] |
Get information about all the licenses avaiable.
Since vSphere API 4.0 |
| source | LicenseSource | Deprecated.
As of vSphere API 4.0, use
QueryAssignedLicenses to get evaluation information.
Set or return a data object type of LocalLicense or LicenseServer.
|
| sourceAvailable | xsd:boolean | Deprecated.
As of vSphere API 4.0, this property is not used.
Current state of the license source. License sources that are LocalSource
are always available.
|
Methods
| Methods defined in this Managed Object |
|---|
| AddLicense, CheckLicenseFeature, ConfigureLicenseSource, DecodeLicense, DisableFeature, EnableFeature, QueryLicenseSourceAvailability, QueryLicenseUsage, QuerySupportedFeatures, RemoveLicense, RemoveLicenseLabel, SetLicenseEdition, UpdateLicense, UpdateLicenseLabel |
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the LicenseManager used to make the method call. |
| licenseKey | xsd:string |
A license. E.g. a serial license.
|
| labels* | KeyValue[] |
array of key-value labels. Ignored by ESX Server.
|
Return Value
| Type | Description |
|---|---|
| LicenseManagerLicenseInfo | Returns information about the license specified in licenseKey. |
Faults
| Type | Description |
|---|---|
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
Events
| Type | |
|---|---|
| None |
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the LicenseManager used to make the method call. |
| host* | ManagedObjectReference
to a HostSystem |
Host to act on if LicenseManager is not on a host.
|
| featureKey | xsd:string |
Name of the feature to enable.
|
Return Value
| Type | Description |
|---|---|
| xsd:boolean | Returns true if the feature is enabled and false if it is not. |
Faults
| Type | Description |
|---|---|
| InvalidArgument | Thrown if a feature name is not found. |
| InvalidState | Thrown if the feature cannot be supported on the platform, potentially because the hardware configuration does not support it. |
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
Events
| Type | |
|---|---|
| None |
This changes the licensing source to be either served or local. Before changing the license source location, the API checks the number of licenses available at the new potential source to ensure there are at least as many licenses there as have been issued by the current source. If there are an equal or greater number of licenses at the new source, all licenses on the current source are released and then reacquired from the new source. If there are not enough licenses available on the new source to reissue all licenses, the operation fails.
This is used to configure the license source on an individual host.
PLATFORM Specific Notes: VirtualCenter - only supports a served source. the host parameter is mandatory. ESX Server - the host parameter is optional.
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the LicenseManager used to make the method call. |
| host* | ManagedObjectReference
to a HostSystem |
Host for which the license manager should be reconfigured.
|
| licenseSource | LicenseSource |
ServedSource or LocalSource.
|
Return Value
| Type | Description |
|---|---|
| None |
Faults
| Type | Description |
|---|---|
| CannotAccessLocalSource | Thrown if the local source cannot be accessed. |
| InvalidLicense | Thrown if the new license source is LocalLicenseSource and the license file is not valid. |
| LicenseServerUnavailable | Thrown if the license server is unreachable. |
| NotEnoughLicenses | Thrown if the new license source does not have enough licenses. |
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
Events
| Type | |
|---|---|
| None |
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the LicenseManager used to make the method call. |
| licenseKey | xsd:string |
A license. E.g. a serial license.
|
Return Value
| Type | Description |
|---|---|
| LicenseManagerLicenseInfo | Returns information about the license specified in licenseKey. |
Faults
| Type | Description |
|---|---|
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
Events
| Type | |
|---|---|
| None |
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the LicenseManager used to make the method call. |
| host* | ManagedObjectReference
to a HostSystem |
Host to act on if LicenseManager is not on a host.
|
| featureKey | xsd:string |
key of the feature to disable.
|
Return Value
| Type | Description |
|---|---|
| xsd:boolean | Returns true if the feature was disabled and false if not. |
Faults
| Type | Description |
|---|---|
| InvalidArgument | Thrown if a feature name is not found or it is not optional. |
| InvalidState | Thrown if the feature is in use. |
| LicenseServerUnavailable | Thrown if the license server is unavailable. |
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
Events
| Type | |
|---|---|
| None |
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the LicenseManager used to make the method call. |
| host* | ManagedObjectReference
to a HostSystem |
Host to act on if LicenseManager is not on a host.
|
| featureKey | xsd:string |
Name of the feature to enable.
|
Return Value
| Type | Description |
|---|---|
| xsd:boolean | Returns true if enabling the feature was successful, false otherwise. |
Faults
| Type | Description |
|---|---|
| InvalidArgument | Thrown if a feature name is not found or it is not optional. |
| InvalidState | Thrown if the feature cannot be supported on the platform, potentially because the hardware configuration does not support it. |
| LicenseServerUnavailable | Thrown if the license server is unavailable. |
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
Events
| Type | |
|---|---|
| None |
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the LicenseManager used to make the method call. |
| host* | ManagedObjectReference
to a HostSystem |
Use the license source of the specified host.
|
Return Value
| Type | Description |
|---|---|
| LicenseAvailabilityInfo[] |
Faults
| Type | Description |
|---|---|
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
Events
| Type | |
|---|---|
| None |
PLATFORM Specific Notes: VirtualCenter - Empty string returns the usage of non-host specific features. Must specify managed host to query. ESX Server - Host argument ignored.
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the LicenseManager used to make the method call. |
| host* | ManagedObjectReference
to a HostSystem |
Host to query for usage. If missing, query the server the
LicenseManager is on.
|
Return Value
| Type | Description |
|---|---|
| LicenseUsageInfo |
Faults
| Type | Description |
|---|---|
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
Events
| Type | |
|---|---|
| None |
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the LicenseManager used to make the method call. |
| host* | ManagedObjectReference
to a HostSystem |
Use the license source of the specified host.
|
Return Value
| Type | Description |
|---|---|
| LicenseFeatureInfo[] |
Faults
| Type | Description |
|---|---|
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
Events
| Type | |
|---|---|
| None |
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the LicenseManager used to make the method call. |
| licenseKey | xsd:string |
A licenses. E.g. a serial license.
|
Return Value
| Type | Description |
|---|---|
| None |
Faults
| Type | Description |
|---|---|
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
Events
| Type | |
|---|---|
| None |
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the LicenseManager used to make the method call. |
| licenseKey | xsd:string |
A license.
|
| labelKey | xsd:string |
A label key.
|
Return Value
| Type | Description |
|---|---|
| None |
Faults
| Type | Description |
|---|---|
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
Events
| Type | |
|---|---|
| None |
To determine what featureKey the current platform will accept, use querySourceAvailablity() at runtime, or consult the documentation for the current platform.
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the LicenseManager used to make the method call. |
| host* | ManagedObjectReference
to a HostSystem |
Host to act on if LicenseManager is not on a host.
|
| featureKey* | xsd:string |
Name of edition feature to select. If featureKey is not
set or set to empty string, the product becomes unlicensed.
|
Return Value
| Type | Description |
|---|---|
| None |
Faults
| Type | Description |
|---|---|
| InvalidArgument | Thrown if a feature key is not an edition feature key. |
| InvalidState | Thrown if the feature cannot be supported on the platform, potentially because the hardware configuration does not support it. |
| LicenseServerUnavailable | Thrown if the license server is unavailable. |
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
Events
| Type | |
|---|---|
| None |
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the LicenseManager used to make the method call. |
| licenseKey | xsd:string |
A license. E.g. a serial license.
|
| labels* | KeyValue[] |
array of key-value labels.
|
Return Value
| Type | Description |
|---|---|
| LicenseManagerLicenseInfo | Returns information about the license specified in licenseKey. |
Faults
| Type | Description |
|---|---|
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
Events
| Type | |
|---|---|
| None |
Parameters
| Name | Type | Description |
|---|---|---|
| _this | ManagedObjectReference | A reference to the LicenseManager used to make the method call. |
| licenseKey | xsd:string |
A license.
|
| labelKey | xsd:string |
A label key.
|
| labelValue | xsd:string |
Value for the label.
|
Return Value
| Type | Description |
|---|---|
| None |
Faults
| Type | Description |
|---|---|
| RuntimeFault | Thrown if any type of runtime fault is thrown that is not covered by the other faults; for example, a communication error. |
Events
| Type | |
|---|---|
| None |
| Top of page | Local Properties | Local Methods | |
| Managed Object Types | Data Object Types | All Properties | All Methods |


Contract manager server
This module implements the contract manager server process, which runs on the Erlang server side, between the UBF driver (or the driver for whatever protocol is being used "over the wire", e.g. JSON-RPC) and the plugin handler server.
In the diagram below, the "Client" is actually the UBF driver (using UBF, EBF, JSON, JSON-RPC, or other transport protocol) that acts on behalf of the remote client. The "Server" is actually the plugin handler server, which acts as an intermediary between the actual server application.
| do_eventIn/4 | |
| do_eventOut/4 | |
| do_lpcIn/4 | |
| do_lpcOut/9 | |
| do_lpcOutError/6 | |
| do_rpcIn/4 | |
| do_rpcOut/9 | |
| do_rpcOutError/5 | |
| do_rpcOutError/6 | |
| start/1 | |
| start/3 |
do_eventIn(Msg, State, Mod, TLogMod) -> any()
do_eventOut(Msg, State, Mod, TLogMod) -> any()
do_lpcIn(Q, State, Mod, TLogMod) -> any()
do_lpcOut(Ref, Q, State, Mod, Reply, ReplyState, NewState, NewMod, TLogMod) -> any()
do_lpcOutError(Ref, Q, State, Mod, Error, TLogMod) -> any()
do_rpcIn(Q, State, Mod, TLogMod) -> any()
do_rpcOut(Ref, Q, State, Mod, Reply, ReplyState, NewState, NewMod, TLogMod) -> any()
do_rpcOutError(Q, State, Mod, Error, TLogMod) -> any()
do_rpcOutError(Ref, Q, State, Mod, Error, TLogMod) -> any()
start(SpawnOpts::list()) -> pid()
start(SimpleRPC::bool(), VerboseRPC::bool(), SpawnOpts::list()) -> pid()
Generated EDoc, $Id$


[ {{ transaction.amount | currency: transaction.CURRENCY_CODE:'symbol' }}]
Package Name - {{transaction.package.name}}
Package Name -{{transaction.package.description}}
Payment Gateway -{{transaction.payment_gateway.name}}
{{transaction.created_at | date: 'short'}}


vignettes/predict.Rmd
predict.Rmd
predict_classes()
function predicts sample classes based on cola classification. It is mainly used in the following two scenarios:
To use a cola classification, users need to select the result from a specific top-value method and partitioning method, i.e., the input should be a ConsensusPartition
object. In the following example, we use the analysis from Golub dataset and we take the result from the method ATC:skmeans
.
data(golub_cola) res = golub_cola["ATC:skmeans"] res
## A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
## On a matrix with 4116 rows and 72 columns.
## Top rows (412, 824, 1235) are extracted by 'ATC' method.
## Subgroups are detected by 'skmeans' method.
## Performed in total 750 partitions by row resampling.
## Best k for subgroups seems to be 3.
##
## Following methods can be applied to this 'ConsensusPartition' object:
## [1] "cola_report" "collect_classes" "collect_plots"
## [4] "collect_stats" "colnames" "compare_signatures"
## [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
## [10] "get_anno_col" "get_anno" "get_classes"
## [13] "get_consensus" "get_matrix" "get_membership"
## [16] "get_param" "get_signatures" "get_stats"
## [19] "is_best_k" "is_stable_k" "membership_heatmap"
## [22] "ncol" "nrow" "plot_ecdf"
## [25] "predict_classes" "rownames" "select_partition_number"
## [28] "show" "suggest_best_k" "test_to_known_factors"
predict_classes()
needs at least three arguments: a ConsensusPartition
object, the number of subgroups and the new matrix. The first two are for extracting the classification as well as the signatures that best separate subgroups. The new matrix should have the same number of rows as the matrix used for cola analysis, also the row orders should be the same. Be careful that the scaling of the new matrix should also be the same as the one applied in cola analysis.
The prediction is based on the signature centroid matrix. The processes are as follows:
ConsensusPartition
object and a selected k, the signatures that discriminate classes are extracted by get_signatures()
. If number of signatures is more than 2000, only 2000 signatures are randomly sampled.silhouette_cutoff
(0.5 as the default) are removed for calculating the centroids.The class prediction is applied as follows. For each sample in the new matrix, the task is basically to test which signature centroid the current sample is the closest to. There are three methods: the Euclidean distance, cosine distance (it is 1-cos(x, y)
) and the correlation (Spearman) distance.
For the Euclidean distance and cosine distance method, for the vector denoted as \(x\) which corresponds to sample \(i\) in the new matrix, to test which class should be assigned to sample \(i\), the distance between sample \(i\) and all \(k\) signature centroids are calculated and denoted as \(d_1\), \(d_2\), …, \(d_k\). The class with the smallest distance is assigned to sample \(i\).
To test whether the class assignment is statistically significant, or to test whether the class that is assigned is significantly closest to sample \(i\), we design a statistic named “difference ratio”, denoted as \(r\) and calculated as follows. First, The distances for \(k\) centroids are sorted increasingly, and we calculate \(r\) as:
\[r = \frac{|d_{(1)} - d_{(2)}|}{\bar{d}}\]
which is the difference between the smallest distance and the second smallest distance, normalized by the mean distance. To test the statistical significance of \(r\), we randomly permute rows of the signature centroid matrix and calculate \(r_{rand}\). The random permutation is performed 1000 times and the p-value is calculated as the proportion of \(r_{rand}\) being larger than \(r\).
For the correlation method, the distance is calculated as the Spearman correlation between sample \(i\) and signature centroid \(k\). The label for the class with the maximal correlation value is assigned to sample \(i\). The p-value is simply calculated by stats::cor.test()
between sample \(i\) and centroid \(k\).
If a sample is tested with a p-value higher than 0.05, the corresponding class label is set to NA
.
To demonstrate the use of predict_classes()
, we use the same matrix as for cola analysis.
mat = get_matrix(res)
Note the matrix was row-scaled in cola analysis, thus, mat
should also be scaled with the same method (z-score scaling).
And we predict the class of mat2
with the 3-group classification from res
.
cl = predict_classes(res, k = 3, mat2)
## The matrix has been scaled in cola analysis, thus the new matrix should also be scaled
## with the same method ('z-score'). Please double check.
## Set `help = FALSE` to suppress this message.
##
## * 70/72 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
## * cache hash: d7b0ab9e8457e94218da8307be387574 (seed 888).
## * calculating row difference between subgroups by Ftest.
## * split rows into 4 groups by k-means clustering.
## * 2076 signatures (50.4%) under fdr < 0.05, group_diff > 0.
 The left heatmap corresponds to the new matrix and the right small heatmap corresponds to the signature centroid matrix. The purple annotation on top of the first heatmap illustrates the distance of each sample to the k signatures.
And if we change to correlation method:
cl = predict_classes(res, k = 3, mat2, dist_method = "correlation")
## The matrix has been scaled in cola analysis, thus the new matrix should also be scaled
## with the same method ('z-score'). Please double check.
## Set `help = FALSE` to suppress this message.
##
## * 70/72 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
## * cache hash: d7b0ab9e8457e94218da8307be387574 (seed 888).
## * calculating row difference between subgroups by Ftest.
## - row difference is extracted from cache.
## * use k-means partition that are already calculated in previous runs.
## * 2076 signatures (50.4%) under fdr < 0.05, group_diff > 0.
 Following is how we manually generate the signature centroid matrix for 3-group classification from Golub dataset:
tb = get_signatures(res, k = 3, plot = FALSE)
## * 70/72 samples (in 3 classes) remain after filtering by silhouette (>= 0.5).
## * cache hash: d7b0ab9e8457e94218da8307be387574 (seed 888).
## * calculating row difference between subgroups by Ftest.
## - row difference is extracted from cache.
## * use k-means partition that are already calculated in previous runs.
## * 2076 signatures (50.4%) under fdr < 0.05, group_diff > 0.
# the centroids are already in `tb`, both scaled and unscaled, we just simply extract it sig_mat = tb[, grepl("scaled_mean", colnames(tb))] sig_mat = as.matrix(sig_mat) colnames(sig_mat) = paste0("class", seq_len(ncol(sig_mat))) head(sig_mat)
## class1 class2 class3
## [1,] -0.5519215 0.52395127 0.3740407
## [2,] -0.4025209 0.06789322 0.7546084
## [3,] -0.3077090 0.58853214 -0.2459700
## [4,] -0.1548451 0.47963596 -0.4051056
## [5,] -0.2048139 -0.15871813 0.6803041
## [6,] -0.3427458 0.40763038 0.1061578
And sig_mat
can be used in predict_classes()
:
cl = predict_classes(sig_mat, mat2) cl = predict_classes(sig_mat, mat2, dist_method = "correlation")
## R version 4.0.2 (2020-06-22)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.5
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] cola_1.5.6 knitr_1.29 markdown_1.1
##
## loaded via a namespace (and not attached):
## [1] mclust_5.4.6 Rcpp_1.0.5 lattice_0.20-41 circlize_0.4.11
## [5] png_0.1-7 assertthat_0.2.1 rprojroot_1.3-2 digest_0.6.25
## [9] slam_0.1-47 R6_2.4.1 backports_1.1.9 stats4_4.0.2
## [13] RSQLite_2.2.0 evaluate_0.14 httr_1.4.2 GlobalOptions_0.1.2
## [17] rlang_0.4.7 annotate_1.66.0 blob_1.2.1 magick_2.4.0
## [21] S4Vectors_0.26.1 GetoptLong_1.0.3 Matrix_1.2-18 rmarkdown_2.3
## [25] pkgdown_1.5.1 desc_1.2.0 splines_4.0.2 stringr_1.4.0
## [29] RCurl_1.98-1.2 bit_4.0.4 compiler_4.0.2 eulerr_6.1.0
## [33] xfun_0.16 microbenchmark_1.4-7 BiocGenerics_0.34.0 shape_1.4.4
## [37] htmltools_0.5.0 IRanges_2.22.2 matrixStats_0.56.0 XML_3.99-0.5
## [41] crayon_1.3.4 MASS_7.3-52 bitops_1.0-6 grid_4.0.2
## [45] xtable_1.8-4 DBI_1.1.0 magrittr_1.5 skmeans_0.2-12
## [49] stringi_1.4.6 impute_1.62.0 genefilter_1.70.0 fs_1.5.0
## [53] xml2_1.3.2 brew_1.0-6 vctrs_0.3.4 rjson_0.2.20
## [57] RColorBrewer_1.1-2 tools_4.0.2 bit64_4.0.5 Biobase_2.48.0
## [61] parallel_4.0.2 survival_3.2-3 yaml_2.2.1 clue_0.3-57
## [65] AnnotationDbi_1.50.3 colorspace_1.4-1 cluster_2.1.0 ComplexHeatmap_2.5.5
## [69] memoise_1.1.0


This is the main heading
Rent from people in over 34,000 cities and 192 countries.
Rock Paper Scissors game
Temperature Converter


Here's diag-btn: a simple web UI improvement for mobile interfaces.
It supports individual buttons and stacked buttons up to any depth. Here's what it looks like:


Constants
(constant) Infinity :number
The name
Infinity
refers to the special number value Infinity
.
See ECMAScript Specification, Section 4.3.23
Type:
- number
(constant) NaN :number
The name
NaN
refers to the special number value NaN
("not a number"). Note that
NaN
is a number, as specified by is_number
.
See ECMAScript Specification, Section 4.3.24
Type:
- number
(constant) undefined :undefined
The name
undefined
refers to the special value undefined
.
See also textbook explanation in section 1.1.2.
Type:
Functions
display(v) → {value}
Displays the value
v
in the console. The notation used for the display of values
is consistent with JSON, but also displays undefined
and function objects.
See also textbook example.
Parameters:
| Name | Type | Description |
|---|---|---|
v |
value | to be displayed |
Returns:
v, the argument value
- Type
- value
display(v, s) → {value}
Displays the given string
s
, followed by a space character, followed by the
value v
in the console. The notation used for the display of values
is consistent with
JSON,
but also displays undefined
and function objects.
Parameters:
| Name | Type | Description |
|---|---|---|
v |
value | to be displayed |
s |
string | to be displayed, preceding v |
Returns:
v, the first argument value
- Type
- value
error(v) → {value}
Displays the value
v
in the console with error flag.
The evaluation
of any call of error
aborts the running program immediately.
The notation used for the display of values
is consistent with JSON, but also displays undefined
and function objects.
See also textbook example.
Parameters:
| Name | Type | Description |
|---|---|---|
v |
value | to be displayed |
Returns:
v, the argument value
- Type
- value
error(v, s) → {value}
Displays the given string
s
, followed by a space character, followed by the
value v
in the console with error flag.
The evaluation
of any call of error
aborts the running program immediately.
The notation used for the display of values
is consistent with
JSON,
but also displays undefined
and function objects.
Parameters:
| Name | Type | Description |
|---|---|---|
v |
value | to be displayed |
s |
string | to be displayed, preceding v |
Returns:
v, the first argument value
- Type
- value
is_boolean(v) → {boolean}
checks whether a given value is a boolean
Parameters:
| Name | Type | Description |
|---|---|---|
v |
value | to be checked |
Returns:
indicating whether the value is a boolean
- Type
- boolean
is_function(v) → {boolean}
checks whether a given value is a function
Parameters:
| Name | Type | Description |
|---|---|---|
v |
value | to be checked |
Returns:
indicating whether the value is a function
- Type
- boolean
is_number(v) → {boolean}
checks whether a given value is a number.
See also textbook example.
Parameters:
| Name | Type | Description |
|---|---|---|
v |
value | to be checked |
Returns:
indicating whether the value is a number
- Type
- boolean
is_string(v) → {boolean}
checks whether a given value is a string.
See also textbook example.
Parameters:
| Name | Type | Description |
|---|---|---|
v |
value | to be checked |
Returns:
indicating whether the value is a string
- Type
- boolean
is_undefined(v) → {boolean}
checks whether a given value is the special value
undefined
Parameters:
| Name | Type | Description |
|---|---|---|
v |
value | to be checked |
Returns:
indicating whether the value is
undefined
- Type
- boolean
parse_int(s, i) → {number}
Interprets a given string
Examples:
See ECMAScript Specification, Section 18.2.5 for details.
s
as an integer,
using the positive integer i
as radix,
and returns the respective value.
Examples:
parse_int("909", 10)
returns the number
909
, and parse_int("-1111", 2)
returns the number
-15
.See ECMAScript Specification, Section 18.2.5 for details.
Parameters:
| Name | Type | Description |
|---|---|---|
s |
string | string to be converted |
i |
number | radix |
Returns:
result of conversion
- Type
- number
prompt(s) → {string}
Pops up a window that displays the string
s
, provides
an input line for the user to enter a text, a Cancel
button and an OK
button.
The call of prompt
suspends execution of the program until one of the two buttons is pressed. If
the OK
button is pressed, prompt
returns the entered text as a string.
If the Cancel
button is pressed, prompt
returns a non-string value.
Parameters:
| Name | Type | Description |
|---|---|---|
s |
string | to be displayed in popup |
Returns:
entered text
- Type
- string
runtime() → {number}
Returns number of milliseconds elapsed since January 1, 1970 00:00:00 UTC.
See also textbook example.
Returns:
current time in milliseconds
- Type
- number
stringify(v,) → {string}
returns a string that represents the value
v
, using a
notation that is is consistent with
JSON,
but also displays undefined
and function objects.
See also textbook example.
Parameters:
| Name | Type | Description |
|---|---|---|
v, |
value | the argument value |
Returns:
string representation of v
- Type
- string


Syllabus
TENTATIVE SYLLABUS/SCHEDULE SUBJECT TO CHANGE
Welcome to APCOMP 215 / CSCIE-115: Advanced practical data science
Course helpline<EMAIL_ADDRESS>Instructor: Pavlos Protopapas
Sessions: Tuesdays and Thursdays - 2:15 PM - 3:30 PM
TFs: Rashmi Banthia, Shivas Jayaram, Andrew Smith, Gordon Hew
Office Hours: TBD
Overview of the Course
This course aims to review existing Deep Learning flow while applying it to a real-world problem. Then we will build and deploy an application that uses the deep learning model to understand how to productionize models. This course follows the CS109 A/B model of balancing between concept, theory, and implementation.
Split into three parts; the course starts with the review of Deep Learning concepts for data and modeling and how to apply them to different tasks, including vision and language tasks. The next part will be Development, where you use the models you trained in part 1 and incorporate them into real-world applications. Finally, you will Deploy the application in Google Cloud Platform (GCP). The three parts will cover in detail topics such as Transfer learning, Containerization using Docker, and Scaling deployments using Kubernetes.
At the end of this module, you will build efficient deep learning models and design, build and deploy applications that scale.
Course Topics
Project Outline:
- Introduction to Projects
- Problem Definition
- Proposed Solutions
- Project Scope
Deep Learning:
-
Data
- Data Pipelines
- TensorFlow Data
- TensorFlow Records
- Dask
- Cloud Storage
-
Models
- Computer Vision: Classification
- Computer Vision: Segmentation
- NLP & Language Models
- Transfer Learning and SOTA Models
- Distillation and Compression
Development:
-
Design
- Virtual Environments, Virtual Machines
- Containers & Docker
- App Design
-
Develop
- Setup and Code organization
- APIs and Model serving
- App frontend
Operations:
- Deployment, Scaling, & Automation
- Google Cloud Platform (GCP)
- Kubernetes
- Ansible
Prerequisites
Your are expected to know the following:
- Good working knowledge of python
- Good understanding on the
Tensorflow
Deep Learning framework - Basic shell commands
Programming:
- Experience with Python: Functions, Classes, Modules, NumPy, Pandas, Tensorflow
- Basic Data Structures: Dictionaries and Lists
- File I/O
Grading Breakdown
| Grading Breakdown | |
|---|---|
| Quiz | 10% |
| Exercises | 20% |
| Milestone 1 | 5% |
| Milestone 2 | 15% |
| Milestone 3 | 20% |
| Final Presentation & Deliverable | 30% |
Course Components
The course includes the following every week:
- 2 Sessions (Tue, Thu)
- Office hours
Sessions
Before the Tuesday session begins, students are expected to complete a pre-class reading assignment and and attempt a quiz based on the same. The sessions will be one and half hours and will have the following layout:
- Sessions will help students develop the intuition for the core concepts, provide the necessary mathematical background, and provide guidance on technical details.
- Sessions will be accompanied by relevant examples to clarify key concepts and techniques.
- Part of the session will be an instructor driven in-depth implementation walk through of code related to the topics covered. This will help you understand the concepts and give you starter code that will help in your projects.
Student participation is highly encouraged in sessions.
Reading Assignments
The course schedule includes weekly readings which will be available before the lecture. The goal of the reading assignments is to prepare for class, to familiarize yourself with new terminology and definitions, and to determine which part of the subject needs more attention.
Each Tuesday session will have a short quiz at the beginning which covers the assigned reading for that week.
Homework
Code that cannot be completed in class will be left as an exercise for the student to complete as homework. We will go over hints to complete your homework which will be an individual effort.
Project
During the entire course you will work in teams and implement a project. The various topics in the class are designed to help you build milestones in an incremental fashion and build towards the end goal. The final outcome with your project will be a fully working AI App.
- Project groups need to be formed by the first week of class
- Group size : 4
- Select a project from the list given or bring your own
-
Criteria for projects are:
- Deep learning task implemented should include preferably both computer vision and language models
- The end product should be a deployable app that uses the models in the backend in some form
-
If you plan to bring your own project idea, the following additional criteria must be met:
- Dataset size 5 Gigabytes or larger
- Data should include preferably images and text
Please find a more detailed summary of all projects here. [TODO]
Deadlines
- All quizzes are due before the next Tuesday session.
- All homework are due before the next Thursday session.
- There will be no extensions given for the homework and quizzes.
- The deadline for the project milestones will be announced in the scaffold.
Software
All softwares required for this course and installation instructions/help will be provided in first week.
Course Policies
Getting Help
For questions about homework, course content, package installation, after you have tried to troubleshoot yourselves, the process to get help is:
- Post the question on ED and hopefully, your peers will answer. Note that questions on ED are visible to everyone. The teaching staff monitors the posts.
- Attend Office Hours, this is the best way to get help.
- For private matters send an email to the instructor.
Academic Honesty
Ethical behavior is an important trait, from ethically handling data to the attribution of code and work of others. Thus, in AC215, we give a strong emphasis on Academic Honesty. As a student, your best guidelines are to be reasonable and fair.
We have included some ideas below of acceptable and not acceptable behaviors. Engaging in not acceptable behavior regarding academic honesty will be handled accordingly.
Please be responsible and when in doubt ask the course instructors.
ACCEPTABLE:
- Discussing materials and engaging in OH.
- Helping debug.
- Using a few lines of code found online or another forum as long as you cite the origin and attribute authorship of code.
- Searching online to expand your knowledge and for debugging
- Using a tutor, provided the tutor does not do your work for you.
NOT ACCEPTABLE:
- Accessing a solution to some problem prior to submitting your own.
- Failing to cite the origins of code or techniques that you discover outside of the course’s own lessons and integrate into your own work.
- Paying or offering to pay an individual for work that you may submit as your own.
- Providing or making available solutions to problem sets to individuals who might take this course in the future.
- Searching for or soliciting outright solutions to problem sets online or elsewhere.
Accommodations for students with disabilities
Students needing academic adjustments or accommodations because of a documented disability must present their Faculty Letter from the Accessible Education Office (AEO) and speak with Pavlos by the end of the third week of the term: Friday, September 17. Failure to do so may result in us being unable to respond in a timely manner. All discussions will remain confidential.


Millie Bobby Brown tells UN summit about toll taken by bullies
The teenager is Unicef’s youngest Goodwill Ambassador.
Millie Bobby Brown and David Beckham have called on world leaders to uphold children’s rights.
The stars, who are Unicef Goodwill Ambassadors, hosted a global summit at the UN headquarters in New York.
Stranger Things actress Brown, who at 15 is Unicef’s youngest Goodwill Ambassador, spoke about an issue that is “very personal to me. Something that so often goes unnoticed – but causes real suffering. Bullying.
 I take nothing for granted. But I also know what it feels like to be vulnerable,” she said.
“At school, I was bullied by a group of students. I remember feeling helpless. School used to be a safe place. Now I was scared to go.
“I was lucky. With the help of my friends, family and people around me, I was able to overcome these negative feelings and take my power back.
“But millions of children aren’t so lucky. They’re still struggling in the darkness. Wrestling with fear. With insecurity.”
Brown said: “Bullying and online threats are never harmless. Never just words. It puts children’s mental health at risk. It causes stress.
“And in the most extreme cases, and in areas around the world where conflict and violence are daily threats, it can lead to self-harm. Sickness. And even suicide.”
“In my role as Goodwill Ambassador, I will continue talking about this issue wherever I go.”
Speaking on World Children’s Day, she called for “real change… policies, programmes, laws and investments that keep children safe.”
Beckham, 44, said in his speech: “As leaders, as public figures, as parents, and of course, as human beings, we must do more to protect children’s dreams. Because the future doesn’t belong to us. It belongs to children.”
UN member states have been asked to align themselves to a Global Pledge promising to renew their commitment to the Convention On The Rights Of The Child and implement child rights fit for the 21st century.
Unicef’s executive director Henrietta Fore said: “Around the world, children and young people are taking the lead and demanding urgent action on the issues they care about, like the climate crisis, the rise of mental illness and the lack of opportunities.
“This World Children’s Day provides world leaders with a momentous opportunity to heed these calls and recommit to the rights of every child, now and for future generations.”
More information on Unicef UK’s World Children’s Day is at www.unicef.org.uk/change-the-world.


Package com.mygdx.auber.entities
Class NPC
- java.lang.Object
-
- com.badlogic.gdx.graphics.g2d.TextureRegion
-
- com.badlogic.gdx.graphics.g2d.Sprite
-
- com.mygdx.auber.entities.NPC
-
- Direct Known Subclasses:
CrewMembers
,Infiltrator
public abstract class NPC extends com.badlogic.gdx.graphics.g2d.Sprite
NPCs use nodes to walk around and A* to navigate between them, the nodes are generated and stored in GraphCreator, while MapGraph is used to search and manipulate the node graph. Generally, NPCs are updated through updateNPC, which calls each npcs step method, which makes them moves, sets their sprite scale, checks if they have reached the next node etc Crewmember is very simple, they walk around randomly and wait for a random amount of time Infiltrator is more complex, they sometimes go to destroy keysystems, and can use abilities
-
-
Method Summary
All Methods Static Methods Instance Methods Abstract Methods Concrete Methods Modifier and Type Method Description void
checkCollision(float speed)
Checks whether the NPC has made it to the next node.void
clearPathQueue()
Clears this NPC's pathQueue.static void
disposeNPC()
Dispose method to be called in dispose method of screen.float
getElapsedTime()
Returns how long this NPC has been waiting for.int
getIndex()
Gets the index of this NPC.com.badlogic.gdx.utils.Queue<Node>
getPathQueue()
Returns the path this NPC is following.Node
getPreviousNode()
Gets the previous node that this NPC visited.com.badlogic.gdx.math.Vector2
getVelocity()
Gets this NPC's velocity.void
incrementElapsedTime(float delta)
Increases the elapsed time by the given value.void
moveNPC(float deltaTime)
Moves the NPC based on their movement vector, and sets their sprite in the direction of movement.abstract void
reachDestination()
A placeholder function to be superceded by subclasses own reachDestination().void
reachNextNode(float speed)
Called when NPC has reached a node, sets the next node to be moved to, or if the path queue is empty, destination is reached.static void
render(com.badlogic.gdx.graphics.g2d.Batch batch)
Render method for rendering all NPCs.void
resetElapsedTime()
Sets the elapsed time to 0.void
setGoal(Node goal, float speed)
Sets the goal node and calculates the path to take there.void
setIndex(int newIndex)
Sets the index of this NPC.void
setSpeedToNextNode(float speed)
Sets the velocity towards the next node.void
setVelocity(com.badlogic.gdx.math.Vector2 newVelocity)
Sets this NPC's velocity.static void
updateNPC(Player p, float delta)
Updates every NPC, to be called in a screens update method.-
Methods inherited from class com.badlogic.gdx.graphics.g2d.Sprite
draw, draw, flip, getBoundingRectangle, getColor, getHeight, getOriginX, getOriginY, getRotation, getScaleX, getScaleY, getVertices, getWidth, getX, getY, rotate, rotate90, scale, scroll, set, setAlpha, setBounds, setCenter, setCenterX, setCenterY, setColor, setColor, setFlip, setOrigin, setOriginBasedPosition, setOriginCenter, setPackedColor, setPosition, setRegion, setRotation, setScale, setScale, setSize, setU, setU2, setV, setV2, setX, setY, translate, translateX, translateY
-
Methods inherited from class com.badlogic.gdx.graphics.g2d.TextureRegion
getRegionHeight, getRegionWidth, getRegionX, getRegionY, getTexture, getU, getU2, getV, getV2, isFlipX, isFlipY, setRegion, setRegion, setRegion, setRegion, setRegionHeight, setRegionWidth, setRegionX, setRegionY, setTexture, split, split
-
-
-
-
Field Detail
-
mapGraph
public MapGraph mapGraph
Mapgraph for the NPC to reference.
-
-
Constructor Detail
-
NPC
public NPC(com.badlogic.gdx.graphics.g2d.Sprite sprite, Node start, MapGraph newMapGraph, float speed)
Constructor for NPC.- Parameters:
sprite
- Sprite to be used for the NPCstart
- Node for the NPC to start atnewMapGraph
- mapGraph for the NPC to referencespeed
- The speed of this NPC.
-
NPC
public NPC(com.badlogic.gdx.graphics.g2d.Sprite sprite, float x, float y, MapGraph newMapGraph, float speed)
-
-
Method Detail
-
updateNPC
public static void updateNPC(Player p, float delta)
Updates every NPC, to be called in a screens update method.- Parameters:
p
- The current instance of the player.delta
- Float of time between last and current frame, used for movement
-
setGoal
public void setGoal(Node goal, float speed)
Sets the goal node and calculates the path to take there.- Parameters:
goal
- Node to move NPC to.speed
- The speed of this NPC.
-
checkCollision
public void checkCollision(float speed)
Checks whether the NPC has made it to the next node.- Parameters:
speed
- The speed of this NPC.
-
reachNextNode
public void reachNextNode(float speed)
Called when NPC has reached a node, sets the next node to be moved to, or if the path queue is empty, destination is reached.- Parameters:
speed
- The speed of this NPC.
-
setSpeedToNextNode
public void setSpeedToNextNode(float speed)
Sets the velocity towards the next node.- Parameters:
speed
- The speed of this NPC.
-
moveNPC
public void moveNPC(float deltaTime)
Moves the NPC based on their movement vector, and sets their sprite in the direction of movement.- Parameters:
deltaTime
- The time since the previous frame in seconds.
-
render
public static void render(com.badlogic.gdx.graphics.g2d.Batch batch)
Render method for rendering all NPCs.- Parameters:
batch
- Batch for the NPCs to render in.
-
disposeNPC
public static void disposeNPC()
Dispose method to be called in dispose method of screen.
-
reachDestination
public abstract void reachDestination()
A placeholder function to be superceded by subclasses own reachDestination().
-
getIndex
public int getIndex()
Gets the index of this NPC.- Returns:
- the index of this NPC.
-
setIndex
public void setIndex(int newIndex)
Sets the index of this NPC.- Parameters:
newIndex
- The new index for this NPC.
-
getVelocity
public com.badlogic.gdx.math.Vector2 getVelocity()
Gets this NPC's velocity.- Returns:
- this NPC's velocity.
-
setVelocity
public void setVelocity(com.badlogic.gdx.math.Vector2 newVelocity)
Sets this NPC's velocity.- Parameters:
newVelocity
- The new velocity for this NPC.
-
getPreviousNode
public Node getPreviousNode()
Gets the previous node that this NPC visited.- Returns:
- The previous node that this NPC visited.
-
getElapsedTime
public float getElapsedTime()
Returns how long this NPC has been waiting for.- Returns:
- the elapsedTime variable.
-
resetElapsedTime
public void resetElapsedTime()
Sets the elapsed time to 0.
-
getPathQueue
public com.badlogic.gdx.utils.Queue<Node> getPathQueue()
Returns the path this NPC is following.- Returns:
- The path that this NPC is following.
-
incrementElapsedTime
public void incrementElapsedTime(float delta)
Increases the elapsed time by the given value.- Parameters:
delta
- The amount to increase the elapsed time by.
-
clearPathQueue
public void clearPathQueue()
Clears this NPC's pathQueue.
-
-


Memory Game
Timer: 60
Score: 0
Tries: 0
New Game
Game Over!
Give another try!
Hurry! Won the memory game
Wanna try!


You need patience, Frank Gogo advices unsigned artistes
by Abdulai Haruna, GNAAccra, Nov. 24, GNA - Mr Frank Gogo, CEO of Worldmap Records, has called on young artistes to be patient as efforts are being made to develop and promote their talents.
He said many people now talk about the success of Stonebwoy but do they also remember how long it took for him to study and emulate his mentor Batman Samini.
Mr Gogo said this in an interview with the Ghana News Agency.
He said ‘Worldmap Records’, which started about three years ago, is here to assist young talents in their effort to produce good music and its record now boasts of renowned stars like KK Fosu, Shotkode and Pacy.
Mr Gogo said many young artistes have come to seek their aid and efforts are being made to finalise agreements adding that they would be selected based on their quality music styles, stage performances and how they carry themselves in public.
He said the music industry is tough and many radio deejays are unhelpful with their unusual demands and this does not often inure to the benefit of the music producer and the musician.
Mr Gogo called for investors to come and aid the sector and facilitate efforts being made by many upcoming musicians.
GNA


This library provides a means to include Highcharts visualizations
within a GWT application. The logical starting point is the {@link org.moxieapps.gwt.highcharts.client.Chart} class,
which provides the primary GWT widget that can be used to create a chart and add it to a GWT container.
To use, first, add the jar file to your project, and include the library in the GWT xml
configuration file for your module:
<inherits name="org.moxieapps.gwt.highcharts.Highcharts"/>
Then, the basic usage of the API is as follows:
// Create the chart widget and configure it using chainable methods
Chart chart = new Chart()
.setType(Series.Type.SPLINE)
.setChartTitleText("Nice Chart")
.setMarginRight(10);
// Add data series to the chart
Series series = chart.createSeries()
.setPoints(new Number[] { 163, 203, 276, 408, 547, 729, 628 });
chart.addSeries(series);
// Add the chart to any GWT container as a normal widget
RootPanel.get().add(chart);
Note that in order for this widget to function you must have included the Highcharts javascript
library and any of its dependencies in the page that the widget will run inside of. E.g.:
<script type="text/javascript" src="http://ajax.googleapis.com/ajax/libs/jquery/1.4.2/jquery.min.js"></script>
<script type="text/javascript" src="js/highcharts.js"></script>
<!-- Optionally, add a highcharts theme file -->
<script type="text/javascript" src="js/themes/gray.js"></script>
<!-- Optionally, include the highcharts exporting module -->
<script type="text/javascript" src="js/modules/exporting.js"></script>
Important note: if you're using the {@link org.moxieapps.gwt.highcharts.client.StockChart} visualization, you'll want
to include the "highstock.js" file in your page instead of the "highcharts.js" file. The highstock.js file includes
all of the capabilities of the core "highcharts.js" file, so including it in your page allows you to use
both {@link org.moxieapps.gwt.highcharts.client.Chart} and {@link org.moxieapps.gwt.highcharts.client.StockChart}
visualization simultaneously.
Please see the GWT Highcharts project page
for more details on how to use this library, and in particular the
showcase application which provides
a collection of code examples that show various usage patterns.


Ghost of the Ancient Railroad Engineer:
Somewhere in this railroad station, I think there is a
hammer with engravings on its handle
.
I think one of the railroad workers
knows where it is.


orwell
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Print a set of API resources generated from instructions in a kustomization.yaml file.
The argument must be the path to the directory containing the file, or a git repository URL with a path suffix specifying same with respect to the repository root.
kubectl kustomize somedir
Examples:
# Use the current working directory
kubectl kustomize .
# Use some shared configuration directory
kubectl kustomize /home/configuration/production
# Use a URL
kubectl kustomize github.com/kubernetes-sigs/kustomize.git/examples/helloWorld?ref=v1.0.6
kubectl kustomize <dir> [flags] [options]
Use "kubectl options" for a list of global command-line options (applies to all commands).


Make sure to remember your password as you will need it to log in manually or connect with our services for programming exercises.
If you forget your password, you can reset it on the login page. You can also change your password now:
Change password


Obfuscare.
We care about your product.
We can scare attackers off.
Next-generation obfuscation
Next-generation obfuscation
We provide a holistic obfuscation for your product that intermingles all the executable code and data, while preserving the original semantics faithfully. Using various techniques for introducing tight coupling between different segments of code and data, including lossless compression with LSTM neural networks, obfuscare generates an executable in which everything is coupled with everything via everything else, very difficult to disentangle.


//= template/head.html
Set your destination to Antalya airport (AYT) and we shall meet you there.
This time we’re bringing together our Gang in a luxurious five-star hotel in the Turkish Riviera.
We’re turning Antalya’s Gloria Hotel & Resort into the #CoinsGang hub for four days. Network all day and party till sunrise. We believe in the power of community. The more people in our gang, the more meaningful the connections. Let’s grow together.
Three years ago we were crazy enough to bring a blockchain event to the seas with our first Blockchain Cruise. Since then, we have achieved 7 unique events from the Caribbean to Asia, to Europe.
event attendees from
80+ countries
companies promoted
their companies
audience reached during the event
We invite you to experience a business event surrounded by legendary hospitality. Lavish accommodations at the Gloria Hotels & Resort in Antalya with exquisite service always at your fingertips. And that’s just the standard fare.
Three hotels in a sprawling oasis. Kick back at the 45-hole golf course, the largest in Turkey. Our VIP guests are invited to wake up facing the links in a luxury villa.


__HEADER_SIDE__
The page you've requested cannot be found. If you think this is an error, plese contact us:
__EMAIL__
.
__FOOTER__


We pick the 10 stocks that have the lowest P/E ratio in our universe, at the beginning of each year, and we invest an equal amount of capital in each stock.
To construct the universe, first, we eliminate stocks which don't have fundamental data and
stocks that have a lower price than $5 per share, using the CoarseSelectionFunction
.
def CoarseSelectionFunction(self, coarse): if self.yearly_rebalance: # drop stocks which have no fundamental data and have low price CoarseWithFundamental = [x for x in coarse if x.HasFundamentalData and x.Price > 5] sortedByDollarVolume = sorted(CoarseWithFundamental, key=lambda x: x.DollarVolume, reverse=False) top = sortedByDollarVolume[:self._NumCoarseStocks] return [i.Symbol for i in top] else: return []
Then, in the FineSelectionFunction
, we retrieve the list of 10 stocks, that have the lowest P/E ratio.
def FineSelectionFunction(self, fine): if self.yearly_rebalance: fine = [x for x in fine if (x.ValuationRatios.PERatio > 0)] for i in fine: i.PERatio = float(i.ValuationRatios.PERatio) sortedPERatio = sorted(fine, key=lambda x: x.PERatio,reverse=True) self.filtered_fine = [i.Symbol for i in sortedPERatio[:self._NumStocksInPortfolio]] self.yearly_rebalance = False return self.filtered_fine else: return []
In OnData()
, we buy the 10 stocks that have the lowest P/E ratio in our universe. We rebalance the portfolio at the beginning of each year.


Edit My Profile
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I suppose if we couldn't laugh at things that don't make sense, we couldn't react to a lot of life.
You know what we need, Hobbes? We need an attitude. Yeah, you can't be cool if you don't have an attitude.
The only skills I have patience to learn are those that have no real application in life.


Items:
Skills:
Your Last Roll:
Join the game with friends. Use the buttons to interact.
Created by Introverted Ape. Forked from Victor Zhou's project on Github.


Reardon (2011) introduced a very interesting concept in which he calculates percentile differences from ordered categorical variables. He explains his procedure very much in detail in the appendix of the book chapter but no formal implementation has been yet available on the web. With this package I introduce two functions that apply the procedure.
The package has two main functions:
perc_diff
, for calculating percentile differencesperc_dist
, for calculating scores for all percentilesYou can install and load the package with these commands:
devtools::install_github("cimentadaj/perccalc") # for development version
# or
install.packages("perccalc") # for stable version
library(perccalc)
Suppose we have a dataset with one continuous variable and one categorical variable:
library(dplyr)
library(ggplot2)
df <-
tibble(
continuous = rnorm(100) + 1:100,
categorical = rep(letters[1:5], each = 20) %>% factor(ordered = TRUE),
wt = rnorm(100, mean = 5)
)
Note that the categorical variable has to be an ordered factor (this is a requirement of both functions). For example, perc_diff
calculates percentile differences using both variables.
perc_diff(df, categorical, continuous, percentiles = c(90, 10))
#> difference se
#> 79.932606 0.366152
You can optionally add weights with the weights
argument.
perc_diff(df, categorical, continuous, weights = wt, percentiles = c(90, 10))
#> difference se
#> 80.0299356 0.4393123
On the other hand, the perc_dist
(short for percentile distribution) allows you to estimate the score for every percentile.
perc_dist(df, categorical, continuous) %>%
head()
#> # A tibble: 6 x 3
#> percentile estimate std.error
#> <int> <dbl> <dbl>
#> 1 1 1.01 0.0531
#> 2 2 2.02 0.104
#> 3 3 3.03 0.152
#> 4 4 4.04 0.198
#> 5 5 5.04 0.242
#> # … with 1 more row
This function also allows the use of weights. For an example with a a real-world dataset, please see the vignette example.
All the intelectual ideas come from Sean Reardon. The R implemention is my own work.


Arizona officials working to fix campaign finance website
PHOENIX (AP) - Arizona officials are attempting to overcome glitches in the state-run campaign finance website as the election year approaches.
The Arizona Capitol Times reported the state’s website See The Money and its campaign-finance database have not worked properly since the 2018 election.
Candidates throughout the state will file the first financial reports for the 2020 campaign cycle in January.
Arizona Secretary of State Katie Hobbs says her staff has spent the past year working to ensure See The Money accurately displays campaign finance information in a simple and intuitive way.
Political professionals say the website’s flaws have led to misleading or confusing data.
Hobbs says the state relies on the public to report problems with posted information, but the site still has not reached the level of being a “functional tool.”
Information from: Arizona Capitol Times, http://www.arizonacapitoltimes.com
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Please read our comment policy before commenting.


I am pursuing my masters in Information Systems. This is my first semester. This website is a part of my assignment under the subject "Web Systems Development" taught by professor Keith Williams.


WITNESS LIST
State Affairs
May 7, 2015 9:00 AM
FOR:
Abrams, Steven (Self), San Antonio, TX
Abrams, Troy (also providing written testimony) (Self), San Antonio, TX
Bearden, Chase Director Advocacy (Coalition of Texans with Disabilities), Austin, TX
Berry, Aaron (Self), Houston, TX
Berry, Matt (Self), Bellaire, TX
Berry, Misha (Self), Houston, TX
Berry, Noah (Self), Houston, TX
Berry, Peter (Self), Houston, TX
Berry, Simone (Self), Bellaire, TX
Berry, Willa (Self), Houston, TX
Diepraam, Warren First Assistant (Waller County District Attorney's Office), Hempstead,
TX
Egdorf, Don Police Officer (Houston Police Dept.), Houston, TX
Floyd, Beaman Executive Director (Texas Coalition for Affordable Insurance Solutions),
Austin, TX
Hunt, Paul (also providing written testimony) (Self and American Council of the Blind of
Texas), Austin, TX
Jamison, Jennifer President Decide2Drive.org (Self), Roanoke, TX
Myers, Sierra (Self), Austin, TX
Navarro, Gilberto Assistant Chief (also providing written testimony) (Laredo Police
Dept.), Laredo, TX
Tankersley, Krista (Self), Dallas, TX
ON:
Ferdinand, Dr. Alva Assistant Professor (also providing written testimony) (Texas A&M
Health Science Center), College Station, TX
Registering, but not testifying:
FOR:
Baum, Walt Executive Vice President (AECT), Austin, TX
Chatelle, Melody Legislative Consultant (Self), Austin, TX
Coyle, Jeff Director of Intergovernmental Relations (City of San Antonio), San Antonio,
TX
Cruz, Velma Government Affairs Manager (SPRINT), Austin, TX
Curbow, Kelly Executive Director (AT&T), Austin, TX
DeBower, Courtney Legislative Communications Coordinator (Texas EMS, Trauma and
Acute Care Foundation), Austin, TX
Eckstein, Kathy Director of Public Policy (Children's Hospital Association of Texas),
Austin, TX
Findeisen, Les Director of Policy (Texas Trucking Association), Austin, TX
Hamilton, Jonna Kay Managing Counsel (Nationwide Insurance), Austin, TX
Lanagan, Lindsay Intergovernmental Relations Manager (City of Houston), Houston, TX
Lawson, Richard (Verizon), Austin, TX
WITNESS LIST
State Affairs
May 7, 2015 9:00 AM
Leo, Myra (Alliance of Automobile Manufacturers), Austin, TX
Myers, Mike (Self), Austin, TX
O'Ryan, Anne Legislative Advocate & Public Policy Strategist (AAA Texas, Interinsurance
Exchange of the Auto Club, Auto Club Co. Mutual), Austin, TX
Pacheco, Michael Associate Legislative Director (Texas Farm Bureau), Austin, TX
Phenix, Billy (Allstate Insurance Company), Austin, TX
Pitts, John R. (UPS), Austin, TX
Rangel, Victoria (Self), Houston, TX
Ratliff, Thomas (American Insurance Association), Austin, TX
Ratliff, Thomas (T-Mobile USA), Austin, TX
Scott, Bruce Lobbyist (State Farm), Austin, TX
Sellers, Tom Mgr. (ConocoPhillips), Austin, TX
Smith, Casey Policy Associate (United Ways of Texas), Austin, TX
Smith, Melinda (Combined Law Enforcement Assoc. of Texas), Austin, TX
Wendell, Ware Deputy Director (Texas Watch), Austin, TX
Wied, Lauren (Texas Health Resources), Austin, TX
Wilson, Stacy VP/Association General Counsel (Texas Hospital Association), Austin, TX
Woods, Joe VP - State Government Relations (Property Casualty Insurers Assn. of
America), Austin, TX
Yarbrough, Brian Attorney (General Motors), Austin, TX
ON:
Bailey, Robert L. Major (Texas DPS), Leander, TX
Rawson, Carol Director - TXDOT Traffic Operations Division (TXDOT), Austin, TX
Providing written testimony:
FOR:
Shannon, Fred (National Safety Council), Austin, TX
Whitehurst, Darren VP - Advocacy (Texas Medical Association), Austin, TX
FOR:
Turner, Guy President (Texas State Association of Fire Fighters), Abilene, TX
Registering, but not testifying:
FOR:
Alvarado, Aidan Vice-President (Laredo Fire Fighters Association), Laredo, TX
Beachley, Pam Attorney (Texas Association of Counties Risk Management Pool), Austin,
TX
Dailey, Sean (Houston Professional Fire Fighters Association), Houston, TX
Deshields, Glen Lobbyist (Texas State Association of Fire Fighters), Austin, TX
Moreno, Randy Legislative Director (Austin Firefighters Association), Austin, TX
Smith, Melinda (Combined Law Enforcement Association of Texas), Austin, TX
Villarreal, Johnny Legislative Director (Houston Fire Fighters Local 341), Houston, TX
ON:
Hatch, Brent Special Advisor (Texas Department of Insurance- Division of Workers
Compensation), Austin, TX
WITNESS LIST
State Affairs
May 7, 2015 9:00 AM
Registering, but not testifying:
FOR:
Campbell, Chuck Legal Counsel (Austin Firefighters Relief & Retirement Fund), Austin,
TX
Johnson, Keith A. Vice Chairman (Austin Firefighters Relief and Retirement System),
Georgetown, TX
Moreno, Randy Legislative Director (Austin Firefighters), Austin, TX
Nicks, Bob President (Austin Firefighters Association), Austin, TX
Stefka, Bill Fund Administrator (Austin Firefighters Relief & Retirement Fund), Austin,
TX
Williams, Nancy N. (City of Austin), Austin, TX
Registering, but not testifying:
ON:
Beverly, Eric V. Policy Analyst (Sunset Advisory Commission), Austin, TX
Dudish, Kim Chief Financial Officer (State Office of Administrative Hearings), Austin, TX
Gipson, Sheri Senior Manager Customer Support Driver License Director (Tx DPS),
Austin, TX
Parsley, Cathleen Chief Administrative Law Judge (State Office of Administrative
Hearings), Austin, TX
Walston, Tom General Counsel (State Office of Administrative Hearings), Austin, TX
FOR:
Bresnen, Steve Attorney (Texas Family Law Foundation), Austin, TX
Thomson, Kristal Attorney (Texas Family Law Foundation), San Antonio, TX
ON:
Valentini, Gene Director (Office of Dispute Resolution for Lubbock County), Lubbock, TX
Registering, but not testifying:
FOR:
White, David Executive Director (Texas Psychological Association), Cedar Park, TX
ON:
Spinks, Darrel Executive Director (TX State Board of Examiners of Psychologists), Austin,
TX
Registering, but not testifying:
ON:
Dower, Benjamin Assistant Attorney General (Office of the Attorney General), Austin, TX


Dear Dry,
NYFLC collage [ http://feministcampus.org/leadership/default.asp ]We hope to see you at the Feminist Majority Foundation’s 9th Annual National Young Feminist Leadership conference THIS weekend, March 23-25! The online registration deadline is tomorrow, March 21, so if you have not already done so register NOW [ https://salsa.democracyinaction.org/o/1400/p/salsa/event/common/public/?event_KEY=76709 ]!
Hundreds of feminist activists and student leaders from across the country will be coming together for two full days of strategizing and skill building, as well as a day on Capitol Hill with policy-makers.
Here are few things to keep in mind if you plan on joining us in Washington, DC:
* Visit our conference website to find information about lodging [ http://feministcampus.org/leadership/2013NYFLC/lodging.asp ], get directions [ http://feministcampus.org/leadership/2013NYFLC/directions.asp ] to the conference, and review a preliminary conference agenda [ http://feministcampus.org/leadership/2013NYFLC/agenda.asp ].
* If you plan on staying Monday for Congressional Visit Day [ http://feministcampus.org/leadership/2013NYFLC/dayofaction.asp ], make sure to RSVP [ http://salsa.democracyinaction.org/o/1400/p/salsa/web/common/public/signup?signup_page_KEY=7362 ] and contact your Representative and Senator’s offices to set up your meetings!
* If you have any questions, or would like to register a group, email<EMAIL_ADDRESS>[<EMAIL_ADDRESS>].
* Start using the hashtag on Twitter [ https://twitter.com/feministcampus ] or post about NYFLC on our Facebook page [ http://www.facebook.com/feministcampus ]!
The entire Campus Team is busy preparing for this weekend, and we hope to see you there!
For equality,
*FMF Campus Team*
duVergne, Brooke, Adriana, Francesca, Miranda and Kari
You have received this e-mail because of your interest in women’s issues. To unsubscribe, please click here. [ http://salsa.democracyinaction.org/o/1400/p/salsa/supporter/unsubscribe/public/index.sjs?unsubscribe_page_KEY=494 ]


Robots.txt for use with Umbraco
I originally posted this over at the Our Umbraco community wiki. [Robots.txt for use with Umbraco] I am only posting it on my blog as a cross-reference. The Our Umbraco wiki version will evolve with the community’s experience and knowledge.
The Robots Exclusion Protocol has been around for many years, yet there are a lot of web-developers who are unaware of the reasons for having a robots.txt file in the root of their websites.
There have been many rumours around whether the bigger search engine crwalers (i.e. Googlebot) consider your website amateurish if you didn’t have a robots.txt – and if handled badly, could lead to your site being invisible on SERPs.
If you are happy for a crawler to crawl/index all of your website’s content, then you can use the following:
User-agent: * Disallow:
However, when using Umbraco to power my websites, it is preferable to define which folders are accessible by the crawler. Personally, I would not like to see the contents of my /umbraco/
folder to be returned in Google’s SERPs.
Here is an example of the robots.txt that I have used on several Umbraco-powered websites.
# robots.txt for Umbraco User-agent: * Disallow: /aspnet_client/ Disallow: /bin/ Disallow: /config/ Disallow: /css/ Disallow: /data/ Disallow: /scripts/ Disallow: /umbraco/ Disallow: /umbraco_client/ Disallow: /usercontrols/ Disallow: /xslt/
From my perspective, there is no reason for a search engine crawler to be crawling/indexing files from any of the above folders – you may have a different perspective, to which you can amend your robots.txt accordingly.
For more information about the robots.txt standard, please refer to the official website: http://www.robotstxt.org/robotstxt.html


OR &expr = n1 or n2
Description Performs a bitwise OR of two numbers. Results Returns the bitwise OR of n1 and n2. Example ; perform a bitwise OR x = %1100 or %1001 ; x = %1101
Description
Performs a bitwise OR of two numbers.
Results
Returns the bitwise OR of n1 and n2.
Example
; perform a bitwise OR x = %1100 or %1001 ; x = %1101
Back to Keywords


I'm a paragraph. Click here to add your own text and edit me. It’s easy. Just click “Edit Text” or double click me and you can start adding your own content and make changes to the font. Feel free to drag and drop me anywhere you like on your page. I’m a great place for you to write more. Tell a story and let your users get to know you.


+++ title = "SENSIBLE-KI" linkTitle = "sensible-ki" +++ {{< blocks/cover title="SENSIBLE-KI" image_anchor="top" height="full" color="dark" >}}
{{< /blocks/cover >}} {{% blocks/lead color="primary" %}} The project SENSIBLE-KI explores solutions to make artificial intelligence (AI) systems in mobile applications and embedded systems secure and trustworthy. {{% /blocks/lead %}} {{% blocks/lead color="white" %}} Partners from industry, applied research and scientific research are working in the project, which is funded by the German Federal Ministry for Economic Affairs and Energy BMWi, to ensure the integrity and authenticity of AI systems. For example, methods are being developed that ensure the confidentiality of the systems themselves, while at the same time protecting the privacy of the data and enabling secure transmission to mobile devices.


Members: Brian Richard, Eric Lei, Kenneth Fang, Tyler Sherman
Team Procedures
Preferred method of communication:
Slack → will be used for all logistics and questions
In person → will be used for major design decisions and reviewing progress
Decision-making policy:
By consensus
All topics will be thoroughly discussed before a decision is made
Method for setting and following meeting agendas:
Current “Team Leader” will create and post meeting agenda in Slack and the meeting minutes document
“Scribe” will record the meeting minutes in the document on Google Drive
This position will be randomly selected and will rotate every week
To help keep the team focused during meetings, time will be alloted for breaks
This is especially true during our 3-hour lab session
All team members should feel comfortable to take a break as needed
Team members are responsible for speaking up if someone seems like they aren’t
taking enough breaks (and their productivity has suffered) or if they’re taking
too many breaks
At the end of each meeting—whether it be for technical work or logistics—the
logistics for the next meeting will be discussed and anticipated work will be
distributed and recorded on the “Tasks” document on Google Drive
Method of record keeping:
Designated Scribe for the meeting is responsible for recording and disseminating meeting minutes
Meeting minutes will always be kept in the shared folder on Google Drive (link also available on the team website)
Agendas and minutes will be kept in the same Google Drive document
Meeting Times:
Weekly → 11:15 - 12:05 PM on Fridays in Upson Hall 142
Weekly → 7:30 - 10:30 PM on Thursdays in Phillips Hall 427
As Needed → 10:00 - 12:00 PM on Saturdays in Phillips Hall 427
Always consult the Slack channel for special circumstances or questions
Team Expectations
Work Quality:
All work must be completed by the deadline set out by the team
This doesn’t mean don’t ask for help. Quite the contrary, ASK for help immediately if you don’t understand what your assigned to work on or need extra assistance
Consequences for failing to meet deadlines or attend meetings include having to bring snacks to the next team meeting and addressing what steps will be taken to prevent this from occurring again
All new code needs to be reviewed by at least one other person
Majority of code should be written using pair programming
All code should be concise and heavily commented
All files should be uploaded to the Google Drive folder or GitHub repository to preserve revisions and make accessibility easy
Team Participation:
Current Team Leader will be responsible for ensuring all members remain on task and on schedule and that all meetings are productive and accomplish the goals outlined in the agenda
All team members are expected to actively participate during team meetings
This includes: proposing ideas, pointing out issues, asking questions, and updating the group on the status of your current work
All tasks assigned to each team member will be clearly outlined in the meeting notes, as well as in the “Tasks” file on Google Drive
Team leader is responsible for ensuring all team members are comfortable with their work distribution and for altering assignments if necessary
Personal Accountability:
Team members are expected to punctually attend and participate at all meetings
Being a few minutes late (5 to 10 minutes) is fine if accompanied by a message in Slack
Any additional tardiness should come with advanced notice (>24 hours in advance)
You are responsible for completing the tasks for which you have been delegated, within the time window the team has defined
This project is representative of all of the group members as a whole
You are expected to take your work seriously as it is a reflection of the entire team
Team members are expected to respond to all Slack messages (or other forms of communication) as soon as reasonably possible
Always send some sort of acknowledgment to show you read and understood a message
Only commit to what you can reasonably achieve
If for some reason you are unable to complete your obligations, take responsibility for that and talk to the team about re-allocating work
Recognize team design decisions are where the efforts of all members will be focused
Voice concerns and tradeoffs during design meetings, but once a decision has been made, team members should support it until it is finished, or a flaw is discovered
Consequences for Failing to Follow Procedures and Fulfill Expectations:
Infractions of any of the obligations of this team contract will be addressed as soon as possible (at the next team meeting)
That being said, we are a team and our goal is to support one another
We will utilize constructive criticism and task conflict, not relationship conflict
The person at fault is responsible for bringing this up and outlining how this will be avoided in the future
If infractions continue, we will schedule a full team meeting with Professor Kirstin and/or a TA and/or Rob Parker to give people an opportunity to voice their opinions and resolve this conflict
Team Leadership
Every person on the team will have to take the role as a leader.
The role of the leader will be to organize meetings and make sure that
everything is submitted in a timely manner. Please note here who will
be responsible when:
Weeks 1 - 4 (Startup, Lab 1, Milestone 1)
August 23 - September 14
Kenneth Fang
Weeks 5 - 8 (Lab 2, Lab 3, Milestone 2)
September 17 - October 12
Eric Lei
Weeks 9 - 12 (Lab 4, Milestone 3)
October 15 - November 9
Brian Richard
Weeks 13 - 16 (Milestone 4, Competition, Final Report)
November 12 - December 4
Tyler Sherman
Signed
I participated in formulating the standards, roles, and procedures as stated in this contract
I understand that I am obligated to abide by these terms and conditions
I understand that if I do not abide by these terms and conditions, I will suffer the consequences as stated in this contract
This contract is understood to be a living document that will be amended as necessary, however, only with the entire group present


Date
Purchase Order Number
Receiving Clerk
Add Receiving Clerks
Supplier
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What is Scrum ?
Scrum is an agile project management methodology or framework used for software development projects with the goal of delivering new software capability every 2-4 weeks.
Project success rates - AGILE vs WATERFALL
Disadvantages Waterfall Methodology
- Difficult to go back and change something
- Late developing software during the life cycle.
- High amounts of risk
- Bad model for a long projects.
- Not suitable for the projects where requirements are changing
Advantages of Scrum Methodology
- Higher productivity
- Better-quality products
- Reduced time to market
- Quick start
- Better team dynamics
- Low amount of risk
Components of Scrum development
- Team roles
- Events
- Artifacts


The 4th AAAI Conference on Human Conference and Crowdsourcing (HCOMP 2016) will be held October 30-November 3 in Austin TX, USA, at the AT&T Executive Conference Center, on campus at the University of Texas at Austin.
To reserve your room at the discount conference rate of $185/night (single/double), please use the conference's dedicated booking website.
Note: Due to limited room availability at the conference hotel on the evening of Saturday, October 29th, the reservation system will only permit Doctoral Consortium participants to reserve rooms for that evening. Consequently, all other conference attendees should select Sunday, October 30th (or thereafter) as the first night of their stay.
Imagine a city bursting with an entrepreneurial spirit, a commitment to personal freedom and a passion for unearthing new discoveries. Add a vibrant, internationally renowned music, film and art scene, along with a thriving economy that leads the way in the technology, engineering and health care industries. Throw in a glittering lake running through the center of the city, big blue skies, gleaming Texas sunshine and the natural beauty of the surrounding Hill Country. Underline all of that with an open-minded sense of community, a serious commitment to breakfast tacos and a deep appreciation for all kinds of people and all kinds of dreams, and you've got Austin, Texas — one of the most amazing places in the world, and the city we're proud to call home.
Hi-Tech Industries
Given the immense talent pool UT Austin produces, it's no surprise that technology companies such as Dell, IBM, Intel, Apple, Samsung and National Instruments have established major operations here in Austin. The city is also becoming a top destination for entrepreneurs and was recently named one of the best startup cities in the country. The vast and ever-growing high-tech scene in Austin, combined with its beautiful hill country, has dubbed the city the "Silicon Hills" complementing California's Silicon Valley. According to Forbes magazine, Austin "boasts the strongest expansion in tech sector employment of any of the nation’s 52 largest metropolitan areas from 2004 to 2014, 73.9%, as well as 36.4% growth in STEM jobs, the fourth-highest growth rate in the country.
Places to See in Austin
The 900ft pool was formed when Barton Creek was dammed up, so it has a natural rock and gravel bottom.
Bob Bullock Texas State History Museum
The story of Texas is told through films and exhibits; home to Austin’s only IMAX theater.
Texas Capitol is the largest in gross square footage of all state capitols and is second in total size only to the National Capitol.
Popular, trendy area of downtown Austin known for clubs, live music and unique restaurants.
Home to the Austin Nature and Science Center, Botanical Gardens, Hillside Theatre and the Zephyr.
Home to eclectic shops and retro clothing stores and the very popular First Thursday event each month.


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engine\remoting\server\serverremotesession.cs (2)
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--- layout: page title: About header-img: "img/about-bg.png" ---
Management consultant in Washington D.C. Alumnus of Washington College on the Eastern Shore of Maryland. Avid reader (my goal for 2019 is to read a new book every two weeks). Passionate sports fan (you will likely find me watching basketball, soccer, or football at any given moment). Aspiring data scientist.


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Some of our friends:
www.hurstphotography.co.uk
www.firststepsnursey.net
doorandgatecraft.web.officelive.com
www.stbelectrical.co.uk
www.thefencingcentre.co.uk


Dear {{ name }}
Hope this mail finds you well.
This is to inform you that a new Milestone has been assigned to you and you are expected to complete it within the specified timelines.
Below are the details of the milestone:
Milestone Name : {{ milestone_name }}
Project : {{ project }}
Start Date : {{ startdate }}
End Date : {{ enddate }}
Revert back to the project Manager Mr. {{ project_manager }} for more details.
Thanks & Regards
PM Team
Sybyl (U) Ltd
Kampala Office


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