Many examples of clustered software systems require stronger guarantees per instance than are provided by the Replication Controller (aka Replication Controllers). Instances of these systems typically require:
Kubernetes should expose a pod controller (a StatefulSet) that satisfies these requirements in a flexible manner. It should be easy for users to manage and reason about the behavior of this set. An administrator with familiarity in a particular cluster system should be able to leverage this controller and its supporting documentation to run that clustered system on Kubernetes. It is expected that some adaptation is required to support each new cluster.
This resource is stateful because it offers an easy way to link a pod’s network identity to its storage identity and because it is intended to be used to run software that is the holders of state for other components. That does not mean that all stateful applications must use StatefulSets, but the tradeoffs in this resource are intended to facilitate holding state in the cluster.
The software listed below forms the primary use-cases for a StatefulSet on the cluster - problems encountered while adapting these for Kubernetes should be addressed in a final design.
Replica sets are designed with a weak guarantee - that there should be N replicas of a particular pod template. Each pod instance varies only by name, and the replication controller errs on the side of ensuring that N replicas exist as quickly as possible (by creating new pods as soon as old ones begin graceful deletion, for instance, or by being able to pick arbitrary pods to scale down). In addition, pods by design have no stable network identity other than their assigned pod IP, which can change over the lifetime of a pod resource. ReplicaSets are best leveraged for stateless, shared-nothing, zero-coordination, embarassingly-parallel, or fungible software.
While it is possible to emulate the guarantees described above by leveraging multiple replication controllers (for distinct pod templates and pod identities) and multiple services (for stable network identity), the resulting objects are hard to maintain and must be copied manually in order to scale a cluster.
By contrast, a DaemonSet can offer some of the guarantees above, by leveraging Nodes as stable, long-lived entities. An administrator might choose a set of nodes, label them a particular way, and create a DaemonSet that maps pods to each node. The storage of the node itself (which could be network attached storage, or a local SAN) is the persistent storage. The network identity of the node is the stable identity. However, while there are examples of clustered software that benefit from close association to a node, this creates an undue burden on administrators to design their cluster to satisfy these constraints, when a goal of Kubernetes is to decouple system administration from application management.
Add a new resource to Kubernetes to represent a set of pods that are individually distinct but each individual can safely be replaced– the name StatefulSet is chosen to convey that the individual members of the set are themselves “stateful” and thus each one is preserved. Each member has an identity, and there will always be a member that thinks it is the “first” one.
The StatefulSet is responsible for creating and maintaining a set of identities and ensuring that there is one pod and zero or more supporting resources for each identity. There should never be more than one pod or unique supporting resource per identity at any one time. A new pod can be created for an identity only if a previous pod has been fully terminated (reached its graceful termination limit or cleanly exited).
A StatefulSet has 0..N members, each with a unique identity which is a name that is unique within the set.
type StatefulSet struct {
ObjectMeta
Spec StatefulSetSpec
...
}
type StatefulSetSpec struct {
// Replicas is the desired number of replicas of the given template.
// Each replica is assigned a unique name of the form `name-$replica`
// where replica is in the range `0 - (replicas-1)`.
Replicas int
// A label selector that "owns" objects created under this set
Selector *LabelSelector
// Template is the object describing the pod that will be created - each
// pod created by this set will match the template, but have a unique identity.
Template *PodTemplateSpec
// VolumeClaimTemplates is a list of claims that members are allowed to reference.
// The StatefulSet controller is responsible for mapping network identities to
// claims in a way that maintains the identity of a member. Every claim in
// this list must have at least one matching (by name) volumeMount in one
// container in the template. A claim in this list takes precedence over
// any volumes in the template, with the same name.
VolumeClaimTemplates []PersistentVolumeClaim
// ServiceName is the name of the service that governs this StatefulSet.
// This service must exist before the StatefulSet, and is responsible for
// the network identity of the set. Members get DNS/hostnames that follow the
// pattern: member-specific-string.serviceName.default.svc.cluster.local
// where "member-specific-string" is managed by the StatefulSet controller.
ServiceName string
}
Like a replication controller, a StatefulSet may be targeted by an autoscaler. The StatefulSet makes no assumptions about upgrading or altering the pods in the set for now - instead, the user can trigger graceful deletion and the StatefulSet will replace the terminated member with the newer template once it exits. Future proposals may offer update capabilities. A StatefulSet requires RestartAlways pods. The addition of forgiveness may be necessary in the future to increase the safety of the controller recreating pods.
A key question is whether scaling down a StatefulSet and then scaling it back up should reuse identities. If not, scaling down becomes a destructive action (an admin cannot recover by scaling back up). Given the safety first assumption, identity reuse seems the correct default. This implies that identity assignment should be deterministic and not subject to controller races (a controller that has crashed during scale up should assign the same identities on restart, and two concurrent controllers should decide on the same outcome identities).
The simplest way to manage identities, and easiest to understand for users, is a numeric identity system starting at I=0 that ranges up to the current replica count and is contiguous.
Future work:
{name}-{0 - replicas-1}
, allow subsets and
complex indexing.When a StatefulSet is scaled up, the controller must create both pods and supporting resources for each new identity. The controller must create supporting resources for the pod before creating the pod. If a supporting resource with the appropriate name already exists, the controller should treat that as creation succeeding. If a supporting resource cannot be created, the controller should flag an error to status, back-off (like a scheduler or replication controller), and try again later. Each resource created by a StatefulSet controller must have a set of labels that match the selector, support orphaning, and have a controller back reference annotation identifying the owning StatefulSet by name and UID.
When a StatefulSet is scaled down, the pod for the removed identity should be deleted. It is less clear what the controller should do to supporting resources. If every pod requires a PV, and a user accidentally scales up to N=200 and then back down to N=3, leaving 197 PVs lying around may be undesirable (potential for abuse). On the other hand, a cluster of 5 that is accidentally scaled down to 3 might irreparably destroy the cluster if the PV for identities 4 and 5 are deleted (may not be recoverable). For the initial proposal, leaving the supporting resources is the safest path (safety first) with a potential future policy applied to the StatefulSet for how to manage supporting resources (DeleteImmediately, GarbageCollect, Preserve).
The controller should reflect summary counts of resources on the StatefulSet status to enable clients to easily understand the current state of the set.
Since each pod needs a unique and distinct identity, and the pod needs to know its own identity, the StatefulSet must allow a pod template to be parameterized by the identity assigned to the pod. The pods that are created should be easily identified by their cluster membership.
Because that pod needs access to stable storage, the StatefulSet may specify a template for one or more persistent volume claims that can be used for each distinct pod. The name of the volume claim must match a volume mount within the pod template.
Future work:
In order to provide stable network identity, given that pods may not assume pod IP is constant over the lifetime of a pod, it must be possible to have a resolvable DNS name for the pod that is tied to the pod identity. There are two broad classes of clustered services - those that require clients to know all members of the cluster (load balancer intolerant) and those that are amenable to load balancing. For the former, clients must also be able to easily enumerate the list of DNS names that represent the member identities and access them inside the cluster. Within a pod, it must be possible for containers to find and access that DNS name for identifying itself to the cluster.
Since a pod is expected to be controlled by a single controller at a time, it is reasonable for a pod to have a single identity at a time. Therefore, a service can expose a pod by its identity in a unique fashion via DNS by leveraging information written to the endpoints by the endpoints controller.
The end result might be DNS resolution as follows:
# service mongo pointing to pods created by StatefulSet mdb, with identities mdb-1, mdb-2, mdb-3
dig mongodb.namespace.svc.cluster.local +short A
<IP_ADDRESS>
dig mdb-1.mongodb.namespace.svc.cluster.local +short A
# IP of pod created for mdb-1
dig mdb-2.mongodb.namespace.svc.cluster.local +short A
# IP of pod created for mdb-2
dig mdb-3.mongodb.namespace.svc.cluster.local +short A
# IP of pod created for mdb-3
This is currently implemented via an annotation on pods, which is surfaced to endpoints, and finally surfaced as DNS on the service that exposes those pods.
# The pods created by this StatefulSet will have the DNS names "mysql-0.NAMESPACE.svc.cluster.local"
# and "mysql-1.NAMESPACE.svc.cluster.local"
kind: StatefulSet
metadata:
name: mysql
spec:
replicas: 2
serviceName: db
template:
spec:
containers:
- image: mysql:latest
// Example pod created by stateful set
kind: Pod
metadata:
name: mysql-0
annotations:
pod.beta.kubernetes.io/hostname: "mysql-0"
pod.beta.kubernetes.io/subdomain: db
spec:
...
The StatefulSet controller is expected to execute like other controllers, as a single writer. However, when considering designing for safety first, the possibility of the controller running concurrently cannot be overlooked, and so it is important to ensure that duplicate pod identities are not achieved.
There are two mechanisms to achieve this at the current time. One is to leverage unique names for pods that carry the identity of the pod - this prevents duplication because etcd 2 can guarantee single key transactionality. The other is to use the status field of the StatefulSet to coordinate membership information. It is possible to leverage both at this time, and encourage users to not assume pod name is significant, but users are likely to take what they can get. A downside of using unique names is that it complicates pre-warming of pods and pod migration - on the other hand, those are also advanced use cases that might be better solved by another, more specialized controller (a MigratableStatefulSet).
The most difficult aspect of managing a member set is ensuring that all members see a consistent configuration state of the set. Without a strongly consistent view of cluster state, most clustered software is vulnerable to split brain. For example, a new set is created with 3 members. If the node containing the first member is partitioned from the cluster, it may not observe the other two members, and thus create its own cluster of size 1. The other two members do see the first member, so they form a cluster of size 3. Both clusters appear to have quorum, which can lead to data loss if not detected.
StatefulSets should provide basic mechanisms that enable a consistent view of cluster state to be possible, and in the future provide more tools to reduce the amount of work necessary to monitor and update that state.
The first mechanism is that the StatefulSet controller blocks creation of new pods until all previous pods are reporting a healthy status. The StatefulSet controller uses the strong serializability of the underlying etcd storage to ensure that it acts on a consistent view of the cluster membership (the pods and their) status, and serializes the creation of pods based on the health state of other pods. This simplifies reasoning about how to initialize a StatefulSet, but is not sufficient to guarantee split brain does not occur.
The second mechanism is having each “member” use the state of the cluster and transform that into cluster configuration or decisions about membership. This is currently implemented using a side car container that watches the master (via DNS today, although in the future this may be to endpoints directly) to receive an ordered history of events, and then applying those safely to the configuration. Note that for this to be safe, the history received must be strongly consistent (must be the same order of events from all observers) and the config change must be bounded (an old config version may not be allowed to exist forever). For now, this is known as a ‘babysitter’ (working name) and is intended to help identify abstractions that can be provided by the StatefulSet controller in the future.
Criteria for advancing to beta:
Criteria for advancing to GA:
Requested features:
StatefulSets were formerly known as PetSets and were renamed to be less “cutesy” and more descriptive as a prerequisite to moving to beta. No animals were harmed in the making of this proposal.


[Background on Dave and Joe can be found in the earlier scenarios.]
The night of the party rolls around, and Dave is on stage setting up his equipment. Joe has all the speakers set up around the dance floor, and Dave syncs up his new AndroiDJ, the newest Android cell phone DJ software, to the speakers. He will control the music from his cell phone. Now, Dave came prepared. Even though he had another tough week of classes, Dave found time create a playlist of about 5 hours' worth of music that he would play that night. With his new software on his phone, Dave had his list of songs queued up in his playlist ready to go. The first song was ready to play, and the next song was "on-deck."
Hundreds of people start showing up to the party, and Dave starts playing his music. But, what Dave wanted to do was to take requests from the audience. So he walked around the party and added each requested song to the end of his playlist. He had most of the requested songs in his library but he noticed that he had been getting the same request from many of the sorority girls at the party, "Party in the USA" by Miley Cyrus. Dave knew he didn't have this song and decided to find the song on Youtube using the searching feature. He hit the search icon and used his on-screen keyboard to type in the song information that he know. Dave had big fingers, so he misspelled a few words. Luckily, these were auto-corrected for him (1). He then streamed it into his cell phone, and played it next. When the girls hear the song, they go wild. Dave knew that the song was streamed and that it would have a little audio interference. So Dave decided to use his software to make the song sound a lot better. He used the AutoEQ button and EQ'ed his song, hitting the "AUTO" labeled button, bringing up a screen that was easy to navigate. Dave masked the bad quality with an automated low-pass filter. Although this is an advanced technique, Dave was able to use it quite easily, as the interface allowed him to draw in his automations using his finger (2). Dave was pleased to find that his automations behaved exactly as he expected, even with only a little experience. But as Dave was playing with the automation, he forgot to play another song from the requested list. Dave doesn't panic as he quickly hits the back button and then swipes up a "drawer" to expose the play controls. A song starts playing. Dave then makes sure all of his songs are lined up the way he wants them to be, swiping the "drawer" down to hide the controls. That way he can't accidentally hit a button to mess up the sound, yet has smooth and fast access to important controls (3). Dave is a huge hit. Everyone loves his DJ-ing skills.
This scenario reflects Interaction Design in that Dave was able to quickly play and change his music using the buttons and sliders that have good affordances, mappings, and feedback. With little constraints, Dave easily manipulates his music to the audience's desires.
The "Search for Music" bar is easily found and is easily used. All the user does is type some keywords into the search bar and a google-like results page shows up with possible songs matching the keywords. The "AUTO" button, when pushed, brings up a window right away to allow the user to play with the song playing.
Consider again Alex is at a party where a DJ is providing music. The DJ plays several popular tracks and everyone is having a great time. Then the DJ plays a "mash-up". Using the multitouch playback controls, that are clearly labeled, he is able to change the volume of one song, while changing the pitch. This creates a very popular building "swoop" sound effect that the audience loves. The DJ was also able to use this effect to help the terrible sounding "mash-ups". Because the volume control slider and the pitch contorl slider do not overlap, and multitouch is provided, Alex could leave one song at a low volume while quickly finding the appropriate pitch to match the beat perfectly to the other song (1). But Alex accidentally clicked outside the pitch control slider and his screen went back to the original two-song display.
In addition to the multitouch volume/pitch combination, he also changes the volume/pan. The DJ presses the clearly labeled "PAN" button that brings up a display screen with sliders. The DJ uses these sliders and creates his pan effect However, he is sweaty, and often messes up the precise touch needed to effectively control the screen (2). Even with the mistakes, this unique sound makes him even more enjoyable to Alex.
In the Information Scenario, the DJ enjoyed the new features, but ended up making mistakes with them. He picked two songs that didn't go together very well. Having easy-to-use sliders that were clearly labeled and that didn't overlap was very helpful. To his expectant ear, he could make the changes before his less attentive audience could really pick up on them.
Also, the DJ used the panning feature by hitting the "PAN" button, bringing up the panning screen. Th audience really enjoyed this feature, and the DJ was able to do it quickly and easily because his interface was clearly labeled.


本书pdf是文字识别版，影印质量一般。
Filtration
Acids and Alkalis
Alkalis in Textile Analysis
Acids and Alkalis in the Qualitative Analysis of Soils
Detection of some of the Compounds Present in Plants
Exercises with Standard Solutions
Sanitary Analysis of Water
Examination of Baking Powder
Analysis of Milk
Examination of Ice Cream, Cheese, and Condensed Milk
Distillation Experiments
Detection of Coal-Tar Dye
Identification of Vegetable Colors
Raffia Dyeing
Chemistry of Stains
Food Preservatives
Examination of Tooth Powders
Experiments with Glucose
Examination of Headache Powders
Tests for Arsenic
Method for Testing Paint and Oils
Determination of Food Values
Testing Urine
Selected Exercises


Try to answer following code-related questions within time limit. Keep in mind that incorrect answers will penalize your score/time by fifteen seconds.
0
1
2
3
YOUR FINAL SCORE IS:


Select language
Menu
Cheeseburger
Beef
,
Emmental
$6
Macaroni
&
Cheese
Vegetarian
$6
Shawarma
Lamb
,
Chicken
,
Veal
$8
T-bone steak
French fries
$11
French fries
$3
Milkshake
Chocolate
/
Vanilla
/
Cherry
$3


Consulting Website using Single-Page Design
Consulting Website using Multi-Page Design
Calculator
Email Template


--- layout: archive author_profile: true --- {% include base_path %}
I am currently a Ph.D. student at The University of Chicago, Department of Statistics working under the guidance of Prof. Jian Ding. I obtained my Bachelors and Masters degree in Statistics from the Indian Statistical Institute, Kolkata in the years 2009 and 2011 respectively. Before joining The University of Chicago I worked for a year in Opera Solutions and Management Consultancy Pvt. Ltd as an analytics specialist.
I am primraily interested in Probability theory. My current research topics include random planar geometry and random walk on random environments. In the past I have worked on random constraint satisfaction problems and combinatorial optimization.
{% for post in paginator.posts %} {% include archive-single.html %} {% endfor %} {% include paginator.html %}


You'll see - everything is possible. From tables and sideboards to windowsills and shelves.
Total Products
Customers
Exports
FEATURED PRODUCT
It is not just furniture! We are striving to add value and uniqueness. Built our brand with care keeping nature and industrial design in mind.
FEATURED PRODUCT
It is not just furniture! We are striving to add value and uniqueness. Built our brand with care keeping nature and industrial design in mind.
FEATURED PRODUCT
It is not just furniture! We are striving to add value and uniqueness. Built our brand with care keeping nature and industrial design in mind.
120-150 Kroner
120-150 Kroner
120-150 Kroner
120-150 Kroner
120-150 Kroner
120-150 Kroner
November 15, 2029 / Furniture
November 15, 2029 / Furniture
November 15, 2029 / Furniture


Look
Send
My Profile
Logout
User Profile
Leads:
User Profile:
User Name:
Email:
Phone:
Change
Cancel


WITNESS LIST Licensing & Administrative Procedures Committee May 1, 2003-8:00A HB 1114 On: Ferrero, David (Texas Alcoholic Beverage Commission/TABC) HB 2005 On: Ferrero, David (Texas Alcoholic Beverage Commission/TABC) HB 3283 On: Thorburn, Wayne (Texas Real Estate Commission) SB 597 For: Pinson, Kathleen S. (Pre-Paid Legal Services, Inc.) Against: Finney, David (Self) Monnin, Gary P. (Texas Legal Protection Plan) Richter, Kellis (Self and Texas Legal Protection Plan) Rische, Ray (Self and Texas Legal Protection Plan) SB 1105 On: Thorburn, Wayne (Texas Real Estate Commission)


--- layout: post title: 'PICNIC07: New interaction partners, Nicolas Nova' date: 2007-09-28 00:00:00 categories: animalia digital-media interfaces-&-interaction ---
PICNIC07: New interaction partners, Nicolas Nova
The problem with ubicomp: the model translated into gaming is messy, it's not clean.
Examples: augmenting animals. Shows a cockroach controlling a robot; a rat with survival goggles; special collar to track floating dogs; wiring poultry up to the internet.
How about playing against animals, or using animals as partners in gaming? Pac-man against animals instead of against an AI; or another one where a rodent is pursuing you through a virtual environment.
MMORPGs for pets: a dog running around a physical environment, transmitting its movements to a dwarf inside Wow. Twitter communication with a cat: when the cat scratches the device, the device reports onto Twitter - or when a message is twittered by the owner, it's reflected on the device.
Nicolas is not interested in trivialising animals, bee-dogs, or just controlling them. It's about animals, plants or weather as new interaction partners.


I love programming
I'm a Businessman, Politician in the Democratic Party, Humanitarian and a Programmer.
My Technical skills are:
- Mobile App Development
- Full stack Web Development
- Image and Motion Graphics
CEO & Founder, Havard
Harvard University
I'd love your feedback !
Swing by for a cup of , or leave me a note:


Want To Join?
Do you join XLine and get all the what it offers well all you need to do is apply to the form in the form section in the website, answer all the questions in the form and very soon we will contact you and set up an interview with you
Apply


Creating HTML5 slides with RStudio, knitr and pandoc
19 Nov 2012Lately I've been spending some time learning how to create slides using HTML5. The good news for R users is that we can generate our html5 slides with R studio, knitr, and pandoc. The not so good news is that, as usual, the learning curve can be relatively steep for newbies, inexperienced users, or html5 illiterate guys like me.
The main source of information is Yihui Xie's knitr website which is full of information and demos. It's really amazing the contribution that Xie has done and I admire his awesome work. However, although there's plenty of information in the knitr's website, I wasn't able to find a tutorial on how to create html5 slides in a relatively easy beginners-style way. So I decided to create a short tutorial that hopefully will help you to get a better idea on how to create your own slides.
A little bit about HTML5 slides
HTML5 slides is just another tool that you can use for creating slides instead of using Keynote, PowerPoint, Google Presentation, etc. If you haven't seen html5 slides before, just take a look at these examples:
- http://yihui.name/slides/knitr-slides.html
- http://yihui.name/slides/2012-knitr-RStudio.html
- http://yihui.name/slides/2011-r-dev-lessons.html#slide1
Personally, I see HTML5 slides as another useful resource that I can use for my work. I don't think it will substitute my use of other slideware, but it can definitely be used as an interesting alternative. Especially if you are interested in reproducible documents containing chunks of R code and graphics, it's worthwhile to try it.
Among the pros of using html5 slides is that you just need a text editor and a web browser (but not necessarily an internet connection). It also offers an interesting format that, if well designed, can provide a different and better visual experience. However, HTML5 slides are not without limitations. Perhaps the main entrance barrier for many users is that you require web coding skills (HTML, CSS, JavaScript). You don't have to be an expert with these languages but you definitely need to have the basics to get the most out of the slides. On the formatting side, my main complain has to do with positioning the elements which is very limited.
Some other general resources about HTML5 slides and HTML5 frameworks (that you can use out of the box)


Really simple demo of how to use Backbone.js and Google Maps with a few simple interactions.
In addition to freeform text, any HTML5 text-based input appears like so.


Stash\STASHAPI::setSignature
api_signature setter - signs the request with the current data in the STASHAPI request instance
Uses the following parameters as part of the sig calculation (these are all contained in the $dataIn array as key=>value pairs) - self::params() array containing the request parameters (could be 0 or more key=>value pairs) - ['url'] contains the URL the request is being sent to - ['api_version'] contains the version string for this API - ['api_id'] contains the ID string for the API user - ['api_timestamp'] contains the epoch / integer timestamp for when the request was created
Signature
public function setSignature(array
$dataIn )
Parameters
$dataIn
— array- - an array of key/value pairs containing the data to sign
Returns
- boolean
- T if the function succeeds
Errors/Exceptions
-
Exception
- for invalid inputs


{% extends '_base.html' %} {% block title %}{% endblock %} {% block content %}
Welcome, {{user.email}}!
Products you've purchased:


Demonstrations Listed by Top-Level Domain
See the quick tour for a smaller
set of demos that highlight the key features of Ptolemy II.
Ptolemy II Domains
Code Generation
- Bouncing Ball (Does not require Java 3D)
- Bouncing Ball (Requires Java 3D, see the GR domain)
- Brownian
- Cart with Pendulum
(Requires Java 3D, see the GR domain)
- Car Tracking
- Compared Clocks
- Continuous Clock
- CTInsideDE
- EfficiencyCurve.xml
- Helicopter Control
- Hierarchical Execution
- Hybrid Plant: Deterministic,
Random
- Hysteresis
- HysteresisWithRandomDelay
- HysteresisWithRandomLosses
- IncreasingRatePoisson
- Level Crossing Detector
- Level Crossing Detector Detects Glitches
- Level Crossing Detector with Different Detecting Directions
- Lorenz Attractors
- Matlab in CT
Windows only, requires that Matlab be installed locally
- MEMS accelerometer
- NewtonsCradle
- NewtonsCradleAnimated
(Requires Java 3D, see the GR domain)
- Newton's Cradle with Complicated Dynamics
(Requires Java 3D, see the GR domain)
- Newton's Cradle with Nondeterministic State Machine
(Requires Java 3D, see the GR domain)
- Newton's Cradle with Perfectly Inelastic Collisions
(Requires Java 3D, see the GR domain)
- Newton's Cradle with Configurable Parameters
(Requires Java 3D, see the GR domain)
- Newton's Cradle with Balls Having Different Masses
(Requires Java 3D, see the GR domain)
- 3D Pendulum
(Requires Java 3D, see the GR domain)
- Poisson
- Sampled Clocks
- Satellite
- Ball Bounncing on a Sinusoidal Surface
- Square Wave Response
- Static Units
- Starmac
- Sticky Point Masses
- Sticky Point Masses Modified Version
- Switching Continuous Signals using Modal Models
- Thermostat
- Transmission
- Triggered Continuous Clock
- Units
- Vehicle 2 Vehicle
- Sleep (Requires some setup)
Requires Java 3D, see the GR domain


Zend\ProgressBar\Upload provides handlers that can give you the actual state of a file upload in progress. To use this feature you need to choose one of the upload progress handlers (APC, uploadprogress, or Session) and ensure that your server setup has the appropriate extension or feature enabled. All of the progress handlers use the same interface.
When uploading a file with a form POST, you must also include the progress identifier in a hidden input. The File Upload Progress View Helpers provide a convenient way to add the hidden input based on your handler type.
There are two methods for reporting the current upload progress status. By either using a ProgressBar Adapter, or by using the returned status array manually.
A Zend\ProgressBar adapter can be used to display upload progress to your users.
1 2 3 4 5 6 7 8 9 10 | $adapter = new \Zend\ProgressBar\Adapter\JsPush();
$progress = new \Zend\ProgressBar\Upload\SessionProgress();
$filter = new \Zend\I18n\Filter\Alnum(false, 'en_US');
$id = $filter->filter($_GET['id']);
$status = null;
while (empty($status['done'])) {
$status = $progress->getProgress($id);
}
|
Each time the getProgress() method is called, the ProgressBar adapter will be updated.
You can also work manually with getProgress() without using a Zend\ProgressBar adapter.
The getProgress() will return you an array with several keys. They will sometimes differ based on the specific Upload handler used, but the following keys are always standard:
All other returned keys are provided directly from the specific handler.
An example of using the status array manually:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | // In a Controller...
public function sessionProgressAction()
{
$id = $this->params()->fromQuery('id', null);
$progress = new \Zend\ProgressBar\Upload\SessionProgress();
return new \Zend\View\Model\JsonModel($progress->getProgress($id));
}
// Returns JSON
//{
// "total" : 204800,
// "current" : 10240,
// "rate" : 1024,
// "message" : "10kB / 200kB",
// "done" : false
//}
|
Zend\ProgressBar\Upload comes with the following three upload handlers:
The Zend\ProgressBar\Upload\ApcProgress handler uses the APC extension for tracking upload progress.
Note
The APC extension is required.
This handler is best used with the FormFileApcProgress view helper, to provide a hidden element with the upload progress identifier.
The Zend\ProgressBar\Upload\SessionProgress handler uses the PHP 5.4 Session Progress feature for tracking upload progress.
Note
PHP 5.4 is required.
This handler is best used with the FormFileSessionProgress view helper, to provide a hidden element with the upload progress identifier.
The Zend\ProgressBar\Upload\UploadProgress handler uses the PECL Uploadprogress extension for tracking upload progress.
Note
The PECL Uploadprogress extension is required.
This handler is best used with the FormFileUploadProgress view helper, to provide a hidden element with the upload progress identifier.
The source code of this file is hosted on GitHub. Everyone can update and fix errors in this document with few clicks - no downloads needed.


OpenProfile
Explore
Hemendra
Create post
Help
settings
logout
Hemendra Khatik
ProjectManager @innovation
Huge fan of HTML, CSS and Javascript. Web design and open source lover.
Home Contact Story FAQs
Projects
Current Project
Skills
Achivements
Blog Posts


Google Analytics:Getting to Know Your Users
As a website owner, blogger, or anyone who has a web presence you want to know if your webpage content, products or services are reaching your intended audience or any audience at all. In the digital age, it is much easier to collect data on marketing campaigns to gauge success, what users are reviewing your website, how long they stay on a website, and how users find products and services on the internet thanks to Google Analytics.
Google Analytics is a “web analytics service offered by Google that tracks and reports website traffic, currently as a platform inside the Google Marketing Platform brand”. Businesses, company’s and organizations around the world use google analytics to collect data on website traffic. A powerful data tracking tool that collects demographic data, user session duration, bounce rates, conversations, acquisitions, and so much more. The significance of such data can impact a business’s bottom line, help leaders make informed decisions about online presence, or even help bloggers, or soon to be developers and or designers drive traffic to their webpages by replicating successful posts, articles or media with users. This post is committed to using Google Analytics to identify the data of users who have interacted with my User Research Journal.
Identifying Data Metrics
The Data metrics used for the User journal Evaluation include for review include:
- Audience: Google Analytics classifies audience data into 15 different categories. The categories for audience evaluation include behavior, technology, and mobile.
- Acquisition: Google Analytics classifies acquisition data into 5 categories. The categories used for this evaluation are all traffic- channels tree maps and referrals.
Questions and Data for Consideration
While conducting the evaluation of the usability Journal the data for the following questions are being collected.
- Demographics: Where are my users geographically located?
- Behavior: How many of my users are new or returning?
- Technology: What kind of browser and networks are visitors using?
- Mobile: What type of device are visitors using?
- Channels: How are website users getting to the User Experience journal?
- Referrals: What websites are users using to get to the User Experience Journal?
- Demographics: User Science Journal users are located in Seattle Washington. The User Experience Journal is a project developed for educational purposes for Seattle University. As a result, the users are most likely cohort peers located in Seattle, Washington.
- Behavior: All of the users are new, view the page once, for 10 minutes or less. The development of the User Journal started in April with the users most likely being cohort peers who viewed the page for content review for academic purposes for a brief moment with little interest beyond reviewing the page for class purposes.
- Technology: Users are most likely using Chrome, Firefox, or Explorer to view the User Science Journal as they have three of the most popular browsers.
- Mobile: Users are using desktop devices to view Usability Journal. The usability journal is viewed from using canvas for academia referred from the canvas website. I’m predicting the users aren’t using mobile devices, or tablets to view course content which is my predicted referral source leaving desktops as the primary device to access the User Science Journal.
- Channels: Users are using direct link to Canvas, Githubio, or twitter to view the User journal. The User Journal was developed for academic purposes, connected to a university course that uses Canvas, and Github to communicate with students. The User experience Journal was posted on Twitter. Users are not using a search option to find the Usability Journal.
- Referrals: Users are using canvas.org and github.com to view the Usability Journal.
- Demographics:Where are Users located?
- Behavior: Are the User Journals New or Returning visitors?
- Technology: What device did Users use to view the Journal?
- Channels:How did Users get to the User Journal?
- Referrals: What websites are users using to get to the User Experience Journal? 57.14% of users are form Github.com alt="Image Refferal Channel data used to view User Journal ">
Predictions
The audience and acquisition data hypothesis are as follows :
Actual Data for User Experience Journal
As predicted many of the users that viewed the User Science Journal where located in the Seattle Area.A review of the data reveals that users are located in differnt cities in the seattle area. 55.6% of the users were located in the Seattle area, while there was an even 11.1% percent distribution of users from four addditional locations- Cashmere, Quincy , Redmond, and Ashburn.
The actual data for the user data is differnt than the predicted data. The actual results reveal that 75% of the users visiting the User journal are new and 25% are returning. Meaning that there was a percentage of users who previously visited the site and found the journal interesting enough to view return to the User Journal.
The actual data for devices is close to the predicted data. The predicted data anticipated that based on the context of the journal users would most likely attract desktop users, though the correlation requires sometesting. There are two mobile device users, interstingly enough the bounce rate for mobile users is much higher than desktop users as desktop users stayed on the user journal 9 minutes longer than mobile users but on everage as predicted users didnt stay on the user journal longer than 10 minutes.
The actual data revealed that 66.7% pecent of users used a direct link to get to the User Journal, while 33.3% percent where reffered to the User Journal. The most viewed post of the User journal was post number 3 with 27.78% percent of users using the direct link for post three to visit the page, 22.2% percent of users visting the User Journal the direct link for post 4 to visit the page.
The predicted and actual data are similar. The actual data revealed that users used github.com, and seattleu.instructue to view the User Journal, while there as no data for users using Twitter to reach the User Journal. 57.14% percent of the Users journal used github.com to visit the user journal.


This plot shows certain features of the plotter. Note that color is disabled, and individual marks are used for the first ten data sets. After that, the marks are recycled, so the eleventh data set is indistinguishable from the first. (Had we used color, we would be able to distinguish up to 110 distinct datasets). Also note that the first two data sets are connected with lines, but the remaining data sets are not. The ranges for the horizontal and vertical axes are computed automatically from the data, but the tick marks for the horizontal axis are specified explicitly in the PlotML file. This is why they appear as words rather than numbers. Note further that each axis and each data set is labeled by a string given in the PlotML file. For details about the PlotML file format, see the Plot Chapter.


BM Grenoble Release Notes
1.8.1
- Restore web search
- Restore loans library info
- Improve loans parsing error message
- Improve loans parsing reliability
1.8
- Update libraries opening hours
- Switch back from API to web view parser
- Remove widget
- Remove search
1.7.3
- Optimized for iPadOS 16 and macOS 13
1.7.2
- Optimized for iOS 16
- List of Digital library services
- Updated libraries webpage links
- Save credentials to Keychain to refresh session automatically
- Non blocking error messages
- Remove Location Button (iOS 15)
1.7.1
- Improve widget error messages
1.7
- Optimized for iOS 15, iPadOS 15, and macOS 12
- Loans widget (iOS 14, macOS 11)
- Loans notifications (1 week before due date)
- List reservations
- Location Button (iOS 15, macOS 12)
- Filter agenda by library (iOS 14, macOS 11)
- Drag and Drop support (News, Agenda)
- Update libraries opening hours
- Improve agenda parsing
- Fix show current location on library maps
1.6.1
- Renew loans
- Search details and availability
- Add loans and search results image placeholders
- Update libraries opening hours
- Add English localization in Library screen
- Improve Dynamic Type support in Library screen
1.6
- Native search
- Add Library Card screen (iOS only)
- Add “Lost Password” on Login screen
- Support formatted authors names
- Improve loading cover images
- Fix search text color in Dark Mode
1.4.4
- Update app icon
- Fix library sync
1.4.3
- Optimized for macOS Big Sur
- Move Info screen to About window (macOS)
- Fix signing out
1.4.2
- Optimized for iOS 14
- Update tab bar icons (iOS 14)
- Add News and Agenda contextual menu (Open in Browser, Share)
- Update libraries opening hours
- Fix library sync
1.4.1
- Alternate Libraries and Library screens layout for large screens
- Update layout to follow readable width (loans placeholder, search)
1.4
- macOS version
- Store credentials in keychain
1.3.3
- Update libraries opening hours
1.3.2
- Add message about temporary opening hours
- Fix library sync
1.3.1
- Fix agenda library name with dash
1.3
- Agenda
- Warning flag for unreturned loans
- Add loans refresh control
1.2
- News
- Add loan item thumbnails
- Refined loans expiration date style
1.1
- Libraries
- Search books
- Improve title formatting
- Search on Goodreads


If you have any questions or comments about the Northeast Regional Middle School Science Bowl, please email:


| Java BluePrints |
java -Xmx256m -jar filename.jar
glassfish/
directoryant -f setup.xml
<javaeesdk.home>
hereafter in this document. <petstore.home>
hereafter in this document. ant
is
available in your path. You can use <javaeesdk.home>/lib/ant/bin/
or you can use your own ant installation as long as it is ant version
1.6.5 or later.<javaeesdk.home>/bin
to your path.<petstore.home>/bp-project/build.properties
and ensure
that the following properties match your Java EE 5 SDK
installation. | Property Name | Description | Examples |
javaee.home |
The installation directory of the Java EE 5 SDK or GlassFish | c:/Sun/AppServer |
javaee.server.name |
Host name of the server where the Java EE 5 SDK is installed | localhost |
javaee.server.port |
The port number for the server you chose while installing Java EE 5 SDK | 8080 |
javaee.server.username |
The administrator username specified for the server while installing Java EE 5 SDK | admin |
javaee.server.passwordfile |
The
path to a file containing the admin
password for the Java EE 5 SDK. The password file needs to be in the
following format:
Where you will replace <javaeesdk-admin-password> with the admin password for the Java EE 5 SDK. |
/path/to/passwordfile |
javaee.adminserver.port |
The port number for admin server you chose while installing the Java EE 5 SDK | 4848 |
proxy.host |
The host name of your HTTP proxy server, if the server running Java EE SDK is behind a firewall. Leave blank otherwise | myproxy.mydomain |
proxy.port |
The port number of your HTTP proxy server, if the server running Java EE SDK is behind a firewall. Leave blank otherwise | 8080 |
<javaeesdk.home>/bin
and issue the following
commands:
asadmin start-database
asadmin start-domain
ant setup
ant run
<javaeesdk.home>/bin
and issue the following
commands:asadmin start-domain
asadmin start-database
<petstore.home>
and enter the command:ant undeploy
ant unsetup
If you have problems when running the application, try the following:
"ant run"
command. Often an error here contains the clue for what went wrongCopyright © 2007 Sun Microsystems, Inc. All rights reserved.


|
F´ Flight Software - C/C++ Documentation
NASA-v1.5.0
A framework for building embedded system applications to NASA flight quality standards.
|
#include <Svc/FileDownlink/FileDownlink.hpp>
Public Member Functions | |
| Mode (void) | |
| Constructor. More... | |
| void | set (const Type value) |
| Set the Mode value. More... | |
| Type | get (void) |
| Get the Mode value. More... | |
| FileDownlink (const char *const compName, const U16 downlinkPacketSize) | |
| void | init (const NATIVE_INT_TYPE queueDepth, const NATIVE_INT_TYPE instance) |
| ~FileDownlink (void) | |
| void | FileDownlink_Cancel_cmdHandler (const FwOpcodeType opCode, const U32 cmdSeq) |
| void | pingIn_handler (const NATIVE_INT_TYPE portNum, U32 key) |
| Os::File::Status | sendDataPackets (void) |
| void | sendCancelPacket (void) |
| void | sendEndPacket (void) |
| void | sendStartPacket (void) |
| void | sendFilePacket (const Fw::FilePacket &filePacket) |
Public Attributes | |
| PRIVATE | __pad1__: void FileDownlink_SendFile_cmdHandler( const FwOpcodeType opCode |
| The opcode. More... | |
| PRIVATE const U32 | cmdSeq |
| The command sequence number. More... | |
| PRIVATE const U32 const Fw::CmdStringArg & | sourceFileName |
| The name of the on-board file to send. More... | |
| PRIVATE const U32 const Fw::CmdStringArg const Fw::CmdStringArg & | destFileName |
| < The name of the destination file on the ground More... | |
| PRIVATE | __pad2__: Os::File::Status sendDataPacket(const U32 byteOffset) |
| PRIVATE | __pad3__: const U32 downlinkPacketSize |
| Mode | mode |
| The mode. More... | |
| File | file |
| The file. More... | |
| FilesSent | filesSent |
| Files sent. More... | |
| PacketsSent | packetsSent |
| Packets sent. More... | |
| Warnings | warnings |
| Warnings. More... | |
| U32 | sequenceIndex |
| The current sequence index. More... | |
Definition at line 23 of file FileDownlink.hpp.
| Svc::FileDownlink::FileDownlink | ( | const char *const | compName, |
| const U16 | downlinkPacketSize | ||
| ) |
Construct object FileDownlink
| compName | The component name |
| downlinkPacketSize | The size of a downlink packet |
Definition at line 23 of file FileDownlink.cpp.
| Svc::FileDownlink::~FileDownlink | ( | void | ) |
Destroy object FileDownlink
Definition at line 47 of file FileDownlink.cpp.
| void Svc::FileDownlink::FileDownlink_Cancel_cmdHandler | ( | const FwOpcodeType | opCode, |
| const U32 | cmdSeq | ||
| ) |
Implementation for FileDownlink_Cancel command handler
| opCode | The opcode |
| cmdSeq | The command sequence number |
Definition at line 124 of file FileDownlink.cpp.
|
inline |
Get the Mode value.
Definition at line 56 of file FileDownlink.hpp.
| void Svc::FileDownlink::init | ( | const NATIVE_INT_TYPE | queueDepth, |
| const NATIVE_INT_TYPE | instance | ||
| ) |
Initialize object FileDownlink
| queueDepth | The queue depth |
| instance | The instance number |
Definition at line 38 of file FileDownlink.cpp.
|
inline |
Constructor.
Definition at line 44 of file FileDownlink.hpp.
| void Svc::FileDownlink::pingIn_handler | ( | const NATIVE_INT_TYPE | portNum, |
| U32 | key | ||
| ) |
Handler implementation for pingIn
| portNum | The port number |
| key | Value to return to pinger |
Definition at line 250 of file FileDownlink.cpp.
| void Svc::FileDownlink::sendCancelPacket | ( | void | ) |
Definition at line 191 of file FileDownlink.cpp.
| Os::File::Status Svc::FileDownlink::sendDataPackets | ( | void | ) |
Definition at line 172 of file FileDownlink.cpp.
| void Svc::FileDownlink::sendEndPacket | ( | void | ) |
Definition at line 202 of file FileDownlink.cpp.
| void Svc::FileDownlink::sendFilePacket | ( | const Fw::FilePacket & | filePacket | ) |
Definition at line 237 of file FileDownlink.cpp.
| void Svc::FileDownlink::sendStartPacket | ( | void | ) |
Definition at line 223 of file FileDownlink.cpp.
|
inline |
Set the Mode value.
Definition at line 49 of file FileDownlink.hpp.
| PRIVATE Svc::FileDownlink::__pad1__ |
The opcode.
Definition at line 238 of file FileDownlink.hpp.
| PRIVATE Svc::FileDownlink::__pad2__ |
Definition at line 268 of file FileDownlink.hpp.
| PRIVATE Svc::FileDownlink::__pad3__ |
Definition at line 286 of file FileDownlink.hpp.
| PRIVATE const U32 Svc::FileDownlink::cmdSeq |
The command sequence number.
Definition at line 248 of file FileDownlink.hpp.
| PRIVATE const U32 const Fw::CmdStringArg const Fw::CmdStringArg& Svc::FileDownlink::destFileName |
< The name of the destination file on the ground
Definition at line 250 of file FileDownlink.hpp.
| File Svc::FileDownlink::file |
The file.
Definition at line 299 of file FileDownlink.hpp.
| FilesSent Svc::FileDownlink::filesSent |
Files sent.
Definition at line 302 of file FileDownlink.hpp.
| Mode Svc::FileDownlink::mode |
The mode.
Definition at line 296 of file FileDownlink.hpp.
| PacketsSent Svc::FileDownlink::packetsSent |
Packets sent.
Definition at line 305 of file FileDownlink.hpp.
| U32 Svc::FileDownlink::sequenceIndex |
The current sequence index.
Definition at line 311 of file FileDownlink.hpp.
| PRIVATE const U32 const Fw::CmdStringArg& Svc::FileDownlink::sourceFileName |
The name of the on-board file to send.
Definition at line 249 of file FileDownlink.hpp.
| Warnings Svc::FileDownlink::warnings |
Warnings.
Definition at line 308 of file FileDownlink.hpp.


An analyses of data for Salaries for government employees of San Fransico showed that their women employees earn, on average, 84 cents for every dollar earned by men. Nationally, in 2014 women earned about 79 cents for every dollar earned by men. This pay gap exist in nearly every occupation. Even though, statistical analysis of available data gives a detailed understanding of this gap, the issue has been widely debated. The right wing policy makers and activists have called this gap a myth. While, AAUW’s The Simple Truth about the Gender Pay Gap addresses these in their very detailed report, we uses data visualization as a tool to show some of these apparent gaps, and debunk the widely misrepresented reasons to call gender pay gap a myth.
The most common reasons for calling gender pay gap a myth reported by articles, The ‘Wage Gap’ Myth That Won’t Die, Wall Street Journal and What’s the real gender pay gap?, Washington Post are:
“Full-time employment is technically defined as more than 35 hours. This raises an obvious problem: A simple side-by-side comparison of all men and all women includes people who work 35 hours a week, and others who work 45. Men are significantly more likely than women to work longer hours.” – WSJ
It is true that in many departments, men are making more money in overtime, but it is impossible to tell from the available data if their hourly rate is same as women and they are truly putting in more hours than women in similar jobs as theirs.
Nonetheless, women are also being discriminated on their base salaries, which can be seen here and in our next visualizations .
“Career choice is another factor. Research in 2013 by Anthony Carnevale, a Georgetown University economist, shows that women flock to college majors that lead to lower-paying careers. Of the 10 lowest-paying majors—such as “drama and theater arts” and “counseling psychology”—only one, “theology and religious vocations,” is majority male. Conversely, of the 10 highest-paying majors—including “mathematics and computer science” and “petroleum engineering”—only one, “pharmacy sciences and administration,” is majority female. Eight of the remaining nine are more than 70% male.” – WSJ
Those numbers do not reflect the number of proportion of men and women in each department and job titles in San Francisco government employment pool. The following visualization shows the scatter pot for average base salary and overtime pay for full time employees for each department. The size of the bubble show the percentage of employees in each gender with respect to their department. For spotting patterns visually, male employees are donated by a blue outline, whereas female employees are donated by red outline of the data points. Hover over a department in the legend to see more information about that department.
“[..] women remain more concentrated than men in lower-paying industries and occupations. They work disproportionately as health-care aides, receptionists, cashiers and food servers. This drags down women’s average wages. The second big difference is that women still have slightly less on-the-job experience than men. This, too, lowers their average wages.” -Washington Post
The following visualization show distribution of pay for each department, separated by their title. For spotting patterns visually, male employees are donated by a blue outline, whereas female employees are donated by red outline of the data points.


[Date]
The following is a summary of the principal terms with respect to the proposed Series Seed Preferred Stock financing of [_______], Inc., a [Delaware] corporation (the “Company”). Except for the section entitled “Binding Terms,” this summary of terms does not constitute a legally binding obligation. The parties intend to enter into a legally binding obligation only pursuant to definitive agreements to be negotiated and executed by the parties.
Shares of Series Seed Preferred Stock of the Company (the “Series Seed”).
$[_____] in aggregate.
[Accredited investors approved by the Company] (the “Purchasers”).
Price per share (the “Original Issue Price”), based on a pre-money valuation of $[__], including an available option pool of [_]%.
One times the Original Issue Price plus declared but unpaid dividends on each share of Series Seed, balance of proceeds paid to Common. A merger, reorganization or similar transaction will be treated as a liquidation.
Convertible into one share of Common (subject to proportional adjustments for stock splits, stock dividends and the like) at any time at the option of the holder.
Votes together with the Common Stock on all matters on an as converted basis. Approval of a majority of the Preferred Stock required to (i) adversely change rights of the Preferred Stock; (ii) change the authorized number of shares; (iii) authorize a new series of Preferred Stock having rights senior to or on parity with the Preferred Stock; (iv) redeem or repurchase any shares (other than pursuant to employee or consultant agreements); (v) declare or pay any dividend; (vi) change the number of directors; or (vii) liquidate or dissolve, including any change of control.
Documents will be identical to the Series Seed Preferred Stock documents published at www.seriesseed.com, except for the modifications set forth in this Term Sheet.
Purchasers who have invested at least [$____] (“Major Purchasers”) will receive standard information and inspection rights and management rights letter.
Major Purchasers will have the right to participate on a pro rata basis in subsequent issuances of equity securities.
[_] directors elected by holders of a majority of common stock, [] elected by holders of a majority of Series Seed and [___] elected by mutual consent.
Company to reimburse counsel to Purchasers for a flat fee of $10,000.
The Series Seed will be given the same rights as the next series of Preferred Stock (with appropriate adjustments for economic terms).
Each Key Holder shall have four years vesting beginning [___]. Full acceleration upon “Double Trigger.” Each Key Holder shall have assigned all relevant IP to the Company prior to closing.
For a period of thirty days, the Company shall not solicit offers from other parties for any financing. Without the consent of Purchasers, the Company shall not disclose these terms to anyone other than officers, directors, key service providers, and other potential Purchasers in this financing.
[______, INC.]
Name:
Title:
Date:
Name:
Title:
Date:


Project 1 - Facebook log in page
Project 2 - Landing page 1
Project 3 - Landing page 2
Project 4 - Landing page 3
Project 5 - Landing page 4
Project 6 - Landing page 5
Go back


 If you know what to do in
the shell, finding the Ansible playbook equivalent is difficult at first.
Type the command you would normally run below, and then see what would go
into the Ansible playbook below. The relevant Ansible docs will also be
shown.
Helper to translate shell commands to Ansible playbook entries.
Samples (click on a sample to try it)
apt-get install toilet fortune
sudo apt-get -y install toilet
apt-get remove lolcat
add-apt-repository -y ppa:foo/bar
apt-key adv --keyserver=hkp://keyserver.ubuntu.com:80 --recv-keys=1337
cp -r configs/ /etc/sandwich/
curl http://example.com/path/file.conf > /etc/foo.conf
docker run crccheck/hello-world
mkdir -p /tmp/farts/
npm install -g grunt-cli
pip install project_runpy==0.3.1
service elasticsearch start
Limitations
Very few commands are supported. Basically, just what's in these samples.
Options must be specified like --port=8000
, not --port 8000


TODGER & OUT
Police called to Bute pub after male stripper’s manhood pops out during raunchy ‘sausage party’ event
by Graham MannCOPS were called out after a male stripper’s manhood popped out — at a raunchy event an Isle of Bute pub had dubbed its “Sausage Party”.
A shocked punter landed the boozer in trouble by making a formal complaint about the fleeting flash of todger.
But last night bosses at the Scottish Honky Tonk in Ardbeg on the Firth of Clyde island blamed the incident on a costume cock-up.
Brody Jamieson, 50, and wife Rima, 43, also insisted they had ordered the performers not to strip off completely like Robert Carlyle in the 1997 film The Full Monty.
It came after they faced Argyll and Bute Council to explain what went wrong at their “Scottish Honky Tonk Sausage Party” in February.
Their representative, Peter Austin, told licensing chiefs: “The dancers were told they were not to go the Full Monty. But these instructions were gone against.
“One dancer covered his modesty with a flag — which was removed.
“It was only visible to a few people, not the entire crowd.”
A poster for the event featured a cartoon image of a grinning sausage.
Chief Superintendent John Paterson told how cops launched a probe as the venue had no adult entertainment licence.
He said: “The fiscal has sent a warning letter.”
The council’s licensing committee chair David Kinniburgh agreed the incident was a one-off, adding: “I think the lesson has been learned.”
Last night Mr Jamieson, who has pledged not to host any more strip nights, insisted: “It really was just a wardrobe malfunction.”


Using Regular Expressions
KSS is capable of finding the exact text you are looking for in any ASCII file or files. However, sometimes you have only part of the information that you want to match, or you want to find a wider range of information. In such cases, KSS has the powerful capability to search for patterns of text using regular expressions.
Regular expressions are a notation for specifying patterns of text, as opposed to exact strings of characters. The notation uses literal characters and metacharacters. Every character that does not have special meaning in the regular expression syntax is a literal character and matches an occurrence of that character. For example, letters and numbers are literal characters. A metacharacter is a symbol with special meaning (an operator or delimiter) in the regular-expression syntax.
The following table lists the metacharacters that the Search For dialog accepts.
|
. |
Period (.) matches any single character except a new line. For example: .P matches any single character followed by a P in a string. Using concatenation we can make regular expressions like 'U.A', which matches any three-character sequence that begins with 'U' and ends with 'A'. |
|
* |
Asterisk means that the preceding regular expression is to be repeated as many times as possible to find a match. For example: ph* applies the * symbol to the preceding h and looks for matches to one p followed by any number of h's. This will also match just p if no h's are present. The * repeats the smallest possible preceding expression (use parentheses if you wish to repeat a larger expression). It finds as many repetitions as possible. For example: (c[ad][ad]*r x) matches a string of the form (car x), (cdr x), (cadr x), and so on. |
|
^ |
Caret matches the beginning of the string or the beginning of a line within the string. For example:^@chapter matches the "@chapter" at the beginning of a string. |
|
$ |
Dollar sign is similar to the caret, but it matches only at the end of a string or the end of a line within the string. For example:p$ matches a record that ends with a p. |
|
[class] |
Character class: it matches any one of the characters that are enclosed in the square brackets. For example: [MVX] matches any one of the characters M, V, or X in a string. Ranges of characters are indicated by using a hyphen between the beginning and ending characters, and enclosing the whole thing in brackets. For example:[0-9] matches any digit. To match '-', write it as '---', which is a range containing only '-'. You may also give '-' as the first or last character in the set. To match '^', put it anywhere except as the first character of a set. To match a ']', make it the first character in the set. For example: []d^]matches either ']', 'd' or '^'. |
|
[^class] |
Inverse class: the first character after the [ must be a ^. It matches any characters except those in the square brackets (or newline). For example: [^0-9] matches any character that is not a digit. |
|
\x |
Backslash is used to suppress the special meaning of a character when matching. For example: \$ matches the character $. |
|
\<xyz |
Word position: beginning of word |
|
xyz\> |
Word position: end of word |


CMInvocationUtils Class Reference
| Inherits from | NSObject |
| Declared in | CMInvocationUtils.h CMInvocationUtils.m |
Overview
- Utility class for creating NSINvocation objects.
Tasks
-
+ constructInvocation:selector:
- Constructs a new NSInvocation with the specified target and selector.
Class Methods
constructInvocation:selector:
- Constructs a new NSInvocation with the specified target and selector.
+ (NSInvocation *)constructInvocation:(id)target selector:(SEL)selector
Discussion
- Constructs a new NSInvocation with the specified target and selector.
*
- @param target the target to invoke.
- @param selector the selector to invoke.
*
- @return the NSInvocation or nil when one of the parameters is not correct.
Declared In
CMInvocationUtils.h


"EMIMS "terrors, a warlike tribe of giants who were defeated by Chedorlaomer and his allies in the plain of Kiriathaim. In the time of Abraham they occupied the country east of Jordan, afterwards the land of the Moabites (Genesis 14:5; Deuteronomy 2:10). They were, like the Anakim, reckoned among the Rephaim, and were conquered by the Moabites, who gave them the name of Emims, i.e., “terrible men”(Deuteronomy 2:11). The Ammonites called them Zamzummims (2:20).
"EMIMS "terrors, a warlike tribe of giants who were defeated by Chedorlaomer and his allies in the plain of Kiriathaim. In the time of Abraham they occupied the country east of Jordan, afterwards the land of the Moabites (Genesis 14:5; Deuteronomy 2:10). They were, like the Anakim, reckoned among the Rephaim, and were conquered by the Moabites, who gave them the name of Emims, i.e., “terrible men”(Deuteronomy 2:11). The Ammonites called them Zamzummims (2:20).


We are a group of Students form Lambda School. We are in different tracks and places in the course and are all filling suitable roles based on those places. Half of our group is in the Data Science Cohort; they oversaw cleaning and scraping the data as well as making the prediction models. The other half of our group was in the Web Development group, they were tasked with, designing the landing pages, creating the login and displaying the results given to them by the DS team.


{{ define "main" }}
Vald is a highly scalable distributed fast approximate nearest neighbor dense vector search engine.
Vald is designed and implemented based on the Cloud-Native architecture. It uses the fastest ANN Algorithm NGT to search neighbors. Vald has automatic vector indexing and index backup, and horizontal scaling which made for searching from billions of feature vector data. Vald is easy to use, feature-rich and highly customizable as you needed.
Usually the graph requires locking during indexing, which cause stop-the-world. But Vald uses distributed index graph so it continues to work during indexing.
Vald implements it's own highly customizable Ingress/Egress filter. Which can be configured to fit the gRPC interface.
Horizontal scalable on memory and cpu for your demand.
Vald supports to auto backup feature using Object Storage or Persistent Volume which enables disaster recovery.
Vald distribute vector index to multiple agent, each agent stores different index.
Vald stores each index in multiple agents which enables index replicas. Automatically rebalance the replica when some Vald agent goes down.
Vald can be easily installed in a few steps.
You can configure the number of vector dimension, the number of replica and etc.
Golang, Java, Nodejs and python is supported.


Region Select
{{ selectedRegion || "All Regions (Global)" }}
This is a POPOVER, when you click elsewhere, I'll vanish!
This is a TOOLTIP, when you hover elsewhere, I'll disappear!!!!!! TESTESTESTESTESTESTESTESTESTESTESTESTESETESTSETESTS
Servers


CAFES
Name: Cafe Solstice
Located At: 925 E Thomas St, Seattle, WA 98102, USA
Rating: 4.5
Distance from Current Location: 11.8 mi
Driving Time: 20 mins
Name: Fonté Café - Seattle
Located At: 1321 1st Ave, Seattle, WA 98101, USA
Rating: 4.4
Distance from Current Location: 13.4 mi
Driving Time: 22 mins
Name: Seattle Meowtropolitan - Seattle's first Cat Cafe
Located At: 1225 N 45th St, Seattle, WA 98103, USA
Rating: 4.7
Distance from Current Location: 12.2 mi
Driving Time: 20 mins
Name: La Marzocco Cafe
Located At: 472 1st Ave N, Seattle, WA 98109, USA
Rating: 4.7
Distance from Current Location: 12.7 mi
Driving Time: 23 mins
Name: Beth's Cafe
Located At: 7311 Aurora Ave, Seattle, WA 98103, USA
Rating: 4.5
Distance from Current Location: 14.6 mi
Driving Time: 22 mins
BREAKFAST
Name: The Fat Hen
Located At: 1418 NW 70th St, Seattle, WA 98117, USA
Rating: 4.5
Distance from Current Location: 16.2 mi
Driving Time: 28 mins
Name: Biscuit Bitch
Located At: 1909 1st Ave, Seattle, WA 98101, USA
Rating: 4.4
Distance from Current Location: 15.7 mi
Driving Time: 23 mins
Name: Portage Bay Cafe - Roosevelt
Located At: 4130 Roosevelt Way NE, Seattle, WA 98105, USA
Rating: 4.3
Distance from Current Location: 11.6 mi
Driving Time: 18 mins
Name: Glo's
Located At: 1621 E Olive Way, Seattle, WA 98102, USA
Rating: 4.5
Distance from Current Location: 12.0 mi
Driving Time: 19 mins
Name: Lowell's Restaurant & Bar
Located At: 1519 Pike Pl, Seattle, WA 98101, USA
Rating: 4.4
Distance from Current Location: 13.4 mi
Driving Time: 23 mins
LUNCH
Name: Il Corvo
Located At: 217 James St, Seattle, WA 98104, USA
Rating: 4.8
Distance from Current Location: 12.9 mi
Driving Time: 19 mins
Name: Market Grill
Located At: 1509 Pike Pl Ste 3, Seattle, WA 98101, USA
Rating: 4.6
Distance from Current Location: 12.7 mi
Driving Time: 21 mins
Name: Matt's in the Market
Located At: 94 Pike St #32, Seattle, WA 98101, USA
Rating: 4.6
Distance from Current Location: 13.3 mi
Driving Time: 21 mins
Name: TAT'S Delicatessen
Located At: 159 Yesler Way, Seattle, WA 98104, USA
Rating: 4.7
Distance from Current Location: 13.2 mi
Driving Time: 20 mins
Name: Tilikum Place Cafe
Located At: 407 Cedar St, Seattle, WA 98121, USA
Rating: 4.6
Distance from Current Location: 13.2 mi
Driving Time: 22 mins
DINNER
Name: The Pink Door
Located At: 1919 Post Alley, Seattle, WA 98101, USA
Rating: 4.6
Distance from Current Location: 12.9 mi
Driving Time: 22 mins
Name: Nue
Located At: 1519 14th Ave, Seattle, WA 98122, USA
Rating: 4.5
Distance from Current Location: 11.7 mi
Driving Time: 22 mins
Name: Canlis
Located At: 2576 Aurora Ave, Seattle, WA 98109, USA
Rating: 4.7
Distance from Current Location: 13.1 mi
Driving Time: 20 mins
Name: Stateside
Located At: 300 E Pike St #1200, Seattle, WA 98122, USA
Rating: 4.5
Distance from Current Location: 12.6 mi
Driving Time: 19 mins
Name: The 5 Point Cafe
Located At: 415 Cedar St, Seattle, WA 98119, USA
Rating: 4.2
Distance from Current Location: 13.3 mi
Driving Time: 22 mins
MUSEUMS
Name: Museum of Pop Culture
Located At: 325 5th Ave N, Seattle, WA 98109, USA
Rating: 4.6
Distance from Current Location: 12.2 mi
Driving Time: 20 mins
Name: Seattle Art Museum
Located At: 1300 1st Ave, Seattle, WA 98101, USA
Rating: 4.6
Distance from Current Location: 12.6 mi
Driving Time: 20 mins
Name: Museum of History & Industry (MOHAI)
Located At: 860 Terry Ave N, Seattle, WA 98109, USA
Rating: 4.6
Distance from Current Location: 11.6 mi
Driving Time: 18 mins
Name: The Museum of Flight
Located At: 9404 E Marginal Way S, Seattle, WA 98108, USA
Rating: 4.8
Distance from Current Location: 21.2 mi
Driving Time: 27 mins
Name: Chihuly Garden and Glass
Located At: 305 Harrison St, Seattle, WA 98109, USA
Rating: 4.7
Distance from Current Location: 12.4 mi
Driving Time: 22 mins
PARKS
Name: Discovery Park
Located At: 3801 Discovery Park Blvd, Seattle, WA 98199, USA
Rating: 4.8
Distance from Current Location: 16.6 mi
Driving Time: 32 mins
Name: Gas Works Park
Located At: 2101 N Northlake Way, Seattle, WA 98103, USA
Rating: 4.7
Distance from Current Location: 11.2 mi
Driving Time: 21 mins
Name: Kerry Park
Located At: 211 W Highland Dr, Seattle, WA 98119, USA
Rating: 4.7
Distance from Current Location: 12.9 mi
Driving Time: 23 mins
Name: Golden Gardens Park
Located At: 8498 Seaview Pl NW, Seattle, WA 98117, USA
Rating: 4.7
Distance from Current Location: 17.8 mi
Driving Time: 34 mins
Name: Green Lake Park
Located At: 7201 East Green Lake Dr N, Seattle, WA 98115, USA
Rating: 4.7
Distance from Current Location: 12.8 mi
Driving Time: 21 mins


class TestRail::Connection
Public Class Methods
Get ID of all test cases from current test run
cases = client.send_get(“get_tests/12”)
# File lib/test_rail_integration/generator/connection.rb, line 95 def self.cases_id(test_run_id) cases = client.send_get("get_tests/#{test_run_id}") cases.map { |test_case| test_case["case_id"] } end
Take all test types
# File lib/test_rail_integration/generator/connection.rb, line 146 def self.cases_with_types types = TYPES cases = client.send_get("get_cases/#{project_id}&suite_id=#{test_suite_id}&type_id=#{types}") case_ids = cases.map { |test_case| test_case["id"] } case_ids end
Changing name of test run from <test run name> in progress to <test run name>
VN LIVE_TEST in progress => VN LIVE_TEST
# File lib/test_rail_integration/generator/connection.rb, line 158 def self.change_test_run_name(run_id = test_run_id) new_name = test_run_name.gsub(IN_PROGRESS, "") client.send_post("update_run/#{run_id}", {name: new_name}) end
Creates connection to TestRail server
client = TestRail::APIClient.new('<TestRail server>',“<User email>”,“<User password>”)
# File lib/test_rail_integration/generator/connection.rb, line 22 def self.client @client_test_rail ||= TestRail::APIClient.new(CONNECTION_DATA) end
Send test result to TestRail for current test run client.send_post(“add_result_for_case/<number_of test run>/<test case id>”, <result that pushes>)
client.send_post(“add_result_for_case/12/3131”, status_id: '1', comment: “Test passed” )
# File lib/test_rail_integration/generator/connection.rb, line 32 def self.commit_test_result(test_case_result) client.send_post("add_result_for_case/#{TEST_RUN_ID}/#{test_case_result.test_case_id}", test_case_result.to_test_rail_api) end
Send request for creation test run with name (“add_run/3”, {suite_id: 3, name “New test run”, include_all: false, case_ids: C31, C32, C33}
# File lib/test_rail_integration/generator/connection.rb, line 167 def self.create_new_test_run_with_name client.send_post("add_run/#{project_id}", {suite_id: test_suite_id, name: generate_test_run_name, include_all: false, case_ids: cases_with_types}) end
Create test run in test rail for project with name
# File lib/test_rail_integration/generator/connection.rb, line 48 def self.create_test_run_with_name(name) client.send_post("add_run/#{project_id}", {suite_id: test_suite_id, name: name, include_all: false, case_ids: cases_with_types}) end
Generate name for test run with date
# File lib/test_rail_integration/generator/connection.rb, line 181 def self.generate_test_run_name "Test run #{Time.now.strftime("%d/%m/%Y")}" end
Get indexes of failed results
# File lib/test_rail_integration/generator/connection.rb, line 76 def self.get_indexes_of_fails(test_case_id) indexes = get_test_result(test_case_id).map.with_index { |result, index| result["status_id"] == TestCaseResult::COMMENT[:fail][:status] ? index : nil } indexes.compact end
Get last failed comment for test case
# File lib/test_rail_integration/generator/connection.rb, line 84 def self.get_last_failed_comment(test_case_id) comments = get_previous_comments(test_case_id) index = Connection.get_indexes_of_fails(test_case_id).first comments[index] end
Parse results and returns previous comment.
# File lib/test_rail_integration/generator/connection.rb, line 66 def self.get_previous_comments(case_id) test_comment = get_test_result(case_id).map { |hash| hash["comment"] } comment = test_comment comment ||= [] comment end
Parse results and returns Failed if this test was marked as failed.
# File lib/test_rail_integration/generator/connection.rb, line 55 def self.get_previous_test_result(case_id) test_results = get_test_result(case_id).map { |status_hash| status_hash["status_id"] } status = TestCaseResult::FAILED if test_results.include?(TestCaseResult::FAILED) status ||= TestCaseResult::PASS if test_results.first == TestCaseResult::PASS status ||= TestCaseResult::NEW status end
Obtaining of all previous test results for current test case
client.send_get(“get_results_for_case/12/3534”)
# File lib/test_rail_integration/generator/connection.rb, line 41 def self.get_test_result(case_id) client.send_get("get_results_for_case/#{test_run_id}/#{case_id}") end
Get all test runs for project
# File lib/test_rail_integration/generator/connection.rb, line 174 def self.get_test_runs client.send_get("get_runs/#{project_id}") end
Setting project id
# File lib/test_rail_integration/generator/connection.rb, line 117 def self.project_id @project_id ||= PROJECT_ID end
Getting information about test run
# File lib/test_rail_integration/generator/connection.rb, line 132 def self.test_run_data(id_of_run=test_run_id) client.send_get("get_run/#{id_of_run}") end
Setting test run id value
# File lib/test_rail_integration/generator/connection.rb, line 110 def self.test_run_id @test_run_id ||= TEST_RUN_ID end
Setting up test run id
# File lib/test_rail_integration/generator/connection.rb, line 103 def self.test_run_id=(test_run_id) @test_run_id = test_run_id end
Get test run name
# File lib/test_rail_integration/generator/connection.rb, line 139 def self.test_run_name(id_of_run=test_run_id) test_run_data(id_of_run)["name"] end
Setting test suite id
# File lib/test_rail_integration/generator/connection.rb, line 125 def self.test_suite_id @test_suite_id ||= TEST_SUITE end


CATSPER
The cation channels of sperm also known as Catsper channels or CatSper, are ion channels that are related to the two-pore channels and distantly related to TRP channels. The four members of this family form voltage-gated Ca 2+ channels that seem to be specific to sperm. As sperm encounter the more alkaline environment of the female reproductive tract, CatSper channels become activated by the altered ion concentration. These channels are required for proper fertilization. The study of these channels has been slow because they do not traffic to the cell membrane in many heterologous systems.
(hgnc.genefamily:186)
Cross-references
Synonyms
None available.
Incoming Relations
Outgoing Relations


| | |
- define_components(mod)
- Augments a Pyomo abstract model object with sets and parameters to
describe fuel markets. Unless otherwise stated, each set
and parameter is mandatory. Unless otherwise specified, all dollar
values are real dollars in BASE_YEAR.
REGIONAL_FUEL_MARKET is the set of all regional fuel markets. This
may be may be abbreviated as rfm in parameter names and indexes, and
may occasionally be referred to as a fuel region. In the current
implementation, the names of each regional fuel market need to be
distinct for each fuel type. That is, you cannot use "SouthWest" as
a name for both natural gas and coal fuels. This is because market
boundaries may be different for different fuel types due to physical
infrastructure. This implementation detail could be revisited later
if it proves cumbersome. An alternate implementation could specify
each regional fuel market as a tuple pair of (region, fuel), but
this might make indexing parameters in the code more verbose,
confusing and error prone.
rfm_fuel[rfm] defines the fuel sold in a regional fuel market.
LZ_FUELS is the set of fuels available in load zones. It is specified
as set of 2-member tuples of (load_zone, fuel).
lz_rfm[z, f] is the regional fuel market that supplies a a given load
zone. Regional fuel markets may be referred to as fuel regions for
brevity. A regional fuel market could be as small as a single load
zone or as large as the entire study region. In general, each fuel
type needs to separately specify its regional fuel market because
most fuels have distinct transportation infrastructure, and
bottlenecks in this infrastructure can form the physical divisions
that define different regional markets.
LZ_RFM is the set of all load-zone regional fuel market combinations.
It is the input data from which lz_rfm[z,f] is derived.
RFM_LOAD_ZONES[rfm] is an indexed set that lists the load zones
within each regional fuel market.
RFM_SUPPLY_TIERS is a set of 3-part tuples that stores:
regional_fuel_market, period, supply_tier
RFM_P_SUPPLY_TIERS[rfm, period] is an indexed set of supply tiers
for a given regional fuel market and period. Supply tiers are an
ordered set typically labeled 1 to n. Each tier of a supply curve
have a cost and limit.
rfm_supply_tier_cost[rfm, period, tier] is the cost of a fuel in a
particular tier of a supply curve of a particular regional fuel
market and investment period. The units are $ / MMBTU.
rfm_supply_tier_limit[rfm, period, tier] is the annual limit of a
fuel available at a particular cost in a supply curve of a
particular regional fuel market and period. The default value of
this parameter is infinity, indicating no limit. The units are MMBTU.
FuelConsumptionByTier[rfm, period, tier] is a decision variable that
denotes the amount of fuel consumed in each tier of a supply curve
in a particular regional fuel market and period. It has an upper bound
of rfm_supply_tier_limit.
FuelConsumptionInMarket[rfm, period] is a derived decision variable
specifying the total amount of fuel consumed in a regional fuel
market in a given period. In a dispatch module, a constraint should
set this equal to the sum of all fuel consumed in that region. At
some point in the future, I may convert this from a decision
variable to an expression.
Enforce_Fuel_Consumption_By_Tier[rfm, period] is a constraint that
forces the total fuel consumption FuelConsumptionInMarket to be
divided into distinct supply tiers.
FuelConsumptionInMarket = sum(FuelConsumptionByTier)
lz_fuel_cost_adder[z, f, p] is an optional parameter that describes
a localized flat cost adder for fuels. This could reflect local
markup from a longer supply chain or more costly distribution
infrastructure. The units are $ / MMBTU and the default value is 0.
The total cost of of a given type of fuel is calculated as:
sum(FuelConsumptionByTier * rfm_supply_tier_cost) +
sum(fuel_consumption_in_load_zone * lz_fuel_cost_adder)
Each regional fuel market has a supply curve with discrete tiers
of escalating costs. Tiered supply curves are flexible format that
allows anything from a flat cost in every load zone with no limits
on consumption, to a detailed supply curve of biomass for each load
zone. To specify a simple flat cost, you would lump every load zone
into a single regional fuel markets and specify a single-tier supply
curve with no upper limit. To specify a detailed biomass supply
curve, you would assign each load zone to a distinct biomass
regional fuel market and specify multiple tiers in each market,
where each tier has an upper bound.
There is a simple data input format for situations where regional
supply curves are unnecessary or undesired. This format specifies a
flat cost for a load zones, fuel and period combination. The import
code will expand this into a regional fuel market containing a
single load zone with a single supply tier that has no upper bound.
See load_inputs() function documentation below for more details.
In SWITCH-WECC, biomass regional fuel markets are defined for each
load area due to relatively high transportation costs, while natural
gas regional fuel markets span the entire WECC region reflecting the
interconnectedness of the pipelines. Prices can differ between load
zones within the region based on different costs of infrastructure
or number of middlemen in the supply chain, but all costs are based
on an underlying commodity supply curve. Load-zone level price
adjustments are specified with the lz_fuel_cost_adder parameter,
based on fuel regions used by the National Energy Modeling System.
For tiers of a supply curve with upper limits, the total volume on
the supply curve is determined by aggregating annual consumption
over all load zones in the regional fuel market. The model could be
adjusted to aggregate consumption over other time scales, but
currently only annual aggregation is implemented for supply curves.
This version of SWITCH does not distinguish costs incurred by
different fuel consumers within a regional fuel market.
This version of SWITCH does not include producer surplus, so the
aggregate cost paid for a given level of consumption does not
reflect a market clearing price. SWITCH looks for societally and
technically optimal solutions on the efficiency frontier that
minimizes total costs, while trying to avoid embedding assumptions
about market structure and dynamics. There are two primary
motivations for this approach. First, many applications of SWITCH
are for non-markets contexts of regulated utilities or state-owned
utilities. Second, we don't currently know how electricity markets
should be structured in high-renewable futures to incentivize
investments that meet long-term societal goals and ensure cost-
effective and reliable electricity. In the future it is quite
possible that a large volume of energy consumption will be procured
with favorable long-term contracts near cost rather than on a spot
market that sets a clearing price equal to the largest accepted bid,
which can awarding significant producer surplus. Alternatively, if
consumers choose what infrastructure they want access to, they may
seek long-term capacity contracts that incentivize investment and
guarantee receipts for capital repayments and fixed costs. I don't
know what the future of energy institutions or markets will hold,
and I don't want to limit the technical possibilities with market
structures from the past. One of our hopes is results from
optimization models such as SWITCH can inform future market and
institutional restructuring to ensure that our societal goals are
achieved cost-effectively.
That being said, if a future researcher wished to include producer
surplus to model a different perspective, that would be relatively
straightforward to accomplish. The basic method is to order each
segment of the supply curve by price, then going from low to high,
increase the cost of each tier to reflect the producer surplus
incurred from moving up from the next cheapest tier.
Currently the model only supports supply curves with monotonically
increasing costs. In theory it would be possible to support supply
curves showing economies of scale with costs falling with higher
volumes, but this is not currently supported. Implementing arbitrary
supply curves would require introducing integer variables and
potentially exposing non-linearities. Also, most scenarios generally
show fuel consumption declining over time as the power sector is
decarbonized, while the optimization becomes insensitive to the
direct cost of carbon-based fuel because the emissions associated
with the fuel are a much larger driver of consumption than the fuel
costs.
RFM_DISPATCH_POINTS[regional_fuel_market, period] is an indexed set
of PROJ_FUEL_DISPATCH_POINTS that contribute to a given regional
fuel market's activity in a given period.
Enforce_Fuel_Consumption is a constraint that ties the aggregate
fuel consumption from dispatch into FuelConsumptionInMarket variable
from the fuel module.
AverageFuelCosts[regional_fuel_market, period] is an expression that
calculates the average cost paid for fuel in each market and period.
This can be useful for post-optimization calculations of costs. Do
not use this term in the optimization or else the problem will
become non-linear.
- load_inputs(mod, switch_data, inputs_dir)
- Import fuel market data. The following files are expected in the
input directory:
regional_fuel_markets.tab:
regional_fuel_market, fuel
fuel_supply_curves.tab
regional_fuel_market, period, tier, unit_cost, max_avail_at_cost
lz_to_regional_fuel_market.tab
load_zone, regional_fuel_market
The next file is optional. If unspecified, lz_fuel_cost_adder will
default to 0 for all load zones and periods.
lz_fuel_cost_diff.tab
load_zone, fuel, period, fuel_cost_adder
The next file is also optional. This file allows simple
specification of one cost per load zone per period. The extra layer
of regional fuel markets could be cumbersome for folks working on
simple models. Internally, the import process converts the simple
cost specifications to a regional fuel market structure. Import of
this file is accomplished through the internal
_load_simple_cost_data function.
fuel_cost.tab
load_zone, fuel, period, fuel_cost
|