Reaper Documentation
Downloads
See the download section for information on how to download and install reaper.
Configuration
An example testing configuration YAML file can be found from within this project repository:
src/test/resources/cassandra-reaper.yaml
The configuration file structure is provided by Dropwizard, and help on configuring the server, database connection, or logging, can be found at:
http://www.dropwizard.io/1.1.0/docs/manual/configuration.html
Backends
Cassandra Reaper can be used with either an ephemeral memory storage or persistent database.
For persistent relational database storage, you must either setup PostgreSQL or H2. You also need to set storageType: database
in the config file.
Sample yaml files are available in the resource
directory for each storage backend:
* cassandra-reaper-memory.yaml
* cassandra-reaper-postgres.yaml
* cassandra-reaper-h2.yaml
* cassandra-reaper-cassandra.yaml
For configuring other aspects of the service, see the available configuration options in later section of this page.
Memory Backend
Running Reaper with memory storage, which is not persistent, means that all
the registered clusters, column families, and repair runs will be lost upon service restart.
The memory based storage is meant to be used for testing purposes only. Enable this type of storage by using the storageType: memory
setting in your config file (enabled by default).
storageType: memory
H2 Backend
When using H2 storage the database will automatically created for you under the path configured in cassandra-reaper.yaml
. Please
comment/uncomment the H2 settings and modify the path as needed or use the cassandra-reaper-h2.yaml
as a base.
storageType: database
database:
# H2 JDBC settings
driverClass: org.h2.Driver
url: jdbc:h2:~/reaper-db/db;MODE=PostgreSQL
user:
password:
Postgres Backend
The schema will be initialized/upgraded automatically upon startup in the configured database.
Make sure to specify the correct credentials in your JDBC settings in cassandra-reaper.yaml
to allow objects creation.
storageType: database
database:
# PostgreSQL JDBC settings
driverClass: org.postgresql.Driver
user: postgres
password:
url: jdbc:postgresql://<IP_ADDRESS>/reaper
Cassandra Backend
For persistent Apache Cassandra storage, you need to set storageType: cassandra
in the config file.
You’ll also need to fill in the connection details to your Apache Cassandra cluster used to store the Reaper schema (reaper_db by default), in the cassandra:
section of the yaml file.
storageType: cassandra
cassandra:
clusterName: "test"
contactPoints: ["<IP_ADDRESS>"]
keyspace: reaper_db
queryOptions:
consistencyLevel: LOCAL_QUORUM
serialConsistencyLevel: SERIAL
When using SSL:
cassandra:
storageType: cassandra
clusterName: "test"
contactPoints: ["<IP_ADDRESS>"]
keyspace: reaper_db
authProvider:
type: plainText
username: cassandra
password: cassandra
ssl:
type: jdk
Other Configuration settings
The Reaper service specific configuration values are:
segmentCount
:
Defines the default amount of repair segments to create for newly registered Cassandra repair runs (token rings). When running a repair run by the Reaper, each segment is repaired separately by the Reaper process, until all the segments in a token ring are repaired. The count might be slightly off the defined value, as clusters residing in multiple data centers require additional small token ranges in addition to the expected. You can overwrite this value per repair run, when calling the Reaper.
repairParallelism
:
Defines the default type of parallelism to use for repairs. Repair parallelism value must be one of: “sequential”, “parallel”, or “datacenter_aware”. If you try to use “datacenter_aware” in clusters that don’t support it yet (older than 2.0.12), Reaper will fall back into using “sequential” for those clusters.
repairIntensity
:
Repair intensity is a value between 0.0 and 1.0, but not zero. Repair intensity defines the amount of time to sleep between triggering each repair segment while running a repair run. When intensity is one, it means that Reaper doesn’t sleep at all before triggering next segment, and otherwise the sleep time is defined by how much time it took to repair the last segment divided by the intensity value. 0.5 means half of the time is spent sleeping, and half running. Intensity 0.75 means that 25% of the total time is used sleeping and 75% running. This value can also be overwritten per repair run when invoking repairs.
incrementalRepair
:
Incremental repair is a boolean value (true | false). Note that this is only supported with the PARALLEL repairParallelism setting. For more details in incremental repair, please refer to the following article.http://www.datastax.com/dev/blog/more-efficient-repairs
Note: We do not currently recommend using incremental repair before Cassandra 4.0 as subtle bugs can lead to overstreaming and cluster instabililty.
repairRunThreadCount
:
The amount of threads to use for handling the Reaper tasks. Have this big enough not to cause blocking in cause some thread is waiting for I/O, like calling a Cassandra cluster through JMX.
hangingRepairTimeoutMins
:
The amount of time in minutes to wait for a single repair to finish. If this timeout is reached, the repair segment in question will be cancelled, if possible, and then scheduled for later repair again within the same repair run process.
scheduleDaysBetween
:
Defines the amount of days to wait between scheduling new repairs. The value configured here is the default for new repair schedules, but you can also define it separately for each new schedule. Using value 0 for continuous repairs is also supported.
storageType
:
Whether to use database or memory based storage for storing the system state. Value can be either “memory”, “database” or “cassandra”. If you are using the recommended (persistent) storage type “database” or “cassandra”, you need to define the database client parameters in a database/cassandra section in the configuration file. See the example settings in provided testing configuration in src/test/resources/cassandra-reaper.yaml.
jmxPorts
:
Optional mapping of custom JMX ports to use for individual hosts. The used default JMX port
value is 7199. CCM users will find IP and port number
to add in ~/.ccm/<cluster>/*/node.conf
or by running ccm <node> show
.
jmxAuth
:
Optional setting for giving username and password credentials for the used JMX connections in case you are using password based JMX authentication with your Cassandra clusters.
jmxAuth:
username: cassandra
password: cassandra
enableCrossOrigin
:
Optional setting which you can set to be “true”, if you wish to enable the CORS headers for running an external GUI application, like this project.
autoScheduling
:
Optional setting to automatically setup repair schedules for all non-system keyspaces in a cluster. If enabled, adding a new cluster will automatically setup a schedule repair for each keyspace. Cluster keyspaces are monitored based on a configurable frequency, so that adding or removing a keyspace will result in adding / removing the corresponding scheduled repairs.
Notice that in the server section of the configuration, if you want to bind the service to all interfaces, use value “<IP_ADDRESS>”, or just leave the bindHost line away completely. Using “*” as bind value won’t work.
Multi-DC
For security reasons, it is possible that Reaper will be able to access only a single DC nodes through JMX.
The allowUnreachableNodes
parameter in cassandra-reaper.yaml
must then be set to true in order for Reaper to control the repair process through the reachable nodes only.
Limitations of this setup are:
- All keyspaces must be replicated on the reachable DC using NetworkTopologyStrategy
- Reaper won’t be able to check the unreachable DC nodes for pending compactions or running repairs, which disables repair overload prevention
Leaving allowUnreachableNodes to false will prevent all repair sessions once a single node from the cluster is unreachable
Rest API
Source code for all the REST resources can be found from package io.cassandrareaper.resources.
Ping Resource
- GET /ping
- Expected query parameters: None
- Simple ping resource that can be used to check whether the reaper is running.
Cluster Resource
GET /cluster
- Expected query parameters:
- seedHost: Limit the returned cluster list based on the given seed host. (Optional)
- Returns a list of registered cluster names in the service.
- Expected query parameters:
GET /cluster/{cluster_name}
- Expected query parameters:
- limit: Limit the number of repair runs returned. Recent runs are prioritized. (Optional)
- Returns a cluster object identified by the given “cluster_name” path parameter.
POST /cluster
- Expected query parameters:
- seedHost: Host name or IP address of the added Cassandra clusters seed host.
- Adds a new cluster to the service, and returns the newly added cluster object, if the operation was successful.
- Expected query parameters:
PUT /cluster/{cluster_name}
- Expected query parameters:
- seedHost: New host name or IP address used as Cassandra cluster seed.
- Modifies a cluster’s seed host. Comes in handy when the previous seed has left the cluster.
- Expected query parameters:
DELETE /cluster/{cluster_name}
- Expected query parameters: None
- Delete a cluster object identified by the given “cluster_name” path parameter. Cluster will get deleted only if there are no schedules or repair runs for the cluster, or the request will fail. Delete repair runs and schedules first before calling this.
Repair Run Resource
GET /repair_run
- Optional query parameters:
- state: Comma separated list of repair run state names. Only names found in io.cassandrareaper.core.RunState are accepted.
- Returns a list of repair runs, optionally fetching only the ones with state state.
GET /repair_run/{id}
- Expected query parameters: None
- Returns a repair run object identified by the given “id” path parameter.
GET /repair_run/cluster/{cluster_name} (io.cassandrareaper.resources.RepairRunResource)
- Expected query parameters: None
- Returns a list of all repair run statuses found for the given “cluster_name” path parameter.
POST /repair_run
- Expected query parameters:
- clusterName: Name of the Cassandra cluster.
- keyspace: The name of the table keyspace.
- tables: The name of the targeted tables (column families) as comma separated list. If no tables given, then the whole keyspace is targeted. (Optional)
- owner: Owner name for the run. This could be any string identifying the owner.
- cause: Identifies the process, or cause the repair was started. (Optional)
- segmentCount: Defines the amount of segments to create for repair run. (Optional)
- repairParallelism: Defines the used repair parallelism for repair run. (Optional)
- intensity: Defines the repair intensity for repair run. (Optional)
- incrementalRepair: Defines if incremental repair should be done. true/false
PUT /repair_run/{id}
- Expected query parameters:
- state: New value for the state of the repair run. Possible values for given state are: “PAUSED” or “RUNNING”.
- Starts, pauses, or resumes a repair run identified by the “id” path parameter.
- Can also be used to reattempt a repair run in state “ERROR”, picking up where it left off.
DELETE /repair_run/{id}
- Expected query parameters:
- owner: Owner name for the run. If the given owner does not match the stored owner, the delete request will fail.
- Delete a repair run object identified by the given “id” path parameter. Repair run and all the related repair segments will be deleted from the database.
Repair Schedule Resource
GET /repair_schedule
- Expected query parameters:
- clusterName: Filter the returned schedule list based on the given cluster name. (Optional)
- keyspaceName: Filter the returned schedule list based on the given keyspace name. (Optional)
- Returns all repair schedules present in the Reaper
- Expected query parameters:
GET /repair_schedule/{id}
- Expected query parameters: None
- Returns a repair schedule object identified by the given “id” path parameter.
POST /repair_schedule
- Expected query parameters:
- clusterName: Name of the Cassandra cluster.
- keyspace: The name of the table keyspace.
- tables: The name of the targeted tables (column families) as comma separated list. If no tables given, then the whole keyspace is targeted. (Optional)
- owner: Owner name for the schedule. This could be any string identifying the owner.
- segmentCount: Defines the amount of segments to create for scheduled repair runs. (Optional)
- repairParallelism: Defines the used repair parallelism for scheduled repair runs. (Optional)
- intensity: Defines the repair intensity for scheduled repair runs. (Optional)
- incrementalRepair: Defines if incremental repair should be done. true/false
- scheduleDaysBetween: Defines the amount of days to wait between scheduling new repairs. For example, use value 7 for weekly schedule, and 0 for continuous.
- scheduleTriggerTime: Defines the time for first scheduled trigger for the run. If you don’t give this value, it will be next mid-night (UTC). Give date values in ISO format, e.g. “2015-02-11T01:00:00”. (Optional)
DELETE /repair_schedule/{id}
- Expected query parameters:
- owner: Owner name for the schedule. If the given owner does not match the stored owner, the delete request will fail.
- Delete a repair schedule object identified by the given “id” path parameter. Repair schedule will get deleted only if there are no associated repair runs for the schedule. Delete all the related repair runs before calling this endpoint.
Running through Docker
Build Reaper Docker Image
First, build the Docker image and add it to your local image cache using the
cassandra-reaper:latest
tag:
mvn clean package docker:build
Start Docker Environment
First, start the Cassandra cluster:
docker-compose up cassandra
You can use the nodetool
Docker Compose service to check on the Cassandra
node’s status:
docker-compose run nodetool status
Once the Cassandra node is online and accepting CQL connections,
create the required reaper_db
Cassandra keyspace to allow Reaper to save
its cluster and scheduling data.
By default, the reaper_db
keyspace is created using a replication factor
of 1. To change this replication factor, provide the intended replication
factor as an optional argument:
docker-compose run initialize-reaper_db [$REPLICATION_FACTOR]
Wait a few moments for the reaper_db
schema change to propagate,
then start Reaper:
docker-compose up reaper
Access The Environment
Once started, the UI can be accessed through:
When adding the Cassandra node to the Reaper UI, use the IP address found via:
docker-compose run nodetool status
The helper cqlsh
Docker Compose service has also been included:
docker-compose run cqlsh
Destroying the Docker Environment
When terminating the infrastructure, use the following command to stop all related Docker Compose services:
docker-compose down
To completely clean up all persistent data, delete the ./data/
directory:
rm -rf ./data/


Virtual Electronic Music
A Rensselaer Center for Open Source (RCOS) Project
ENTER YOUR ROOM CODE BELOW:
JOIN ROOM


@* * Copyright 2023 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import config.AppConfig @import models.request.AuthenticatedRequest @import models.viewmodels.ManagerToolsKeywordsTab @import models.viewmodels.SubNavigationTab @import views.html.components.manager_tools_secondary_navigation @import views.html.includes.main @this( main: main ) @(keyword: String)(implicit request: AuthenticatedRequest[_], messages: Messages, appConfig: AppConfig) @main( pageTitle = messages("management.create-keyword.new-keyword-done") ) {
@messages("management.create-keyword.new-keyword-done.link")
}


This tracker is now in a functional state.
You can use it by adding it to your torrent by using the following URL:
http://nullrebel.com:1337/announce
This tracker currently only supports /announce. /scrape is a planned feature.


This package interacts with a suite of web 'APIs' for taxonomic tasks, such as verifying species names, getting taxonomic hierarchies, and verifying name spelling.
Allows users to search over many websites for species names (scientific and common) and download up- and downstream taxonomic hierarchical information - and many other things.
The functions in the package that hit a specific API have a prefix and suffix
separated by an underscore. They follow the format of service_whatitdoes
.
For example, gnr_resolve
uses the Global Names Resolver API to resolve
species names.
General functions in the package that don't hit a specific API don't have
two words separated by an underscore, e.g., classification
You need API keys for Encyclopedia of Life (EOL), and Tropicos.
| API | prefix |
| SOAP? | Encyclopedia of Life (EOL) |
| eol | FALSE |
| Taxonomic Name Resolution Service | tnrs |
| FALSE | Integrated Taxonomic Information Service (ITIS) |
| itis | FALSE |
| Global Names Resolver (from EOL/GBIF) | gnr |
| FALSE | Global Names Index (from EOL/GBIF) |
| gni | FALSE |
| IUCN Red List | iucn |
| FALSE | Tropicos (from Missouri Botanical Garden) |
| tp | FALSE |
| Theplantlist.org | tpl |
| FALSE | Catalogue of Life |
| col | FALSE |
| National Center for Biotechnology Information | ncbi |
| FALSE | CANADENSYS Vascan name search API |
| vascan | FALSE |
| International Plant Names Index (IPNI) | ipni |
| FALSE | World Register of Marine Species (WoRMS) |
| worms | TRUE |
| Barcode of Life Data Systems (BOLD) | bold |
| FALSE | Pan-European Species directories Infrastructure (PESI) |
| pesi | TRUE |
| Mycobank | myco |
| TRUE | National Biodiversity Network (UK) |
| nbn | FALSE |
| Index Fungorum | fg |
| FALSE | EU BON |
| eubon | FALSE |
| Index of Names (ION) | ion |
| FALSE | Open Tree of Life (TOL) |
| tol | FALSE |
| World Register of Marine Species (WoRMS) | worms |
| FALSE | NatureServe |
| natserv | FALSE |
If the source above has a TRUE
in the SOAP?
column, it is not available
in this package. They are available from a different package called taxizesoap.
See the GitHub repo for how to install https://github.com/ropensci/taxizesoap


President among guests at tonight's 'really special' Late Late tribute to Gay Byrne
by By Digital Desk staffRTE One is broadcasting a special Late Late Show tribute to Gay Byrne tonight.
Ryan Tubridy promised that tonight's programme will be "really special".
The broadcasting legend had hosted the show for almost four decades, and presented his last episode in 1999.
Among tonight's guests is the President of Ireland, Michael D Higgins, who will appear along with Joe Duffy, Sharon Shannon, John Sheahan, Finbar Furey, Tommy Tiernan, Pat Shortt, Eamon Dunphy, Twink and Mary Black.
There will also be contributions from the iconic broadcaster's friends and colleagues including Bob Geldof, Andrea Corr, Pat Kenny, John Sheahan and Mary McAleese.
He will be laid to rest after mass at the Pro-Cathedral in Dublin at midday on Friday after he passed away yesterday.
It will be broadcast live on RTE One.
Books of condolence are open in Dublin and Galway.
The full line-up for tonight's show is President Michael D Higgins, Mary McAleese, Bob Geldof, Pat Kenny, Joe Duffy, Mike Murphy, Andrea Corr, Sharon Shannon, John Sheahan, Finbar Furey, Nell McCafferty, John McColgan, Tommy Tiernan, Pat Shortt, Jon Kenny, Rosaleen Linehan, Eamon Dunphy, Twink, Fr Brian D'arcy, Paddy Maloney, Donal Lunny, Michael Carruth, Moya Doherty, RTÉ Director General Dee Forbes, Vincent Browne, Mary Black, Frank McNamara and Aonghus McAnally.
READ MORE
Govt approves plans to combat fake news and disinformation in political advertising


Table S86. Prediction of damaging effect on VEGFA
|
SNP |
Protein ID |
Amino acid |
Amino acid change |
SIFT |
PolyPhen2 |
PMut |
MutPred |
SNAP2 |
SNP&GO |
PANTHER |
|
rs62401172 |
NP_001020537 |
412 |
G365V |
Damaging |
Probably Damaging |
0.5934 Pathological |
0.291 |
Neutral |
Neutral |
Probably Benign |
|
rs76869573 |
NP_001020537 |
412 |
P312T |
Damaging |
Probably Damaging |
Neutral |
0.358 |
Effect 66% |
Neutral |
Probably Damaging |
|
rs114262569 |
NP_001020537 |
412 |
R288W |
Damaging |
Probably Damaging |
0.9757 Pathological |
0.603 |
Effect 75% |
Neutral |
Possibly Damaging |


APM
is the abbreviation of Application Performance Monitoring. Currently its core function is the performance diagnosis of distributed system, including call chain demonstration, application topology analysis, etc.
Sharding-JDBC Team work with SkyWalking Team to introduce an automatic prober of Sharding-JDBC
to send the performance data of Sharding-JDBC
to SkyWalking
.
Please refer to SkyWalking Manual。
If you want to use other APM systems which support OpenTracing, you can use the sharding-jdbc-opentracing plugin to work with those APM systems.
Notices: When using SkyWalking’s OpenTracing probe, disabling the original ShardingJDBC probe plugin is necessary to avoid conflicting with each other.
The application is a SpringBoot
application, using Sharding - JDBC
to access two databases of ds_0
and ds_1
, and each owns two tables in the database.
Although the user accesses the application once, each database is accessed twice. This is because this visit involves two splitting tables in each database, four tables in total.
Four visits in total in this figure.
/SJDBC/TRUNK/*
: Represents the overall execution performance of this SQL.
/SJSBC/BRANCH/*
: Represents the performance of the actual SQL.


This app visualizes complex numbers and their arithmetic in the complex plane. A complex number $Z = a + ib$ can either be defined via real part $a$ and imaginary part $b$ or by choosing the absolute value $| Z | = \sqrt{a^2 + b^2}$ and the phase angle $\alpha$; with $tan(\alpha) = \frac{Im(Z)}{Re(Z)}$.
In this app the user can choose two complex numbers $Z1$ and $Z2$ by defining their absolute value $| Z | $ and phase angle $\alpha$ using the sliders below. Pushing the green button $Z2$ will be set to the complex conjugate of $Z1$.
Besides $Z1$ and $Z2$, their addition $Z3$, subtraction $Z4$, multiplication $Z5$ and division $Z6$ are plotted in the complex plane. Real and imaginary part of the complex numbers can be extracted from the plot and the table on the right.


THE FANTASTIC FOUR A film review by Michael John Legeros Copyright 1994 Michael John Legeros
Directed by Oley Sassone (FINAL EMBRACE, BLOODFIST 3) Written by Craig J. Nevius and Kevin Rock, based on the Marvel Comics characters Cast Alex Hyde-White............Reed Richards Rebecca Staab..............Sue Storm Jay Underwood..............Johnny Storm Michael Bailey Smith.......Ben Grimm Joesph Culp................Victor Von Doom MPAA Rating Unknown, if rated. Running Time Approx. 90 minutes
==
Sitting on a shelf, somewhere in Hollywood, is Roger Corman's low-budget adaptation of "The Fantastic Four." Produced last year, the film was thrown into limbo after a certain Major Studio decided to explore a bigger-budget version of the popular Marvel Comics comic book. Someday, maybe, the film will be released and that would both delight and disappoint fans who have long known that decent adaptations of Marvel Comics characters are few and far between.
As any boy under sixty knows, the Fantastic Four are super-scientist Reed Richards, his best-friend and former test-pilot Ben Grimm, Reed's girlfriend Sue Storm, and her younger brother Johnny. Together, they take a ride in Reed's spaceship (don't ask) until something goes wrong and they all get exposed to "mysterious energies" before crashing back to Earth.
Once on the ground, they discover they have "super powers." Reed can stretch like, uh, Plastic Man, Sue can turn herself invisible, and Johnny can fire fireballs. Only Grimm gets the raw deal--he turns into a super-strong, rocky-skinned creature affectionately known as The Thing.
Corman's film faithfully recounts their origin, as described above, and even issues them costumes!  Also on display is The Jeweler, a Mole Man knockoff, whose presence has something to do with a super-sized diamond that Reed has and Doom wants.
With a few exceptions--such as Doom faking his own death after a failed experiment with Reed!--the story rarely strays from the source material. Present and accounted-for include Alicia Masters, the Baxter Building, and, yes, the Fantasticar. (But where's Willie Lumpkin?)
Credit writers Craig J. Nevius and Kevin Rock for a spartan set-up that introduces each character without having to resort to an overlong exposition. They do err, though, in the origin of Doctor Doom. There is none.
Director Oley Sassone (who?) keeps the superheroics to a bare minimum. Johnny throws a couple neat fireballs and "flames on" once. Sue's invisibility "trick" is pretty cheesy--but she projects a pretty-cool force field. Reed is a bust; his "super stretching" is used for a couple *really* long punches and that's about it. And The Thing gets to walk through a few walls. Whoopee.
Hey, rent SUPERMAN II if you want to see a *real* fight.
With almost zero-budget for EFX, the burden of proof rests squarely on the shoulders of the actors and, to their credit, they perform their parts handsomely. Only Joesph Culp is a wash--he's okay as the pre-Doctor Doom Doom, but he doesn't have much to do after getting encased in armor. Bad speeches and overgesticulating do not a character make.
Too bad that the production design can't match the enthusiasm of the actors. The throne room of Castle Doom is bad, the interiors of the Baxter Building are worse, and the inside of Reed's spaceship is just plain awful. Even bad sci-fi looks better than this stuff.
NOTE: Film is neither available on video nor in the theaters.
BOTTOM LINE: Enthusiastic performers and a faithful storyline can't do much for cheap EFX and a flimsy production design. Looks lousy, but still beats THE PUNISHER any day of the week.
Grade: C-
.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


{% extends "layout.html" %} {% block page_title %} Login {% endblock %} {% block proposition_header %} {% include "includes/propositional_navigation_logged_out.html" %} {% endblock %} {% block content %} {% include "includes/phase_banner_alpha.html" %} Sign in Sign in or create an account to get started. Sign in Email address Password {% endblock %}
Sign in or create an account to get started.


rainboard
The isomorphic MIDI controller
Features
61 key isomorphic midi keyboard
Genuine Sanwa arcade buttons
5 octave range
MIDI USB out
Adjustable keyboard layouts
Open source and customizable


precedence lossage
`Prev `__
P
`Next `__
--------------
**precedence lossage**: /pre´s@·dens los'@j/, n.
[C programmers] Coding error in an expression due to unexpected grouping
of arithmetic or logical operators by the compiler. Used esp. of certain
common coding errors in C due to the nonintuitively low precedence
levels of **&**, **\|**, **^**, **<<**, and **>>** (for this reason,
experienced C programmers deliberately forget the language's
`*baroque* <../B/baroque.html>`__ precedence hierarchy and parenthesize
defensively). Can always be avoided by suitable use of parentheses.
`*LISP* <../L/LISP.html>`__ fans enjoy pointing out that this can't
happen in *their* favorite language, which eschews precedence entirely,
requiring one to use explicit parentheses everywhere. See `*aliasing
bug* <../A/aliasing-bug.html>`__, `*memory
leak* <../M/memory-leak.html>`__, `*memory
smash* <../M/memory-smash.html>`__, `*smash the
stack* <../S/smash-the-stack.html>`__, `*fandango on
core* <../F/fandango-on-core.html>`__, `*overrun
screw* <../O/overrun-screw.html>`__.
--------------
+-------------------------+----------------------------+-------------------------+
| `Prev `__ | `Up <../P.html>`__ | `Next `__ |
+-------------------------+----------------------------+-------------------------+
| pr0n | `Home <../index.html>`__ | pred |
+-------------------------+----------------------------+-------------------------+


The Complete User Guide to Load Balancers¶
Prerequisites¶
Client¶
To use the load balancers service, you must first instantiate a Rackspace client object.
use OpenCloud\Rackspace;
$client = new Rackspace(Rackspace::US_IDENTITY_ENDPOINT, array(
'username' => '<YOUR RACKSPACE CLOUD ACCOUNT USERNAME>',
'apiKey' => '<YOUR RACKSPACE CLOUD ACCOUNT API KEY>'
));
Load Balancer Service¶
All operations on load balancers are done via a load balancer service object.
$loadBalancerService = $client->loadBalancerService('cloudLoadBalancers', 'DFW');
Cloud Servers¶
Many of the examples in this document use two cloud servers as nodes for the load balancer. The variables $serverOne and $serverTwo refer to these two cloud servers.
Load Balancers¶
A load balancer is a device that distributes incoming network traffic amongst multiple back-end systems. These back-end systems are called the nodes of the load balancer.
Create Load Balancer¶
$loadBalancer = $loadBalancerService->loadBalancer();
$serverOneNode = $loadBalancer->node();
$serverOneNode->address = $serverOne->addresses->private[0]->addr;
$serverOneNode->port = 8080;
$serverOneNode->condition = 'ENABLED';
$serverTwoNode = $loadBalancer->node();
$serverTwoNode->address = $serverTwo->addresses->private[0]->addr;
$serverTwoNode->port = 8080;
$serverTwoNode->condition = 'ENABLED';
$loadBalancer->addVirtualIp('PUBLIC');
$loadBalancer->create(array(
'name' => 'My smart load balancer',
'port' => 80,
'protocol' => 'HTTP',
'nodes' => array($serverOneNode, $serverTwoNode)
));
List Load Balancer Details¶
You can retrieve a single load balancer’s details by using its ID.
$loadBalancer = $loadBalancerService->loadBalancer('254889');
/** @var $loadBalancer OpenCloud\LoadBalancer\Resource\LoadBalancer **/
List Load Balancers¶
You can retrieve a list of all your load balancers. An instance of OpenCloud\Common\Collection\PaginatedIterator is returned.
$loadBalancers = $loadBalancerService->loadBalancerList();
foreach ($loadBalancers as $loadBalancer) {
/** @var $loadBalancer OpenCloud\LoadBalancer\Resource\LoadBalancer **/
}
Update Load Balancer Attributes¶
You can update one or more of the following load balancer attributes:
- name: The name of the load balancer
- algorithm: The algorithm used by the load balancer to distribute traffic amongst its nodes. See also: Load balancing algorithms.
- protocol: The network protocol used by traffic coming in to the load balancer. See also: Protocols.
- port: The network port on which the load balancer listens for incoming traffic.
- halfClosed: Enable or Disable Half-Closed support for the load balancer.
- timeout: The timeout value for the load balancer to communicate with its nodes.
- httpsRedirect: Enable or disable HTTP to HTTPS redirection for the load balancer. When enabled, any HTTP request will return status code 301 (Moved Permanently), and the requestor will be redirected to the requested URL via the HTTPS protocol on port 443. For example, http://example.com/page.html would be redirected to https:// example.com/page.html. Only available for HTTPS protocol (port = 443), or HTTP Protocol with a properly configured SSL Termination (`secureTrafficOnly=true, securePort=443). See also: SSL Termination.
Updating a single attribute of a load balancer¶
$loadBalancer->update(array(
'name' => 'New name'
));
Updating multiple attributes of a load balancer¶
$loadBalancer->update(array(
'name' => 'New name',
'algorithm' => 'ROUND_ROBIN'
));
Remove Load Balancer¶
When you no longer have a need for the load balancer, you can remove it.
$loadBalancer->delete();
Nodes¶
A node is a backend device that provides a service on specified IP and port. An example of a load balancer node might be a web server serving HTTP traffic on port 8080.
A load balancer typically has multiple nodes attached to it so it can distribute incoming network traffic amongst them.
List Nodes¶
You can list the nodes attached to a load balancer. An instance of OpenCloud\Common\Collection\PaginatedIterator is returned.
$nodes = $loadBalancer->nodeList();
foreach ($nodes as $node) {
/** @var $node OpenCloud\LoadBalancer\Resource\Node **/
}
Add Nodes¶
You can attach additional nodes to a load balancer. Assume $loadBalancer already has two nodes attached to it - $serverOne and $serverTwo - and you want to attach a third node to it, say $serverThree, which provides a service on port 8080.
Important: Remember to call $loadBalancer->addNodes() after all the calls to $loadBalancer->addNode() as shown below.
$address = $serverThree->addresses->private[0]->addr;
$loadBalancer->addNode($address, 8080);
$loadBalancer->addNodes();
The addNode method accepts three more optional parameters, in addition to the two shown above:
—————– | | 1 | IP address of node | String | Yes | - | | 2 | Port used by node’s service | Integer | Yes | - | | 3 | Starting condition of node: | 4 | Type of node to add: | 5 | Weight, between 1 and 100, given to node when distributing traffic using either the WEIGHTED_ROUND_ROBIN or the WEIGHTED_LEAST_CONNECTIONS load balancing algorithm. | Integer | No | 1 |
Modify Nodes¶
You can modify one or more of the following node attributes:
- condition: The condition of the load balancer:
- ENABLED – Node is ready to receive traffic from the load balancer.
- DISABLED – Node should not receive traffic from the load balancer.
- DRAINING – Node should process any traffic it is already receiving but should not receive any further traffic from the load balancer.
- type: The type of the node:
- PRIMARY – Nodes defined as PRIMARY are in the normal rotation to receive traffic from the load balancer.
- SECONDARY – Nodes defined as SECONDARY are only in the rotation to receive traffic from the load balancer when all the primary nodes fail.
- weight: The weight, between 1 and 100, given to node when distributing traffic using either the WEIGHTED_ROUND_ROBIN or the WEIGHTED_LEAST_CONNECTIONS load balancing algorithm.
Modifying a single attribute of a node¶
use OpenCloud\LoadBalancer\Enum\NodeCondition;
$node->update(array(
'condition' => NodeCondition::DISABLED
));
Modifying multiple attributes of a node¶
use OpenCloud\LoadBalancer\Enum\NodeCondition;
use OpenCloud\LoadBalancer\Enum\NodeType;
$node->update(array(
'condition' => NodeCondition::DISABLED,
'type' => NodeType::SECONDARY
));
Remove Nodes¶
There are two ways to remove a node.
Given an OpenCloud\LoadBalancer\Resource\Node instance¶
$node->delete();
Given an OpenCloud\LoadBalancer\Resource\LoadBalancer instance and a node ID¶
$loadBalancer->removeNode(490639);
The removeNode method, as shown above, accepts the following arguments:
| Position | Description | Data type | Required? | Default value |
|---|---|---|---|---|
| 1 | ID of node | Integer | Yes |
View Node Service Events¶
You can view events associated with the activity between a node and a load balancer. An instance of OpenCloud\Common\Collection\PaginatedIterator is returned.
$nodeEvents = $loadBalancer->nodeEventList();
foreach ($nodeEvents as $nodeEvent) {
/** @var $nodeEvent OpenCloud\LoadBalancer\Resource\NodeEvent **/
}
Virtual IPs¶
A virtual IP (VIP) makes a load balancer accessible by clients. The load balancing service supports either a public VIP address (PUBLIC), routable on the public Internet, or a ServiceNet VIP address (SERVICENET), routable only within the region in which the load balancer resides.
List Virtual IPs¶
You can list the VIPs associated with a load balancer. An instance of OpenCloud\Common\Collection\PaginatedIterator is returned.
$vips = $loadBalancer->virtualIpList();
foreach ($vips as $vip) {
/** @var $vip of OpenCloud\LoadBalancer\Resource\VirtualIp **/
}
Add Virtual IPv6¶
You can add additional IPv6 VIPs to a load balancer.
use OpenCloud\LoadBalancer\Enum\IpType;
$loadBalancer->addVirtualIp(IpType::PUBLIC, 6);
The addVirtualIp method, as shown above, accepts the following arguments:
—————– | | 1 | Type of VIP: | 2 | IP version: Must be 6 | Integer | Yes | - |
Remove Virtual IPs¶
You can remove a VIP from a load balancer.
$vip->remove();
Please note that a load balancer must have at least one VIP associated with it.
Algorithms¶
Load balancers use an algorithm to determine how incoming traffic is distributed amongst the back-end nodes.
List Load Balancing Algorithms¶
You can list all supported load balancing algorithms using a load balancer service object. An instance of OpenCloud\Common\Collection\PaginatedIterator is returned.
$algorithms = $loadBalancerService->algorithmList();
foreach ($algorithms as $algorithm) {
/** @var $algorithm OpenCloud\LoadBalancer\Resource\Algorithm **/
}
Protocols¶
When a load balancer is created a network protocol must be specified. This network protocol should be based on the network protocol of the back-end service being load balanced.
List Load Balancing Protocols¶
You can list all supported network protocols using a load balancer service object. An instance of OpenCloud\Common\Collection\PaginatedIterator is returned.
$protocols = $loadBalancerService->protocolList();
foreach ($protocols as $protocol) {
/** @var $protocol OpenCloud\LoadBalancer\Resource\Protocol **/
}
Session Persistence¶
Session persistence is a feature of the load balancing service that forces multiple requests, of the same protocol, from clients to be directed to the same node. This is common with many web applications that do not inherently share application state between back-end servers.
There are two types (or modes) of session persistence:
| Name | Description |
|---|---|
| HTTP_COOKIE | A session persistence mechanism that inserts an HTTP cookie and is used to determine the destination back-end node. This is supported for HTTP load balancing only. |
| SOURCE_IP | A session persistence mechanism that will keep track of the source IP address that is mapped and is able to determine the destination back-end node. This is supported for HTTPS pass-through and non-HTTP load balancing only. |
List Session Persistence Configuration¶
$sessionPersistence = $loadBalancer->sessionPersistence();
$sessionPersistenceType = $sessionPersistence->persistenceType;
/** @var $sessionPersistenceType null | 'HTTP_COOKIE' | 'SOURCE_IP' **/
In the example above:
- If session persistence is enabled, the value of $sessionPersistenceType is the type of session persistence: either HTTP_COOKIE or SOURCE_IP.
- If session persistence is disabled, the value of $sessionPersistenceType is null.
Enable Session Persistence¶
$sessionPersistence = $loadBalancer->sessionPersistence();
$sessionPersistence->update(array(
'persistenceType' => 'HTTP_COOKIE'
));
Disable Session Persistence¶
$sessionPersistence = $loadBalancer->sessionPersistence();
$sessionPersistence->delete();
Connection Logging¶
The connection logging feature allows logs to be delivered to a Cloud Files account every hour. For HTTP-based protocol traffic, these are Apache-style access logs. For all other traffic, this is connection and transfer logging.
Check Logging Configuration¶
/** @var $connectionLogging bool **/
$connectionLogging = $loadBalancer->hasConnectionLogging();
In the example above:
- If connection logging is enabled, the value of $connectionLogging is true.
- If connection logging is disabled, the value of $connectionLogging is false.
Enable Connection Logging¶
$loadBalancer->enableConnectionLogging(true);
Disable Connection Logging¶
$loadBalancer->enableConnectionLogging(false);
Error Page¶
An error page is the html file that is shown to the end user when an error in the service has been thrown. By default every virtual server is provided with the default error file. It is also possible to set a custom error page for a load balancer.
View Error Page Content¶
$errorPage = $loadBalancer->errorPage();
$errorPageContent = $errorPage->content;
/** @var $errorPageContent string **/
In the example above the value of $errorPageContent is the HTML for that page. This could either be the HTML of the default error page or of your custom error page.
Set Custom Error Page¶
$errorPage = $loadBalancer->errorPage();
$errorPage->update(array(
'content' => '<HTML content of custom error page>'
));
Delete Custom Error Page¶
$errorPage = $loadBalancer->errorPage();
$errorPage->delete();
Allowed Domains¶
Allowed domains are a restricted set of domain names that are allowed to add load balancer nodes.
List Allowed Domains¶
You can list all allowed domains using a load balancer service object. An instance of OpenCloud\Common\Collection\PaginatedIterator is returned.
$allowedDomains = $loadBalancerService->allowedDomainList();
foreach ($allowedDomains as $allowedDomain) {
/** @var $allowedDomain OpenCloud\LoadBalancer\Resource\AllowedDomain **/
}
Access Lists¶
Access Lists allow fine-grained network access to a load balancer’s VIP. Using access lists, network traffic to a load balancer’s VIP can be allowed or denied from a single IP address, multiple IP addresses or entire network subnets.
Note that ALLOW network items will take precedence over DENY network items in an access list.
To reject traffic from all network items except those with the ALLOW type, add a DENY network item with the address of <IP_ADDRESS>/0.
View Access List¶
You can view a load balancer’s access list. An instance of OpenCloud\Common\Collection\PaginatedIterator is returned.
$accessList = $loadBalancer->accessList();
foreach ($accessList as $networkItem) {
/** @var $networkItem OpenCloud\LoadBalancer\Resource\Access **/
}
Add Network Items To Access List¶
You can add network items to a load balancer’s access list very easily:
$loadBalancer->createAccessList(array(
(object) array(
'type' => 'ALLOW',
'address' => '<IP_ADDRESS>/24'
),
(object) array(
'type' => 'DENY',
'address' => '<IP_ADDRESS>/0'
)
));
In the above example, we allowed access for 1 IP address, and used the “<IP_ADDRESS>” wildcard to blacklist all other traffic.
Remove Network Item From Access List¶
You an remove a network item from a load balancer’s access list.
$networkItem->delete();
Content Caching¶
When content caching is enabled on a load balancer, recently-accessed files are stored on the load balancer for easy retrieval by web clients. Requests to the load balancer for these files are serviced by the load balancer itself, which reduces load off its back-end nodes and improves response times as well.
Check Content Caching Configuration¶
/** @var $contentCaching bool **/
$contentCaching = $loadBalancer->hasContentCaching();
In the example above:
- If content caching is enabled, the value of $contentCaching is true.
- If content caching is disabled, the value of $contentCaching is false.
Enable Content Caching¶
$loadBalancer->enableContentCaching(true);
Disable Content Caching¶
$loadBalancer->enableContentCaching(false);
SSL Termination¶
The SSL Termination feature allows a load balancer user to terminate SSL traffic at the load balancer layer versus at the web server layer. A user may choose to configure SSL Termination using a key and an SSL certificate or an (Intermediate) SSL certificate.
When SSL Termination is configured on a load balancer, a secure shadow server is created that listens only for secure traffic on a user-specified port. This shadow server is only visible to and manageable by the system. Existing or updated attributes on a load balancer with SSL Termination will also apply to its shadow server. For example, if Connection Logging is enabled on an SSL load balancer, it will also be enabled on the shadow server and Cloud Files logs will contain log files for both.
View current SSL termination config¶
/** @var $sslConfig OpenCloud\LoadBalancer\Resource\SSLTermination **/
$sslConfig = $loadBalancer->SSLTermination();
Update SSL termination config¶
$sslConfig->update(array(
'enabled' => true,
'securePort' => 443,
'privateKey' => $key,
'certificate' => $cert
));
For a full list, with explanations, of required and optional attributes, please consult the official documentation
Delete SSL termination config¶
$sslConfig->delete();
Metadata¶
Metadata can be associated with each load balancer and each node for the client’s personal use. It is defined using key-value pairs where the key and value consist of alphanumeric characters. A key is unique per load balancer.
List metadata¶
$metadataList = $loadBalancer->metadataList();
foreach ($metadataList as $metadataItem) {
printf("Key: %s, Value: %s", $metadataItem->key, $metadataItem->value);
}
Please consult the iterator documentation for more information about iterators.
Add metadata¶
$metadataItem = $loadBalancer->metadata();
$metadataItem->create(array(
'key' => 'foo',
'value' => 'bar'
));
Modify metadata¶
$metadataItem = $loadBalancer->metadata('foo');
$metadataItem->update(array(
'value' => 'baz'
));
Remove metadata¶
$metadataItem->delete();
Monitors¶
The load balancing service includes a health monitoring operation which periodically checks your back-end nodes to ensure they are responding correctly. If a node is not responding, it is removed from rotation until the health monitor determines that the node is functional. In addition to being performed periodically, the health check also is performed against every node that is added to ensure that the node is operating properly before allowing it to service traffic. Only one health monitor is allowed to be enabled on a load balancer at a time.
/** @var $healthMonitor OpenCloud\LoadBalancer\Resource\HealthMonitor **/
$healthMonitor = $loadBalancer->healthMonitor();
printf(
"Monitoring type: %s, delay: %s, timeout: %s, attempts before deactivation: %s",
$healthMonitor->type, $healthMonitor->delay, $healthMonitor->timeout
);
For a full list, with explanations, of required and optional attributes, please consult the official documentation
Update or delete¶
// Update
$healthMonitor->update(array(
'delay' => 120,
'timeout' => 60,
'type' => 'CONNECT'
'attemptsBeforeDeactivation' => 3
));
// Delete
$healthMonitor->delete();
Statistics¶
You can retrieve detailed stats about your load balancer, including the following information:
- connectTimeOut – Connections closed by this load balancer because the ‘connect_timeout’ interval was exceeded.
- connectError – Number of transaction or protocol errors in this load balancer.
- connectFailure – Number of connection failures in this load balancer.
- dataTimedOut – Connections closed by this load balancer because the ‘timeout’ interval was exceeded.
- keepAliveTimedOut – Connections closed by this load balancer because the ‘keepalive_timeout’ interval was exceeded.
- maxConn – Maximum number of simultaneous TCP connections this load balancer has processed at any one time.
/** @var $stats OpenCloud\LoadBalancer\Resource\Stats **/
$stats = $loadBalancer->stats();
Usage Reports¶
The load balancer usage reports provide a view of all transfer activity, average number of connections, and number of virtual IPs associated with the load balancing service. Current usage represents all usage recorded within the preceding 24 hours. Values for both incomingTransfer and outgoingTransfer are expressed in bytes transferred.
The optional startTime and endTime parameters can be used to filter all usage. If the startTime parameter is supplied but the endTime parameter is not, then all usage beginning with the startTime will be provided. Likewise, if the endTime parameter is supplied but the startTime parameter is not, then all usage will be returned up to the endTime specified.
# View billable LBs
$billable = $service->billableLoadBalancerList();
foreach ($billable as $loadBalancer) {
/** @var $loadBalancer OpenCloud\LoadBalancer\Resource\LoadBalancer **/
# View usage
/** @var $usage OpenCloud\LoadBalancer\Resource\UsageRecord **/
$usage = $loadBalancer->usage();
echo $usage->averageNumConnections, PHP_EOL;
}


What???s the Difference Between Stemming and Lemmatization? - Ask Dr. Search
Last Updated Mar 2009
A Reader Asks:
What???s the Difference Between Stemming and Lemmatization? I see these terms everywhere, though stemming seems more common.
Editors Note: The two spellings lemmatization and lemmatisation are both in use in the literature. This question is from a FAST Search customer and FAST spells it with a ???z???, so we will use that here. Wikipedia uses an ???s??? extended from lemmatise. In our opinion both are correct.
Dr. Search Responds:
A great question, thanks! First, I???d like to talk generally about what these terms mean:
General Definition:
As you suspect, they are related. Both have to do with getting words to match each other even if they are not in the exact same form. For example, I search for ???house???, and a document contains the word ???houses???, and since most people would consider that a match we???d like the search engine to find it, even though one is plural and one is singular. This can be extended to match different forms of verbs, adjectives and adverbs, and even for synonyms and wildcard matching. At this extended level, people sometimes refer to it as ???fuzzy??? matching, though that is not a standard.
This sounds pretty simple, doesn???t it? It???s such a common practice these days that you might not even have noticed it. It turns out that doing this efficiently, for millions and millions of documents, and for all word forms, is a bit tricky.
But like everything in software, the devil is in the details. Here are some of the challenges, depending on the implementation:
- If an engine DOESN???T do it, users will likely be annoyed because they won???t find what they are looking for. (techies would say it impacts ???recall???)
- If an engine does too much of it and starts matching everything under the sun, incorrect matches will be returned, and users will also be annoyed. For example matching ???sun??? to ???son??? is probably too aggressive for a first search. (techies would say it impacts ???precision???)
- There are many exceptions to the rules. The plural of house is houses, but the plural of mouse is mice. And although the suffix ???ed??? often indicates the past tense of a verb, it???s also a valid word ending on its own. So lifted should match lift, but breed is not the past tense of ???bre???.
- If a search engine handles multiple languages, it needs to apply completely different rules to each document, depending on that language. For example, handling the ???ing??? in English verbs and ???ando??? for Spanish verbs.
- It???s helpful to be able to turn on and off different types of rules for some queries, or combine them in different ways. For example, I might want to allow for singular and plural nouns to match, but not for synonyms. Or perhaps I???d like to give extra credit to an exact match, but I would also accept a partial match if there are no exact matches.
- Implementation complexity. High end search engines do give developers this fine grain level of control, but as you can imagine it brings with it some added configuration and coding to fully utilize.
Differences:
Now to your question on the difference between lemmatization and stemming:
Lemmatization implies a broader scope of fuzzy word matching that is still handled by the same subsystems. It implies certain techniques for low level processing within the engine, and may also reflect an engineering preference for terminology.
FAST and Lucene documentation talk about lemmatization, whereas most other engines refer to this as stemming. Taking FAST as an example, their lemmatization engine handles not only basic word variations like singular vs. plural, but also thesaurus operators like having ???hot??? match ???warm???.
This is not to say that other engines don???t handle synonyms, of course they do, but the low level implementation may be in a different subsystem than those that handle base stemming.
For example:
A lemmatization system would handle matching ???car??? to ???cars??? along with matching ???car??? to ???automobile???. In a more traditional search engine, matching ???car??? to ???cars??? would be handled by stemming, but matching ???car??? to ???automobile??? would be handled by a separate system.
With all that said, most business customers don???t need to worry about it too much. Your vendor will tend towards one term or the other, but as long as they have functionality of both, you???re probably OK. Be advised that, for some engines, stemming and thesaurus matching is an extra cost option.
A few other questions you might ask the vendor:
Does it work for all parts of speech, or just nouns? Or can this be configured?
Is stemming done via rules or via a dictionary? Or perhaps a hybrid? A dictionary allows you to override certain words that rules would not cover, for example matching ???mouse??? and ???mice???, and not taking the ???ed??? off the end of ???breed???.
Verify that you can you combine stemming and thesaurus operations in the same query.
Verify that they give you a standard thesaurus for your language, and that you can add your own custom terms if needed. And ask how this is done.
Fuzzy Matching Types:
I???d like to spell out some of the more common types of word matching options on the market. Note that some of these might not be handled by lemmatization, even for vendors who use that term.
- Basic stemming for nouns: cat/cats, mouse/mice, etc.
- Stemming for verbs: run/runs/running/ran
- Other parts of speech
- Thesaurus / synonym matching: dog/pooch/mutt
- Wildcard matching: dog* matches dogma.
- Advanced wildcard: *tion* matches ???nation???, ???definitions???, etc.
- Regular expression matching.
- Soundex / sound alike: Smith matches Smyth
- Typo, OCR and Levenshtein: lemmatization matches lemmetization and lemmitization
- Case sensitivity / casedex: control over whether ???mark??? matches ???Mark???
- Accent normalization: insure that resum?? matches resume and r??sum??
- Abbreviations and their expanded form (a type of thesaurus)
- Variations of words with punctuation, such as hyphens. For example: Meta Data, meta-data and metadata.
- Entity normalization: Dates for example, so that 6/18/09 matches June 18th, 2009
In the above list, advanced operations like full wildcard matching, Levenshtein and entity matching would not be simple lemmatization subsystem activities; the engine would have to call on other subsystems and do a lot more work.
Expansion and Reduction
Although you didn???t ask about this, there are a number of techniques that are used to handle stemming and lemmatization. Just in case a vendor starts throwing these terms around, I did want to mention them briefly. This is rather advanced, but something your local search guru should commit to memory.
There are three general ways to achieve matching on different word variations:
- Expand words put into the index to include all variations; this is called ???index time expansion??? or ???document expansion???.
- Expand the query to include all variations; this is called ???query expansion??? or ???runtime expansion???.
- Reduce all words to their base form when creating the index AND for each word in the query when running a search. This must be done at both index and query time and usually just called ???by reduction???.
It???s also possible to combine these methods, and there are some good reasons an engine might want to do so.
We???ll walk through these with some examples. Since reduction was actually more common in the early days of the search industry, we???ll work through that first.
Reduction:
Reduction is applied at both index and search time. All words are consistently reduced to their base form so that they will match each other.
Source document:
Some houses have many mice. Our house only has one mouse.
Each word will be reduced to its base form before being stored into the fulltext search index, so we would have:
some house has many mouse. our house only has one mouse.
Notice that the nouns ???house??? and ???mouse??? are reduced to their base singular forms, and the verbs ???have??? and ???has??? were reduced to the present tense base form ???has???.
Query submitted by user:
how to get rid of mice
Reduced query submitted to search engine:
how to get rid of mouse
Notice that ???mice??? was reduced to ???mouse???, and will match two of the indexed words for our sample document (the 2 instances of ???mouse???).
The biggest advantage of this method is that the index size is not increased. Since disk space was very expensive in the 1980s and 90s, this was almost always how it was done. There were two disadvantages to this method, however.
- You couldn???t search for the other forms of the word, unless you created an additional index. In our above example, you would not be able to search for the literal word ???mice???. In some advanced searches that level of control is nice to have as an option.
- If additional forms of the word need to be added, for example ???rodent???, then the documents need to be completely reindexed. In our sample, a search for ???rodent??? would also be reduced to ???mouse???, so the search would still work. But original documents containing the word ???rodent??? would not have that converted to ???mouse??? until they are reindexed, so would not be immediately findable. This would give inconsistent and confusing results.
Expansion at Index Time:
In this method additional forms of the words are written to the fulltext index when the document is indexed. The original source document itself is not modified, but additional entries in the index have the other word forms recorded as belonging to that document.
In the example below, we will also assume a lemmatizing subsystem that is also expanding for synonyms as well.
Source document:
Some houses have many mice. Our house only has one mouse.
Each word will be expanded to include all variations before being stored into the fulltext search index, so we would have:
some few ???
houses house home homes domicile ???
have has had having possess contains ???
many multiple lots dozens ???
mice mouse rodent ???
our my ???
house houses home homes domicile ???
only sole solely ???
has have had having possess contains ???
one single solitary unity ???
In the example index above, the dots represent other word forms. I???ve also listed the original form of each word first; some engines keep track of which form was originally used, to maintain the option for doing an exact match.
Later, at search time, the query is submitted as is, without modification. Any variations to the search terms have already been accounted for in the index.
An example query of:
how to get rid of rodents
Would be submitted as is, completely unmodified, and it would match the document about the mouse because rodent was also recorded as belonging to that document.
Although this method does expand the fulltext index, it???s not as bad as it might initially look due to the efficient way fulltext indexes are organized. For example, the word ???house??? appears on line 2 and 7, but the actual string will only be stored once. Most search engines have a very efficient index structure where a word will only appear once, and be followed by a numerical list of pointers indicating all the places it was seen. Techies might call this an ???instance vector???, but we won???t go into that here.
The other problem with index time expansion shares with reduction is that if new word variations are added, the documents must be reindexed in order to fully reflect that.
Given the disadvantages of increased index size and reduction???s problem of needing reindexing to reflect changes, why would anybody use this method? Actually, we???ve already covered that. Notice in the above example that I said the query would be submitted unmodified, this is the key advantage. Index time expansion has two main benefits:
- 1: Queries can be submitted directly to the search engine, without modification.
- 2: Performance is on a par with reduction; the larger index can make the search a bit slower, but it???s still very good.
And in theory the index could be appended to if new word variations are added, to just add those new variations to existing documents, though in practice we don???t know of any engine that works in that way.
Expansion at Search Time:
In this method a document???s words are stored in the fulltext index unmodified, and no extra forms are recorded. The index size stays reasonably small and document indexing is relatively fast.
At search time, however, the users??? searches are expanded to include additional word forms.
Going back to our original example, suppose a user submits:
how to get rid of mice
The Expanded query submitted to search the search engine would be something like:
how method means ??? to get rid of remove eradicate exterminate ??? mice mouse rodent rodents???
The dots indicate other expanded terms. And I???ve cheated a bit here, the phrase ???get rid of??? is three separate words, and this theoretical query expander knew that I meant exterminate, eradicate, etc. Simpler query expanders would have expanded each word separately, so ???get??? might become ???get, got, getting???, etc. and rid might have become ???rid, remove, riddens???, etc. But that type of situation could have easily been applied to index time expansion and reduction.
You???ll notice that the number of query terms in the search has risen dramatically. Adding additional query terms can slow a search engine down because it has to do quite a bit more work. Each expanded word must be looked up in the search engine???s fulltext index, and each lookup takes computing resources. This extent of the slowdown, by expanding the query, may be larger than the slowdown incurred using index time expansion. There is also some time needed to actually expand the query itself, though this is usually relatively efficient. Keep in mind, however, that index time expansion creates a larger search index, and takes longer to index documents.
The one big advantage to query time expansion, and this can be quite significant, is that changes to word and synonyms or other word variations can be added at any time!
In our previous example, as soon as ???rodent??? is defined as a synonym for ???mouse???, the very next query will be expanded to include the new term. So query time expansion does not require reindexing of documents.
This is becoming a more popular option as search engines get faster. If they can handle the longer queries (from the expanded terms), then using this method means many fewer document reindexes. This is particularly important for search engine installations that make heavy use of thesaurus terms that are updated frequently.
Expansion techniques, at either index or query time, may not be appropriate for languages that have an inordinate number of word variations, and reduction might be preferred.
The Hybrid Approach: Combining Techniques
I mentioned earlier on that these various methods can be combined in some systems. This is done to minimize the performance compromises inherent in each method. In particular, word rules that almost never change can be stored in the fulltext index, whereas items that could change frequently are expanded only at search time.
In English, the word ???mice??? has been the plural form of ???mouse??? for quite some time! This is unlikely to change on some random Monday morning. Whereas in a rapidly evolving technical field, terminology and abbreviations can change rapidly, and perhaps the thesaurus needs monthly updates. In this scenario, the variations of mouse would be stored in the fulltext index, whereas abbreviations and technical terms would be expanded at query time.
One final example to show this hybrid approach, and this may show my age. In the technology field back in the 1980s a ???ps 2??? referred to IBM???s Personal System /2 line of computers, whereas now it generally refers Sony???s gaming platform, The Playstation 2.
Sample document:
Connect a USB mouse to older computers with a PS/2 adapter.
The index reflects additional forms of the words whose rules are not likely to change:
connect, connecting, connected, connects ???.
USB, usb, U.S.B. ???
mouse, mice ???
??? (some terms omitted) ???
PS/2, ps/2, ps 2, ps2, ps-2
adapter, adapt, adapters, adapting, adaptive ???
The index has captured most of the static word variations we might care about.
Now imagine a user query of:
mice for ps2
This would be expanded only to get thesaurus variations in place, so this is what would be sent to the engine:
mice rodent for ps2 IBM Personal System 2 /2 Sony Playstation Play Station 2 II two
This query will now match most variations, including word form, punctuation and synonyms.
The query sent to the engine captures both product names, along with variations on the number 2, and includes the spurious synonym ???rodent???, which is likely not what they are looking for. That last point is particularly interesting, this search will likely match some documents that mention the word ???rodent???. If there were enough other pertinent words in that document, it might be ranked high enough to show near the top of the results. As we said, overuse of fuzzy matches can annoy users. In a large enough document set, disparate contexts that happen to use same words become much more frequent, so care should be taking when turning on fuzzy matching options.
In Summary:
Both stemming and lemmatization allow queries to match different forms of words. Stemming was commonly implemented with Reduction techniques, though this is not universal. Lemmatization implies a possibly broader scope of functionality, which may include synonyms, though most engines support thesaurus-aided searches in one form or another. Lemmatization also tends to be expansion based (either index or query time), though this is not universal. Word variation rules that rarely change are often implemented with reduction or index time expansion, while rules that periodically change are best served with query time expansion.
The main reasons to care about this are:
- For advanced search applications, make sure your vendor offers different choices on how to handle these issues. Ideally a developer should be able to turn various fuzzy matching features on and off as needed.
- Index time expansion increases index size, and possibly indexing time.
- Query time expansion can affect search performance.
- Only query time expansion allows rule changes to be reflected immediately, without the need to reindex documents, allowing you to add thesaurus terms whenever you want.
- A reduction system may not allow you to find exact forms of the words, although this is not always true, depending on the vendor???s implementation.
- Some vendors charge extra for some advanced features. In fairness to them, the features may take more time test and support. We believe basic s


What is COBRA?
The COnstraints Based Reconstruction and Analysis (COBRA) approach to systems biology accepts the fact that we do not possess sufficiently detailed parameter data to precisely model, in the biophysical sense, an organism at genome-scale.
Increasingly, omics data has been used to define the set of feasible states for a biological network in a given condition based on current knowledge. These constraints include compartmentalization, mass conservation, molecular crowding, and thermodynamic directionality. More recently, transcriptome data have been used to reduce the size of the set of computed feasible states.
Although COBRA methods may not provide a unique solution, they provide a reduced set of solutions that may be used to guide biological hypothesis development. Given its success, COBRA has attracted attention from many investigators and has developed rapidly in recent years based on contributions from a growing number of laboratories – COBRA methods have been used in hundreds of studies to deal with the complex relationships and high dimensionality of the next generation of COBRA models.


A positioner includes a shift magnitude calculating portion that calculates a shift magnitude from the equilibrium state of a pilot relay, from an input air pressure that is inputted into the pilot relay and an output air pressure that is outputted from the pilot relay. A control calculating portion determines a control signal from an actual opening signal, an opening setting value, and the shift magnitude from the equilibrium state of the pilot relay that is calculated by the shift magnitude calculating portion, and outputs it to the electropneumatic converter.
This application claims priority to Japanese Patent Application No. 2012-131255, filed on Jun. 8, 2012, the entire content of which being hereby incorporated herein by reference.
The present invention relates to a positioner for controlling the opening of a valve.
Conventionally, positioners for controlling the openings of valves have been, for example, positioners wherein the critical components have been configured as illustrated in figref[FIG. 3] . In this figure, 200 ( 200A) is a positioner, and 300 is a valve, where the valve 300 is provided with a position sensor 10 for detecting a position that indicates the degree of opening of the valve.
The positioner 200A is provided with an electric current-SP converting portion 1, a control calculating portion 2, an electropneumatic converter 3, a pilot relay 4, and a valve opening calculating portion 5.
In the positioner 200A, the electric current-SP converting portion 1 converts into an opening setting signal SP an input signal that is sent, as a signal of between 4 and 20 mA, from a higher level device. The valve opening calculating portion 5 calculates the current valve opening of the valve 200A from the position that indicates the opening of the valve, detected by the position sensor 10, and outputs, as an actual opening signal PV, a signal depending on the calculated opening. The control calculating portion 2 calculates the difference between the opening setting signal SP from the electric current-SP converting portion 1 and the actual opening signal PV from the valve opening calculating portion 5, and outputs, as a control signal MV, an electric signal obtained through performing PID control calculations on the difference.
The electropneumatic converter 3 converts into an air pressure (a nozzle back pressure) Pn the control signal MV from the control calculating portion 2. The pilot relay 4 uses the pneumatic signal Pn from the electropneumatic converter 3 as an input air pressure and amplifies this input air pressure Pn to produce an output air pressure Po, and outputs it to the operating device 11 of the valve 300. Doing so causes the air of the air pressure Po to flow into a diaphragm chamber within the operating device 11, to adjust the opening of the valve portion 12.
In this positioner 200A, that which is subject to control by the control calculating portion 2 includes the electropneumatic converter 3 and the pilot relay 4, which apply the air flow rate and the air pressure to the valve 300. If the characteristics of the electropneumatic converter 3 and the pilot relay 4 were linear, and were well-behaved characteristics, then such a control method would be adequate; however, in practice both the electropneumatic converter and the pilot relay 4 have non-linear elements such as hysteresis and a dead band, and so control is complex. Given this, because in the positioner 200A the feedback information is only the actual opening signal PV of the valve 300, if a change does not appear in the actual opening signal PV, then there is no change in the control output (the control signal MV). Because of this, controllability is a problem. Given this, a positioner with improved controllability has been proposed in Japanese Patent 3595554 (“the JP '554”).
figref[FIG. 4] is a diagram illustrating schematically the positioner shown in the JP '554. In this positioner 200 ( 200B), the differential value dPo/dt of the output air pressure Po that is outputted from the pilot relay 4, as a pressure differential value, is fed back to the control calculating portion 2 in addition to the actual opening signal PV that indicates the current degree of opening of the valve 300. The output air pressure Po changes more rapidly than the actual opening signal PV. Because of this, feeding back the magnitude of change of the output air pressure Po makes it possible to estimate, in advance, the change that will occur in the actual opening signal PV. This enables superior control when compared to that of feeding back only the opening information.
However, in the positioner 200B disclosed in the JP '554, even though the differential information for the output air pressure Po (the control pressure for the diaphragm portion of the operating device 11) of the pilot relay 4, wherein the response is faster than that of the actual opening of the valve 300, is fed back, when there is a noise, and the like, in the differential information, the output becomes extremely large. Because of this, there is a problem in that the control tends to become unstable.
The present invention was created in order to solve the problem as set forth above, and an aspect thereof is to provide a positioner that improves substantially responsiveness without a loss of settling performance in control.
In order to achieve the aspect set forth above, the present invention is a positioner including a control calculating portion that inputs an opening setting signal for a valve, sent from a higher level device, and an actual opening signal that indicates the current degree of opening of the valve, to produce a control signal from the opening setting signal and the actual opening signal, an electropneumatic converter that converts the control signal from the control calculating portion into an air pressure, and a pilot relay that uses, as an input air pressure, the air pressure converted by the electropneumatic converter, to amplify the input air pressure to produce an output air pressure, to output to driving unit that drives the valve. The positioner further includes a shift magnitude calculating portion that calculates a shift magnitude from the equilibrium state of the pilot relay from the input air pressure that is inputted into the pilot relay and the output air pressure that is outputted from the pilot relay. The control calculating unit determines the control output to the electropneumatic converter from the actual opening signal, the opening setting signal, and the shift magnitude from the equilibrium state of the pilot relay.
While the output air pressure of the pilot relay is determined in response to the input air pressure, when there has been a change in the input air pressure from the equilibrium state, there will be a delay until the output air pressure response. In the present invention a magnitude of shift from the equilibrium state of the pilot relay is calculated from the input air pressure that is inputted into the pilot relay and the output air pressure that is outputted from the pilot relay, to determine the control output to the electropneumatic converter by taking into consideration the magnitude of shift from the equilibrium state of the pilot relay, that is, prior to the actual change, the magnitude of change in the output air pressure, which changes in response to a change in the input air pressure into the pilot relay, is estimated in advance, to thereby improve the responsiveness without a loss of settling performance in control.
For example, in the present invention the magnitude of shift from the equilibrium state of the pilot relay is calculated as Po−(K·Pn−F). Here Pn is the input air pressure that is inputted into the pilot relay, Po is the output air pressure, F is the force required before Po starts to change, and K is dPo/dPn.
In the present invention a magnitude of shift from the equilibrium state of the pilot relay is calculated from the input air pressure that is inputted into the pilot relay and the output air pressure that is outputted from the pilot relay, the control calculating portion determines, and outputs as a control signal to the electropneumatic converter, a control output from the actual opening signal, the opening setting signal, and the magnitude of shift from the equilibrium state of the pilot relay, and thus prior to the actual change, the magnitude of change in the output air pressure, which changes in response to a change in the input air pressure into the pilot relay, is estimated in advance, to thereby improve the responsiveness without a loss of settling performance in control.
figref[FIG. 1] is a diagram illustrating the configuration of the critical portions in an example of a positioner according to the present invention.
figref[FIG. 2] is a diagram for explaining the magnitude of shift from the equilibrium status of the pilot relay, calculated by the shift magnitude calculating portion of the positioner.
figref[FIG. 3] is a diagram illustrating the critical components in a conventional positioner.
figref[FIG. 4] is a diagram illustrating the critical components in the positioner shown in the JP '554.
An example according to the present invention will be explained below in detail, based on the drawings. figref[FIG. 1] is a diagram illustrating the configuration of the critical portions in an example of a positioner according to the present invention. In this figure, codes that are the same as those in figref[FIG. 3] indicate identical or equivalent structural elements as the structural elements explained in reference to figref[FIG. 3] , and explanations thereof are omitted. The positioner according to the present invention will be indicated by the code 100 in order to differentiate from a conventional positioner.
In the present example, the positioner 100 is provided with a shift magnitude calculating portion 6 for calculating the magnitude of shift d from the equilibrium state of the pilot relay 4 from the input air pressure Pn that is inputted into the pilot relay 4, and the output air pressure Po that is outputted from the pilot relay 4. It also is provided with a function for determining the control signal MV from the shift magnitude d from the equilibrium state of the pilot relay 4, calculated by the shift magnitude calculating portion 6, and outputting it to the electropneumatic converter 3.
The shift magnitude calculating portion
6 calculates the magnitude of shift d from the equilibrium state of the pilot relay
4 using the calculating equation given in Expression (1), below, from the input air
pressure Pn that is inputted into the pilot relay
4 and the output air pressure Po that is outputted from the pilot relay
4.
d=Po−(
K·Pn−F) (1)
Note that Pn is the input air pressure that is inputted into the pilot relay 4, Po is the output air pressure that is outputted from the pilot relay 4, F is the force required before Po starts to change, and K is dPo/dPn.
The magnitude of shift d from the equilibrium state of the pilot relay 4, calculated by the shift magnitude calculating portion 6, estimates, prior to the actual change, the magnitude of change of the output air pressure Po that changes in response to a change in the input air pressure Pn that is inputted into the pilot relay 4. figref[FIG. 2] illustrates the input/output characteristics of the pilot relay 4. The output air pressure Po of the pilot relay 4 changes in accordance with an equation expressed by Po=K·Pn−F, as indicated by the input/output characteristic I. When the relationship of the input air pressure Pn and the output air pressure Po is on this input/output characteristic I, the pilot relay 4 is in the equilibrium state.
In the equilibrium state of the pilot relay 4, the output air pressure Po assumes a value that depends on the input air pressure Pn. However, because the response of the output air pressure Po is delayed when compared to the input air pressure Pn, for some time after a change in the input air pressure Pn there will be a deviation from this input/output characteristic I. In this case, we can consider the cases wherein the current output air pressure Po is such that K·Pn−F>Po and wherein the current output air pressure Po is such that K·Pn−F<Po. In the case that the current output air pressure Po is such that K·Pn−F>Po (the ( 1) state illustrated in figref[FIG. 2] ), we can anticipate the output air pressure Po to increase by the magnitude of shift d from the equilibrium state. In the case that the current output air pressure Po is such that K·Pn−F<Po (the ( 2) state illustrated in figref[FIG. 2] ), we can anticipate the output air pressure Po to decrease by the magnitude of shift d from the equilibrium state.
Consequently, the magnitude of shift d from the equilibrium state of the pilot relay 4 can be said to be an estimate, prior to an actual change, of the magnitude of change in the output air pressure Po that changes in response to a change in the input air pressure Pn that is inputted into the pilot relay 4. The shift magnitude d from the equilibrium state of the pilot relay 4 is calculated as Po−(K·Pn−F) in the shift magnitude calculating portion 6, and this calculated shift magnitude d is sent to the control calculating portion 2. The shift magnitude d is an estimate of the amount of change there will be in the output air pressure Po, so by feeding this back it is possible to estimate the change in opening at an earlier stage than when feeding back the amount of change in the output air pressure Po. Because of this, the controllability is improved substantially.
The control calculating portion
2 determines the control signal MV from the actual opening signal PV, the opening setting
value SP, and the shift magnitude d from the equilibrium state of the pilot relay
4 that is calculated by the shift magnitude calculating portion
6, and outputs it to the electropneumatic converter
3. Note that the control signal MV is determined through Expression (2), below:
MV=Kp·(
SP−PV)+∫
Ki(
SP−PV)
dt+Kd·(
dPV/dt)+
Km·d (2)
Here Kp is the proportional gain, Ki is the integral gain, Kd is the differential gain, and Km is the shift magnitude gain.
Note that while in the example, set forth above, the shift magnitude d from the equilibrium state of the pilot relay 4 was calculated using Expression (1), above, there is no limitation to this expression. For example, instead the shift magnitude d from the equilibrium state of the pilot relay 4 may be read out from a table wherein the relationships in Expression (1), described above, are stored as data. Moreover, while in the examples set forth above the position sensor 10 was provided outside of the positioner 100, it may instead be provided within the positioner 100.
Furthermore, in the examples set forth above, the functions of the control calculating portion 2, the shift magnitude calculating portion 6, and the like, in the positioner 100, may be embodied through hardware that includes a processor and a storage device and a program, which operates jointly with this hardware, for achieving these functions as a controlling device.
While the present invention has been explained above in reference to the examples, the present invention is not limited to the examples set forth above. The structures and details in the present invention may be varied in a variety of ways, as can be understood by one skilled in the art, within the scope of technology in the present invention.


{%extends 'base.html'%} {%load bootstrap4%} {{block.super}} {%block content%}
{{name}}
Update profile
{{i.bio}}
You have no Product Published Do you own business ? Publish your Product


|
Bullet Collision Detection & Physics Library
|
Go to the source code of this file.
Macros | |
| #define | CONVEX_DISTANCE_MARGIN btScalar(0.04) |
| The CONVEX_DISTANCE_MARGIN is a default collision margin for convex collision shapes derived from btConvexInternalShape. More... | |
| #define CONVEX_DISTANCE_MARGIN btScalar(0.04) |
The CONVEX_DISTANCE_MARGIN is a default collision margin for convex collision shapes derived from btConvexInternalShape.
This collision margin is used by Gjk and some other algorithms Note that when creating small objects, you need to make sure to set a smaller collision margin, using the 'setMargin' API
Definition at line 22 of file btCollisionMargin.h.


Issue Books
home
Branch
Employees
Customer
Return Status
Books
Issue Book
Issued_Book_Name :
Issue_id :
Issued_Cust :
ISBN_Book :
Employee_Id :
Issue_Date (YYYY-MM-DD):
Issue
Issued Books
VIEW


Full-Stack Junior Developer
I am a junior Full-Stack developer, who prefers a Back-end then Front-end. I use JavaScript as a programming language to build my application.
Skill :
- MySQL
- Node.js
- JavaScript
- TypeScript
- React Js
- React Native
- PHP
- Linux


GreedyTree¶
There are many interesting and complex data structures for doing proximity search such as nearest neighbor search. This one is designed as a simple hybrid between the sb data structure of Ken Clarkson and Covertrees by Beygelzimer et al.
The main advantage over previous structures is its profound simplicity. Another side interest is that it doesn’t require logarithms because there are no explicit levels in the tree.
-
class
GreedyTree
(M, seed=None, scaling=inf)¶ The GreedyTree encodes a tree of points. If the points are ordered according to the greedy permutation, the child of a point is its nearest predecessor in the ordering.
-
ann
(q, eps=0)¶ Return a (1+eps)-approximate nearest neighbor to q.
-
nn
(q)¶ Return the nearest neighbor of q in the GreedyTree.
-
rangecount
(center, radius, slack=0)¶ Count the points in the ball with the given center and radius.
If the slack is nonzero then the count could include some points within distance radius + slack of the center.
-


--- title: n? author: Richard Careaga date: '2018-10-27' slug: 'n' categories: - Data Science tags: - statistics - heuristics ---
Got n?
There was a 100% increase in 1-hour parking meter costs this year!
(Imagined conversation in a small town.)
It appears to be hardwired into our wetware to forget to look for the underlying integers. You might ask, for example from what to what? and learn that it went up from a nickle to a dime.
This is a manifestation what Daniel Kahneman, author of Thinking Fast, and Slow (2011, Ferrar, Straus and Giroux, New York) calls The Law of Small Numbers. Our favorite ballplayer has a hot hand (random variation), an image of a religious figure appears in the bird tracks on a beach (randonness doesn’t look uniform, there are all sorts of random patterns) and, the big tell, statistical finidings based on a small sample size, n are particularly vulnerable to random effects.
In one example the author gives as an example a survey of 1,662 schools in Pennsylvania. Of the top 50, six were small schools, about four times as many as you would expect to be exceptional. So, a well-known philantropist, joined by some famous foundations, set up a program to split larger schools up into smaller schools. If small schools do better than average, after all, it only makes sense.
Unfortunately, turning the question around, small schools also tend to have worse outcomes than average. The smaller schools, good, bad or indifferent, are simply more variable.
Look for n, your first line of defense against putting your money where the facts aren’t.


Git
Github
Bash
Github
A web-based hosting service for git
Why I love you
Seamless integration with git
Bug Tracking
Feature Requests
Wikis
Project management with boards
Open Source


Choose a photo below and it will appear with an option to download the image with the metadata cleaned from it. It will also display a list of the metadata seen in the EXIF file of the image.


SF5 optical glass
SF5 is a popular optical glass. Most glass makers produce this or very similar glass under slightly different names.
SF5 and similar glasses produced by different makers
| Maker |
Glass |
| Schott |
N-SF5 |
| Hikari |
E-SF5 |
| HOYA |
E-FD5 |
| Sumita |
K-SFLD5 |
| CDGM |
ZF2 |


Sport stars and volunteers lauded
by Aaron KirbyTHE Mandurah Sports Awards were hosted last week at David Grays Arena.
Nine awards were handed out, including the prestigious Mandurah Sports Person of the Year title, which went to Featherweight boxer Jackson England.
England is a state and national champion and trains 15 hours a day.
Another boxer was honoured on the night. Sophie ‘The Bullet’ Ingledew was named joint Junior Sports Person of the Year with sailor Georgia Payne.
Both girls are looking to competing at next year’s Olympics in Tokyo.
Ingledew said she found a unique path into the sport when she was a child.
“I watched The Karate Kid with my brother, then went and did karate and it flowed from there,” she said.
Mandurah Dragon Boat Club president Malcolm Anderson was named the Sports Person of the Year with a Disability and said he was proud to have found a sport he and his family could do together.
“It’s a family affair; we all do it,” he said.
Cathy Raynor won Senior Sports Person of the Year for her Barefoot Water Skiing achievements, while the Peel Thunder Rogers Cup team claimed Junior Sports Team of the Year for their premiership triumph.
The volunteers that keep sport running were also honoured on the night, with Andrea (AJ) Camarda named Female Volunteer of the Year for her work in netball and Mandurah Surf Life Saving Club’s Russell Price winning the Male Volunteer of the Year award.
Mandurah Surf Life Saving Club was also awarded Club of the Year as well as having its Starfish Nippers program recognised with the Sport Inclusion Award.
Guests sat riveted to their seats as special guest, Olympic pole vaulter Liz Parnova, shared her story.
Nate Lansdall provided entertainment and music while Channel 7’s Mark Readings was the MC.


|
|
Colm Byrne
Product Manager
|
Colm is learning html - again. My udemy training course.
Work Experience
| Date |
Position |
| July 2020 |
Pace Ventures |
| March 2020 |
BIV |
Skills & Experience
| Javascript |
😀 |
HTML |
😀😀😀 |
| React |
😀 |
CSS |
😀😀😀 |
| Mongodb |
😀 |
Node |
😀😀😀 |
My hobbies
Get in touch with >me
My daily goals
- Meditation - just 10 mins maybe with headspace but better without/li>
- Run 7km of the y daily. But needs to be done with Yoga so knees don't get damaged or alternate with another exercise like
swimming or cycling
- Coding - goal is to be able to build out my own projects easily with a full stack or protoyype etc
- Writing - 500 words a day on a topic. Though its getting that outline which is the hard part!
- situps nad pressups. Start with just 5 mins a day and work up


Bookstack
You forgot your password?
Oh that's okay. These things happen sometimes, right? We'll help you get a new one.
What's your Email?
Send me a password reset
Email:
Password:
Log In


Rakuten Multi-modal Product Data Classification and Retrieval challenge is organized by Rakuten Institute of Technology, the research and innovation department of Rakuten group. This challenge focuses on two topics, namely large-scale multi-modal (text and image) classification and cross-modal retrieval. The goal of the multi-modal classification task is to predict each product’s 'type code' as defined in the catalog of Rakuten France. In the cross-modal retrieval task, presented with the text of the products, the goal is to retrieve the images corresponding to the products.
The cataloging of product listings through some type of text or image categorization method is a fundamental problem for any e-commerce marketplace, with applications ranging from personalized search and recommendations to query understanding. Manual and rule-based approaches to categorization are not scalable since commercial products are organized in many and sometimes thousands of classes. When actual users categorize product data, it has often been observed that not only the text of the title and description of the product is useful but also its associated images.
ChallengesIn the taxonomy of Rakuten France, products sharing the same product type code share the same exact array of attributes fields and possible values. Product type codes are numbers that match a generic product name, such as 1500 is Watches, 120 is Laptops, and so on. In that sense, the type code of a product is its category label.
In the product catalog of Rakuten France, a product with a French title Klarstein Présentoir 2 Montres Optique Fibre is associated with an image and sometimes with an additional description. This product is categorized with a product type code of 1500, signifying watches. There are other products with different titles, images and with possible descriptions, which are under the same product type code.
Given these information on the products, like the example above, this challenge proposes participating teams build and submit systems that classify previously unseen products into their corresponding product type codes.
The main tasks for this challenge are as follows:
For this challenge, Rakuten France has released approximately 99K product listings in tsv format, including a training (84,916) and test set (13,812). The dataset consists of product titles, product descriptions, product images and their corresponding product type codes. The test set will be released towards the end of the data challenge. Furthermore, one can assume the test set has been generated from the same data distribution as the training set.
A detailed description of the data is included in this pdf file.
Participation and SubmissionPlease register in this link for participation. The submission is team-based, only team leader can submit the prediction file. Also the same person cannot be team leader of multiple teams. There is no limit on maximum team size. We will send you the details about downloading the data file after we receive your sign-up.
Participants need to provide a prediction output file in the same format as the training output file (associating each Integer_id, Image_id and Product_id tuple with the predicted Prdtypecode). The first line of this test output file should contain the header. Please DO NOT change the order of the test titles in your submission file.
A detailed instruction of the format of the submissions is included in this pdf file.
Accepted contributions will be presented during the eCom Workshop in SIGIR 2020.
Evaluation MetricSince in this challenge, we are dealing with many classes with highly asymmetric number of samples, an item weighted metric used to rank the participants will not reveal the deficiencies of the classification algorithms. The evaluation script is included in the downloadable data file.
Participants build and test models on the training data. The leaderboard only shows the model performance on a SUBSET of the test set according to your LATEST submission. Each team can submit at most 4 times per day in this stage. The leaderboard freezes on July 15 at 5 PM PDT i.e. UTC 00:00:00 the next day.
Stage 2 - Model Evaluation (July 15 - July 23)The final leaderboard will freeze on July 23 at 5 PM PDT i.e. UTC 00:00:00 the next day, and show the model performance on the remaining held out test set according to your LATEST submission. In this stage each team can submit at most 8 times during the time period that the evaluation is open, and there must be a period of 24 hours between two submissions.
System Description PaperSystem description papers will be peer reviewed (single-blind) by the program committee. All submissions must be formatted according to the latest ACM SIG proceedings template. There will be no specific constraint on the content but it should cover the implementation details, such as data preprocessing, including token normalization and feature extraction, additional data used from external sources; model descriptions, including specific implementations, parameter tuning, etc. and error analysis, if any. Suggested paper length is 2-4 pages, and parameter tuning settings or similar information can be moved to an Appendix section.
Instructions to submit the system description paper should be available soon. The deadline for paper submission is July 17, 2020 (11: 59 P.M. UTC).
Timeline| April 20 | Registration Opens, Evaluation Stage 1 Starts! |
| July 15 | Leaderboard for Stage 1 Closes (Registration closes) |
| July 15 | Evaluation Stage 2 Starts |
| July 23 | Evaluation Stage 2 Closes (Final Leaderboard) |
| July 30 | eCom Full Day Workshop |
| July 17 | System Description Paper Submission (Suggested paper length 2-4 pages with separate Appendix) |
| July 23 | Paper Acceptance Notification |
| July 27 | Camera Ready Version of Papers Due (Updated with your final methodology and results) |
If you have any question, please contact Hesam Amoualian<EMAIL_ADDRESS>or Parantapa Goswami (parantapa.goswami@rakuten.com).
| Rank | Team Name | Last Submission | Macro-F1 score |
|---|---|---|---|
| 1 | Transformers | 2020 Jul 13 06:53:43 | 91.94 |
| 2 | zenit84 | 2020 Jun 27 17:33:34 | 91.63 |
| 3 | Alto | 2020 Jul 14 15:40:57 | 91.63 |
| 4 | Beantown | 2020 Jul 15 23:47:03 | 90.89 |
| 5 | Synerise AI | 2020 Jul 07 13:45:38 | 89.72 |
| 6 | pa_curis | 2020 Jul 15 17:38:26 | 89.65 |
| 7 | RIT-Paris Baseline | 2020 Jul 15 10:48:14 | 87.05 |
| 8 | tester | 2020 Jun 24 17:53:50 | 86.94 |
| 9 | testers | 2020 Jul 08 16:19:24 | 85.87 |
| 10 | MMG_AI_TEAM | 2020 Jul 15 11:27:08 | 84.81 |
| 11 | DeepData | 2020 Jun 18 09:11:58 | 84.32 |
| 12 | overfiTTers | 2020 Jul 12 12:57:20 | 81.9 |
| 13 | Team MLG | 2020 Jul 15 05:01:11 | 65.8 |
| 14 | qrudraksh | 2020 May 27 20:03:26 | 58.0 |
| 15 | 7ate9 | 2020 Jun 10 04:39:36 | 53.29 |
| Rank | Team Name | Last Submission | Macro-F1 score |
|---|---|---|---|
| 1 | pa_curis | 2020 Jul 21 10:25:24 | 91.44 |
| 2 | Alto | 2020 Jul 23 21:35:59 | 90.87 |
| 3 | Transformers | 2020 Jul 23 16:23:52 | 90.53 |
| 4 | zenit84 | 2020 Jul 23 22:22:36 | 90.39 |
| 5 | Beantown | 2020 Jul 22 03:58:44 | 90.22 |
| 6 | Synerise AI | 2020 Jul 17 04:42:21 | 89.78 |
| 7 | MMG_AI_TEAM | 2020 Jul 22 13:22:00 | 86.94 |
| 8 | RIT-Paris Baseline | 2020 Jul 18 09:19:53 | 85.36 |
| 9 | Team MLG | 2020 Jul 17 01:22:23 | 64.48 |
| Rank | Team Name | Last Submission | Recall@1 score |
|---|---|---|---|
| 1 | Synerise AI | 2020 Jul 01 12:30:48 | 50.23 |
| 2 | changer | 2020 Jul 12 11:14:59 | 46.85 |
| 3 | pa_curis | 2020 May 27 09:34:52 | 41.89 |
| 4 | Beantown | 2020 Jul 15 20:38:29 | 38.96 |
| 5 | Alto | 2020 Jul 03 01:49:35 | 38.29 |
| 6 | MMG_AI_TEAM | 2020 Jul 15 11:29:07 | 27.25 |
| 7 | kenneth | 2020 Jun 16 20:12:10 | 1.35 |
| Rank | Team Name | Last Submission | Recall@1 score |
|---|---|---|---|
| 1 | Synerise AI | 2020 Jul 17 19:04:22 | 34.28 |
| 2 | changer | 2020 Jul 21 16:59:52 | 31.93 |
| 3 | Beantown | 2020 Jul 22 17:05:28 | 23.3 |
| 4 | Alto | 2020 Jul 20 23:40:02 | 19.99 |
| 5 | pa_curis | 2020 Jul 23 13:19:58 | 19.74 |
| 6 | MMG_AI_TEAM | 2020 Jul 20 12:39:02 | 15.77 |