Entities¶
Creating Custom Data Entities¶
This article describes how to create custom data entities and entity properties. Entity types correspond to the name of collection to which they are posted. For example, if you create a new custom “dog” entity, a “dogs” collection will be created if one did not already exist. If a “dogs” collection already exists, the new “dog” entity will be saved in it. All user-defined properties are indexed, and strings that contain multiple words are keyword-indexed.
The methods cited in this article should be used to create custom data entities. If you are using one of the Nobackend SDKs, use one of the entity type-specific SDK methods to create default data entities.
Note: Although not shown in the API examples below, you need to provide a valid access token with each API call. See Authenticating Users & App Clients for details.
Creating a custom entity¶
When a new entity is created, Nobackend will automatically create a corresponding collection if one does not already exist. The collection will automatically be named with the plural form of the entity type. For example, creating a custom entity of type ‘item’ will automatically create a collection named ‘items’ in which all future ‘item’ entities will be saved.
Request Syntax¶
curl -X POST https://api.tbaas.co/<org>/<app>/<entity_type> -d 'json_object'
Parameters
| Parameter | Description |
|---|---|
| org | Organization UUID or organization name |
| app | Application UUID or application name |
| entity_type | Entity type to create |
| json_object | JSON representation of entity properties |
(For a full list of default properties, see Default Data Entity Types)
Nobackend will create a corresponding collection if one does not already exist. To add an entity to an existing collections, use the pluralized collection name for entity_type.
Example Request/Response¶
Request:
curl -X POST "https://api.tbaas.co/your-org/your-app/item" -d '{"name":"milk", "price":"3.25"}'
Response:
{
"action" : "post",
"application" : "4a1edb70-d7a8-11e2-9ce3-f315e5aa568a",
"params" : { },
"path" : "/items", "uri" : "http://api.tbaas.co/my-org/my-app/items",
"entities" : [ {
"uuid" : "83e9b7ea-e8f5-11e2-84df-e94123890c7a",
"type" : "item",
"name" : "milk",
"created" :<PHONE_NUMBER>230,
"modified" :<PHONE_NUMBER>230,
"metadata" : {
"path" : "/items/83e9b7ea-e8f5-11e2-84df-e94123890c7a"
},
"name" : "milk",
"price" : "3.25"
} ],
"timestamp" :<PHONE_NUMBER>225,
"duration" : 635,
"organization" : "my-org",
"applicationName" : "my-app"
}
Creating multiple custom entities¶
Request Syntax¶
curl -X POST https://api.tbaas.co/<org>/<app>/<entity_type>/ -d 'json_array'
Parameters
| Parameter | Description |
|---|---|
| org | Organization UUID or organization name |
| app | Application UUID or name |
| entity_type | Custom entity type to create |
| json_array | JSON array of entites to be created |
Nobackend will create a corresponding collection if one does not already exist. To add an entity to an existing collections, use the collection name or collection UUID in place of the entity type.
Example Request/Response¶
Request:
curl -X POST "https://api.tbaas.co/your-org/your-app/item" -d '[{"name":"milk", "price":"3.25"}, {"name":"bread", "price":"2.50"}]'
Response:
{
"action" : "post",
"application" : "f34f4222-a166-11e2-a7f7-02e9sjwsf3d0",
"params" : { },
"path" : "/items",
"uri" : "http://api.tbaas.co/your-org/your-app/items",
"entities" : [ {
"uuid" : "f3a8061a-ef0b-11e2-9e92-5f4a65c16193",
"type" : "item",
"name" : "milk",
"price" : "3.25",
"created" :<PHONE_NUMBER>609,
"modified" :<PHONE_NUMBER>609,
"metadata" : {
"path" : "/multis/f3a8061a-ef0b-11e2-9e92-5f4a65c16193"
},
"name" : "milk"
}, {
"uuid" : "f3be262a-ef0b-11e2-a51b-6715d5ef47a6",
"type" : "item",
"name" : "bread",
"price" : "2.50",
"created" :<PHONE_NUMBER>754,
"modified" :<PHONE_NUMBER>754,
"metadata" : {
"path" : "/items/f3be262a-ef0b-11e2-a51b-6715d5ef47a6"
},
"name" : "bread"
} ],
"timestamp" :<PHONE_NUMBER>584,
"duration" : 388,
"organization" : "your-org",
"applicationName" : "your-app"
}
Creating an entity with sub-properties¶
Any valid JSON object can be stored in an entity, regardless of the level of complexity, including sub-properties. For example, suppose you have an ‘items’ collection that contains an entity named ‘milk’. You might store the different varieties of milk as sub-properties of a ‘varieties’ property:
{
"type" : "item"
"name" : "milk"
"varieties" : [ {
"name" : "1%",
"price" : "3.25",
"sku" : "0393847575533445"
}, {
"name" : "whole",
"price" : "3.85",
"sku" : "0393394956788445"
}, {
"name" : "skim",
"price" : "4.00",
"sku" : "0390299933488445"
} ]
}
Updating sub-properties¶
An array of sub-properties is treated as a single object. This means that sub-properties cannot be updated atomically. All sub-properties of a given property must be updated as a set. For more on updating an existing sub-property, see Updating Data Entities.
Example Request/Response
Request:
//Note the use of square brackets for specifying multiple nested objects
curl -X POST "https://api.tbaas.co/your-org/your-app/items" -d '{"varieties":[{"name":"1%","price" : "3.25", "sku" : "0393847575533445"},{"name" : "whole", "price" : "3.85", "sku" : "0393394956788445"}, {"name" : "skim", "price" : "4.00", "sku" : "0390299933488445"}]}'
Response:
{
"action" : "post",
"application" : "f34f4222-a166-11e2-a7f7-02e81adcf3d0",
"params" : { },
"path" : "/items",
"uri" : "http://api.tbaas.co/your-org/your-app/items",
"entities" : [ {
"uuid" : "0d7cf92a-effb-11e2-917d-c5e707256e71",
"type" : "item",
"name" : "milk",
"created" :<PHONE_NUMBER>666,
"modified" :<PHONE_NUMBER>666,
"metadata" : {
"path" : "/items/0d7cf92a-effb-11e2-917d-c5e707256e71"
},
"name" : "milk",
"varieties" : [ {
"name" : "1%",
"price" : "3.25",
"SKU" : "0393847575533445"
}, {
"name" : "whole",
"price" : "3.85",
"SKU" : "0393394956788445"
}, {
"name" : "skim",
"price" : "4.00",
"SKU" : "0390299933488445"
} ]
} ],
"timestamp" :<PHONE_NUMBER>826,
"duration" : 50,
"organization" : "your-org",
"applicationName" : "your-app"
}
Retrieving Data Entities¶
This article describes how to retrieve entities from your account.
Note: Although not shown in the API examples below, you need to provide a valid access token with each API call. See Authenticating Users & App Clients for details.
With the exception of the user entity, all data entities can be retrieved by using their UUID or a ‘name’ property. The user entity can be retrieved by UUID or the ‘username’ property. The value for the ‘name’ or ‘username’ property must be unique.
Retrieving an entity¶
Request Syntax¶
curl -X GET https://api.tbaas.co/<org>/<app>/<collection>/<entity>
Parameters
| Parameter | Description |
|---|---|
| org | Organization UUID or application name |
| app | Application UUID or application name |
| collection | Collection UUID or collection name |
| entity | Entity UUID or entity name |
Example Request/Response¶
Request:
Retrieve by UUID:
curl -X GET "https://api.tbaas.co/your-org/your-app/items/da4a50dc-38dc-11e2-b2e4-02e81adcf3d0"
Retrieve by ‘name’ property:
curl -X GET "https://api.tbaas.co/your-org/your-app/items/milk"
Response:
{
"action" : "get",
"application" : "f34f4222-a166-11e2-a7f7-02e81adcf3d0",
"params" : { },
"path" : "/items",
"uri" : "http://api.tbaas.co/amuramoto/sandbox/items",
"entities" : [ {
"uuid" : "5bb76bca-1657-11e3-903f-9ff6c621a7a4",
"type" : "item",
"name" : "milk",
"created" :<PHONE_NUMBER>796,
"modified" :<PHONE_NUMBER>796,
"metadata" : {
"path" : "/items/5bb76bca-1657-11e3-903f-9ff6c621a7a4"
},
"name" : "milk",
"price" : "3.25"
} ],
"timestamp" :<PHONE_NUMBER>763,
"duration" : 31,
"organization" : "amuramoto",
"applicationName" : "sandbox"
}
Retrieving multiple entities¶
This example describes how to retrieve multiple entities by UUID. You can also retrieve a set of entities by using a query string. For more information on querying your data, see Querying your data.
Request Syntax¶
curl -X GET https://api.tbaas.co/<org_id>/<app_id>/<collection>?ql= uuid = <entity_uuid> OR uuid = <entity_uuid>;
Parameters
| Parameter | Description |
|---|---|
| org_id | Organization UUID or application name |
| app_id | Application UUID or application name |
| collection | Collection UUID or collection name |
| entity | Entity UUID or entity name |
The query must be in Nobackend Query Language, for example:
?ql=uuid="<entity_uuid>"" OR name="<entity_name>" OR...
You may also specify the following for certain entity types:
User entities: username = <entity_username>
All other entities except groups: name = <entity_name>
Example Request/Response¶
Request:
//note the url-encoded query string
curl -X GET "https://api.tbaas.co/your-org/your-app/items?ql=name%3D'milk'%20OR%20UUID%3D1a9356ba-1682-11e3-a72a-81581bbaf055&limit="
Note: The query parameter of the request must be url encoded for curl requests
Response:
{
"action" : "get",
"application" : "f34f4222-a166-11e2-a7f7-02e81adcf3d0",
"params" : {
"ql" : [ "name='milk' OR UUID=1a9356ba-1682-11e3-a72a-81581bbaf055" ]
},
"path" : "/items",
"uri" : "http://api.tbaas.co/your-org/your-app/items",
"entities" : [ {
"uuid" : "5bb76bca-1657-11e3-903f-9ff6c621a7a4",
"type" : "item",
"name" : "milk",
"created" :<PHONE_NUMBER>796,
"modified" :<PHONE_NUMBER>796,
"metadata" : {
"path" : "/items/5bb76bca-1657-11e3-903f-9ff6c621a7a4"
},
"name" : "milk",
"price" : "3.25"
}, {
"uuid" : "1a9356ba-1682-11e3-a72a-81581bbaf055",
"type" : "item",
"name" : "bread",
"created" :<PHONE_NUMBER>867,
"modified" :<PHONE_NUMBER>867,
"metadata" : {
"path" : "/items/1a9356ba-1682-11e3-a72a-81581bbaf055"
},
"name" : "bread",
"price" : "2.50"
} ],
"timestamp" :<PHONE_NUMBER>729,
"duration" : 63,
"organization" : "your-org",
"applicationName" : "your-app",
"count" : 2
}
Updating Data Entities¶
This article describes how to update entities in your account.
Note: Although not shown in the API examples below, you need to provide a valid access token with each API call. See Authenticating Users & App Clients for details.
Updating an entity¶
One or more properties can be updated with a single PUT request. For information on updating sub-properties, see Updating sub-properties below.
Request Syntax¶
curl -X PUT https://api.tbaas.co/<org>/<app>/<collection>/<entity> -d {<property>}
Parameter
| Parameter | Description |
|---|---|
| org_id | Organization UUID or application name |
| app_id | Application UUID or application name |
| collection | Name of the collection containing the entity to be updated |
| Uuid|name | UUID or name of the data entity to be updated |
| json_object | JSON object with a field for each property to be updated |
An entity property to be updated, formatted as a key-value pair. For example:
{"property_1":"value_1", "property_2":"value_2",...}
Example Request/Response¶
Request:
curl -X PUT https://api.tbaas.co/your-org/your-app/items/milk -d '{"price":"4.00", "availability":"in-stock"}'
Response:
{
"action" : "put",
"application" : "f34f4222-a166-11e2-a7f7-02e81adcf3d0",
"params" : { },
"path" : "/items",
"uri" : "http://api.tbaas.co/your-org/your-app/items",
"entities" : [ {
"uuid" : "5bb76bca-1657-11e3-903f-9ff6c621a7a4",
"type" : "item",
"name" : "milk",
"created" :<PHONE_NUMBER>796,
"modified" :<PHONE_NUMBER>077,
"availability" : "in-stock",
"metadata" : {
"path" : "/items/5bb76bca-1657-11e3-903f-9ff6c621a7a4"
},
"name" : "milk",
"price" : "4.00"
} ],
"timestamp" :<PHONE_NUMBER>050,
"duration" : 87,
"organization" : "your-org",
"applicationName" : "your-app"
}
Updating a sub-property¶
Data entities may contain sets of sub-properties as nested JSON objects. Unlike normal entity properties, however, sub-properties cannot be updated individually. Updating a nested object will cause all sub-properties within it to be overwritten.
For example, if you have a data entity with the following nested object:
Request Syntax¶
curl -X PUT https://api.tbaas.co/<org_id>/<app_id>/<collection>/<uuid|name> -d '{<property> : [{<sub_property>}, {<sub_property>}...]}'
Parameters
| Parameter | Description |
|---|---|
| org_id | Organization UUID or application name |
| app_id | Application UUID or application name |
| collection | Name of the collection containing the entity to be updated |
| Uuid|name | UUID or name of the data entity to be updated |
| json_object | JSON object with a field for each property to be updated |
Example Request/Response¶
Request:
curl -X PUT https://api.tbaas.co/your-org/your-app/items/milk -d '{"varieties":[{"name":"1%","price":"3.25"},{"name":"whole","price":"4.00"}]}'
Response:
{
"action" : "put",
"application" : "f34f4222-a166-11e2-a7f7-02e81adcf3d0",
"params" : { },
"path" : "/items",
"uri" : "http://api.tbaas.co/your-org/your-app/items",
"entities" : [ {
"uuid" : "5bb76bca-1657-11e3-903f-9ff6c621a7a4",
"type" : "item",
"name" : "milk",
"created" :<PHONE_NUMBER>796,
"modified" :<PHONE_NUMBER>069,
"availability" : "in-stock",
"metadata" : {
"path" : "/items/5bb76bca-1657-11e3-903f-9ff6c621a7a4"
},
"name" : "milk",
"uri" : "http://api.tbaas.co/your-org/your-app/items/5bb76bca-1657-11e3-903f-9ff6c621a7a4",
"varieties" : [ {
"name" : "1%",
"price" : "3.25"
}, {
"name" : "whole",
"price" : "4.00"
} ]
} ],
"timestamp" :<PHONE_NUMBER>047,
"duration" : 62,
"organization" : "your-org",
"applicationName" : "your-app"
}
Deleting Data Entities¶
This article describes how to delete data entities.
Deleting an entity¶
Request Syntax
curl -X DELETE https://api.tbaas.co/<org>/<app>/<collection>/<entity>
Parameters
| Parameter | Description |
|---|---|
| org | Organization UUID or application name |
| app | Application UUID or application name |
| collection | Collection UUID or collection name |
| entity | Entity UUID or entity name |
Example Request/Response¶
Request:
Delete by UUID:
curl -X DELETE "https://api.tbaas.co/your-org/your-app/items/da4a50dc-38dc-11e2-b2e4-02e81adcf3d0"
Delete by ‘name’ property:
curl -X DELETE "https://api.tbaas.co/your-org/your-app/items/milk"
Response:
{
"action" : "delete",
"application" : "f34f4222-a166-11e2-a7f7-02e81adcf3d0",
"params" : { },
"path" : "/items",
"uri" : "http://api.tbaas.co/your-org/your-app/items",
"entities" : [ {
"uuid" : "328fe64a-19a0-11e3-8a2a-ebc6f49d1fc4",
"type" : "item",
"name" : "milk",
"created" :<PHONE_NUMBER>500,
"modified" :<PHONE_NUMBER>500,
"metadata" : {
"path" : "/items/328fe64a-19a0-11e3-8a2a-ebc6f49d1fc4"
},
"name" : "milk",
"price" : "3.25"
} ],
"timestamp" :<PHONE_NUMBER>016,
"duration" : 324,
"organization" : "your-org",
"applicationName" : "your-app"
}


Processing Community Day @ Worldwide currently have 80+ registered node cities around the world. Please look for your nearest city on the map and contact your local organizer directly about attending.
Don't see your city on the map? Join our newsletter to receive updates on PCD @ Worldwide sites near you or consider hosting a Processing Community Day.
The Processing Foundation is currently accepting registration from communities around the world to organize a Processing Community Day in your own city.
Pick a date and time between January 15 and February 15, 2019 to host a Processing Community Day.
The duration can be as short as a two-hour programming tutorial, or as long as an all day event that includes workshops, discussions on network culture, or a show & tell on software art.
This is an open question depending on your local culture and what you have access to, but generally we recommend collaborating with public facilities such as libraries, schools, or community-driven spaces with good, stable Wi-Fi such as community centers, art / culture venues, hackerspaces, cafes, tea houses, or bars.
The Processing Foundation is currently gathering a list of PCD node organizers around the world through online registration. Registration is important as it helps us keep you posted with useful organizing information and materials, as well as connecting you to other parts of the Processing Community.
We are unable to provide financial assistance for the node events, however we will be able to provide an Organizer’s Kit, which includes a step-by-step organizing guide, promotion and tutorial packages. We will also support your event through our social media, and provide a platform for you to exchange experience and knowledge with communities around the world. Please use the hashtag #PCD2019 when posting on social media so that we can help promote your event.
We do not manage or distribute tickets on behalf of our node events. As an organizer, you will determine whether ticketing is a preferable option for your event. We encourage all organizers who are planning to charge a fee for the event to provide affordable options to promote accessibility and inclusivity.


The gyroradius of a particle is given by ρα = mv∕BZe, which can be further written as
|
| (104) |
where Ek is the kinetic energy of the particle. For an electron with the same kinetic energy of a ion, Eq. (104) indicates that the gyroradius of the electron is smaller than that of the ion by the factor . Now comes the question: Is the width of the guiding center orbit of an electron with the same kinetic energy of a ion smaller than that of the ion? Examine the constant of motion Pϕ which is given by
|
| (105) |
The function g(Ψ)∕Ω is usually a weak function of Ψ, thus can be asssumed to be a contant along a drift orbit. The orbit width can be characterised by ΔΨ, which is written
|
| (106) |
where Δv∥ is the variation range of v∥ in one poloidal period of the orbit. For trapped particles, this variation can be approximated as
|
| (107) |
Using this, Eq. (106) is written as
|
| (108) |
which indecates that, for the same temperature, ΔΨ is proportional to . (For circulationg ions, the variation of v∥ during one poloidal period can not be approximated by vt. I do not know how to estimate the orbit width in this case).
The variation of the poloidal ﬂux ΔΨp can be approximated by
|
| (109) |
where Δr is the variation of the minor radius, Bp is the average poloidal magnetic ﬁeld on a magnetic surface. Using this and the deﬁntion ΔΨ = ΔΨp∕2π in Eq. (108), we obtain
|
| (110) |
which indicates that the width of guiding-center orbits is inversely proportional to the poloidal magnetic ﬁeld Bp, rather than the toroidal magnetic ﬁeld Bt (ﬁrst got to know this conclusion from J. Wession’s book “Science of JET”, and later wrote the above derivation).
Comparing Eq. (110) and (104), we know Δr is just the “poloidal larmor radius” which is obtained by replacing the B in Eq. 104) by the poloidal magnetic ﬁeld Bp. It follows that the ratio between them is given by
|
| (111) |
which is about q∕𝜀 for large aspect-ratio tokamaks, where q is the safety factor.
The average poloidal magnetic ﬁeld on a magnetic surface neare the plasma edge is approximately given by
|
| (112) |
Using this, Eq. (110) is written as
|
| (113) |
which indicates that Δr is proportional to 1∕Ip. This explains why high plasma current is beneﬁcial to the conﬁnement of energetic particles (because high current corresponds to smaller orbit width and thus better conﬁnement of energetic particles which usually have larger drift orbit width than thermal particles).
A numerical example in Fig. 25 indicate, as expected, that the guiding center orbit width of an electron with the same kinetic energy of a ion is much smaller than that of the ion.


Da Vinci Payer Data exchange - Local Development build (v0.3.7). See the Directory of published versions
Previous Page - US Core ImplantableDevice
The US Core Location profile SHALL be used to record location/facility-specific information.
The essential fields to be provided in the US Core Location resource are:
| R4 Hierarchical Name | R4 Name | Card. | Type |
|---|---|---|---|
| Location | Location | 0..* | |
| Location.id | id | 0..1 | id |
| Location.status | status | 0..1 | code |
| Location.name | name | 1..1 | string |
| Location.telecom | telecom | 0..* | ContactPoint |
| Location.address | address | 0..1 | Address |
| Location.address.line | line | 0..* | string |
| Location.address.city | city | 0..1 | string |
| Location.address.state | state | 0..1 | string |
| Location.address.postalCode | postalCode | 0..1 | string |
| Location.managingOrganization | managingOrganization | 0..1 | Reference(US Core Organization Profile) |
A collaboration of Health Plan experts have performed an evaluation of claims information and developed a mapping of data for Members to the US Core Location profile. This is shown below as an assistance to implementers:
| Line | PayerSourceRecord | CMS BB 2.0 Field | Data Descriptor | FHIR Profile | Profile Field | ValueSet | Notes |
|---|---|---|---|---|---|---|---|
| 15.1 | Claim | N/A | Claim bill facility type code | US Core Location | .type | http://build.fhir.org/v3/ServiceDeliveryLocationRoleType/vs.html | |
| 5.1 | Claim-Provider | N/A | Claim site of service NPI | US Core Location | .identifier.value | ||
| 16.1 | Claim-Provider | N/A | Claim service location NPI | US Core Location | .identifier.value | ||
| 7.1 | Claim-Pharmacy | N/A | Pharmacy service type code | US Core Location | .type |
Where an entry is provided in the CMS BB2.0 FIELD column the definition of the field can be reviewed using the following URL:
https://bluebutton.cms.gov/resources/variables/{CMS_BB2.0_FIELD}/
Where {CMS_BB2.0_FIELD} is replaced with the Field value in lower case. For example:
https://bluebutton.cms.gov/resources/variables/bene_id/ https://bluebutton.cms.gov/resources/variables/dob_dt/
An example mapping of a Location resource is shown here:
{ "resourceType" : "Location", "id" : "hl7east", "meta" : { "profile" : [ "http://hl7.org/fhir/us/core/StructureDefinition/us-core-location" ] }, "text" : { "status" : "generated", "div" : "
Generated Narrative with Details
id: hl7east
meta:
identifier: 29
status: active
name: Health Level Seven International - Amherst
description: HL7 Headquarters - East
telecom: ph: (+1)<PHONE_NUMBER>
address: 3300 Washtenaw Avenue, Suite 227 Amherst MA 01002 USA
Positions

- Longitude Latitude
 * -72.519854 42.373222 managingOrganization: Health Level Seven International

" }, "identifier" : [ { "system" : "http://www.acme.org/location", "value" : "29" } ], "status" : "active", "name" : "Health Level Seven International - Amherst", "description" : "HL7 Headquarters - East", "telecom" : [ { "system" : "phone", "value" : "(+1)<PHONE_NUMBER>" } ], "address" : { "line" : [ "3300 Washtenaw Avenue, Suite 227" ], "city" : "Amherst", "state" : "MA", "postalCode" : "01002", "country" : "USA" }, "position" : { "longitude" : -72.519854, "latitude" : 42.373222 }, "managingOrganization" : { "display" : "Health Level Seven International" } }
Refer to the US Core Additional examples of the US Core R4 Implementation Guide for further examples of completed US Core Location Profiles .


- pinchIn(Selector, int, int) - 接口 中的方法com.github.uiautomator.stub.AutomatorService
-
Performs a two-pointer gesture, where each pointer moves diagonally toward the other, from the edges to the center of this UiObject .
- pinchIn(String, int, int) - 接口 中的方法com.github.uiautomator.stub.AutomatorService
-
Performs a two-pointer gesture, where each pointer moves diagonally toward the other, from the edges to the center of this UiObject .
- pinchIn(Selector, int, int) - 类 中的方法com.github.uiautomator.stub.AutomatorServiceImpl
-
Performs a two-pointer gesture, where each pointer moves diagonally toward the other, from the edges to the center of this UiObject .
- pinchIn(String, int, int) - 类 中的方法com.github.uiautomator.stub.AutomatorServiceImpl
-
Performs a two-pointer gesture, where each pointer moves diagonally toward the other, from the edges to the center of this UiObject .
- pinchOut(Selector, int, int) - 接口 中的方法com.github.uiautomator.stub.AutomatorService
-
Performs a two-pointer gesture, where each pointer moves diagonally opposite across the other, from the center out towards the edges of the this UiObject.
- pinchOut(String, int, int) - 接口 中的方法com.github.uiautomator.stub.AutomatorService
-
Performs a two-pointer gesture, where each pointer moves diagonally opposite across the other, from the center out towards the edges of the this UiObject.
- pinchOut(Selector, int, int) - 类 中的方法com.github.uiautomator.stub.AutomatorServiceImpl
-
Performs a two-pointer gesture, where each pointer moves diagonally opposite across the other, from the center out towards the edges of the this UiObject.
- pinchOut(String, int, int) - 类 中的方法com.github.uiautomator.stub.AutomatorServiceImpl
-
Performs a two-pointer gesture, where each pointer moves diagonally opposite across the other, from the center out towards the edges of the this UiObject.
- ping() - 接口 中的方法com.github.uiautomator.stub.AutomatorService
-
It's to test if the service is alive.
- ping() - 类 中的方法com.github.uiautomator.stub.AutomatorServiceImpl
-
It's to test if the service is alive.
- Point - com.github.uiautomator.stub中的类
-
Created with IntelliJ IDEA.
- Point() - 类 的构造器com.github.uiautomator.stub.Point
-
- pressKey(String) - 接口 中的方法com.github.uiautomator.stub.AutomatorService
-
Simulates a short press using key name.
- pressKey(String) - 类 中的方法com.github.uiautomator.stub.AutomatorServiceImpl
-
Simulates a short press using key name.
- pressKeyCode(int) - 接口 中的方法com.github.uiautomator.stub.AutomatorService
-
Simulates a short press using a key code.
- pressKeyCode(int, int) - 接口 中的方法com.github.uiautomator.stub.AutomatorService
-
Simulates a short press using a key code.
- pressKeyCode(int) - 类 中的方法com.github.uiautomator.stub.AutomatorServiceImpl
-
Simulates a short press using a key code.
- pressKeyCode(int, int) - 类 中的方法com.github.uiautomator.stub.AutomatorServiceImpl
-
Simulates a short press using a key code.
- PressKeysWatcher - com.github.uiautomator.stub.watcher中的类
-
Created with IntelliJ IDEA.
- PressKeysWatcher(UiSelector[], String[]) - 类 的构造器com.github.uiautomator.stub.watcher.PressKeysWatcher
-


|
GSM Based Home Automation
Participants
| M irfan Rind |
Abdul Ghafoor |
Introduction
The objectives of this assignment are:
-
Our semester project is to design a GSM based home automation system. The device can control domestic equipment for energy saving applications.
-
Our objective in this project is to control our home appliances through SMS.
Such devices are commercially available in the market, and come with a variety interfaces like GSM, WiFi and Ethernet. These devices are central component of fully automated "smart homes".
How we Start ?
When our mentor assigned us to this project we were confused how start and as we started reviewing literature things became very clear.
Deligation of Tasks
High Level Design
The module recieves the SMS and passes it to Microcontroller and microcontroller will compare it with the preloaded set of messages. After getting result microcontroller will give instruction to relay and relay will finally take action as defined by user.
Brief Description of Major Component
Microcontroller
Although many micro-controllers are available in the market, ATMEGA328P is the most popular of all because of its features, cost and rich set of resouces available on the internet. Arduino boards are also developed on this micro-controller.
With program memory of 32 Kbytes ATMEGA328P applications are many.
With various Power Saving modes it can work as a portable embedded device.
With Watchdog timer to reset under error it can be used on systems with minimal human interference.
With advanced RISC architecture, the controller executes programs quickly.
Also with in chip temperature sensor the controller can be used at extreme temperatures.
These all features add up to selection of ATMEGA328P for our project.
For Further info
- It has EEPROM memory of 1KB
-
It has SRAM memory of 2KB
- It has 8 pins for Analouge to Digital Conversion operation (denoted by PA0 to PA7).
-
It has 14 (fourteen) Digital pins specified by (D0 to D13)
GSM Shield 900
Mobile phone is a revolutionary invention of the 20th century. It was primarily designed for making and receiving calls & text messages, but it has become the whole world after the smart phone comes into the picture. In this project we are building a home automation system, where one can control the home appliances, using the simple GSM based phone, just by sending SMS through his phone. In this project, no smart phone is needed, just the old GSM phone will work to switch ON and OFF any home electronic appliances, from anywhere
Shield 900 Front
Shield 900 Back
IMPORTANT NOTE
We are using GSM 900 shield. We want to use GSM module but we can't due to unavailablity of it and registration of GSM device with PTA. To check GSM there are two LEDs one is power led showing power in GSM and other is status led showing SIM status. If status led is blinking with the pause of three seconds then GSM is working correctly. From our experience working on this project we realized that there is a power issue in the GSM shield. It takes almost 1.5A for first five seconds then 150mA is needed continously. Power can be given through the adapter as well as power supply. But one thing which is very important is the you are not supposed to take power from the GSM shield for microcontrolar not for any other usage. It will heatup your Shield and it can be damaged. An other point is you are not supposed to use Rx Tx pins for GSM because it cause issue while loading any programe so use any Digital pins for this purpose we are using 7 and 8 pins for GSM .
Nokia 5110 LCD
-
Display the status of system.
-
Display the value of Temprature
-
Operating Voltage is 2.7V to 3.3V
-
Current consumption is 6mA
-
Has a 84×48 pixel monochrome display
-
Works using SPI interface
-
Consists of Philips PCD8544 interface chip for easy interfacing
-
Can be easily interfaced with Arduino
-
Supports decent graphics of bitmap images
-
Available in green and blue backlight.
DHT22 Sensor
-
Measures the temprature and humidity, transmits data over I2C protocol.
4 Channel Relay
This is a 5V 4-channel relay interface board, and each channel needs a 15-20mA driver current. It can be used to control various appliances and equipment with large current. It is equipped with high-current relays that work under AC250V 10A or DC30V 10A. It has a standard interface that can be controlled directly by microcontroller.
A relay is an electromagnetic switch used to turn on/off a circuit through a low power control signal, or where several circuits must be controlled by one signal.
Implementation Process
- Firstly we interfaced GSM module with Arduino just to send and recieve SMS through GSM.
Here is diagram where we confirmed that GSM is functioning and which pins we have to use.
- We started off our work through basic interfacing of LCD and DHT22 sensor with Arduino Board
- We also interface GSM with Relay For the Purpose how we have to work in project
- Then we make a breadboard circuit where we use leds for the purpose of load. Through this basic implementation we achieved 100% output from this prototype.
Next Plan
After Prototype we move forward for PCBs we make two PCBs. 1st PCB for Micro-controller and 2nd For GSM , LCD , Relay , and sensor.
Design of Project
Electrical Circuit
Here is PCB layout of microcontroller board. Alot of time and thought was invested in the process to squeeze all the components together in the minimal space.
Milled PCB
1)
First PCB for microcontroller we just insert 14 pin connector therefore our required component setting like sensor, LCD , Relay
Functional PCB
when we come up with a fully soldered microcontrolar board then next task is to burn the boatloader program on the micro-controller. For burning programme we first did bootloader through SPI protocol. Then we upload test programme to test 13 pin LED. And to our surprise we succeed to bootload the micro-controller at the very first attempt.
Milled PCB 2
In second PCB there is network for GSM , Relay and Sensor.
2)
2nd PCB in order to design sandwich shape just put GSM on that Board . There are three Pin using therefore Rx,Tx and Ground after making two boards, we realize that there will be irregular shape of our project. From our experience, we come to conclude that where possible design of product with mutliple boards should be avoided.
PCB Milling Machine
We milled our PCB using the milling machine available inp our lab.
Bill of Material
Here is the bill of material of our micro-controller based device.
Bill of Material for Second Board
- GSM Shield 900
- Four Channel Relay
- Nokia 5110 LCD
- DHT22 Sensor
PCB Layout
Software Development
In a pictorial format you may describe the flow of your algorithm and how you have used the functions to implement the code in an efficient way.
Design of Finished Product
Here is printed enclosure of our module. The enclosure has width of 2.5" while the hieght is 3"
Front View
Top View
Our 3D Printer
Results
At last we came up with functional product and here is the video link of functional product.
project Vedio
Commercialization Aspects
GSM Based Home Automation has a great potential for commercialization. Automation of equipment and plants through Internet of Things is being used widely. So if a product is commercialized it's price matters. We made this device just to control four loads of any kind. So it's price is seven thousands only. The price of the device can be lowered significantly by using GSM module instead of shield which is the main component of our project.
As I mentioned above that we are using GSM shield which is very expensive as compared to GSM module. It's price can be vary by varing number of loads.
Conclusions
This is our semester project for the module Introduction to Embedded System. We learnt some life long things from it includings some technical Skills Software as well as Hardware skills. And learn how to read datasheets of different components.
We learn how to search websites and also learn how to choose compnents, we face problem while choosing GSM shield due to PTA registration issue. We choose ATMEGA328 IC because it is full filling our requirements.
We learn how to interface different components with micro-controller.
SOFTWARE CASE:
We learnt EAGLE software by making of different PCBs including simple circuit, micro-controllar and PCB for interfacing different components. We have full command on it now.
And we also use Solid Works for making enclosure for our product using 3D printer(ULTIMAKER). We have also command on it. We aslo make sheet for laser cutter for LCD.
And We also learn programing Skills from this project and learn Arduino language for writting programes. C language is used in arduino programming. We faced alot of problems while doing programming and while routing of PCBs and making casing is another big challenge for us. These issues are very helpful for us to learn different things in detail.
HARDWARE CASE:
In case of Hardware we learnt soldering of SMT as well as DIP components on Printed Circuit Board. And we also learnt the assembly of components. Although we faced alot of issues in assembly of components because we take very compact measurements of our product which cause a big problem for us. We also learned interfacing of components(GSM, SENSOR,NOKIA LCD,RELAY )
with Arduino.
In conclusion we learn many things as we were facing problem and one thing is that we learn how to tackle with the problem and how to search about problems and how to solve them. Problems can be of any kind.
It can be interfacing of components, routing of PCBs, soldering of components, Programming , working on Solid Works, assembly problems and many more.
Appendix
Total expenditure of our project is given below component wise.
Eagle PCB Layout files
Arduino Code


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This tool aims to make datasets within the Sequence Read Archive more accessible.
Loading..
Showing results.
| Title | Accession | Instrument | Total Bases (Mb) | Date Created | |
|---|---|---|---|---|---|
| {{ x.title }} | {{ x.accession }} | {{ x.platform }} | {{ x.total_bases }} | {{ x.createdate | date:'dd MMM yyyy' }} |
To download FastQ files directly, sra-explorer queries the ENA for each SRA run accession number.
The following is a list of links to download the selected SRA runs as FastQ from the ENA.
Loading / ..
{{ x.fastq_url }}{{ nlChr }}
This list of bash curl
commands to download each SRA run FastQ file from the ENA, and save with a nicer filename, with the cleaned dataset title appended.
Loading / ..
#!/usr/bin/env bash
{{ nlChr }}curl -L {{ x.fastq_url }} -o {{ x.fastq_niceFilename }}
This list of bash ascp
commands to download each FastQ file from the ENA using the Aspera download tool.
Loading / ..
#!/usr/bin/env bash
{{ nlChr }}ascp -QT -l 300m -P33001 -i {{ ascp_openssh_location }} {{ x.fastq_asperaurl }} . && mv {{ x.fastq_filename }} {{ x.fastq_niceFilename }}
This list of URLs is followed by a nicer filename, with the cleaned dataset title appended. This is suitable for use with the Cluster Flow --file_list
download option.
Loading / ..
{{ x.fastq_url }}{{ tabChr }}{{ x.fastq_niceFilename }}{{ nlChr }}
This list of URLs is followed by a nicer filename. This is suitable for use with bcbio-nextgen analysis pipelines.
Loading / ..
samplename,description
{{ nlChr }}{{ x.fastq_url }},{{ x.fastq_niceFilename }}
These download links are automatically generated based on the URL schema of the NCBI SRA.
The following is a list of links to download the selected SRA files.
{{ x.sra_url }}{{ nlChr }}
This list of bash curl
commands to download each SRA file and save with a nicer filename, with the cleaned dataset title appended.
#!/usr/bin/env bash
{{ nlChr }}curl -L {{ x.sra_url }} -o {{ x.sra_niceFilename }}
This list of URLs is followed by a nicer filename, with the cleaned dataset title appended. This is suitable for use with the Cluster Flow --file_list
download option.
{{ x.sra_url }}{{ tabChr }}{{ x.sra_niceFilename }}{{ nlChr }}
These files contain the metadata used by SRA-Explorer for downstream use. Note that each SRA record is repeated for every ENA FastQ entry.
The following is a TSV (tab separated values) file with all metadata fields for the selected samples.
Loading / ..
Accession{{ tabChr }}Title{{ tabChr }}Platform{{ tabChr }}Total bases{{ tabChr }}Create date{{ tabChr }}SRA URL{{ tabChr }}SRA filename{{ tabChr }}SRA nice filename{{ tabChr }}FastQ URL{{ tabChr }}FastQ Aspera URL{{ tabChr }}FastQ filename{{ tabChr }}FastQ nice filename
{{ nlChr }}{{ x.accession }}{{ tabChr }}{{ x.title }}{{ tabChr }}{{ x.platform }}{{ tabChr }}{{ x.total_bases }}{{ tabChr }}{{ x.createdate }}{{ tabChr }}{{ x.sra_url }}{{ tabChr }}{{ x.accession }}.sra{{ tabChr }}{{ x.sra_niceFilename }}{{ tabChr }}{{ x.fastq_url }}{{ tabChr }}{{ x.fastq_asperaurl }}{{ tabChr }}{{ x.fastq_filename }}{{ tabChr }}{{ x.fastq_niceFilename }}
The following is a JSON file with all metadata fields for the selected samples.
Loading / ..
{{ savedResultsENAfastq | json }}
The following is a YAML file with all metadata fields for the selected samples.
Loading / ..
{{ savedResultsENAfastqYAML }}
Query URL =


Web Application Of
Diabetic Retinopathy Classification Using
Keras And API Tensorflow of Pre-trained Deep Learning Models
Normal:
Mild:
Moderate:
Severe:
PDR:
Predict


Classes and scripts placed here can be made available by name to any actor in the project without an import statement.


Open Angel Arena 3.13.10 Update
General Changes
Fixed Grimstroke.
Added bottles for contributors.
Added item builds for Sohei and Chatterjee.
Hero Changes
Grimstroke:
Phantom's Embrace latch duration rescaled from 4/4.5/5/5.5/6/6.5 to 4/4/5/5/6/6 seconds.
Ink Swell movement speed bonus reduced from 28%/32%/36%/40%/44%/48% to 18%/22%/26%/30%/34%/38%.
Ink Swell damage and stun amounts now range from 0 to max, instead of from a base value to max.
Ink Swell will not stun if heroes aren't damaged with it.
Return to Home Page


--- layout: null permalink: /latest/ index: false --- {% assign redirect=site.posts.first %}
{% include common/redirect.html url=site.posts.first.url delay=3 %}You are being redirected. If your browser does not automatically take you to the next page, click here.


I am technology enthusiast and enjoy working in IT feild.
This is a Resturant Website Design.It is a single page responsive desktop first design.This site consist of mainly 5 sections:Home,Menu Reservation,Our Team, Contact Us.
Apart from being a web designer, I enjoy most of my time being outdoors.I enjoy get together with friends,hiking and natural photography
When forced indoors,I enjoy listening romantic songs, Cooking, read novels and lern web design related technlogy .


--- layout: post status: publish published: true title: "回家..." author: Leask author_login: leask author_email<EMAIL_ADDRESS>author_url: https://leaskh.com wordpress_id: 568 wordpress_url: http://leaskh.wordpress.com/2006/04/30/%e5%9b%9e%e5%ae%b6 date: '2006-04-30 02:26:54 +0800' date_gmt: '2006-04-30 02:26:54 +0800' categories: - Life tags: [] comments: - id: 272 author: Unknown author_email: '' author_url: '' date: '2006-05-05 18:59:22 +0800' date_gmt: '2006-05-05 18:59:22 +0800' content: "回家...我们的归宿.我们的避风港." - id: 273 author: "Ｓirose" author_email: '' author_url: '' date: '2006-05-01 17:34:01 +0800' date_gmt: '2006-05-01 17:34:01 +0800' content: "別忘記4008" ---


Guidance
Technical and vocational qualifications for teaching from September 2016 and reporting in 2018 performance tables.
Ref: DFE-00308-2015 PDF , 399KB , 12 pages
Ref: DFE-00003-2016 PDF , 645KB , 20 pages
Ref: DFE-00017-2016 PDF , 704KB , 21 pages
Ref: DFE-00018-2016 PDF , 432KB , 16 pages
Lists of qualifications for reporting in the 2018 performance tables in the following categories:
You can find more information on the performance tables website.
Technical awards are practical qualifications for students aged 14 to 16.
Technical certificates, tech levels, and applied general qualifications are technical and applied qualifications for students aged 16 to 19 .
Published: 18 December 2015
Updated: 5 August 2016


Internal Wiki
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About us
Collaborative Computational Project No. 4
Software for Macromolecular X-Ray Crystallography
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|
Midnight Blue Game and Engine
|
HUD to show in the galaxy view. More...
Public Member Functions | |
| GalaxyHud (ContentManager content) | |
| Initializes a new instance of the T:MB2D.GalaxyHud class. More... | |
| void | Refresh (Inventory inventory) |
| Refreshed the HUD with the specified inventory values. More... | |
| Public Member Functions inherited from MB2D.UI.UIView | |
| UIView (int rows, int cols) | |
| Initializes a new instance of the T:MB2D.UI.UIView class. Divides itself into the number of rows and columns evenly based on the size of the current viewport. More... | |
| void | Update () |
| Updates and handles input for all elements in the View. More... | |
| void | Draw (SpriteBatch spriteBatch, SpriteBatch uiSpriteBatch) |
| Draws the View and its elements to the window More... | |
| void | Add (UIElement element, int atRow, int atCol, int rowSpan, int colSpan) |
| Adds a new UIElement to the View More... | |
| void | AddToLookup (UIElement element) |
| Adds an element to the lookup table used by the view More... | |
Additional Inherited Members | |
| Properties inherited from MB2D.UI.UIView | |
| UIElement | this[string key] [get] |
| Gets the T:MB2D.UI.UIElement with the specified key. More... | |
| UIElement [,] | Content [get] |
| Gets the elements this View contains in a 2D array More... | |
| Texture2D | BackgroundTexture [get, set] |
| Gets or sets the background texture of the view. More... | |
| bool | StretchBackground [get, set] |
| Gets or sets a value indicating whether the background image shoudl stretch to fit the window. More... | |
HUD to show in the galaxy view.
|
inline |
Initializes a new instance of the T:MB2D.GalaxyHud class.
| content | Content to use in loading fonts and textures. |
|
inline |
Refreshed the HUD with the specified inventory values.
| inventory | Inventory to use to refresh the display. |


culture
star wars
politics
philosophy
news
bias
humor
fun
phd
writing
free speech
ISIS
science
personal development
wisdom
math
classical education
singularity
workflow
money
movies
feminism
conservatism
markdown
inklings
Trump
Star Wars
language
semantics
linguistics
prepositions
business
apologies
forgiveness
children
Classical education
yale
prophecy
the future
retrospective
facebook
liberal privilege
abductive reasoning
Jesus
Christianity
dissertations
Saint Constantine School
stipends
academia
YouTube
Socrates
Facebook
economics
essay
fear of death
human rights
Alasdair MacIntyre
books
Berkeley
SJWs
progressivism
cultural marxism
deification
theology
transhumanism
learning styles
fathers
babies
Overton window
epistemology
weird views
life updates
buhlers


Hi! I’m Prasanna.
A self-taught designer
Who believes in building
Impactful experiences through great UX
& designing visually-engaging
Market oriented digital products
My Work
Ola Cabs ( ANI Tech. Pvt. Ltd. )
Creating a lasting, positive impact on a billion lives. Building for the future, from India to the world, from Mobility to Money to Food and now to Electric Vehicles!


Montana Catalunya Marathon
Sant Llorenc de Savall ESP
Race Winners
(21 runnings)
29 Oct
2006
2005
21 Jul
2004
2003
2002
2001
2000
24 Oct
1999
1998
1997
1996
1995
Notes: 1995 was the inaugural year. The course is on mountain trails.
25 Oct
2015
3:28:12
Just Sociats Asensio-3
5:05:53
Mariona Jorda Rubio (ESP)
26
Oct
2014
3:39:47
Just Sociats Asensio-2
4:17:15
Laia Andreu Trias (ESP)
27
Oct
2013
3:53:09
Xevi Vidal Subinya (ESP)
3:47:22
Joan Salamana Maresma (ESP)
28
Oct
2012
3:42:05
Ahmed El Qayed-2
4:13:45
Ragna-Cathelijne Debats (ESP)
30 Oct
2011
3:35:19
Ahmed El Qayed (ESP)
4:46:46
Lola Brusau Alos (ESP)
31 Oct
2010
3:38:41
Just Sociats Asensio (ESP)
4:40:08
Joan Egea Burgueno (ESP)
25 Oct
2009
3:45:35
Aurelio-Antonio Olivar Roldan (ESP)
4:45:17
Monica Aguilar Viladomiu-2
26 Oct
2008
3:35:58
Xavier Aspina Martinez (ESP)
4:35:27
Monica Aguilar Viladomiu (ESP)
28 Oct
2007
3:32:26
Adolfo Aguilo Bort (ESP)
4:25:46
Theresa Munne Forn-2
3:25:45
Jose Lozano Garcia (ESP)
4:40:30
Theresa Munne Forn (ESP)
3:25:38
Javier Espina (ESP)
---
n/a
---
Xevi Guinvart (ESP)
---
n/a
3:00:14
nfn Aznar Navarro (ESP)
---
n/a
2:41:34
Benito Ojeda Sanz (ESP)
---
n/a
---
n/a
---
n/a
---
n/a
---
n/a
2:55:48
Eduard Alvarez (ESP)
3:30:48
Theresa Munne Forn (ESP)
2:51:45
A Albizua Uriarte (ESP)
---
n/a
---
n/a
---
n/a
---
n/a
---
n/a
---
n/a
---
n/a
Most Wins
(1995/date)
Men
3
Just Sociats Asensio (ESP)
2010,2014-15
Women
2
Theresa Munne Forn (ESP)
2006-07
Monica Aguilar Viladomiu (ESP)
2008-09
Prize Money
(ADR qualified runners)
No prize money has been awarded at this race.
Race Time Bias
(sec/km)
Insufficent information to calculat the race time bias.
Competitive Level
(1990-date)
Insufficent information to calculat the competitive level.
Quality Performances
Men
No man has run under 2:20
Women
No woman has run under 2:50
Last Updated on 29 Oct 2015
Contributor: Klaas Loonstra (40 points)


Site done by Radiolab
Audio software from Adobe that lets editors modify audio.
Voco has not been released...yet
source: @JohnLegum
source: buzzfeed
est. 1890s
source: Thinking Fast and Slow, Daniel Kahneman
Fast, automatic, intuitive.
☝Beliefs
Analytical, reasoning
It's hard to process information that differs from our beliefs
We are wired to have shallow knowledge
As people invented new tools for new ways of living, they simultaneously created new realms of ignorance; if everyone had insisted on, say, mastering the principles of metalworking before picking up a knife, the Bronze Age wouldn’t have amounted to much.
As a rule, strong feelings about issues do not emerge from deep understanding... but it deepens as more people believe this together
source: The Knowledge Illusion
source: Clay Johnson
[t]he Internet was done so well that most people think of it as a natural resource like the Pacific Ocean, rather than something that was man-made. When was the last time a technology with a scale like that was so error-free?
— Alan Kay
[the] API uses machine learning models to score the perceived impact a comment might have on a conversation.
source: perspectiveapi.com
Sponsoring more projects that tackle Fake News
source: knightfoundation.org
cecy.co/fake-news-psych


fetchers
A wrapper over Fetch API with semantic REST methods.
Contents
Quick example
import {Fetcher} from 'fetchers';
const fetcher = new Fetcher('http://example.com', {credentials: 'include'});
// GET
fetcher.get().then(response => ...);
// POST
fetcher.post(data).then(response => ...);
// PUT
fetcher.put(data).then(response => ...);
// DELETE
fetcher.delete().then(response => ...);
Features
The advantages over bare .fetch()
are following:
- Semantic REST methods:
get()
,post()
,put()
,delete()
,head()
andpatch()
- Convenient defaults for all methods:
- Default url and options
- Default request body handler, e.g.
JSON.stringify
- Default response handler, e.g.
response.json()
- Attaching different paths to base url, e.g.
http://example.com
+ (/get
,/post
, ...)
Requirements
The only requirement is global fetch()
.
All major browsers already support it,
for others you can use fetch polyfill.
In Node.js consider node-fetch package.
Installation
npm install fetchers --save
Usage
There are two classes:
Fetcher
- used for requests to constant urlPathFetcher
- used for requests to constant base url with different relative paths
The examples below are for Fetcher
but suitable for PathFetcher
as well.
1. Semantic REST requests
To perform GET, POST, PUT, DELETE, HEAD and PATCH there are corresponding methods:
import {Fetcher} from 'fetchers';
const fetcher = new Fetcher('http://example.com');
fetcher.get().then(...);
fetcher.post(body).then(...);
fetcher.put(body).then(...);
fetcher.delete().then(...);
fetcher.head().then(...);
fetcher.patch().then(...);
2. Default options and headers
You can set default options for every request from Fetcher
instance.
Example - include cookies in all requests and accept JSON:
const fetcher = new Fetcher('http://example.com', {
credentials: 'include',
headers: {
Accept: 'application/json'
}
});
fetcher.get();
fetcher.post(body);
Add custom options to particular request:
fetcher.post(body, {mode: 'cors'})
3. Handle request body
To apply some transformation to body of every request use handlers.handleRequestBody
.
Example - convert every request body to JSON:
const fetcher = new Fetcher('http://example.com', {}, {
handleRequestBody: body => JSON.stringify(body)
});
fetcher.post({foo: 'bar'});
4. Handle response
To apply some transformation to every response use handlers.handleResponse
.
Example - convert every response to JSON:
const fetcher = new Fetcher('http://example.com', {}, {
handleResponse: async response => await response.json()
});
fetcher.get().then(json => console.log(json));
Example - throw error in case of non 2xx
response:
const fetcher = new Fetcher('http://example.com', {}, {
handleResponse: async response => {
if (!response.ok) {
throw new Error(`${response.status} ${response.statusText} ${await response.text()}`);
}
return response;
}
});
5. Send requests to relative paths
PathFetcher
can send requests to different urls.
The first parameter in all methods is string - relative path attached to base url:
import {PathFetcher} from 'fetchers';
const fetcher = new PathFetcher('http://example.com');
// GET http://example.com/get
fetcher.get('/get').then(response => ...);
// POST to http://example.com/post
fetcher.post('/post', body).then(response => ...);
API
License
MIT @ Vitaliy Potapov


{% if altsite_url %}
The {{ scope }} search service is not currently responding or encountered a problem. Alternatively, you may wish to try your search in the
{{ altsite_label }}.
{% else %}
The {{ scope }} search service is not currently responding or encountered a problem. Please try your request again.
{% endif %}


Galactic Age Calculator
Galactic Age Calculator
Input your Information to output your age and life expectancy on other planets.
Earth
Third planet from our sun. Our home.
Mercury
First planet from our sun. Nice cool temperature of 801 degrees Fahrenheit.
Venus
Second planet from our sun. Our sister planet, mostly dead.
Mars
Fourth planet from our sun. Maybe Elon Musk will let us move here soon.
Jupiter
Fifth planet from our sun. Just a big ball of angry gas.
Naboo
A planet located in the Mid Rim of the Galaxy. Major galactic faction.
Kashyyk
A jungle world. Home of the Wookies.


public static interface UserDefinedFunction.Argument
| Modifier and Type | Method and Description |
|---|---|
Object |
evaluate(Evaluator evaluator)
Evaluates the argument.
|
Iterable |
evaluateIterable(Evaluator eval)
Evaluates the argument to an iterable over members or tuples.
|
List |
evaluateList(Evaluator eval)
Evaluates the argument to a list of members or tuples.
|
Object |
evaluateScalar(Evaluator evaluator)
Evaluates the argument as a scalar expression.
|
Type |
getType()
Returns the type of the argument.
|
Type getType()
Object evaluateScalar(Evaluator evaluator)
The effect is the same as
evaluate(mondrian.olap.Evaluator)
except if the argument
evaluates to a member or tuple. This method will set the context
to the member or tuple and evaluate the current measure, whereas
evaluate
would return the member or tuple.
The effect is similar to creating a calculated member in an MDX query:
WITH MEMBER [Measures].[Previous Period] AS
([Measures].[Unit Sales], [Time].[Time].PrevMember)
SELECT {[Measures].[Unit Sales],
[Measures].[Previous Period]} on 0,
[Time].[Time].Children on 1
FROM [Sales]
Note how [Measures].[Previous Period]
is defined as a
tuple, but evaluates to a number.
evaluator
- Evaluation contextObject evaluate(Evaluator evaluator)
If the argument is a set of members or tuples, this method may
return either a List
or an Iterable
. It is not safe
to blindly cast to List
. For guaranteed type, call
evaluateList(mondrian.olap.Evaluator)
or
evaluateIterable(mondrian.olap.Evaluator)
.
evaluator
- Evaluation contextList evaluateList(Evaluator eval)
eval
- Evaluation context


As explained in the last two posts, we need a termination checker to ensure that LiquidHaskell is not tricked by divergent, lazy computations into telling lies. Happily, it turns out that with very little retrofitting, and a bit of jiu jitsu, we can use refinements themselves to prove termination!

Looping Over Vectors
Lets write a bunch of little functions that operate on 1-dimensional vectors
54: type Val = Int 55: type Vec = Vector Val
Next, lets write a simple recursive function that loops over to add up
the first n
elements of a vector:
62: sum :: Vec -> Int -> Val 63: x1:(Data.Vector.Vector (GHC.Types.Int)) -> {VV : (GHC.Types.Int) | (VV >= 0) && (VV < (vlen x1))} -> (GHC.Types.Int)sum (Data.Vector.Vector (GHC.Types.Int))a 0 = x1:(GHC.Prim.Int#) -> {VV : (GHC.Types.Int) | (VV == (x1 : int))}0 64: sum a n = ({VV : (Data.Vector.Vector (GHC.Types.Int)) | (VV == a) && ((vlen VV) >= 0)}a x1:(Data.Vector.Vector (GHC.Types.Int)) -> {VV : (GHC.Types.Int) | (VV < (vlen x1)) && (0 <= VV)} -> (GHC.Types.Int)! ({VV : (GHC.Types.Int) | (VV >= 0) && (VV < (vlen a))}nx1:(GHC.Types.Int) -> x2:(GHC.Types.Int) -> {VV : (GHC.Types.Int) | (VV == (x1 - x2))}-{VV : (GHC.Types.Int) | (VV == (1 : int))}1)) x1:(GHC.Types.Int) -> x2:(GHC.Types.Int) -> {VV : (GHC.Types.Int) | (VV == (x1 + x2))}+ x1:(Data.Vector.Vector (GHC.Types.Int)) -> {VV : (GHC.Types.Int) | (VV >= 0) && (VV < (vlen x1))} -> (GHC.Types.Int)sum {VV : (Data.Vector.Vector (GHC.Types.Int)) | (VV == a) && ((vlen VV) >= 0)}a ({VV : (GHC.Types.Int) | (VV >= 0) && (VV < (vlen a))}nx1:(GHC.Types.Int) -> x2:(GHC.Types.Int) -> {VV : (GHC.Types.Int) | (VV == (x1 - x2))}-{VV : (GHC.Types.Int) | (VV == (1 : int))}1)
Proving Termination By Hand(waving)
Does sum
terminate?
First off, it is apparent that if we call sum
with a
negative n
then it will not terminate.
Thus, we should only call sum
with non-negative integers.
Fine, lets assume n
is non-negative. Why then does it terminate?
Intuitively,
If
n
is0
then it trivially returns with the value0
.If
n
is non-zero, then we recurse but with a strictly smallern
…… but ultimately hit
0
at which point it terminates.
Thus we can, somewhat more formally, prove termination by induction on n
.
Base Case n == 0
The function clearly terminates for the base case input of 0
.
Inductive Hypothesis Lets assume that sum
terminates on all 0 <= k < n
.
Inductive Step Prove that sum n
only recursively invokes sum
with values that
satisfy the inductive hypothesis and hence, which terminate.
This reasoning suffices to convince ourselves that sum i
terminates for
every natural number i
. That is, we have shown that sum
terminates
because a well-founded metric (i.e., the natural number i
) is decreasing
at each recursive call.
Proving Termination By Types
We can teach LiquidHaskell to prove termination by applying the same reasoning as above, by rephrasing it in terms of refinement types.
First, we specify that the input is restricted to the set of Nat
ural numbers
109: {-@ sum :: a:Vec -> {v:Nat | v < (vlen a)} -> Val @-}
where recall that Nat
is just the refinement type {v:Int | v >= 0}
.
Second, we typecheck the body of sum
under an environment that
restricts sum
to only be called on inputs less than n
, i.e. using
an environment:
a :: Vec
n :: Nat
sum :: Vec -> n':{v:Nat | v < n} -> Val
This ensures that any (recursive) call in the body only calls sum
with inputs smaller than the current parameter n
. Since its body
typechecks in this environment, i.e. sum
is called with n-1
which
is smaller than n
and, in this case, a Nat
, LiquidHaskell proves
that sum terminates for all n
.
For those keeping track at home, this is the technique of sized types, , expressed using refinements. Sized types themselves are an instance of the classical method of proving termination via well founded metrics that goes back, at least, to Turing.
Choosing the Correct Argument
The example above is quite straightforward, and you might well wonder if this method works well for ``real-world” programs. With a few generalizations and extensions, and by judiciously using the wealth of information captured in refinement types, the answer is an emphatic, yes!
Lets see one extension today.
We saw that liquidHaskell can happily check that some Natural number is decreasing
at each iteration, but it uses a naïve heuristic to choose which one – for
now, assume that it always chooses the first Int
parameter.
As you might imagine, this is quite simpleminded.
Consider, a tail-recursive implementation of sum
:
153: {-@ sum' :: a:Vec -> Val -> {v:Nat| v < (vlen a)} -> Val @-} 154: sum' :: Vec -> Val -> Int -> Val 155: x1:(Data.Vector.Vector (GHC.Types.Int)) -> (GHC.Types.Int) -> {VV : (GHC.Types.Int) | (VV >= 0) && (VV < (vlen x1))} -> (GHC.Types.Int)sum' (Data.Vector.Vector (GHC.Types.Int))a (GHC.Types.Int)acc 0 = {VV : (GHC.Types.Int) | (VV == acc)}acc x1:(GHC.Types.Int) -> x2:(GHC.Types.Int) -> {VV : (GHC.Types.Int) | (VV == (x1 + x2))}+ {VV : (Data.Vector.Vector (GHC.Types.Int)) | (VV == a) && ((vlen VV) >= 0)}ax1:(Data.Vector.Vector (GHC.Types.Int)) -> {VV : (GHC.Types.Int) | (VV < (vlen x1)) && (0 <= VV)} -> (GHC.Types.Int)!{VV : (GHC.Types.Int) | (VV == (0 : int))}0 156: sum' a acc n = x1:(Data.Vector.Vector (GHC.Types.Int)) -> (GHC.Types.Int) -> {VV : (GHC.Types.Int) | (VV >= 0) && (VV < (vlen x1))} -> (GHC.Types.Int)sum' {VV : (Data.Vector.Vector (GHC.Types.Int)) | (VV == a) && ((vlen VV) >= 0)}a ({VV : (GHC.Types.Int) | (VV == acc)}acc x1:(GHC.Types.Int) -> x2:(GHC.Types.Int) -> {VV : (GHC.Types.Int) | (VV == (x1 + x2))}+ {VV : (Data.Vector.Vector (GHC.Types.Int)) | (VV == a) && ((vlen VV) >= 0)}ax1:(Data.Vector.Vector (GHC.Types.Int)) -> {VV : (GHC.Types.Int) | (VV < (vlen x1)) && (0 <= VV)} -> (GHC.Types.Int)!{VV : (GHC.Types.Int) | (VV >= 0) && (VV < (vlen a))}n) ({VV : (GHC.Types.Int) | (VV >= 0) && (VV < (vlen a))}nx1:(GHC.Types.Int) -> x2:(GHC.Types.Int) -> {VV : (GHC.Types.Int) | (VV == (x1 - x2))}-{VV : (GHC.Types.Int) | (VV == (1 : int))}1)
Clearly, the proof fails as liquidHaskell wants to prove that the acc
umulator
is a Nat
ural number that decreases at each iteration, neither of which may be
true.
n
using a Decrease
annotation:
164: {-@ Decrease sum' 3 @-}
which directs liquidHaskell to verify that the third argument (i.e., n
) is decreasing.
With this hint, liquidHaskell will happily verify that sum'
is indeed a terminating function.
Thats all for now, next time we’ll see how the basic technique can be extended to a variety of real-world settings.


If you have entered your login/email correctly, an email with a link to reset your password has been sent to you. Please check your inbox and follow the link to reset your password.


Before Change
def _CheckImage(self):
Tries to get image, if found continues execution otherwise aborts.
cmd = os_utils.OpenStackCLICommand(self, "image", "show", self.image)
stdout, stderr, _ = cmd.Issue()
if stderr:
raise errors.Config.InvalidValue(" ".join(
("Image %s could not be found." % self.image,
"For valid image IDs/names run "openstack image list".",)))
def _CheckFlavor(self):
Tries to get flavor, if found continues execution otherwise aborts.
cmd = os_utils.OpenStackCLICommand(self, "flavor", "show",
self.machine_type)
After Change
def _CheckImage(self):
Tries to get image, if found continues execution otherwise aborts.
cmd = os_utils.OpenStackCLICommand(self, "image", "show", self.image)
msg = " ".join(
("Image %s could not be found." % self.image,
"For valid image IDs/names run "openstack image list".",))
self._IssueCommandCheck(cmd, msg)
def _CheckFlavor(self):
Tries to get flavor, if found continues execution otherwise aborts.
cmd = os_utils.OpenStackCLICommand(self, "flavor", "show",


Thank you for choosing The Skyliner. The Skyliner rewards program is a great way to get involved with us and earn benefits on the way. With continued flights with us under rewards you can earn sky miles. Every 4 miles you can earn a mile to use on flights. You will also be alerted upon the discount of flights that you might be interested in.


Relation Extraction
Automatic Knowledge Base Construction
Denis Savenkov
Emory NLP Group Meeting
February 9, 2015
"Scientia Potentia Est"
- Solving difficult problems requires a lot of knowledge
- Human spend a significant part of their life learning
- Computers need to have this knowledge as well!
Structured Information
- Most of the information in the world is unstructured:
- Unstructured information is hard to work with
- We need to add some structure...
Example: Question answering
Who was the PhD advisor of Prof. Jinho Choi?
What if we had a database with facts?
We could just query the database and get the answer:
Who was the PhD advisor of Prof. Jinho Choi?
SELECT advisor
FROM phd_advisors
WHERE student = "Jinho D. Choi"
From words to entities
Entities
- We may use different words to refer to the same thing
- Rafa, The King of Clay, Rafael Nadal
- Attributes of entities
- types: e.g. tennis player
- characteristics: e.g. height, weight, birth date
- Some entities are related
- [Tony Nadal] <coach> [Rafael Nadal]
Predicates
- Entities are related in different ways:
- [Tony Nadal] <coach-of> [Rafael Nadal]
- [Tony Nadal] <uncle-of> [Rafael Nadal]
- [Rafael Nadal] <parents> [Sebastián Nadal]
- [Rafael Nadal] <parents> [Ana María Parera]
- Entities with their relations constitute a knowledge base
- We can represent a knowledge base as a graph
Knowledge Base
Knowledge Graphs
* image from KDD'14 "Constructing and Mining Web-scale Knowledge Graphs" workshop slides
Some challenges
- Validation: knowledge graphs are not always correct
- Interface: how to make it easier to access the knowledge?
- Intelligence: how to create AI fom knowledge graphs?
- Growth: knowledge graphs are incomplete
- link prediction
- ontology matching
- knowledge extraction (this presentation)
from KDD 2014 Tutorial on Constructing and Mining Web-scale Knowledge Graphs, New York, August 24, 2014
Applications
Entity summarization
Applications
Question Answering
- 47M entities and 2.5B facts
- fully structured (entities and relations come from a fixed lexicon rather than free text)
- constructed by community members
- Built by MetaWeb and acquired by Google in 2010
- Data is publicly available
- Will be shut down in 2015 and data transitioned to WikiData
- Tuple: [/m/0jcx, /m/04m8, /m/019xz9] means Albert Einstein was born in Ulm
Incompleteness
71% of people in Freebase have no information on place of birth and 75% have no known nationality *
- Long-tail distribution: we know a lot about popular entities, but there is a heavy tail of less known entities
- How to increase coverage?
- Ask people: crowdsourcing
- Merge with other knowledge bases: ontology matching
- Extract from the available data
* from "Knowledge Vault : A Web-Scale Approach to Probabilistic Knowledge Fusion" by X.Dong et al. 2014
Wrapper Induction
"Wrapper Induction for Information Extraction" by N.Kushmerick et al. 1997
Tables on the web
- Relational data on the web is often represented as tables and it is possible to extract this data (e.g. [1])
[1] "WebTables: Exploring the Power of Tables on the Web", M.Cafarella et al. 2008
DeepWeb
- Large volumes of data is accessible only through HTML form interfaces
- We can automatically make queries and extract the hidden knowledge e.g. [1]
[1] "Web-Scale Extraction of Structured Data" by M.Cafarella et al. 2008
Relation extraction from text
[Emory College] was founded in [1836] in [Oxford, Georgia] by the [Methodist Episcopal Church].
- Focused extraction: need to find a particular attribute of a particular entity (slot-filling)
- Unfocused extraction: process text and extract everything we can
TREC KBA (knowledge base acceleration) http://trec-kba.org/
Focused extraction
"Knowledge Base Completion via Search-Based Question Answering" by B.West et al 2014 (WWW)
Relation extraction from NL
- Structured extractions (fixed entity/relations lexicon)
- Supervised relation extraction
- Semi-supervised relation extraction
- Distant supervision for relation extraction
- Open information extraction (entities and relations expressed in natural language)
Relation extraction from NL
- Today, computers can't understant natural language text
- How do we teach them to extract knowledge then?
- M.Hearst* proposed to extract hyponyms using simple patterns (Hearst patterns)
- Bruises, wounds, broken bones or other injuries...
- temples, treasuries,and other important civic buildings
- All common-law countries, including Canada and England...
- ...
* "Automatic Acquisition of Hyponyms from Large Text Corpora" by Marti Hearst, 1992
Supervised relation extraction
- Training dataset with sentence-level labels for each relation
- Emory College was founded in 1836 (+)
- Founded in 1836, Emory College ... (+)
- Emory College opened in 1838 (-)
- Datasets: ACE 2004 (Automatic Content Extraction), MUC-7 (Message Understanding Conference), BioNLP challenges
- Solves relation extraction as binary classification problem
- Research studied various features* and training methods
* "Combining Lexical, Syntactic, and Semantic Features with Maximum Entropy Models for Extracting Relations" by N.Kambhatla 2004
Features
- words between entities
- types of entities (person, location, organizaton, etc)
- # of words between entities
- path between entities in a parse tree
- ...
Kernel-based methods
Alternatively, one can define a kernel (think similarity measure) between text fragments and apply kernel-based ML method (e.g. SVM or anything else)
- Parse-tree kernels: similarity of parse trees of 2 text fragments
- Each node can have multiple attributes (word, POS, NER type, etc), which are than used to compute the kernel
- "A shortest path dependency kernel for relation extraction" by R. Bunescu & R. Mooney, 2005
- "Tree Kernel-based Relation Extraction with Context-Sensitive Structured Parse Tree Information" by GuoDong Zhou et al, 2007
Supervised relation extraction
- Cons:
- Expensive to obtain the data!
- Adding new relation requires labelling
- Pros:
- High quality training data
- Explicit negative examples
Semi-supervised relation extraction
- Reduce the amount of supervision required
- Examples: DIPRE, Snowball, KnowItAll
- Based on bootstrapping (iteratively improving the system)
From "Snowball: Extracting Relations from Large Plain-Text Collections" by E.Agichtein & L.Gravano, 2000
Semi-supervised relation extraction
- Pros:
- Less supervision required
- Can extract more knowledge triples thanks to bootstrapping
- Cons:
- Semantic drift: as we iterate the system extracts more and more incorrect patterns/triples
- Extending to new relations still requires seed data
Distant supervision
Utilize existing knowledge base to label data and train a model
Image from KDD 2014 Tutorial on Constructing and Mining Web-scale Knowledge Graphs, New York, August 24, 2014
Distant supervision assumptions
Assume we have a knowledge triple $(e_1, p, e_2)$
- All sentences that mentions $e_1$ and $e_2$ together expresses the predicate p
- At least one sentence that mentions $e_1$ and $e_2$ together expresses the predicate p (multi-instance setting)
- A sentence that mentions $e_1$ and $e_2$ together might express the predicate p and a pair of entities can be related with different predicates (multi-instance multi-label setting)
- "Distant supervision for relation extraction without labeled data" by M.Mintz et al 2009
- "Modeling Relations and Their Mentions without Labeled Text" by S.Riedel et al 2010
- "Multi-instance Multi-label Learning for Relation Extraction" by M.Surdeanu et al 2012
Distant supervision training
- Extract features for all sentences that mention a related pair of entities
- Randomly sample sentences with non-related entities as negative examples
- Train a multiclass classification model
Distant supervision
- Pros:
- Scalable!
- Can be applied in different languages
- Cons:
- Training data is noisy!
- No explicit negative examples
Open Information Extraction
- Introduced in [1]
- Extracts natural language triples from text:
- Apple announced a new iPhone 6. =>
(Apple, announced, iPhone 6)
- Extracts noun phrases as entities and verb phrases as predicates
- A trained classifier is used to predict whether an extraction is good
TextRunner [trained extractor] -> ReVerb [chunking] -> Ollie [dependency tree] -> OpenIE 4 (Srlie + RelNoun) [semantic roles]
[1]. "Open Information Extraction from the Web" by M.Banko et al. 2007
Open Information Extraction
- Pros:
- Even more scalable! ($O(N)$ vs $O(N|R|)$)
- Do not require any training data
- Cons:
- Lack of structure: need to cluster predicates
Link prediction
- Some knowledge can be inferred from already acquired knowledge
- [Kyle Korver] plays_for [Atlanta Hawks]
+ [Atlanta Hawks] league [NBA]
= Means that: [Kyle Korver] is [basketball player]
- "Random Walk Inference and Learning in A Large Scale Knowledge Base" by N.Lao et al, 2011
- "Logistic Tensor Factorization for Multi-Relational Data" by M.Nickel and B.Tresp, 2013
Never Ending Language Learning
"Toward an Architecture for Never-Ending Language Learning" by A. Carlson et al 2010
Google Knowledge Vault
"Knowledge Vault: A Web-Scale Approach to Probabilistic Knowledge Fusion" by X.Dong et al 2014
Google Knowledge Vault
from KDD 2014 Tutorial on Constructing and Mining Web-scale Knowledge Graphs, New York, August 24, 2014
Summary
- Computers need data structures
- Knowledge graphs can be used to structure knowledge: entities and relations (RDF graphs)
- Knowledge can be effectively acquired from unstructured data, e.g. natural language text


kevin.b.tu
Sample Text
swgreen
Sample Text
shrig94
Sample Text
daniel.l.mendelsohn
Sample Text
Test!
Test!
Test!


Provides an implementation of Regularized LS-TreeBoost & LAD-TreeBoost algorithm for Regulatory Network inference from any type of expression data (Microarray/RNA-seq etc). See Mall et al (2017) <doi:10.1101/132670>.
| Version: | 1.0-8 |
| Depends: | foreach, plyr, doParallel |
| Published: | 2018-01-09 |
| Author: | Raghvendra Mall [aut, cre], Khalid Kunji [aut], Melissa O'Neill [ctb] |
| Maintainer: | Raghvendra Mall <rmall at hbku.edu.qa> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| CRAN checks: | RGBM results |
| Reference manual: | RGBM.pdf |
| Package source: | RGBM_1.0-8.tar.gz |
| Windows binaries: | r-devel: RGBM_1.0-8.zip, r-release: RGBM_1.0-8.zip, r-oldrel: RGBM_1.0-8.zip |
| OS X binaries: | r-release: RGBM_1.0-8.tgz, r-oldrel: RGBM_1.0-8.tgz |
| Old sources: | RGBM archive |
Please use the canonical form https://CRAN.R-project.org/package=RGBM to link to this page.


MCSCF in Practice
Practical HCISCF Procedure
- Converge orbitals for a set of configurations
- Run final "tight" HCI calculation to get a more accurate energy
Important takeaways
- Orbitals converge with a "loose" \( \epsilon_1 \)
- PT correction doesn't improve orbitals
James E. T. Smith, BM, AAH, SS. JCTC.
(2017) Editor's Choice


You have stepped out of the circle of moonlight and into the deep woods.
You hear a howl in the distance.
You are somewhere you do not belong.
Return to the sanctuary of moonlight.
Wolfpack Alliance


TODO: The maintainer of this repo has not yet edited this file
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- Not sure? Fill out a SPOT intake as though the answer were "Yes". CSS will help you decide.
Then remove this first heading from this SUPPORT.MD file before publishing your repo.
Support
How to file issues and get help
This project uses GitHub Issues to track bugs and feature requests. Please search the existing issues before filing new issues to avoid duplicates. For new issues, file your bug or feature request as a new Issue.
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Support for this PROJECT or PRODUCT is limited to the resources listed above.


This dialog window appears after clicking the Create shared keys button from within the Diffie-Hellman Demonstration.
You can create the shared keys of Alice and Bob after a click on the OK button.
You can only create a party‚s shared key if you already defined a party‚s secret!
This circumstance can easily be understood if you take a look at the following equation which defines a party‚s shared key:
A = gamod p
Bob‚s shared key is computed analogically, but you have to raise to the power with the secret of Bob (b) instead of Alice‚s secret (a).
The equation clarifies that a party‚s secret is indispensable for the computation of the shared key.
For that reason, it is possible that you can only compute one of the two shared keys! In this case, please correct your input and add the missing secret number.


Hello,
My Name is Melese Kefyalew
CSE student
From Adama
My Name is Melese Kefyalew ,I am 22 year old and I live in Adama City ,I am interested in compute Science and Sport,Computer Science is first Appeared in Mylife. Then I had got my first PC .At first I was Just playing game,butsome time later,I noticed tha I could do a lot more things with the computer,for example programmig,I hope that in the future I will get a job as a computer science
My skill is create static page website and web development
MY future plan is develop webisite for different company
I think for the future graph design by website
website is very important for digital marketing so i have create website for marketing
I work above project


Things True about girls that they never want to talk about
By colline
10 Things you should never do in your marriage
By Naera clare
To achieve great things, avoid these seven toxic habits
By Christopher lumbert
You aint lazy, your over stimulated
By Jimm Adams
How to always get on top of your game with coding
By James kit mars
Things we miss out in Town
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7 coding tips you should never miss out
By Christopher Robins
How to be there for each other as a familly
By Ssentongo cyprian
Why Ugandans beat Kenyans in Fashion
By Pasha Nata
The right estates you wanna invest your money so bad
By Kawuki Christopher


ActivityPub Twitter Adapter
Basically parsing twitter.com and making ActivityPub resources out of it,
so you can boost them from Mastodon.
It does not post any tweet or toot anywhere or let you follow anyone;
it's more of a better way to replace the previous quote-retweets made on Mastodon.
It's using the same URL paths, so you can just replace twitter.com by {{.Domain}} and put it into your Mastodon search box.
{{if .Config.Motd}}Server: {{.Config.Motd}}
{{end}}Server Information
| Population: | {{.Stats.DbTweets}} tweets from {{.Stats.DbAccounts}} users |
| DB/users: | ttl={{.Config.AccountCacheTtl}} h/m={{.Stats.DbAccountHitRatio}} |
| DB/tweets: | ttl={{.Config.TweetCacheTtl}} h/m={{.Stats.DbTweetHitRatio}} |
| Uptime: | {{.Stats.Uptime}} ({{.Stats.StartTime | fdate}}) |


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শহুরে মানুষের হাতে সময় কম। দিন থেকে রাত ব্যস্ততার মধ্যে ....
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leptospirosis incidence meteorological OpenUrl weekly PMID: rainfall CrossRef Salvador, time cases urban Brazil model study associated seasonal series temperature risk tropical Central Oswaldo PMCID: Search data humidity site (panel Instituto Reis disease diseases. period Leptospira neglected observed relative Cruz, Fundação Ministério PMC. Saúde, factors transmission Costa Ribeiro rainfall, trend used ./journal.pntd. Epidemiology Gonçalo Leptospirosis Moniz, Pesquisas View fitted incidence. lag models suspected variables weeks New Salvador Science Web average credible population temporal variation Abstract Biology Brazil, WOS:. dynamic effects extreme human identified increased solid transformed using Bayesian Figure Health, Santos Wunder Yale case clinical environment expected hospital included leptospirosis, leptospirosis. maximum mean residual values (black Carvalho Department Diseases, Download Heaven, Med Microbial Public School Text USA University, clinically higher increase intervals lagged lags million onset previous relationship showed slum surveillance survival years Brazilian Diggle FREE Federico Gouveia Guilherme Rio Urban account accumulated analysis association blood change climatic daily developing drivers environmental events flooding generalized health important infection infectious laboratory long-term obtained outbreak short short-term state (grey ./S-()- AI, Adriano Albert Andreia Bahia, Brazil. Cunha Edilane Elsio Federal Fig. Hagan However, Jr. Júnior Lancaster, Lauren MAT Manila Marcelo Marília Mitermayer Nivison ORCID Peter Pischel Queiroz Rainfall Renato Saúde Slum Statistical Study Table Text). Trop Universidade West acute associations city compared confirmed considered cumulative days deaths decrease events. findings forecasts high incidence, including increasing interaction interrogans line) line), linear lower measures number one-week related results sample severe similar studies temperatures trends two-week variable variables, variables. variations week work


Report: Arkansas Coaching Candidate Is More Interested In Florida State
by Chris RosvoglouWhile there are a plethora of programs focusing on the remaining games on their schedule, Arkansas’ football program is conducting its coaching search for next season.
Arkansas fired Chad Morris before he could finish his season year as the head coach. He finished with an abysmal with a 4-18 record.
The Razorbacks reportedly have their eyes on Memphis head coach Mike Norvell, but they won’t be the only Power Five program with interest.
Norvell has already met with Arkansas for its job opening. However, the 38-year-old apparently is more intrigued by the opening at Florida State.
From FootballScoop.com:
Sources tell FootballScoop that Arkansas has met with Memphis head coach Mike Norvell. At this time Norvell is said to be more interested in the opening at Florida State than Arkansas; however we wouldn’t rule Norvell out of this one just yet.
Memphis is currently enjoying another strong season under Norvell as the team owns a 9-1 record.
Norvell has led the program to 35 wins over the past four season. He’s one of the brightest offensive minds in college football, so it’s not too surprising that he’s a hot commodity on the coaching market.
The Seminoles, meanwhile, have also been linked to another big-name.
Leaving Memphis for Arkansas or Florida State would be quite the promotion for Norvell, but his resume warrants it.


CHICKEN is a compiler for the Scheme programming language.
CHICKEN produces portable, efficient C, supports almost all of the
R5RS
Scheme language standard, and includes many enhancements and
extensions. CHICKEN runs on Linux, MacOS X, Windows, and many Unix flavours.
FEATURES
- Includes a full-featured interactive interpreter as well as an optimizing batch compiler
- Usable for interpreted scripts or compiled standalone executables with either dynamic or static linkage
- Full support for tail recursion, first-class continuations and hygienic macros
- Highly portable and known to run on many platforms, including x86,
x86-64, IA-64, PowerPC, SPARC and UltraSPARC, Alpha, MIPS, ARM and
S/390
- Distributed free for use and modification under the terms of the BSD License
- Transparent support for dynamically loadable compiled code and linkage to C
- An easy to use foreign function interface for accessing C and C++ libraries from Scheme code
- Lightweight user-level threads based on first-class continuations
- Provides high- and low-level hygienic macros, including syntax-rules
- Includes a powerful module system that integrates hygienic macros and separate compilation
- Execution profiling, debugging, backtrace and single-stepping support
- A POSIX interface that covers environment and filesystem access,
pipes, processes, signals, locks, sockets, and low-level and
memory-mapped I/O
- Perl compatible regular expressions, including support for SRE syntax (Structured Regular Expressions)
- Support for interpreted or compiled shell scripts under Unix and Windows
- Support for a large number of Scheme Requests For Implementation (SRFIs)
- Many libraries and extensions are available
at "Eggs Unlimited"
DOWNLOAD
Get the tarball for the most recent release (4.0.0) here:
chicken-4.0.0.tar.gz
DOCUMENTATION
Browse the User's manual at the CHICKEN
wiki
MAILING LIST
The CHICKEN Users
mailing list is a medium-volume but fast-response list for discussing all
things related to CHICKEN. You can send a message to the list by addressing
it to<EMAIL_ADDRESS>If you are interested in the development of CHICKEN,
check out
CHICKEN Hackers.
DEVELOPMENT
The current CHICKEN development version can be accessed through the
Subversion revision control system, like this:
$ svn co https://galinha.ucpel.tche.br/svn/chicken-eggs/chicken/trunk
(username:
anonymous, password: <none>)
The CHICKEN bug tracking system is located here.
CONTACT
If you have any questions, suggestions or insults regarding CHICKEN,
don't hesitate to join the chicken-users mailing list. Bug reports
should be directed to<EMAIL_ADDRESS>preferrably using the chicken-bug(1) tool.


Message In a Bottle (1999)
Warner Brothers; rated PG-13 (mild violence, sexual situations); 132 minutes
Director: Luis Mandoki
Screenplay: Gerald Di Pego (from the novel by Nicholas Sparks)
Cast: Kevin Costner, Robin Wright-Penn, Paul Newman, Illeana Douglas, Robbie Coltrane, Jesse James, John Savage.
Review By: Geoff Berkshire
Star Rating: * (out of ****)
I'm not an overly cynical guy. There have been many glossy Hollywood romances that have carried me away with their romanticism over the years. However, I have my limits and I also have standards. This brings us to the subject at hand: Message In a Bottle, the big ticket romance that Warner Brothers' unleashed upon the movie going public just in time for Valentine's Day.
The story, what little of it that there is, involves boring Chicago Tribune reporter Theresa Osborne (Robin Wright-Penn) dealing with her recent divorce and trying to raise her young son Jason (Jesse James). During a brief stay somewhere in New England she finds the titular message in a bottle while on a morning run by the ocean. The letter, written to a mystery woman named Catherine, instantly captivates her. Upon her return, Theresa shares it with her best friend Lina (Illeana Douglas), her boss Charlie (Robbie Coltrane), and the entire city of Chicago (the newspaper publishes an article about it).
It turns out that the message was written by grieving widower Garret Blake (Kevin Costner) and so Theresa travels to North Carolina and tracks him down. He turns out to have a colorful father (Paul Newman) but is otherwise perfectly dull and overly obsessed with sailing. This is somehow attractive to Theresa and the two begin their awkward courtship. Of course she doesn't tell him that she found his letter, she wants to but the rules of this type of film require him to find out later (preferably right after they first make love). This way Garret can get very angry and the relationship can be threatened.
The discovery of the message and Garret's discovery that Theresa discovered the message are really the only two noteworthy events that happen during the nearly two and a quarter hour running time of this film.  A fun way to pass the time is to take bets on exactly who will die, although it becomes pretty clear by the second reel. The actual death sequence is one of the most ridiculously forced, and unintentionally humorous, sequences filmed since... well, since Costner's The Postman (1997).
Message In a Bottle is one slow moving film. Last year audiences were offered endurance tests such as The Horse Whisperer and Meet Joe Black but both of those films resemble Jerry Bruckheimer productions next to this. They also had redeeming qualities in the form of quality performances and some stand out technical work.
Message In a Bottle has a decent enough cast but they're fighting the material all the way, and losing badly. Costner and, especially, Wright-Penn are both likable and attractive enough to cheer for but their characters are simply too boring. They also fail to generate any kind of real romantic chemistry.
The supporting players are given very little to do. The reliable Douglas is particularly wasted.  A confrontational scene he has with Costner near the end is especially well played. However, too frequently he just reminds us how unexciting our lead characters are.
The film is very polished on the technical side to be sure but it only works to undercut the story. Gabriel Yared, who previously set the romantic moods of The English Patient (1996) and City of Angels (1998) with his scores, overdoes it a bit here. Caleb Deschanel's camera makes everything look a little too beautiful. Do the offices of the Chicago Tribune really need to look heavenly? The editing by Steven Weisberg is troubling not only considering all that could have been cut out but is also simply messy at times.
The real offender here is screenwriter Gerald Di Pego. Working from a best- selling novel by Nicholas Sparks (which I have not read but have been told is on the same literary level as The Bridges of Madison County), Di Pego creates one of the most uninspired scripts of recent times. Its strict adherence to clichés brings to mind such disasters as I Still Know What You Did Last Summer (1998). There simply isn't an original scene in this film. The dialogue is rarely better than laughable and this is only accentuated by the excessively long pauses every character takes while speaking.
This is director Mandoki's first film since When a Man Loves a Woman (1994), the solid Meg Ryan/Andy Garcia romance. He's simply going through the motions with this.
Message In a Bottle is easily the worst of the several romantic offerings available in theaters at the moment and vies with What Dreams May Come (1998) as one of the most misguided romances of the decade.
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.
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The formatting of the review is likely to differ from the original due
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Related links: index of all rec.arts.movies.reviews reviews


Games
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Learning Personal Finance through a Space Shooter Game Teaching finance through an engaging space shooter game. Team: Sydney Andreasen, Carly Cameron, Ashley Colwell, CJ Jurgens Mentor: Brian Ricks |
Gambling Odds Simulator Experiencing the long odds of winning a lottery. Team: William Heller, Logan Romanus, Ben Sachs Mentor: Brian Ricks |
|
Remote Controlled Pong A game to demonstrate remote game control from mobile device. Team: Jean Paulsen, AJ Whiting, Travis Wisecup Mentor: Brian Ricks |
Touchless Interactive Game A game to illustrate possibilities for touchless interaction by simulating the funhouse mirror experience. Team: Dillon Damme, Chen Su, Joseph Wright Mentor: Brian Ricks |
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Xplor Mobile Treasure Hunt Game A treasure hunting game inspired by Pokemon Go, to be used for interacting with local businesses and community members. Team: Derek Day, Dan Hoang, Jarrett Loughry, Natie Selenke, Liam Tinsley |
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Prairie STEM SimBot Virtual Reality Experience Integrating virtual reality to Prairie STEM's SimBot. Team: Alfred Balanay, Erik Anderson, Ethan Casey, Joseph Keenan |
CryptoTutor (Q&A Forum) A Q&A recommender system to guide students in making the correct API calls to Java cryptography library. Team: Tyler Bauer, Daniel Brinkman, Zoe Larson, David Lentsch Mentor: Myoungkyu Song |
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Agro-AI Education Platform Gamified experience for learning about AI in an agricultural context. Team: Daniel Bresnahan, Minwook Chae, Gabe Drew, Max Hobday |
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Supporting Businesses and Nonprofits
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Dragon's Lair Comics Inventory and Pull List System An information system to support a comic book store, enabling easy flagging of new releases for subscribers. Team: Yahya Al-Kindi, Kevin McEnhill, Jack Reefe, Logan Wood |
WeCare Insurance Lender Platform An insurance customer management system for auto lenders, in collaboration with WeCare Insurance. Team: Zekun Gao, Xiaobiao Billy Luo, Zilong Wang |
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BuilderTrend Document Text Extraction and Search A project with BuilderTrend for indexing and searching information extracted from documents and images. Interfaces with ElasticSearch. Team: Pajie Bimpolo, Jacob Kirshenbaum, Kyle Maynard, Edward Niemann |
Optimized Meal Delivery System for Intercultural Senior Center Calculates optimal routes for delivering meals to senior citizens. Team: Nick Cox, Joel McMaken, William Palmer, Jacob Peterson |
Supporting UNO Operations
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Academic Assessment Smart Assistant Supporting the review of degree program assessment reports through generating stats and providing smart guidance for report feedback. Team: Dylan Keefer, Kennedy Kersten, Louis Nodskov, Patrik Oliveira, Connon Peterson |
PKI Classroom Scheduler An application to support educational timetabling by assigning rooms to classes in PKI. Team: Ghaday Altayyar, Tariro Nangati |


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Intro to JavaScript
With Candy Box
with J3RN
JavaScript Basic Types
- Numbers
- Strings
- Booleans
- Null and Undefined
JavaScript Complex Types
- Object
- Array
- Function!?!?1/1/1/1
What does this have to do with CANDIES!?!?1/1/1/
Patience
Let's make some candies!
`setInterval`
Using Objects effectively


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