|
MicrOS
1.1
This is a small micro kernel operating system for embedded systems
|
Flexible Static Memory Controller Bank2. More...
#include <stm32f407xx.h>
Public Attributes | |
| __IO uint32_t | PCR2 |
| __IO uint32_t | SR2 |
| __IO uint32_t | PMEM2 |
| __IO uint32_t | PATT2 |
| uint32_t | RESERVED0 |
| __IO uint32_t | ECCR2 |
| uint32_t | RESERVED1 |
| uint32_t | RESERVED2 |
| __IO uint32_t | PCR3 |
| __IO uint32_t | SR3 |
| __IO uint32_t | PMEM3 |
| __IO uint32_t | PATT3 |
| uint32_t | RESERVED3 |
| __IO uint32_t | ECCR3 |
Flexible Static Memory Controller Bank2.
| __IO uint32_t FSMC_Bank2_3_TypeDef::ECCR2 |
NAND Flash ECC result registers 2, Address offset: 0x74
| __IO uint32_t FSMC_Bank2_3_TypeDef::ECCR3 |
NAND Flash ECC result registers 3, Address offset: 0x94
| __IO uint32_t FSMC_Bank2_3_TypeDef::PATT2 |
NAND Flash Attribute memory space timing register 2, Address offset: 0x6C
| __IO uint32_t FSMC_Bank2_3_TypeDef::PATT3 |
NAND Flash Attribute memory space timing register 3, Address offset: 0x8C
| __IO uint32_t FSMC_Bank2_3_TypeDef::PCR2 |
NAND Flash control register 2, Address offset: 0x60
| __IO uint32_t FSMC_Bank2_3_TypeDef::PCR3 |
NAND Flash control register 3, Address offset: 0x80
| __IO uint32_t FSMC_Bank2_3_TypeDef::PMEM2 |
NAND Flash Common memory space timing register 2, Address offset: 0x68
| __IO uint32_t FSMC_Bank2_3_TypeDef::PMEM3 |
NAND Flash Common memory space timing register 3, Address offset: 0x88
| uint32_t FSMC_Bank2_3_TypeDef::RESERVED0 |
Reserved, 0x70
| uint32_t FSMC_Bank2_3_TypeDef::RESERVED1 |
Reserved, 0x78
| uint32_t FSMC_Bank2_3_TypeDef::RESERVED2 |
Reserved, 0x7C
| uint32_t FSMC_Bank2_3_TypeDef::RESERVED3 |
Reserved, 0x90
| __IO uint32_t FSMC_Bank2_3_TypeDef::SR2 |
NAND Flash FIFO status and interrupt register 2, Address offset: 0x64
| __IO uint32_t FSMC_Bank2_3_TypeDef::SR3 |
NAND Flash FIFO status and interrupt register 3, Address offset: 0x84


Outputs a Summary
protocol buffer with audio.
tf.compat.v1.summary.audio( name, tensor, sample_rate, max_outputs=3, collections=None, family=None )
The summary has up to max_outputs
summary values containing audio. The
audio is built from tensor
which must be 3-D with shape [batch_size,
frames, channels]
or 2-D with shape [batch_size, frames]
. The values are
assumed to be in the range of [-1.0, 1.0]
with a sample rate of
sample_rate
.
The tag
in the outputted Summary.Value protobufs is generated based on the
name, with a suffix depending on the max_outputs setting:
max_outputs
is 1, the summary value tag is 'name/audio'.max_outputs
is greater than 1, the summary value tags are
generated sequentially as 'name/audio/0', 'name/audio/1', etcname
: A name for the generated node. Will also serve as a series name in
TensorBoard.tensor
: A 3-D float32
Tensor
of shape [batch_size, frames, channels]
or a 2-D float32
Tensor
of shape [batch_size, frames]
.sample_rate
: A Scalar float32
Tensor
indicating the sample rate of the
signal in hertz.max_outputs
: Max number of batch elements to generate audio for.collections
: Optional list of ops.GraphKeys. The collections to add the
summary to. Defaults to [_ops.GraphKeys.SUMMARIES]family
: Optional; if provided, used as the prefix of the summary tag name,
which controls the tab name used for display on Tensorboard.A scalar Tensor
of type string
. The serialized Summary
protocol
buffer.


Your cart
| Booking | Date | Price | Number | Total |
|---|---|---|---|---|
Grand Plaza Serviced Apartments
|
Fri, Apr 10toFri, Apr 17
Fri, Apr 10toFri, Apr 17
|
$345/night
$345/night
|
1 room
1 room
|
$345 |
Departure to New York
American Airlines
08:35 AMBKK 08:35 AMBKK |
Fri, Apr 10 | $215 |
1 person
|
$300 |
Return to Hanoi
American Airlines
08:35 AMBKK 08:35 AMBKK |
Fri, Apr 10 | $215 |
1 person
|
|
Economy 2/4Door CarChevy Aveo or similar
|
Fri, Apr 10toFri, Apr 17 | $215 |
1 car
|
$300 |
Tokyo to New York
American Airlines
08:35 AMBKK 08:35 AMBKK |
Fri, Apr 10 | $215 |
1 person
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$300 |
Grand Plaza Serviced Apartments
|
Fri, Apr 10toFri, Apr 17 | $345/night |
1 person
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$345 |
7-night Caribbean Cruise
|
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Berlin & Prague plus Vienna
|
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$345 |
| $345 |


{% extends 'base.html' %} {% block title %}Flight Information{% endblock title %} {% block body %}
| Flight Id. | Flight No. | Airline | No. of seats | Departure | Destination | Departure Time | Arrival Time | {{ flight.flight_no}} | {{ flight.flight_id}} | {{ flight.airline_name}} | {{ flight.no_of_seats }} | ({{ flight.source_code}}) {{ flight.source}} | ({{ flight.destination_code}}) {{ flight.destination}} | {{ flight.departure_time}} | {{ flight.arrival_time}} | {% if flight.no_of_seats > 0 %} Book Now! {% else %} {% endif %} | {% endfor %}
|---|


Once you have built TESLA, you need to either install it to your PATH or else set two environment variables:
The TESLA workflow deviates from a more typical LLVM-based workflow in that it adds two steps:
This overall workflow is pictured below:
On this page, we apply this workflow to a simple example: two C files
foo.c
and bar.c
that are compiled into a binary:
In the analysis stage, TESLA is used to parse temporal assertions defined by
the programmer as described in
Programming with TESLA.
To analyse source files foo.c and bar.c that require
CFLAGS="-Wno-error -D VERSION=42"
, the programmer
(or the build system) should run the following commands:
The TESLA analyser needs to know the appropriate CFLAGS because it is running a full Clang parser on the C code, and errors, warnings, condititional compilation, etc. need to be consistent with those options used by Clang when compiling the source into LLVM IR.
The LLVM instrumenter modifies LLVM IR, adding hooks for events that are named in a TESLA manifest. If once again CFLAGS="-Wno-error -D VERSION=42", the TESLA instrumenter is run as follows:
Calls to instrumentation are inserted inline within LLVM basic blocks:
@@ -108,7 +202,9 @@
%3 = bitcast i8* %2 to i32*, !dbg !62
%4 = load i32* %3, align 4, !dbg !62
%add = add nsw i32 %4, 1, !dbg !62
+ call void @__tesla_instrumentation_struct_field_store_struct.object.refcount(%struct.object* %0, i3
2 %add, i32* %3), !dbg !62
store i32 %add, i32* %3, align 4, !dbg !62
+ call void @__tesla_instrumentation_callee_return_hold(%struct.object* %o)
ret void, !dbg !63
}
These language-level events are translated by machine-generated instrumentation into symbols that can be consumed by TESLA automata:
define void @__tesla_instrumentation_callee_enter_hold(%struct.object*) {
preamble:
%1 = call i32 (...)* @tesla_debugging([13 x i8]* @debug_name)
%2 = icmp ne i32 %1, 0
br i1 %2, label %printf, label %entry
printf: ; preds = %preamble
%3 = call i32 (i8*, ...)* @printf(i8* getelementptr inbounds ([20 x i8]* @8, i32 0, i32 0), %struct
.object* %0)
br label %entry
entry: ; preds = %printf, %preamble
br label %"example.c:51#2:instr"
"example.c:51#2:instr": ; preds = %entry
%key = alloca %tesla_key+ %4 = ptrtoint %struct.object* %0 to i64+
%5 = getelementptr inbounds %tesla_key* %key, i32 0, i32 0+ store i64 %4, i64* %5+
%6 = getelementptr inbounds %tesla_key* %key, i32 0, i32 4+ store i32 1, i32* %6+
%7 = call i32 @tesla_update_state(i32 1, i32 6, %tesla_key* %key, i8* getelementptr inbounds ([15 x i8]* @10, i32 0, i32 0), i8* getelementptr inbounds ([328 x i8]* @11, i32 0, i32 0), %tesla_transitions* @transitions4)
%8 = icmp eq i32 %7, 0
br i1 %8, label %"example.c:85#8:instr", label %die
"example.c:85#8:instr": ; preds = %"example.c:51#2:instr"
%key1 = alloca %tesla_key
%9 = ptrtoint %struct.object* %0 to i64
%10 = getelementptr inbounds %tesla_key* %key1, i32 0, i32 0
store i64 %9, i64* %10
%11 = getelementptr inbounds %tesla_key* %key1, i32 0, i32 4
store i32 1, i32* %11
%12 = call i32 @tesla_update_state(i32 1, i32 12, %tesla_key* %key1, i8* getelementptr inbounds ([1
5 x i8]* @42, i32 0, i32 0), i8* getelementptr inbounds ([684 x i8]* @43, i32 0, i32 0), %tesla_transi
tions* @transitions24)
%13 = icmp eq i32 %12, 0
br i1 %13, label %exit, label %die
exit: ; preds = %"example.c:85#8:instr"
ret void
die: ; preds = %"example.c:85#8:instr", %"example.c:51#2
:instr"
call void @tesla_die(i8* getelementptr inbounds ([42 x i8]* @9, i32 0, i32 0))
ret void
}
These instrumentated .ll files can be linked together into the final binary
(or shared library) using Clang.
The result must be linked against libtesla, which provides the
tesla_update_state()
function.


Supplies a set of functions to interface with General Bikeshare Feed Specification .json feeds in R, allowing users to save and accumulate tidy .rds datasets for specified cities/bikeshare programs.
| Version: | 1.1.0 |
| Imports: | dplyr, readr, stringr, jsonlite, lubridate |
| Suggests: | knitr, rmarkdown |
| Published: | 2018-09-21 |
| Author: | Kaelyn Rosenberg [aut], Simon P. Couch [aut, cre], Mark Padgham [ctb] |
| Maintainer: | Simon P. Couch <simonpatrickcouch at gmail.com> |
| BugReports: | https://github.com/ds-civic-data/gbfs/issues |
| License: | CC0 |
| URL: | https://github.com/ds-civic-data/gbfs |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | gbfs results |
| Reference manual: | gbfs.pdf |
| Package source: | gbfs_1.1.0.tar.gz |
| Windows binaries: | r-devel: gbfs_1.1.0.zip, r-release: gbfs_1.1.0.zip, r-oldrel: gbfs_1.1.0.zip |
| OS X binaries: | r-release: gbfs_1.1.0.tgz, r-oldrel: gbfs_1.1.0.tgz |
| Old sources: | gbfs archive |
Please use the canonical form https://CRAN.R-project.org/package=gbfs to link to this page.


| This inspection reports any instances of JavaScript comma expressions. Comma expressions are often a sign of overly clever code, and may lead to subtle bugs. Comma expressions in the initializer or update section of a for loop are ignored by this inspection. |
| Powered by InspectionJS |


THE HAUNTING OF HILL HOUSE
Reviewed by Harvey Karten, Ph.D. DreamWorks Pictures Director: Jan De Bont Writer: David Self, book by Shirley Jackson Cast: Liam Neeson, Lili Taylor, Catherine Zeta-Jones, Owen Wilson
Based on its trailers, "The Haunting" comes across as an antidote to "The Blair Witch Project," but here's a case in which the corrective is worse than the venom. Whereas the highly overrrated "Blair" flaunts its forbearance of special effects, tightly-written dialogue, and big-name performers, "The Haunting" resembles a glorified ride through a Coney Island spook ride as Donald Trump would have constructed it. If "The Blair Witch Project" suffers from a kind of reverse pretension--claiming a blessing from its avoidance of fancy pyrotechnics and seeking the most naturalistic adventure possible in a horror movie--"The Haunting" goes to the opposite extreme. Director Jan de Bont, known for the razzle he put into the exciting movie "Speed" and the subsequent dud "Twister," proves himself unable to break away from depending on dazzle to substitute for substance. Based on Shirley Jackson's novel "The Haunting of Hill House," which mercifully leaves the terror to the reader's imagination, the Dreamworks release relies almost completely on kitschy imagery, vapid dialogue, and an all-too-literal replica of purgatory to stimulate the fancy of moviegoers that still retain an smidgen of imagination in an age of visual overload.
The only scary part of the movie occurs at the very beginning as Eleanor (Lili Taylor) is told by her sister that she is to be dispossesed of her home per her deceased mother's will. Having no family, no friends, and now no place to live, the mousy Nell becomes desperate, grasping eagerly at a newspaper ad calling for volunteers for research that could help insomniacs like her. Unknown to her, Dr. David Marrow (Liam Neeson), who is conducting the inquiry, is more interested in exploring the nature of fear and has set up his experiment in a spacious gothic mansion that had existed somewhere in New England since 1837. Conveniently, the estate is unoccupied, looked after by a caretaker (Bruce Dern) and his wife (Marian Seldes), neither of whom ventures near the place after dark. In fact the caretaker locks the gate securely when he leaves each evening.
At the house, Nell meets Dr. Jeffrey Marrow and two other subjects for the experiment, Theo (Catherine Zeta-Jones) and Luke (Owen Wilson)--both cockier and more confident than she. As things begin to creak and groan and move and moan in the night, Nell starts to lose it and is comforted by her fellow subjects and the doctor. Not long after that, though, all who occupy the house are convinced that it is haunted.
As the performers strut and cower about the house, the corridors resound with ominous noises. Doors close suddenly and loudly, ghostly children crawl inside the sheets and float about the rooms, and ultimately an enormous painting of the home's diabolic owner comes to life like a Dickensian ghost of Christmas-Yet-To-Come, challenging little Nell in a conclusive duel to the death.
Lily Taylor comes off surprisingly well. Once known as the queen of the indies for her role in small, creative movies like "I Shot Andy Warhol," she takes on a role in a big budget movie and does what she can with as the only character with any development. By contrast the sensuous Catherine Zeta- Jones and the current cover-man of TimeOutNY magazine, Owen Wilson as the third subject of the experiment, Luke, have little to do but become wide-eyed as the mansion takes on a life of its own. Ms. Zeta-Jones hints at the bisexuality of her character, but nothing comes of this.
Despite the unintentionally comic moves made by the torsoes and heads of the figures that inhabit the walls and floors of the incredible Hill House, the movie will perhaps be nominated for an academy award for its production design, which Eugenia Zenetti ("What Dreams May Come") has created with an inspiration from the Harlaxton and Belvoir Castle in Leicestershire, England. The outside is not a set but the Harlaxton Manor in England's Nottinghamshire, a building now used as a foreign campus of Indiana's University of Evansville.
Though I have not read Ms. Jackson's story, I am a fan of her scariest, most allegorical tale, "The Lottery," about a group of rural townspeople who hold a drawing each year to determine which resident gets stoned to death. The little movie that came out of that novella remained true to the book's creative dialogue, hence retaining the fright and resonance of the printed page. "The Haunting," by contrast, stands as yet another fragment of evidence that more is often less.
Rated PG-13. Running Time: 117 minutes. (C) 1999 Harvey Karten
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Apache Hadoop 3.0.1 incorporates a number of significant enhancements over the previous major release line (hadoop-2.x).
This release is generally available (GA), meaning that it represents a point of API stability and quality that we consider production-ready.
Users are encouraged to read the full set of release notes. This page provides an overview of the major changes.
All Hadoop JARs are now compiled targeting a runtime version of Java 8. Users still using Java 7 or below must upgrade to Java 8.
Erasure coding is a method for durably storing data with significant space savings compared to replication. Standard encodings like Reed-Solomon (10,4) have a 1.4x space overhead, compared to the 3x overhead of standard HDFS replication.
Since erasure coding imposes additional overhead during reconstruction and performs mostly remote reads, it has traditionally been used for storing colder, less frequently accessed data. Users should consider the network and CPU overheads of erasure coding when deploying this feature.
More details are available in the HDFS Erasure Coding documentation.
We are introducing an early preview (alpha 2) of a major revision of YARN Timeline Service: v.2. YARN Timeline Service v.2 addresses two major challenges: improving scalability and reliability of Timeline Service, and enhancing usability by introducing flows and aggregation.
YARN Timeline Service v.2 alpha 2 is provided so that users and developers can test it and provide feedback and suggestions for making it a ready replacement for Timeline Service v.1.x. It should be used only in a test capacity.
More details are available in the YARN Timeline Service v.2 documentation.
The Hadoop shell scripts have been rewritten to fix many long-standing bugs and include some new features. While an eye has been kept towards compatibility, some changes may break existing installations.
Incompatible changes are documented in the release notes, with related discussion on HADOOP-9902.
More details are available in the Unix Shell Guide documentation. Power users will also be pleased by the Unix Shell API documentation, which describes much of the new functionality, particularly related to extensibility.
The hadoop-client Maven artifact available in 2.x releases pulls Hadoop’s transitive dependencies onto a Hadoop application’s classpath. This can be problematic if the versions of these transitive dependencies conflict with the versions used by the application.
HADOOP-11804 adds new hadoop-client-api and hadoop-client-runtime artifacts that shade Hadoop’s dependencies into a single jar. This avoids leaking Hadoop’s dependencies onto the application’s classpath.
A notion of ExecutionType has been introduced, whereby Applications can now request for containers with an execution type of Opportunistic. Containers of this type can be dispatched for execution at an NM even if there are no resources available at the moment of scheduling. In such a case, these containers will be queued at the NM, waiting for resources to be available for it to start. Opportunistic containers are of lower priority than the default Guaranteed containers and are therefore preempted, if needed, to make room for Guaranteed containers. This should improve cluster utilization.
Opportunistic containers are by default allocated by the central RM, but support has also been added to allow opportunistic containers to be allocated by a distributed scheduler which is implemented as an AMRMProtocol interceptor.
Please see documentation for more details.
MapReduce has added support for a native implementation of the map output collector. For shuffle-intensive jobs, this can lead to a performance improvement of 30% or more.
See the release notes for MAPREDUCE-2841 for more detail.
The initial implementation of HDFS NameNode high-availability provided for a single active NameNode and a single Standby NameNode. By replicating edits to a quorum of three JournalNodes, this architecture is able to tolerate the failure of any one node in the system.
However, some deployments require higher degrees of fault-tolerance. This is enabled by this new feature, which allows users to run multiple standby NameNodes. For instance, by configuring three NameNodes and five JournalNodes, the cluster is able to tolerate the failure of two nodes rather than just one.
The HDFS high-availability documentation has been updated with instructions on how to configure more than two NameNodes.
Previously, the default ports of multiple Hadoop services were in the Linux ephemeral port range (32768-61000). This meant that at startup, services would sometimes fail to bind to the port due to a conflict with another application.
These conflicting ports have been moved out of the ephemeral range, affecting the NameNode, Secondary NameNode, DataNode, and KMS. Our documentation has been updated appropriately, but see the release notes for HDFS-9427 and HADOOP-12811 for a list of port changes.
Hadoop now supports integration with Microsoft Azure Data Lake and Aliyun Object Storage System as alternative Hadoop-compatible filesystems.
A single DataNode manages multiple disks. During normal write operation, disks will be filled up evenly. However, adding or replacing disks can lead to significant skew within a DataNode. This situation is not handled by the existing HDFS balancer, which concerns itself with inter-, not intra-, DN skew.
This situation is handled by the new intra-DataNode balancing functionality, which is invoked via the hdfs diskbalancer CLI. See the disk balancer section in the HDFS Commands Guide for more information.
A series of changes have been made to heap management for Hadoop daemons as well as MapReduce tasks.
HADOOP-10950 introduces new methods for configuring daemon heap sizes. Notably, auto-tuning is now possible based on the memory size of the host, and the HADOOP_HEAPSIZE variable has been deprecated. See the full release notes of HADOOP-10950 for more detail.
MAPREDUCE-5785 simplifies the configuration of map and reduce task heap sizes, so the desired heap size no longer needs to be specified in both the task configuration and as a Java option. Existing configs that already specify both are not affected by this change. See the full release notes of MAPREDUCE-5785 for more details.
HADOOP-13345 adds an optional feature to the S3A client of Amazon S3 storage: the ability to use a DynamoDB table as a fast and consistent store of file and directory metadata.
See S3Guard for more details.
HDFS Router-Based Federation adds a RPC routing layer that provides a federated view of multiple HDFS namespaces. This is similar to the existing ViewFs) and HDFS Federation functionality, except the mount table is managed on the server-side by the routing layer rather than on the client. This simplifies access to a federated cluster for existing HDFS clients.
See HDFS-10467 and the HDFS Router-based Federation documentation for more details.
The OrgQueue extension to the capacity scheduler provides a programmatic way to change configurations by providing a REST API that users can call to modify queue configurations. This enables automation of queue configuration management by administrators in the queue’s administer_queue ACL.
See YARN-5734 and the Capacity Scheduler documentation for more information.
The YARN resource model has been generalized to support user-defined countable resource types beyond CPU and memory. For instance, the cluster administrator could define resources like GPUs, software licenses, or locally-attached storage. YARN tasks can then be scheduled based on the availability of these resources.
See YARN-3926 and the YARN resource model documentation for more information.
The Hadoop documentation includes the information you need to get started using Hadoop. Begin with the Single Node Setup which shows you how to set up a single-node Hadoop installation. Then move on to the Cluster Setup to learn how to set up a multi-node Hadoop installation.


Title*
Description
Author*
Version*
Date and time
Genre
Puzzle
Shooter
Application
Demo
Action
Arcade
Platformer
RPG
Racing
Sports
Misc
Publisher
Idea
Code developer
Artist
Sound composer
URL for more information
Source code URL
Email address for support
Companion program URL
Banner filename
Screenshots
Screenshot file 1
Filename
Title
+ Screenshot file
Loadable files
Arduboy binary file 1
Filename
Title
Device
Arduboy
DevKit
+ Arduboy binary file
Button usage
Button action performed 1
Button or button sequence
Action performed
+ Button action performed
EEPROM usage
Location is variable
true
false
Start address
End address
Get JSON output


Our Store Locations
1st and Pike open 6AM - 8PM
123 Pike st
Seattle, WA 55555
Seatac Airport open 6AM - 8PM
12 Airport rd
Seattle, WA 55555
Seattle Center open 6AM - 8PM
734 running out of names ave
Seattle, WA 55555
Capitol Hill open 6AM - 8PM
23 No creativity lp
Seattle, WA 55555
Alki open 6AM - 8PM
13 filler st
Seattle, WA 55555


Rod Petrie promises to address the Hampden bugbear that annoys every supporter
The SFA president is adamant that taking control of the ground from Queen's Park will make a big impact as he outlines 2030 World Cup dream.
by Scott McDermott, https://www.dailyrecord.co.uk/authors/scott-mcdermott/Rod Petrie wants to have a revamped Hampden Park in place to host games at the 2030 World Cup.
The SFA president admits the fan experience at the national stadium is nowhere near good enough.
But he hopes when they take full ownership of the ground in August, they can begin to make gradual improvements.
And if the UK are successful in their proposed joint bid for the World Cup in a decade – he’d love to have a fully renovated Hampden as one of the key venues.
Petrie accepts that a lot of hard work – on both the bid and the stadium - will need to be done to make it happen.
But as president, he’s determined to make Hampden a better place to go for supporters in the future.
Petrie said: “Hampden will be European class next summer when it hosts Euro 2020 games.
“But we are in discussions with other home associations about a 2030 World Cup bid which would give us a 10-year timeline to look at Hampden as a host stadium for that.
“We’d all be delighted with that because we want a stadium which is entirely appropriate for the best competition in the world.
“It’s early stages and a lot of work has to be done. We take over the stadium in August after Euro 2020 and that’s been a game-changer.
“With access to Hampden 365 days a year, we can find ways to enhance the revenue for the benefit of Scottish football – and that will mean some changes to the stadium.
“We have to have a plan, a target, an objective to achieve. And the 2030 bid could give us that.
“I’m not going to sit here and say Hampden is perfect. But decisions made in the past have delivered what it is today.
“In terms of being European class there have been enhancements, like big screens and digital turnstile access.
“These things will make it comparable to the 11 other venues at Euro 2020.
“But the supporter experience, as we all know, doesn’t score very highly.
“The reason for that is the 24 degree factor rate of the stands compared to a 34 degree rate at the likes of Easter Road or Tynecastle.
“So that’s the challenge for us. If we are getting a new stadium, why are we getting it?
“Because we want to make things better for Scottish football. Then it’s about the vision, in terms of the enhancements we can make.
“For domestic football, we have to make it atmospheric when it’s not full – but ready to rock when it’s full.
“And that’s also relevant when it might be a neutral venue for other big games that we might attract.”
The venue of the 2030 World Cup will be decided by FIFA in 2024 and if the UK are successful, the SFA would then look at how to pay for a new Hampden.
Income from qualifying for major tournaments would help – but Petrie says his board are capable of finding funds from elsewhere.
He said: “We have to look at the creativity of the people on the SFA board.
“We have a big change now, by taking over the ownership of Hampden.
“Generating money from qualifying and doing great things on the pitch would be a strong contributor.
“But we have to be more creative and see if there are other ways to bring funding to the party for the things we want to see done.”


COVID-19 Adjustment
About
Global numbers
Total cases
Total deaths (rate:
%)
Total recovered
Total active case
Adjusted total Cases
Adjust the total case based on the death rate of:
-- select --
or specify the death rate:
#
Country
Total Cases
Deaths
Recovered
Death Rate (%)
Adjusted Total


anglicisms.py:
This module extracts anglicisms from the online wikipedia wictionary. (Check it out here: https://www.wiktionary.org/)
The program looks into the html-code and checks if an anglicisms has an own entry in the wictionary. If so, it will search in it for a german translation.
Generates array of tuples (anglicism, wiktionary-link).
Extracts a list of anglicisms from a wiktionary page.
Looks up the English translation of an anglicism.
dict_extract.py:
This module extracts the dict.cc entries of a .txt-file. Check out dict.cc here: http://www.dict.cc/ Download the vocabulary database here: http://www1.dict.cc/translation_file_request.php
The programs extracts every information for every entry stored in ‘dict_cc_entries.txt’ and returns them as an array of tuples.
Connects the parts of the entry in parenthesis because else they get split up.
Extracts dictionary entries and returns an array of tuples.
Extracts the different parts of an entry.
false_friends.py:
This module extracts false-friend-pairs from the “Liste falscher Freunde - Wikipedia”.html file.
Extracts false friends from .txt file.
file_handling.py:
This module contains all methods needed for file handling of any kind, which means writing files in different forms as well as reading them into differed formats.
Takes an object as an argument and dumps its content on disk using specified “name” as its file name. If no file name is specified, that object’s __repr__ will be used instead.
Loads a dictionary from the specified file.
Loads a cPickle object
Reads a file into a dictionary.
Reads a file.
Reads a tuple file. Tuples are separated by separation_character.
Reads a tuple file into a dictionary.
Reads a vector file.
Reads a vector file into a dictionary with word as key.
Simple file writing.
Enhanced function for writing a tuple file.
filter.py:
This module is used to filter out unwanted data in dict.cc-entries, false-friend-pairs or anglicisms.
Tells if two array share at least one element.
Tells if a character from charSet appears in a string s.
Creates a random subset of a tuple-array.
Filters out redundant tuples and multiple word expressions if needed and formats the remaining ones.
Deletes whitspaces in a string before and after a word.
Deletes entries which are empty strings in an array.


HL7 V2.4 Contents
Contents
1 . Introduction
2 .Control
3 .Patient Administration
4 .Order Entry
5 .Query
6. Financial Management
7 .Observation Reporting
8 .Master Files
9 .Medical Records/Information Management (Document Management)
10 .Scheduling
11 .Patient Referral
12 .Patient Care
13 .Clinical Laboratory Automation
14 .Application Management
15 .Personnel Management
A .Data Definition Tables
B. Lower Layer Protocols
C. Version 2.4 BNF Message Descriptions
D. Glossary
HL7 V2.4 Appendix B
The information formerly carried in Appendix B - Lower Layer Protocol (version
2.4) has been moved to the HL7 Implementation Guide. This page serves as
a placeholder for backward compatibility with HL7 version 2.1.


This is the requisite "Hello World" example for the demonstration. The TypeScript code is defining a global namespace and exporting a single execute function. That function is simply alerting the value "Hello, world!". In the Transpiled Functionality area, that function is wired to the "Click Me" button's click event via "javascript:HelloWorld.execute()".
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TypeScript
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JavaScript
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WITNESS LIST Public Health Committee April 16, 1997-2:00P HB 1897 For: Gray, Patricia (Self, Representative) HB 2226 For: Lovelace, Joe (TAFMI) On: Alexander, Cindy (TXCPA) Gilbert, Don (MHMR) HB 2307 For: Junell, Robert (Self, Representative) On: McKinney, Mike (HHSC) HB 2397 For: Finnell, Charles (Self, Representative) On: Magers, Bonnie (TDH) HB 2449 For: Branstetter, Anita (Self, TX Dietetic Assn.) Hooser, Greg (TX Dietetic Assn.) Penfield, Susan (TDH) HB 2677 For: Chavez, Norma (Self, Representative) Sosa, Lily (Self) HB 2913 On: Dunkelburg, Anne (CPPP) Gilbert, Don (MHMR) McGiffert, Lisa (Consumers Union) McKinney, Mike (HHSC) Patterson, Patti (TDH) HB 2984 For: Baughn, Cynthia (Self, THTKB) Hawley, Melissa (Self, THTKB) Hunter, Bob (Self, Representative) Loftin, Keith (Self, THTKB) Ortegon, Debra (Self, THTKB) Spites, Sarah (TAHC) Tuley, Mark (Self) Walsh, Robert (Self) Warton, Lory (Self, THTKB) On: Penfield, Susan (TDH) HB 3075 For: Vasik, Heather (TAHC) HB 3121 For: Chavez, Norma (Self, Representative) On: Evans, John (TDH) HB 3135 For: Herman, Guy (Self) Naishtat, Elliott (Self, Representative) HB 3487 For: Francisco, C.J. (TMA) Holzheauser, Steve (Self, Representative) Against: Bower, Bruce (Self) Dunkelberg, Anne (CPPP) Heard, John (Self) Perales, Gabriel (Self) Richardson, Bob (Self) HB 3514 For: Francisco, C.J. (TMA) Goolsby, Tony (Self, Representative) HCR 189 On: McKinney, Mike (HHSC) SB 291 For: Allen, Mike (Self) Doolan, Kim (Self) Gauthier, Debbie (Self) Haggerty, Pat (Self, Representative)


Trump, Macron to meet after French president criticized NATO
by Associated PressPARIS (AP) - French President Emmanuel Macron says he will meet with U.S. President Donald Trump ahead of the Dec. 3-4 NATO summit in London.
Macron tweeted that he had an “excellent discussion” with Trump on Monday evening about Syria, Iran and the NATO military alliance. They evoked “lots of convergences,” he said, without elaborating.
The phone call comes after Macron claimed last week that a lack of U.S. leadership is causing the “brain death” of NATO and said the European Union must step up and start acting as a strategic world power.
Trump’s preoccupation with defense spending has been a constant theme since he came to office in 2016 and is expected to feature at the Dec. 3-4 summit in London.
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Copyright © 2019 The Washington Times, LLC.
Please read our comment policy before commenting.


White House releases statement on Trump’s surprise visit to Walter Reed
by Ben FeuerherdThe White House released a statement from Walter Reed Medical Center in Washington, DC, on Monday that said President Trump’s visit there over the weekend was a “routine” checkup.
The statement, written by Navy Commander Sean Conley, was released by White House press secretary Stephanie Grisham amid rumors about Trump’s medical condition.
“Despite some of the speculation, the President has not had any chest pain, nor was he evaluated or treated for any urgent or acute issues,” Conley wrote in the letter.
“Specifically, he did not undergo any specialized cardiac or neurological evaluations.”
The letter added that the visit was kept “off the record” due to uncertainties about the president’s schedule.
On Saturday, Grisham said the visit was part of his annual checkup, which he was getting out of the way early, but then revealed that he didn’t stay at Walter Reed National Military Medical Center for very long.
“Anticipating a very busy 2020, the President is taking advantage of a free weekend here in Washington, D.C., to begin portions of his routine annual physical exam at Walter Reed,” Grisham said in a statement Saturday afternoon.
Trump in February spent more than four hours at Walter Reed for a checkup supervised by his physician and involving a panel of 11 specialists.


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Proof-of-Stake cryptocurrency research focused on staking yields, passive income, masternodes and dividends with coin metrics, news, blockchain stats, calculator, market overview and ranking list
NutellaLicka28-Jun-19 03:18 AM
@Deleted User I understand that. It is called a faraday cage. I dont think you read what I said. I dont appreciate you claiming I said something when I didnt either.
I'll summarise what my thoughts for you again. If you think the addition of a 5G network and associated radiation is going to have a significant impact on our futile lives, more than the current amount of radiation is having on us, you're misguided.
polycryptoblog28-Jun-19 03:21 AM
@Deleted User They are safe unless you get in the dielectric between plates, then it will heat you up.
(Where you put the food )
tolken28-Jun-19 04:08 AM
So uhh.... how about that Kmd?
actionslacks28-Jun-19 04:38 AM
it's about to moon!
tolken28-Jun-19 04:56 AM
According to CMC Kmd was $0.002143 USD in March 2017.
manugarc28-Jun-19 05:09 AM
anyone from the team around here?
need assistance
BlackJesus28-Jun-19 05:10 AM
I just did the math supernet is generating 1500 kmd a day with its holdings
Markus28-Jun-19 05:28 AM
thats pretty fine
547k a year
compounding at its finest
actionslacks28-Jun-19 05:33 AM
yes, but the other alts have better marketing
Markus28-Jun-19 06:18 AM
cause they generated millions from icos?
actionslacks28-Jun-19 06:19 AM
yeah that probably helps
tolken28-Jun-19 06:23 AM
quite a lul in crypto market after the recent bonanza
actionslacks28-Jun-19 06:31 AM
it had to stop to breathe a little.
should just ignore this market for awhile, trying to catch shooting rockets and falling knives hit my bags pretty hard last time.
hyperDEX28-Jun-19 07:07 AM
@actionslacks marketing did not save eos with 4B
We need to get over this mentality that marketing will fix alts, real partnerships and real tech will win out in the end
Everyone in the community has a responsibility to themselves to go out and tell people about KMD if they want to move away this bot/TA trading environment we currently have to a more sustainable FA based market
Marketing is only a small % of brand awareness, the other major parts are a working product/tech and people spreading this by word of mouth.
If the marketing is failing, the community is failing to deliver. People need to take some responsibility for this failure as well, the question is will the community step up and fix it or procrastinate and complain?
If it is the former, great, we will be able to achieve great things together, if it is the latter, better sell now and head to greener alts like insight chain with 5x today on 5k volume.
Bittersweet28-Jun-19 07:16 AM
Let's get real, even a 100m market cap is crazy for 90% of successful altcoin projects
That's not even talking about the worthless projects
i just think kmd (and co) is exceptional among all
Crypto.com Chain — a high-performing native blockchain solution that will drive cryptocurrency adoption globally by enabling instant crypto payment transactions.
Or Bitcoin Diamond Bitcoin Diamond 221M
Or Aurora at 175M
The answer is not marketing, the answer is pump and dump bots/teams
How do we stop this? By having the market mature and only invested into coins that have FA/ tech and a future, not stuff that has nothing and gets pumped and dumped all the time.
Keppie28-Jun-19 07:25 AM
All heavily premined aswell I think
hyperDEX28-Jun-19 07:25 AM
Not necessarily, just big enough coins with ok liquidity that they can move up and down at will.
Keppie28-Jun-19 07:26 AM
Noobs be like (wow its bitcoin, and its dirt cheap!)
hyperDEX28-Jun-19 07:26 AM
each pump of aurora brings in millions for whoever is doing it, then wait till it dumps then do it again
Keppie28-Jun-19 07:26 AM
we should rename to Bitcoin Green
hyperDEX28-Jun-19 07:26 AM
We should do a stock split 1KMD = 1000KMDs
Then we would be worth 0.001 and be really cheap
But then again this is what the appeal of these projects like tron are, they are cheap and they can pump on hype
But as the market matures, through every bull and bear market, they will slowly be weeded out
What will be left are the googles and amazons, not the pets.coms
Which project has the biggest market cap right now is thinking about this wrong, which projects will outlast and win is the right one.
Keppie28-Jun-19 07:30 AM
This space is blinded by short term gains. Lets just win the long race & keep collecting rewards. We doing well
hyperDEX28-Jun-19 07:37 AM
It takes a few BTC to drop 10%, it will take a few BTC to pump us 10%. The issue is not the price, the issue is real liquidity
I remember back in 2017, KMD had hundreds of BTC in buy support and there was 10-20bTC buys/sells and there wasnt too big of an issue
Markets moved slightly.
tolken28-Jun-19 07:39 AM
@hyperDEX what I’m afraid of, is the Facebook affect. What do i mean by that?  It was marketing and a bit of luck that helped it succeed. The tech wasn’t that impressive - but they’ve made it for the long haul.
hyperDEX28-Jun-19 07:39 AM
But now with so many people looking for "returns" whilst shooting this space in the face by diverting funds and eye balls on great tech and FA, they have shifted everything to this tech is a hindrance mentality
@tolken that will only work in the short term, same goes for verge and all these other useless projects
Short term, easy to understand and pump vaporware does the best, in the long term they will fade away and when the market matures, the smart money will invest because of FA, because that is where the value is.
tolken28-Jun-19 07:41 AM
But what about EOS, Cosmos, Tron... fake it till you make it!
hyperDEX28-Jun-19 07:41 AM
Exactly
tolken28-Jun-19 07:41 AM
Cardano
hyperDEX28-Jun-19 07:41 AM
But do you think institutions will buy into it?
What is the risk reward there
tolken28-Jun-19 07:41 AM
They’ll just use libra?
hyperDEX28-Jun-19 07:42 AM
So this is why we need to position ourselves not for today/this year, but for the next 2-3 years.
Just like what we did with DEX, it took 2 years to get it to a point where it works, now as KYC supernova is going to blow, we are ready to be that solution.
tolken28-Jun-19 07:44 AM
True, seems Kmd is on the verge of showing the world real world use. I’m ready to get a bob setup with liquidity.
hyperDEX28-Jun-19 07:44 AM
So whilst it may mean we are not the pump of the day nor do we have liquidity that can support our valuation (not many can), we need to build for not what the market wants or needs now, but what they will need in the future. DEX is the first, but smart contracts and smart chains and other things will be what people will be needing to solve their issues in a year or 2
tolken28-Jun-19 07:46 AM
Hopefully the Antara release inspires people to use Kmd like never before and moves it from an enigma to an accessible suite of software.
hyperDEX28-Jun-19 07:48 AM
I think most are pinning too much hope on that. The thing that will take us up in valuation and actual usage to back it up is atomicDEX and having a very liquid DEX to boot. So how can the community help to make themselves rich? Provide liquidity, promote it on socials, speaks to friends, tell youtubers livestreaming about it, print out flyers and act like a crazy nutjob at work talking about it constantly....
Marketing may start with the marketing team but it does not stop there. The community needs to do it's part to spread the word.
4
4
1
alen28-Jun-19 07:54 AM
Just make a usefriendly, idiotproof UI and people will use it
The only thing stopping BarterDex in the past was usability. Assuming it’s as solid as I hear, liquidity won’t be an issue.
mobipoi28-Jun-19 08:24 AM
I agree with @hyperDEX on this one DEX first, the most important need in the ecosystem, it just solves the needs of millions , DEX release should be priority, everything else is a prelude
Without DEX it would be hard to grow the community very few people care about smart contracts and even fewer enterprise are thinking of their use case. Use case will come from within the ecosystem project launching on DEX /DICO etc(edited)
It the only way to maintain and grom kmd valuation long term so what are we waiting for launch the dex already and we can evolve as we move along
alen28-Jun-19 08:38 AM
Will it be possible to exchange coins a d tokens for stablecoins..i mean will stablecoins be included?
If yes...this is a winner....
We just use a crypto paycard with multiwallets and this really is a win win
alen28-Jun-19 08:52 AM
How will it work regarding liquidity?
Will it be strictly one customer to another..one on one..
Or example..i want to exchanher 15btc for xxx amount of kmd.... now: will you have to wait for one person who holds 15btc worth.of kmd and then exchange between them....
Or a better way...like torrent file sharing....there is not one on dex who jas 1btc worth kmd....can the dex work like...it finds 6 people who have summ of 15btc worth kmd and then the app does exchange among them..
That would.solve a lot.
KomodoWorld28-Jun-19 08:55 AM
I read @Mylo is developing a marketmaker app, so you can easily setup liquidity. Parhaps he can explain
jansako28-Jun-19 09:01 AM
The user experience is expected to be similar to a CEX. You see an order you can take it, or you post your own order and it gets matched.
Mylo28-Jun-19 09:01 AM
yeah i might get started on it next month
jansako28-Jun-19 09:01 AM
The difference is execution time, it will take a couple of minutes or so (block confirms)
KomodoWorld28-Jun-19 09:04 AM
the 0conf feature will be added again later, eventually it will be fast like mm1 but with better ux, and some stablecoins are supported
Mylo28-Jun-19 09:04 AM
it's text based.
1
e.g. a text console.
with a tutorial on how to recreate in any of your programming languages.
this is for the token DEX, not marketmaker. marketmaker next month. @jorian is making a prettier gui one atm
jansako28-Jun-19 09:05 AM
Just so we are clear, the marketmaker app is a different beast form the trading UI for the general user pop.


PureBasic - Ftp
Overview
Ftp (File Transfer Protocol) is a way to share files based amongst users on a client-server model. This library implement the client side of Ftp, and allows to connect to a remote server and manipulate files (like download, upload, list available files, navigate trough the directories and more).
All the Ftp commands are based on the network library, so InitNetwork() has to be called before using them.
Command Index
AbortFTPFile
CheckFTPConnection
CloseFTP
CreateFTPDirectory
DeleteFTPDirectory
DeleteFTPFile
ExamineFTPDirectory
FTPDirectoryEntryAttributes
FTPDirectoryEntryDate
FTPDirectoryEntryName
FTPDirectoryEntryRaw
FTPDirectoryEntrySize
FTPDirectoryEntryType
FTPProgress
FinishFTPDirectory
GetFTPDirectory
IsFtp
NextFTPDirectoryEntry
OpenFTP
ReceiveFTPFile
RenameFTPFile
SendFTPFile
SetFTPDirectory
Example
Ftp.pb
Supported OS
All


--- layout: post title: alphabeasties blogless a blog about design date: '2010-06-24T09:55:00+01:00' tags: [] tumblr_url: http://backlog.robbevan.com/post/730786074/alphabeasties-blogless-a-blog-about-design ---
Alphabeasties – BlogLESS: A Blog about Design Ethics


Do you prefer Java , Python, Ruby or C#
Java
C#
Ruby
Python
What is your favorite web framework ?
SpringBoot
ASP.NET
Rails
Apache Spark
Sinatra
Submit


@* * Copyright 2017 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import uk.gov.hmrc.play.views.html.helpers._ @import uk.gov.hmrc.cbcrfrontend.AppConfig @import play.api.i18n.Messages.Implicits._ @import uk.gov.hmrc.cbcrfrontend.views.html._ @import helper._ @import tags._ @import uk.gov.hmrc.cbcrfrontend.model._ @import uk.gov.hmrc.cbcrfrontend.controllers.routes @(asideCbc: Html, phaseBannerBeta: Html)(implicit request: Request[_], messages: Messages) @sidebarContent = { @asideCbc } @main_template("Country by Country Reporting", sidebarLinks = Some(sidebarContent)) {
@Messages("notRegistered.content")


-
Episode 24: Ok Multiplatform with Jesse Wilson and Egor Andreevich
In this episode Artem and Hannes chatted with Jesse and Egor from Square about multiplatform development with Kotlin.
-
Survey: Help us make podcast better
Please participate in a little 2 minutes survey to give us feedback on how to improve this show.
-
Episode 23: Rise of the Machines (droidcon Berlin 2018)
We've collaborated with droidcon Berlin 2018 (June 25) where Hannes was speaking about MVI, and they've recorded panel discussions for us and allowed us to publish them with our commentary.
-
Episode 22: Women in Tech (droidcon Berlin 2018)
We've collaborated with droidcon Berlin 2018 (June 25) where Hannes was speaking about MVI, and they've recorded panel discussions for us and allowed us to publish them with our commentary.
-
Episode 21: Rx Must Die (droidcon Berlin 2018)
We've collaborated with droidcon Berlin 2018 (June 25) where Hannes was speaking about MVI, and they've recorded panel discussions for us and allowed us to publish them with our commentary.
-
Episode 20, Part 2: public final Agile
In the second part of episode 20 Artem and Hannes continue the discussion with Alexey Alexeev about Agile, Scrum, Kanban and everything related to project management.
-
Episode 20, Part 1: public final Agile
In this episode Artem and Hannes chatted with Alexey Alexeev about Agile, Scrum, Kanban and everything related to project management.
-
Episode 19, Part 2: Model-View-Intent with Benoît Quenaudon from Square
In the second part of episode #19 Artur and Hannes continue the discussion with Benoît Quenaudon from Square about Model-View-Intent.
-
Episode 19, Part 1: Model-View-Intent with Benoît Quenaudon from Square
In the first part of episode #19 Artur and Hannes chatted with Benoît Quenaudon from Square about Model-View-Intent.
-
Episode 18, Part 2: Android Everywhere
In the second part of episode #18 Artur, Hannes and Artem discuss Android TV, Chromecast and Android Auto.
-
Episode 18, Part 1: Android Everywhere
In the first part of episode #18 Artur, Hannes und Artem discuss Android tablets, Chromebooks and Android Wear (Wear OS).
-
Episode 17: Switching Gears to C# and .NET
Artur chatted with Dmitry Savchenko about C#, .NET and everything in between.
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Episode 16: Tools
In this episode Artem, Artur and Hannes discuss the tools they use for development.
-
Episode 15: 2017 in Retrospective
In this episode Artur and Hannes do a retrospective on 2017. They share their personal highlights, favorite talks, disapointments, learnings and much more.
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Episode 14: RxJava — the Present and Future with David Karnok (core maintainer)
In this episode we chatted with core maintainer David Karnok about the present and the future of RxJava.
-
Episode 13: Conductor with Eric Kuck
In this episode we talked about Conductor with creator Eric Kuck.
-
Episode 12: Instant Apps with Lukas Olsen and Christian Bahl
Hannes chatted with his coworkes Lukas and Christian about Instant Apps.
-
Episode 11: Migration to RxJava 2 with Artur Dryomov from Juno
We've talked to Artur about Juno's way to migrate their Android Riders App from RxJava 1 to RxJava 2.
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Episode 10: Kotlin Language Design Nitpicking with Dmitry Jemerov from JetBrains
We've talked to Dmitry Jemerov from Kotlin team at JetBrains about some language design decisions made in Kotlin
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Episode 9, Part 2: Kotlin Gradle plugin, compilers and build systems with Alexey Tsvetkov
In the second part of episode 9 we have talked about build systems for android development: Gradle, Buck and Bazel
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Episode 9, Part 1: Kotlin Gradle plugin, compilers and build systems with Alexey Tsvetkov
In this episode we have talked to Alexey Tsvetkov from Jetbrains about Kotlin Gradle plugin, compilers and build systems.
-
Episode 8: Damn Functional Programming with Paco Estevez
In this episode we have talked with Paco Estevez about Functional Programming and how he applies Functional Programming in his android apps.
-
Episode 7: React Native with Felipe Lima from Airbnb
In this episode we have talked with Felipe Lima about React Native, a cross platform solution to build native mobile apps using JavaScript and React, and how React Native is used at Airbnb.
-
Episode 6, Part2: Continuous Integration (CI) & Continuous Delivery (CD)
In this episode we have talked about Continious Integration (CI) and Continuous Delivery (CD). Fernando Cejas gives us some insights how Soundcloud do CI and CD.
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Episode 6, Part1: Continuous Integration (CI) & Continuous Delivery (CD)
In this episode we have talked about Continious Integration (CI) and Continuous Delivery (CD). Fernando Cejas gives us some insights how Soundcloud do CI and CD.
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Remember, sending advice to us is the best way to mold Alex + Keiths into the best Alex + Keiths you know and love. If you have any questions or concerns, please fill in the form below, submit it, and our dedicated tech team will reach out to you as soon as possible!


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iDreamSky Game Engine
v1.0.0
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This is interface for the Services. 更多...
#include <Service.h>
公開方法(Public Methods) | |
| IService (const char *name) | |
| IService Constructor. 更多... | |
| virtual | ~IService () |
| IService Destructor. 更多... | |
| virtual bool | initiate ()=0 |
| Initiate the Services. 更多... | |
| virtual void | process ()=0 |
| Update the Services. | |
| virtual void | pause ()=0 |
| Called when the application is pause(e.g system bring the app to background, let the service to release resources) | |
| virtual void | resume ()=0 |
| Called when the application is resume(e.g system bring back the app from background, let the service to reload resources) | |
| virtual void | terminate ()=0 |
| Terminate the Services, called when the app is terminate. | |
| virtual void | clear ()=0 |
| Call when the services needed to be clean up, e.g. 更多... | |
| 公開方法(Public Methods) 繼承自 IDreamSky::Link< IService > | |
| operator IService * () const | |
| operator IService & () const | |
| IService & | owner () const |
| IService & | owner (IService &owner_) |
| List< IService > * | parent () |
| Link< IService > * | prev () |
| Link< IService > * | next () |
| const List< IService > * | const_parent () const |
| const Link< IService > * | const_prev () const |
| const Link< IService > * | const_next () const |
| void | link_first (List< IService > &list) |
| void | link_last (List< IService > &list) |
| void | link_prev (Link< IService > &link) |
| void | link_next (Link< IService > &link) |
| void | remove () |
| void | unlink () |
| Link (IService &owner_) | |
公開屬性 | |
| char | name [15+1] |
This is interface for the Services.
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pure virtual |
Call when the services needed to be clean up, e.g.
during scene transition.
|
pure virtual |


Normal /
None
Rounded /
None
Smooth /
None
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Orthogonal
Rounded /
Orthogonal
Normal /
Manhattan
Rounded /
Manhattan
Normal /
Metro
Rounded /
Metro
Double Click shape to edit.


Syllabus
Course helpline<EMAIL_ADDRESS>Welcome to AC295: advanced practical data science. The course will be divided into three major topics:
1. How to scale a model from a prototype (often in jupyter notebooks) to the cloud. In this module, we cover virtual environments, containers, and virtual machines before learning about containers and Kubernetes. Along the way, students will be exposed to Dask.
2. How to use existing models for transfer learning. Transfer learning is a machine learning method where a model developed for a task is reused as the starting point for a model on a second task. It is a popular approach in deep learning where pre-trained models are used as the starting point on computer vision and natural language processing tasks. This could be very important, given the vast computing resources required to develop neural network models on these problems and the huge gains that these models can provide. In this part of the course, we will examine various pre-existing models and techniques in transfer learning.
3. In the third part, we will introduce several intuitive visualization tools for investigating and diagnosing models. We will be demonstrating a number of visualization tools ranging from the well established (like saliency maps) to recent examples that have appeared in https://distill.pub.
Lectures (online): Tuesday and Thursday 10:30-11:45am (and possibly depending on timezone of students repeat Tuesday and Thursday from 6:00-7:15pm)
TFs: Rashmi Banthia, William Palmer, Andrea Porelli, Shivas Jayaram, Hai Bui, Javid Lakha, Yujiao Chen
Office Hours: TBD
List of Contents
Prerequisites
Students are expected to be fluent in programming (Python), statistics knowledge at the level of Stat 110 or above, data science (or machine learning) at the level of AC209A and AC209B.
Software
We will be using a variety of software, primarily Python 3, Pytorch, Tensorflow, and Docker. More details in class.
Topics
The course is organized in three modules.
-
Deploy data science (integration + scalability)
1a. Virtual Environments and Virtual Boxes
1b. Containers
1c. Kubernetes
1d. Dask -
Transfer learning and distillation
2a. Intro to Transfer Learning: basics and Convolutional Neural Networks (CNNs) review
2b. Transfer Learning for Images and SOTA Models
2c. Language Models and Transfer Learning with Text Data
2d. Attention and Transformers
2e. Distillation and Compression -
Visualization as investigative tool
3a. Introduction and Overview of Viz for Deep Models: lime and shapley
3b. CNNs for Image Data, Activation Maximization and Saliency Maps
3c. Attention for Debugging Language Models
Course Activities
Each module is structured in three types of activities: Lectures, Reading Discussion, and Practicum. Each activity requires the students to complete different assignments in the form of exercise/homework, discussions, reading assignments, and presentations (see Assignments below). During the first weeks of each module, students will attend a lecture on Tuesday and reading discussion on Thursday. The last week of each module will be Practicum. Attendance is mandatory.
-
Reading List consists of papers, blogs, and other reading material that will be released no later than the beginning of each week. This will be the base for all the activities during the week. See Readings Guidelines here link to guidelines.
-
Lectures are held online Tuesdays from 10:30-11:45am (and possibly depending on timezone of students repeat Tuesday from 6:00-7:15pm). During this activity, we will discuss and summarize the basic concepts of the material covered during the week.
-
Journal Discussions are held online on Thursdays from 10:30-11:45 am (and possibly depending on timezone of students repeat Thursday from 6:00-7:15 pm). During this activity, two groups will present one paper each from the Reading List to the rest of the class and lead the discussion. See Paper Presentation Guidelines here link to guidelines.
-
Practicum are activities in the form of a project based on the material covered in the module. The students will work in groups and be expected to deliver a complete assignment in 10 days. There will be two practicums.
Assignments
The final grade will be calculated using the following weights for each assignment:
Exercises
There are eight (8) exercises to complete. They will be released at the end of each regular week Lecture and due a week later. The exercises are graded on a scale 1 to 5, where 5 is the highest grade.
Discussion Forum
There will be a discussion forum the day before the Reading Discussion on Thursday based on the reading from Reading List. All discussions will be on the Ed Platform (select Ed from the tab on the canvas course's main page).
Presentations
At every Reading Discussion, groups will present the reading material assigned at the beginning of the week. Please see these on the presentations.
Practicums
There will be two practica during the first two modules (see the schedule for details).
Final Projects
There will be a final group project due during Exams period encompassing all the material learned in class.
| Assignment | Final Grade Weight |
|---|---|
| Discussion Forum | 10% |
| Exercises | 10% |
| Presentations | 15% |
| Practicums | 40% |
| Final Projects | 25% |
| Total | 100% |
Getting Help
For questions about exercise, course content, package installation, and after you have tried to troubleshoot yourselves, the process to get help is:
- Go to Office Hours; this is the best way to get help.
- Post the question in Ed Forum, and hopefully, your peers will answer.
Course Policies
Collaboration Policy
We encourage students to talk and discuss the assignments with their fellow students. Discussion is encouraged. Presentation during Reading Discussion, Practicum, and Projects are group activities.
Communication from Staff to Students
Class announcements will be through Ed Forum.
Diversity and Inclusion Statement
Data Science, like many fields of science, has historically only been represented by a small portion of the population. This is despite some of the pioneers in computer science being from groups that are historically and presently underrepresented. Whenever possible, I will try to highlight the contributions that people have been from a variety of backgrounds. To start, here is a list of some really nice references.:
I welcome any additions to this list you may have!
In an ongoing effort to foster a more inclusive environment in computer science, recent initiatives have attempted to overcome some barriers to entry for underrepresented groups:
Like the list above, this list is not exhaustive, but I welcome any additions and suggestions you may have. I would like to attempt to discuss diversity in data science from time to time where appropriate and possible. Please contact me (in person or electronically) or submit anonymous feedback if you have any suggestions to improve the quality of the course materials. The best way to provide anonymous feedback is to use Ed, which allows you to provide comments anonymously. Furthermore, I would like to create a learning environment for my students that supports a diversity of thoughts, perspectives and experiences, and honors your identities (including race, gender, class, sexuality, religion, ability, etc.) To help accomplish this:
- If you have a name and/or set of pronouns that differ from those that appear in your official Harvard records, please let me know!
- If you feel like your performance in the class is being impacted by your experiences outside of class, please don’t hesitate to come and talk with me. I want to be a resource for you. Remember that you can also submit anonymous feedback (which will lead to me making a general announcement to the class if necessary to address your concerns). If you prefer to speak with someone outside of the course, you may find helpful resources at the Harvard Office of Diversity and Inclusion.
- I (like many people) am still in the process of learning about diverse perspectives and identities. If something was said in class (by anyone) that made you feel uncomfortable, please talk to me about it. (Again, anonymous feedback is always an option.)
- As a participant in course discussions, you should also strive to honor the diversity of your classmates.
Academic Honesty
Ethical behavior is an important trait of a Data Scientist, from ethically handling data to attribution of code and work of others. Thus, in AC295 we give a strong emphasis to Academic Honesty. As a student your best guidelines are to be reasonable and fair. We encourage teamwork for problem sets, but you should not split the assignments and you should work on all the problems together.
Accommodations for students with disabilities
Students needing academic adjustments or accommodations because of a documented disability must present their Faculty Letter from the Accessible Education Office(AEO) and speak with Pavlos by the end of the third week of the term: Friday, September 18. Failure to do so may result in us being unable to respond in a timely manner. All discussions will remain confidential.
Accommodations for students with disabilities


The International Conference on Machine Learning (ICML) 2020 is being hosted virtually from July 13th - July 18th. We’re excited to share all the work from SAIL that’s being presented, and you’ll find links to papers, videos and blogs below. Feel free to reach out to the contact authors directly to learn more about the work that’s happening at Stanford!
List of Accepted Papers
Active World Model Learning in Agent-rich Environments with Progress Curiosity
Authors: Kuno Kim, Megumi Sano, Julian De Freitas, Nick Haber, Daniel Yamins
Contact<EMAIL_ADDRESS>Links: Video
Keywords: curiosity, active learning, world models, animacy, attention
Graph Structure of Neural Networks
Authors: Jiaxuan You, Jure Leskovec, Kaiming He, Saining Xie
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: neural network design, network science, deep learning
A Distributional Framework For Data Valuation
Authors: Amirata Ghorbani, Michael P. Kim, James Zou
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: shapley value, data valuation, machine learning, data markets
A General Recurrent State Space Framework for Modeling Neural Dynamics During Decision-Making
Authors: David Zoltowski, Jonathan Pillow, Scott Linderman
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: computational neuroscience, dynamical systems, variational inference
An Imitation Learning Approach for Cache Replacement
Authors: Evan Zheran Liu, Milad Hashemi, Kevin Swersky, Parthasarathy Ranganathan, Junwhan Ahn
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: imitation learning, cache replacement, benchmark
An Investigation of Why Overparameterization Exacerbates Spurious Correlations
Authors: Shiori Sagawa*, Aditi Raghunathan*, Pang Wei Koh*, Percy Liang
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: robustness, spurious correlations, overparameterization
Better Depth-Width Trade-offs for Neural Networks through the Lens of Dynamical Systems.
Authors: Vaggos Chatziafratis, Sai Ganesh Nagarajan, Ioannis Panageas
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: expressivity, depth, width, dynamical systems
Bridging the Gap Between f-GANs and Wasserstein GANs
Authors: Jiaming Song, Stefano Ermon
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: gans, generative models, f-divergence, wasserstein distance
Concept Bottleneck Models
Authors: Pang Wei Koh, Thao Nguyen, Yew Siang Tang, Stephen Mussmann, Emma Pierson, Been Kim, Percy Liang
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: concepts, intervention, interpretability
Domain Adaptive Imitation Learning
Authors: Kuno Kim, Yihong Gu, Jiaming Song, Shengjia Zhao, Stefano Ermon
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: imitation learning, domain adaptation, reinforcement learning, generative adversarial networks, cycle consistency
Encoding Musical Style with Transformer Autoencoders
Authors: Kristy Choi, Curtis Hawthorne, Ian Simon, Monica Dinculescu, Jesse Engel
Contact<EMAIL_ADDRESS>Links: Paper | Blog Post | Video
Keywords: sequential, network, and time-series modeling; applications - music
Fair Generative Modeling via Weak Supervision
Authors: Kristy Choi, Aditya Grover, Trisha Singh, Rui Shu, Stefano Ermon
Contact<EMAIL_ADDRESS>Links: Paper | Video
Keywords: deep learning - generative models and autoencoders; fairness, equity, justice, and safety
Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods
Authors: Daniel Y. Fu, Mayee F. Chen, Frederic Sala, Sarah M. Hooper, Kayvon Fatahalian, Christopher Ré
Contact<EMAIL_ADDRESS>Links: Paper | Blog Post | Video
Keywords: weak supervision, latent variable models
Flexible and Efficient Long-Range Planning Through Curious Exploration
Authors: Aidan Curtis, Minjian Xin, Dilip Arumugam, Kevin Feigelis, Daniel Yamins
Contact<EMAIL_ADDRESS>Links: Paper | Blog Post | Video
Keywords: planning, deep learning, sparse reinforcement learning, curiosity
FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis
Authors: Aman Sinha, Matthew O’Kelly, Hongrui Zheng, Rahul Mangharam, John Duchi, Russ Tedrake
Contact<EMAIL_ADDRESS><EMAIL_ADDRESS>Links: Paper | Video
Keywords: distributional robustness, online learning, autonomous driving, reinforcement learning, simulation, mcmc
Goal-Aware Prediction: Learning to Model what Matters
Authors: Suraj Nair, Silvio Savarese, Chelsea Finn
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: reinforcement learning, visual planning, robotics
Graph-based, Self-Supervised Program Repair from Diagnostic Feedback
Authors: Michihiro Yasunaga, Percy Liang
Contact<EMAIL_ADDRESS>Links: Paper | Blog Post | Video
Keywords: program repair, program synthesis, self-supervision, pre-training, graph
Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions
Authors: Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo Anthony Celi, Emma Brunskill, Finale Doshi-Velez
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: reinforcement learning, off-policy evaluation, interpretability
Learning Near Optimal Policies with Low Inherent Bellman Error
Authors: Andrea Zanette, Alessandro Lazaric, Mykel Kochenderfer, Emma Brunskill
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: reinforcement learning, exploration, function approximation
Maximum Likelihood With Bias-Corrected Calibration is Hard-To-Beat at Label Shift Domain Adaptation
Authors: Amr Alexandari*, Anshul Kundaje†, Avanti Shrikumar*† (*co-first †co-corresponding)
Contact<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>Links: Paper | Blog Post | Video
Keywords: domain adaptation, label shift, calibration, maximum likelihood
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Authors: Tony Duan*, Anand Avati*, Daisy Yi Ding, Sanjay Basu, Andrew Ng, Alejandro Schuler
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: gradient boosting, uncertainty estimation, natural gradient
On the Expressivity of Neural Networks for Deep Reinforcement Learning
Authors: Kefan Dong, Yuping Luo, Tianhe Yu, Chelsea Finn, Tengyu Ma
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: reinforcement learning
On the Generalization Effects of Linear Transformations in Data Augmentation
Authors: Sen Wu, Hongyang Zhang, Gregory Valiant, Christopher Ré
Contact<EMAIL_ADDRESS>Links: Paper | Blog Post | Video
Keywords: data augmentation, generalization
Predictive Coding for Locally-Linear Control
Authors: Rui Shu*, Tung Nguyen*, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung Bui
Contact<EMAIL_ADDRESS>Links: Paper | Video
Keywords: representation learning, information theory, generative models, planning, control
Robustness to Spurious Correlations via Human Annotations
Authors: Megha Srivastava, Tatsunori Hashimoto, Percy Liang
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: robustness, distribution shift, crowdsourcing, human-in-the-loop
Sample Amplification: Increasing Dataset Size even when Learning is Impossible
Authors: Brian Axelrod, Shivam Garg, Vatsal Sharan, Gregory Valiant
Contact<EMAIL_ADDRESS>Links: Paper | Video
Keywords: learning theory, sample amplification, generative models
Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM
Authors: Kunal Menda, Jean de Becdelièvre, Jayesh K. Gupta, Ilan Kroo, Mykel J. Kochenderfer, Zachary Manchester
Contact<EMAIL_ADDRESS>Links: Paper | Video
Keywords: system identification; time series and sequence models
The Implicit and Explicit Regularization Effects of Dropout
Authors: Colin Wei, Sham Kakade, Tengyu Ma
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: dropout, deep learning theory, implicit regularization
Training Deep Energy-Based Models with f-Divergence Minimization
Authors: Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: energy-based models; f-divergences; deep generative models
Two Routes to Scalable Credit Assignment without Weight Symmetry
Authors: Daniel Kunin*, Aran Nayebi*, Javier Sagastuy-Brena*, Surya Ganguli, Jonathan M. Bloom, Daniel L. K. Yamins
Contact<EMAIL_ADDRESS>Links: Paper | Video
Keywords: learning rules, computational neuroscience, machine learning
Understanding Self-Training for Gradual Domain Adaptation
Authors: Ananya Kumar, Tengyu Ma, Percy Liang
Contact<EMAIL_ADDRESS>Links: Paper | Video
Keywords: domain adaptation, self-training, semi-supervised learning
Understanding and Mitigating the Tradeoff between Robustness and Accuracy
Authors: Aditi Raghunathan*, Sang Michael Xie*, Fanny Yang, John C. Duchi, Percy Liang
Contact<EMAIL_ADDRESS><EMAIL_ADDRESS>Links: Paper | Video
Keywords: adversarial examples, adversarial training, robustness, accuracy, tradeoff, robust self-training
Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling
Authors: Yao Liu, Pierre-Luc Bacon, Emma Brunskill
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: reinforcement learning, off-policy evaluation, importance sampling
Visual Grounding of Learned Physical Models
Authors: Yunzhu Li, Toru Lin*, Kexin Yi*, Daniel M. Bear, Daniel L. K. Yamins, Jiajun Wu, Joshua B. Tenenbaum, Antonio Torralba
Contact<EMAIL_ADDRESS>Links: Paper | Video
Keywords: intuitive physics, visual grounding, physical reasoning
Learning to Simulate Complex Physics with Graph Networks
Authors: Alvaro Sanchez-Gonzalez, Jonathan Godwin, Tobias Pfaff, Rex Ying, Jure Leskovec, Peter W. Battaglia
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: simulation, graph neural networks
Coresets for Data-Efficient Training of Machine Learning Models
Authors: Baharan Mirzasoleiman, Jeff Bilmes, Jure Leskovec
Contact<EMAIL_ADDRESS>Links: Paper | Video
Keywords: Coresets, Data-efficient training, Submodular optimization, Incremental gradient methods
Which Tasks Should be Learned Together in Multi-Task Learning
Authors: Trevor Standley, Amir Zamir, Dawn Chen, Leonidas Guibas, Jitendra Malik, Silvio Savarese
Contact<EMAIL_ADDRESS>Links: Paper | Video
Keywords: machine learning, multi-task learning, computer vision
Accelerated Message Passing for Entropy-Regularized MAP Inference
Authors: Jonathan N. Lee, Aldo Pacchiano, Peter Bartlett, Michael I. Jordan
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: graphical models, map inference, message passing, optimization
On Learning Sets of Symmetric Elements
Authors: Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: equivariance, sets, pointclouds, graphs
Outstanding Paper Award
Individual Calibration with Randomized Forecasting
Authors: Shengjia Zhao, Tengyu Ma, Stefano Ermon
Contact<EMAIL_ADDRESS>Links: Paper
Keywords: calibration, uncertainty estimation
We look forward to seeing you at ICML 2020!


DLDLHTDL 26.5 Lbs Large Food Dispenser, Rice Dispenser, Rice Container Storage with Lid Measuring Cylinder Moisture Proof Household Cereal Dispenser Bucket for Kitchen Soybean Corn
DLDLHTDL Refrigerator Organizer Bins Fridge Storage Bins Narrow Ventilated Plastic Baskets 4 Pack
DLDLHTDL 4 Pack Refrigerator Soda Can Organizer Portable Beverage Beer Holder for Kitchen Cabinet Fridge Freezer Storage Dispenser Holds up to 16 Cans 4 Colors
DLDLHTDL Soap Box Toilet Bathroom Creative Drain soap Box Sealed Lock Travel Portable soap Box
DLDLHTDL Bath Brush with Handle Bath Tile Brush Magic Sponge Wipe Cleaning Brush Kitchen decontamination Brush
DLDLHTDL Nordic hangable Coral Fleece Hand Towel Kitchen Cleaning Towel lint-Free Absorbent Cloth Dish Cloth Cleaning Cloth


- getActivityComment() - Method in class dayplanner.AddActivityPanel
-
Comment input retrieval
- getActivityEnd() - Method in class dayplanner.AddActivityPanel
-
End time input retrieval
- getActivityEnd() - Method in class dayplanner.SearchActivityPanel
-
End time input retrieval
- getActivityKeys() - Method in class dayplanner.SearchActivityPanel
-
Keyword input retrieval
- getActivityLocation() - Method in class dayplanner.AddActivityPanel
-
Location input retrieval
- getActivityStart() - Method in class dayplanner.AddActivityPanel
-
Start time input retrieval
- getActivityStart() - Method in class dayplanner.SearchActivityPanel
-
Start time input retrieval
- getActivityTitle() - Method in class dayplanner.AddActivityPanel
-
Title input retrieval
- getActType() - Method in class dayplanner.AddActivityPanel
-
Activity type input retrieval
- getActType() - Method in class dayplanner.SearchActivityPanel
-
Activity type input string accessor
- getActTypeBox() - Method in class dayplanner.AddActivityPanel
-
Activity type component accessor
- getActTypeBox() - Method in class dayplanner.SearchActivityPanel
-
Activity type component accessor
- getCancelButton() - Method in class dayplanner.ExitWindow
-
Cancel button accessor
- getComment() - Method in class dayplanner.Activity
-
Get the value of comment
- getDay() - Method in class dayplanner.Time
-
Get the value for day
- getEndingTime() - Method in class dayplanner.Activity
-
Get the value of ending time
- getEnterButton() - Method in class dayplanner.AddActivityPanel
-
Enter button accessor
- getEnterButton() - Method in class dayplanner.SearchActivityPanel
-
Enter button accessor
- getHour() - Method in class dayplanner.Time
-
Get the value for hour
- getLocation() - Method in class dayplanner.OtherActivity
-
Get the value of location
- getMinute() - Method in class dayplanner.Time
-
Get the value for minute
- getMonth() - Method in class dayplanner.Time
-
Get the value for month
- getNoButton() - Method in class dayplanner.ConfirmExitWindow
-
- getNoButton() - Method in class dayplanner.ConfirmSaveExitWindow
-
- getNoButton() - Method in class dayplanner.ExitWindow
-
No button accessor
- getOKButton() - Method in class dayplanner.ErrorWindow
-
OK button accessor
- getResetButton() - Method in class dayplanner.AddActivityPanel
-
Reset button accessor
- getResetButton() - Method in class dayplanner.SearchActivityPanel
-
Reset button accessor
- getStartingTime() - Method in class dayplanner.Activity
-
Get the value of starting time
- getTitle() - Method in class dayplanner.Activity
-
Get the value of title
- getYear() - Method in class dayplanner.Time
-
Get the value for year
- getYesButton() - Method in class dayplanner.ExitWindow
-
Yes button accessor
- guiSearchList(Class<?>, Time, Time, String[]) - Method in class dayplanner.DayPlanner
-
Has the same functionality as searchList, except it outputs the results
into a string formatted for the GUI


{% extends "base.html" %} {% block body_content %} {% include "partial/navbar.html" %} {% block page_content %}{% endblock %} {%block footer%}
© 2013 Samuele Santi - Under Apache License Version 2.0
This application is not in any way affiliated with GitHub.


Say Hello!
We will be back in 24 hrs with solution of your querries
Max Smart
Addressline 1 here
Addressline 2 here, 123456
P:<PHONE_NUMBER>
We are at social
Get connected with us on social
Copyright 2016. All Rights Reserved.


I am a postgraduate student of Information technology with an advanced understanding of programming and software engineering concepts. During my 2 years of experience at HCL Technologies as a Software engineer, I had the opportunity to learn from the experts in the IT industry. My responsibilities were writing code, testing, and documentation. Currently, I'm about to finish my Master degree in Information technology and aspiring to be a graduate software developer. During the course of my degree, I have done a number of projects on Web application development, Machine learning, and Data analytics. The university provided a great platform to socialize and be part of various student organizations. Main areas of my interest are -Full-stack web application development -Programming Languages: Java/C/Python/HTML/SQL -Data analytics -Mobile application development -Software engineering.
Worked one-on-one with students seeking help in subjects related to Computer science and programming - Helped struggling student improve programming fundamentals - Achieved 100% student satisfaction while teaching independentl
- Designed, tested, and documented scripts and assisted in the implementation of software - Conducted regularly-scheduled Problem Management meetings with stakeholders - Carried out deep technical analysis of the production to identify performance, stability and resilience enhancements. - Key Achievements: Designed and automated jobs which increased the efficiency of the system by 18% which improved the customer service experience.
- Designed small features for an in-house application. - Developed reusable UI components and a sample application. - Learned Android frameworks and how to build a scalable application.
WAM: 85%
- Information technology project - Big Data on Cloud - Internet client engineering - Computational Intelligence - Intermediate object-oriented programming - Algorithms and Data structures
GPA: 7.5/10
I love being outdoors and during summer, I am mostly camping, hiking or traveling. When not working on projects and forced indoors, I enjoy watching war and horror movies. I aspire to be a Farmer one day and enjoy a bit of gardening.


{% extends "index.html" %} {% block body %}
Welcome to the upload section. Before we proceed, we would like to remind you that upload only files
with the extension '.docx'.
These files can be produced from a variety of word processors including
Microsoft Word, Google Documents, and Pages.
Before you upload your assignment, we would like to request your permission to use your assignment for research purposes. Systems like this are only possible to be improved if there is relevant data available. As NTU students, your privacy is very important to us, and any data you agree to release will be hand-checked and anonymised before being used for research. Anonymised data will be released under a Creative Commons CC0 Licence and used to improve this system.


| EasyRoads3D V3 Manual |
Release Notes v3.1.9.f1
Important
Importing package updates Please do NOT remove the EasyRoads3D folder before importing a package update. Apart from newly created dynamic and custom connection prefabs, the EasyRoads3D folder also includes assets with project info such as road types, side objects. When you remove the EasyRoads3D folder these assets will be lost. Also make sure to close the Custom Prefab Editor window if currently open before importing a package update. Additionally, it is also recommended to switch road networks back to Edit Mode or better open an empty scene before importing a package update . And please always backup your project first. It is recommended to regularly backup your project anyway.
Unity terrain objects EasyRoads3D can backup your terrain(s) and restore the terrain(s) in case something went wrong. For additional safety measures it is recommended to duplicate the terrain object in the project panel so you always have a full back up at hand. Make sure to repeat this process after you changed the terrain! This also applies to runtime scripts using the API to generate roads. Although this should work just fine, see the demo project runtime scene, it is always recommended to backup your terrains. To back up your terrains simply duplicate the terrain object stored in the project panel. To find a reference to this terrain asset for the terrain in the scene, select the terrain in the scene and look in the Inspector: Terrain Collider Component > Terrain Data. Put focus on the terrain slot and the corresponding terrain will be highlighted in the project panel. Select it and do CTRL + D to duplicate it. Simply drag the duplicate terrain asset in the scene to replace the original if necessary.
The Runtime API: The following is only related to scripted road networks created with the runtime API. The below does not affect road networks manually created inside the editor. In order to preserve the original terrain data, make sure you backup your terrains! In general restoring the terrains works well using RoadNetwork.RestoreRoadNetwork(), but it has occured that the terrain was not restored leaving the road shape in the terrain after exiting Play Mode. This particularly happened when you put focus on the scene view window while in Play Mode! If you want to create a road network at runtime using the runtime API, it is recommended to check the above using a test terrain or make backups of your terrain(s).
Side Objects and the river example in the demo project / video In the video the terrain is manually smoothend out at the river edges. In v3 manual terrain changes on areas not affected by roads or other deformation objects are preserved when switching back to Edit Mode. The outer part is not affected by the road, the manual changes will remain visible in the terrain. So be careful with this, only smoothen out the terrain when you are happy with the river shape or when you do not mind to manually make corrections to the terrain after switching back to Edit Mode.
Release Notes: Please visit our website for beta release notes
New: - CTRL + SHIFT + M: Snap all the road markers to the terrain height at the markers position - CTRL + M: Snap the selected road marker to the terrain height at that position - Scripting API: ERRoad.GetMarkerCount(), returns the total number of markers for a the road - Scripting API: ERRoad.GetDistance(int markerIndex), returns the distance of the section corresponding to the passed marker index Improved: - "Ratio" control for Side Object Connection objects. This represents how often the connection object is instantiated. 1 is every section, 2 is every two sections, and so on. This is for example useful for bridge pillars that should be instantiated less frequently then every repeated section. - The side objects "Default active state for each marker" can now also be set / unset for individual road objects.
Fixed: - Miscellaneous other small bugs and improvements
To Do / Current limitations:
- Roundabouts: when adding new connections you can use the position slider to set the position of the new connection on the roundabout. When the current position overlaps another connection the roundabout will not be rebuild, a warning will appear in the console and the left and right side handles will turn red instead of green. When the current position overlaps the start or end index, a similar warning message will appear as well. So stay within "save" ranges from the start (0 index) and end (depends on the resolution and radius). The troubleshooting page includes more on this.
|
|


Serpentine creatures from the family of draconians. Not to be confused with white, black, red, stone, or gold dragons. The last recorded sighting took place in 1262 in the mountains, on the outskirts of the domain of King Nedamir. This dragon was slain by Yarpen Sigrin, although he only provided a few dragon teeth to prove it.


Usage
1) Inject the TutorialService in your appComponent or wherever you want.
2) Decorate as many elements you want with the tutorial directive.
3) Tell the TutorialService to PLAY!
Demo
TutorialService Methods
| Method | Description |
|---|---|
| addAction | Used for programmatically add a tutorial into any element. |
| playAll | It plays all tutorials that are being rendered with the tutorialDirective or added manually at that time. |
| playByKey | It's similar to the playAll, but it'll play only the tutorials which has the provided key. It has an opcional parameter onlyOnce which tells the Service to use the localstorage and play that key only once. |
| moveNext | Programmatically moves to the next Tutorial. |
| movePrev | Programmatically moves to the previous Tutorial. |
| exit | Programmatically exits the Tutorial. |
| onStart | An Event fired when a tutorial is started. |
| onExit | An Event fired when a tutorial is finished. |
| onStepChanged | An Event fired everytime a tutorial step is changed. |
TutorialDirective Options
| Property | Type | Description |
|---|---|---|
|
key opcional |
string | An identification used when you want to show a certain group of tutorals by key. |
|
title opcional |
string | The tutorial's block title. |
| text | string | The tutorial's block text. |
|
order opcional |
number | Defines the ascendent order where each tutorial should be played. |


SECTION: 200-General TITLE: HotDeploy QUESTION: Can Jetty Hot Deploy?
Jetty is fully hot deployable, but does not have any native hot deployers. What this means is that Jetty contexts, servlets and filters may be added, stopped, started and reloaded dynamically, but that Jetty does not have any services that trigger these events.
The reason that Jetty does not have any native hot deployers is that the requirements for hot deployment vary greatly depending on the environment and developers. For example, which files and/or directories should be watched to trigger a hot deployment? The WAR, the unpacked WAR directory, the web.xml, the class files for the servlets or every class file loaded by the context?
Once the need for a hot deployment is detected, it is unclear what should be redeployed? Should just the servlets be reloaded? Should the context be stopped, totally reloaded and then restarted? Should the listeners be stopped so that load balancers don't send request while redeployment is happening?
There are answers to these questions, but they are very environment specific. Thus when Jetty is embedded in JBoss, it supports JBoss style hot deployment. Ditto for Geronimo and avalon. If you want hot deployment for a stand-alone Jetty, it is not difficult to write code to detect your own hotdeployment criteria and then to stop/start the jetty components that you know are affected.
For development mode, you can run Jetty as a normal application in any IDE that supports class reloading. Also there now is a i Jetty 6 plugin for maven2 users that will run a webapplication and automatically hot redploy if anything changes.
See also Reload Servlet.


Your fresh Hybrid experience starts with the NSBridge!
Click Me to show a Native Action Sheet on the iOS
Click Me to create a Native Local Notification on the iOS
Make a System.IO request to the Native iOS file system and see the results on this NSBWebView!


Wrappers around tidycensus to build redistricting data at various geographies
build_acs() mem_build_acs()
build_acs()
mem_build_acs()
Build Data from the Decennial Census
build_dec() mem_build_dec()
build_dec()
mem_build_dec()
Functions to collapse racial categories
collapse4()
Collapse Full Race Categories into 4 Categories
collapse4_pop()
Collapse Population Race Categories into 4 Categories
collapse4_vap()
Collapse Voting Age Population Race Categories into 4 Categories
collapse5()
Collapse Full Race Categories into 5 Categories
collapse5_pop()
Collapse Population Race Categories into 5 Categories
collapse5_vap()
Collapse Voting Age Population Race Categories into 5 Categories
Functions to recode common state variables as other identifiers
recode_abb_ansi()
Recode Abb by ANSI
recode_abb_fips()
Recode Abb by FIPS
recode_abb_name()
Recode Abb by Name
recode_ansi_abb()
Recode ANSI by Abb
recode_ansi_fips()
Recode ANSI by FIPS
recode_ansi_name()
Recode ANSI by Name
recode_fips_abb()
Recode FIPS by Abb
recode_fips_ansi()
Recode FIPS by ANSI
recode_fips_name()
Recode FIPS by Name
recode_name_abb()
Recode Name by Abb
recode_name_ansi()
Recode Name by ANSI
recode_name_fips()
Recode Name by FIPS
Functions to join common state variables to other identifiers
join_abb_ansi()
Join Abb by ANSI
join_abb_fips()
Join Abb by FIPS
join_abb_name()
Join Abb by Name
join_ansi_abb()
Join ANSI by Abb
join_ansi_fips()
Join ANSI by FIPS
join_ansi_name()
Join ANSI by Name
join_fips_abb()
Join FIPS by Abb
join_fips_ansi()
Join FIPS by ANSI
join_fips_name()
Join FIPS by Name
join_name_abb()
Join Name by Abb
join_name_ansi()
Join Name by ANSI
join_name_fips()
Join Name by FIPS
Mimic or work with Census GEOIDs
breakdown_geoid()
Breakdown Census GEOID into Components
construct_geoid()
Create GEOID from Default Columns
custom_geoid()
Create a GEOID from Columns
Transform State Identifiers
match_abb()
Try to Match to State Abbreviation
match_ansi()
Try to Match to State ANSI
match_fips()
Try to Match to State FIPS
match_name()
Try to Match to State Name
Data Included for Examples and Testing
fips_2000
Counties FIPS 2000
fips_2010
Counties FIPS 2010
fips_2020
Counties FIPS 2020
mt_county
Montana County Data
stata
stata (State Data)
Other Functions
add_r_environ()
Add Entry to Renviron